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 Surgical Procedure- Mitral Valve Replacement  

Scenario: A patient was admitted into the hospital and is scheduled to have open-heart surgery within 8 hours of arrival. You are the Preop Nurse assigned to the patient. You are also assigned to two other patients that need to be in surgery by 7:30 am.

PLEASE FOLLOW THE RUBRIC BELOW EVERYTHING IS THERE FOR THIS SCENARIO!!

Introduction

HIPAA, Legal, and Regulatory Discussion

Scenario Ending and Recommendations

Scenario ending: A technology downtime that impacts patient care occurs, and an error is made.  Construct based on those reflections.

Advantages and Disadvantages

Conclusion and Reflections   

Purpose

The purpose of this assignment is to investigate informatics in healthcare and to apply professional, ethical, and legal principles to its appropriate use in healthcare technology.

Course outcomes: This assignment enables the student to meet the following course outcomes:

CO 4: Investigate safeguards and decision‐making support tools embedded in patient care technologies and information systems to support a safe practice environment for both patients and healthcare workers. (PO 4)

CO 6: Discuss the principles of data integrity, professional ethics, and legal requirements related to data security, regulatory requirements, confidentiality, and client’s right to privacy. (PO 6)

CO 8: Discuss the value of best evidence as a driving force to institute change in the delivery of nursing care. (PO 8)

Due date: Your faculty member will inform you when this assignment is due. The Late Assignment Policy applies to this assignment.

Total points possible: 240 points

Requirements:

· Research, compose, and type a scholarly paper based on the scenario provided by your faculty, and choose a conclusion scenario to discuss within the body of your paper. Reflect on lessons learned in this class about technology, privacy concerns, and legal and ethical issues and address each of these concepts in the paper. Consider the consequences of such a scenario. Do not limit your review of the literature to the nursing discipline only because other health professionals are using the technology, and you may need to apply critical thinking skills to its applications in this scenario.

· Use Microsoft Word and APA formatting. Consult your copy of the Publication Manual of the American Psychological Association, as well as the resources in Doc Sharing if you have questions (e.g., margin size, font type and size (point), use of third person, etc.). Take advantage of the writing service SmartThinking, which is accessed by clicking on the link called the Tutor Source, found under the Course Home area.

· The length of the paper should be four to five pages, excluding the title page and the reference page. Limit the references to a few key sources (minimum of three required).

· The paper will contain an introduction that catches the attention of the reader, states the purpose of the paper, and provides a narrative outline of what will follow (i.e., the assignment criteria).

· In the body of the paper, discuss the scenario in relation to HIPAA, legal, and other regulatory requirements that apply to the scenario and the ending you chose. Demonstrate support from sources of evidence (references) included as in‐text citations.

· Choose and identify one of the possible endings provided for the scenario, and construct your paper based on its implications to the scenario. Make recommendations about what should have been done and what could be done to correct or mitigate the problems caused by the scenario and the ending you chose. Demonstrate support from

sources of evidence (references) included as in‐text citations.

· Present the advantages and disadvantages of informatics relating to your scenario and describe professional and ethical principles appropriate to your chosen ending. Use facts from supporting sources of evidence, which must be included as in‐text citations.

· The paper’s conclusion should summarize what you learned and make reflections about them to your practice.

· Use the “Directions and Assignment Criteria” and “Grading Rubric” below to guide your writing and ensure that all

components are complete.

· Review the section on Academic Honesty found in the Chamberlain Course Policies. All work must be original (in your own words). Papers will automatically be submitted to TurnItIn when submitted to the Dropbox.

NR360 Information Systems in Healthcare RUA: We Can, But Dare We? Guidelines

© 2022 Chamberlain University. All Rights Reserved.

NR360_RUA_We_Can_But_Dare_We_Guidelines_JULY22 1

· Submit the completed paper to the “We Can But Dare We?” Dropbox by the end of Week 3. Please refer to the Syllabus for due dates for this assignment. For online students, please post questions about this assignment to the weekly Q & A Forums so that the entire class may view the answers.

Preparing the assignment

Background

Healthcare is readily embracing any technology to improve patient outcomes, streamline operations, and lower costs, but we must also consider the impact of such technology on privacy and patient care.

Your faculty member will provide a scenario for you to address in your paper.


Choose an ending to the scenario, and construct your paper based on those reflections.

Choose one of the following outcomes:

1. A HIPAA violation occurs, and client data is exposed to the media.

2. A medication error has harmed a client.

3. A technology downtime that impacts patient care occurs, and an error is made.

4. A ransomware attack has occurred, and the organization must contemplate paying the ransom or lose access to patient data.

Follow these guidelines when completing this assignment. Speak with your faculty member if you have questions. Include the following sections:

a. Introduction – 40 points/17%

· Catches attention of the reader

· States purpose of the paper

· Provides a narrative outline of the paper (i.e., the assignment criteria)

b. HIPAA, Legal, and Regulatory Discussion – 40 points/17%

· Presents evidence from recent scholarly publications to address the impact of technology on nursing care related to:

· Patient privacy and HIPAA standards

· Healthcare regulations

· Legal guidelines on appropriate use of technology

c. Scenario Ending and Recommendations – 50 points/21%

· Selects and presents one scenario ending as the focus of the assignment.

· Evaluates the actions taken by healthcare providers as the situation evolved.

· Recommends actions that could have been taken to mitigate the circumstances presented in the selected scenario ending.

· Supports recommendations with evidence from recent scholarly publications.

d. Advantages and Disadvantages – 50 points/21%

· Presents evidence from recent scholarly publications to address the impact of technology on nursing care related to:

· The advantages of appropriately using technology in healthcare

· Risks of technology use in healthcare

· Describes professional and ethical principles guiding the appropriate use of technology in healthcare.

e. Conclusion and Reflections – 30 points/12%

· Summarizes what new information was learned by completing this assignment.

· Reflects on how this new knowledge will impact future behavior as a healthcare professional.

f. Scholarly Writing and APA Format – 30 points/12%

· Paper submitted as a Microsoft Word document.

· Adheres to current APA formatting guidelines including proper use of:

· Title page

· Page numbers

· Length is 4-5 pages, excluding title and reference pages.

· Includes at least three (3) references that are:

· From recent (within the last 5 years) scholarly sources

· Cited in text appropriately

· Included on an APA formatted reference page

· Scholarly writing reflects:

· Accurate spelling

· Correct use of professional grammar

· Logical organization of thoughts (mechanics)

For writing assistance, visit the Writing Center.

Please note that your instructor may provide you with additional assessments in any form to determine that you fully understand the concepts learned in the review module.

(
NR360 Information Systems in Healthcare

RUA: We

Can,

But

Dare

We? Guidelines
)

© 2022 Chamberlain University. All Rights Reserved.

NR360_RUA_We_Can_But_Dare_We_Guidelines- JULY22 1

Grading Rubric Criteria are met when the student’s application of knowledge demonstrates achievement of the outcomes for this assignment.

Assignment Section and Required Criteria

(Points possible/% of total points available)

Highest Level of Performance

High Level of Performance

Satisfactory Level of Performance

Unsatisfactory Level of Performance

Section not present in paper

Introduction

(40 points/17%)

40 points

36 points

32 points

15 points

0 points

Required criteria

· Catches attention of the reader.

· States purpose of the paper.

· Provides a narrative outline of the paper (i.e., the assignment criteria).

Meets all requirements for section.

Includes no fewer than 2 requirements for section.

Includes no less than 1 requirement for section.

Present, yet includes no required criteria.

No requirements for this section presented.

HIPAA, Legal, and Regulatory Discussion

(40 points/17%)

40 points

36 points

32 points

15 points

0 points

Required criteria

Presents evidence from recent scholarly publications to address the impact of technology on nursing care related to:

· Patient privacy and HIPAA standards

· Healthcare regulations

· Legal guidelines on appropriate use of technology

Meets all requirements for section.

Includes no fewer than 2 requirements for section.

Includes no fewer than 1 requirement for section.

Present, yet includes no required criteria.

No requirements for this section presented.

Scenario Ending and Recommendations

(50 points/21%)

50 points

46 points

42 points

19 points

0 points

Required criteria

· Selects and presents one scenario ending as the focus of the assignment.

· Evaluates the actions taken by healthcare providers as the situation evolved.

· Recommends actions that could have been taken to mitigate the circumstances presented in the selected scenario ending. Supports recommendations with evidence from

· recent scholarly publications.

Meets all requirements for section.

Includes no fewer than 3 requirements for section.

Includes 1-2 requirements for section.

Section present yet includes no required criteria.

No requirements for this section presented.

(
NR360 Information Systems in Healthcare

RUA: We

Can,

But

Dare

We?

Guidelines
)

© 2022 Chamberlain University. All Rights Reserved.

NR360_RUA_We_Can_But_Dare_We_Guidelines- JULY22 1

Assignment Section and Required Criteria

(Points possible/% of total points available)

Highest Level of Performance

High Level of Performance

Satisfactory Level of Performance

Unsatisfactory Level of Performance

Section not present in paper

· Supports recommendations with evidence from

recent scholarly publications.

Advantages and Disadvantages

(50 points/21%)

50 points

46 points

42 points

19 points

0 points

Required criteria

· Presents evidence from recent scholarly publications to address the impact of technology on nursing care.

· Evidence includes the advantages of appropriately using technology in healthcare.

· Evidence includes risks of inappropriately using technology in healthcare.

· Describes professional and ethical principles guiding the appropriate use of technology in healthcare.

Meets all requirements for section.

Includes no fewer than 3 requirements for section.

Includes 1-2 requirements for section.

Section present yet includes no required criteria

No requirements for this section presented.

Conclusion and Reflections

(30 points/12%)

30 points

15 points

0 points

Required criteria

· Summarizes new information learned by completing this assignment.

· Reflects on how this new knowledge will impact future behavior as a healthcare professional.

Meets all requirements for section.

Includes 1 requirement for section.

No requirements for this section presented.

Scholarly Writing and APA Format

(30 points/12%)

30 points

26 points

22 points

12 points

0 points

Required criteria

· Paper submitted as a Microsoft Word document.

· Adheres to current APA formatting guidelines including proper use of:

Meets all requirements for section.

Includes no fewer than 4 fully met requirements for section.

Includes no fewer than 3 fully met requirements for section.

Includes 1-2 requirements fully met requirements for section.

No requirements for this section presented.

Assignment Section and Required Criteria

(Points possible/% of total points available)

Highest Level of Performance

High Level of Performance

Satisfactory Level of Performance

Unsatisfactory Level of Performance

Section not present in paper

· Title page

· Page numbers

· Length is 4-5 pages, excluding title and reference pages.

· Includes at least three (3) references that are:

· From recent (within the last 5 years) scholarly sources

· Cited in text appropriately

· Included on an APA formatted reference page

· Scholarly writing reflects:

· Accurate spelling

· Correct use of professional grammar

· Logical organization of thoughts (mechanics)

Total Points Possible = 240 points

NURSING INFORMATICS
and the Foundation of
Knowledge
FOURTH EDITION

Dee McGonigle, PhD, RN, CNE, FAAN, ANEF
Director, Virtual Learning Experiences (VLE) and
Professor Graduate Program, Chamberlain College of
Nursing Member, Informatics and Technology Expert
Panel (ITEP) for the American Academy of Nursing

Kathleen Mastrian, PhD, RN
Associate Professor and Program Coordinator for
Nursing Pennsylvania State University, Shenango Sr.
Managing Editor, Online Journal of Nursing Informatics
(OJNI)

JONES & BARTLETT
LEARNING

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All rights reserved. No part of the material protected by
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herein. Nursing Informatics and the Foundation of
Knowledge, Fourth Edition is an independent
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There may be images in this book that feature models;
these models do not necessarily endorse, represent, or
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The authors, editor, and publisher have made every
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VP, Executive Publisher: David D. Cella
Executive Editor: Amanda Martin
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Composition: S4Carlisle Publishing Services
Cover and Text Design: Michael O’Donnell
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Cover Image (Title Page, Part Opener, Chapter
Opener): © fotomak/Shutterstock
Printing and Binding: LSC Communications
Cover Printing: LSC Communications

Library of Congress Cataloging-in-Publication Data
Names: McGonigle, Dee, editor. | Mastrian, Kathleen
Garver, editor.
Title: Nursing informatics and the foundation of
knowledge/[edited by]
Dee McGonigle, Kathleen Mastrian.
Description: Fourth edition. | Burlington, MA: Jones &
Bartlett Learning,
[2018] | Includes bibliographical references and index.
Identifiers: LCCN 2016043838 | ISBN 9781284121247
(pbk.)
Subjects: | MESH: Nursing Informatics | Knowledge
Classification: LCC RT50.5 | NLM WY 26.5 | DDC
651.5/04261–dc23

LC record available at
https://lccn.loc.gov/2016043838

6048
Printed in the United States of America
21 20 19 18 17 10 9 8 7 6 5 4 3 2 1

The Pedagogy
Nursing Informatics and the Foundation of
Knowledge, Fourth Edition drives comprehension
through a variety of strategies geared toward meeting
the learning needs of students, while also generating
enthusiasm about the topic. This interactive approach
addresses diverse learning styles, making this the ideal
text to ensure mastery of key concepts. The
pedagogical aids that appear in most chapters include
the following:

Special Acknowledgments
We want to express our sincere appreciation to the
staff at Jones & Bartlett Learning, especially Amanda,
Christina, and Carolyn, for their continued
encouragement, assistance, and support during the
writing process and publication of our book.

Contents
Preface
Acknowledgments
Contributors

SECTION I: BUILDING BLOCKS OF
NURSING INFORMATICS

1 Nursing Science and the Foundation of
Knowledge
Dee McGonigle and Kathleen Mastrian
Introduction
Quality and Safety Education for Nurses
Summary
References

2 Introduction to Information, Information
Science, and Information Systems
Kathleen Mastrian and Dee McGonigle
Introduction
Information
Information Science
Information Processing
Information Science and the Foundation of
Knowledge
Introduction to Information Systems

Summary
References

3 Computer Science and the Foundation of
Knowledge Model
Dee McGonigle, Kathleen Mastrian, and
June Kaminski
Introduction
The Computer as a Tool for Managing
Information and Generating Knowledge
Components
What Is the Relationship of Computer Science
to Knowledge?
How Does the Computer Support Collaboration
and Information Exchange?
Cloud Computing
Looking to the Future
Summary
Working Wisdom
Application Scenario
References

4 Introduction to Cognitive Science and
Cognitive Informatics
Kathleen Mastrian and Dee McGonigle
Introduction
Cognitive Science
Sources of Knowledge
Nature of Knowledge

How Knowledge and Wisdom Are Used in
Decision Making
Cognitive Informatics
Cognitive Informatics and Nursing Practice
What Is AI?
Summary
References

5 Ethical Applications of Informatics
Dee McGonigle, Kathleen Mastrian, and
Nedra Farcus
Introduction
Ethics
Bioethics
Ethical Issues and Social Media
Ethical Dilemmas and Morals
Ethical Decision Making
Theoretical Approaches to Healthcare Ethics
Applying Ethics to Informatics
Case Analysis Demonstration
New Frontiers in Ethical Issues
Summary
References

SECTION II: PERSPECTIVES ON NURSING
INFORMATICS

6 History and Evolution of Nursing
Informatics

Kathleen Mastrian and Dee McGonigle
Introduction
The Evolution of a Specialty
What Is Nursing Informatics?
The DIKW Paradigm
Capturing and Codifying the Work of Nursing
The Nurse as a Knowledge Worker
The Future
Summary
References

7 Nursing Informatics as a Specialty
Dee McGonigle, Kathleen Mastrian, Julie A.
Kenney, and Ida Androwich Introduction
Nursing Contributions to Healthcare
Informatics
Scope and Standards
Nursing Informatics Roles
Specialty Education and Certification
Nursing Informatics Competencies
Rewards of NI Practice
NI Organizations and Journals
The Future of Nursing Informatics
Summary
References

8 Legislative Aspects of Nursing
Informatics: HITECH and HIPAA

Kathleen M. Gialanella, Kathleen Mastrian,
and Dee McGonigle Introduction
HIPAA Came First
Overview of the HITECH Act
How a National HIT Infrastructure Is Being
Developed
How the HITECH Act Changed HIPAA
Implications for Nursing Practice
Future Regulations
Summary
References

SECTION III: NURSING INFORMATICS
ADMINISTRATIVE
APPLICATIONS: PRECARE
AND CARE SUPPORT

9 Systems Development Life Cycle: Nursing
Informatics and Organizational Decision
Making
Dee McGonigle and Kathleen Mastrian
Introduction
Waterfall Model
Rapid Prototyping or Rapid Application
Development
Object-Oriented Systems Development
Dynamic System Development Method
Computer-Aided Software Engineering Tools

Open Source Software and Free/Open Source
Software
Interoperability
Summary
References

10 Administrative Information Systems
Marianela Zytkowski, Susan Paschke,
Kathleen Mastrian, and Dee McGonigle
Introduction
Types of Healthcare Organization Information
Systems
Communication Systems
Core Business Systems
Order Entry Systems
Patient Care Support Systems
Interoperability
Aggregating Patient and Organizational Data
Department Collaboration and Exchange of
Knowledge and Information
Summary
References

11 The Human–Technology Interface
Dee McGonigle, Kathleen Mastrian, and
Judith A. Effken Introduction
The Human–Technology Interface
The Human–Technology Interface Problem
Improving the Human–Technology Interface

A Framework for Evaluation
Future of the Human–Technology Interface
Summary
References

12 Electronic Security
Lisa Reeves Bertin, Kathleen Mastrian, and
Dee McGonigle Introduction
Securing Network Information
Authentication of Users
Threats to Security
Security Tools
Offsite Use of Portable Devices
Summary
References

13 Workflow and Beyond Meaningful Use
Dee McGonigle, Kathleen Mastrian, and
Denise Hammel-Jones Introduction
Workflow Analysis Purpose
Workflow and Technology
Workflow Analysis and Informatics Practice
Informatics as a Change Agent
Measuring the Results
Future Directions
Summary
References

SECTION IV: NURSING INFORMATICS
PRACTICE APPLICATIONS:
CARE DELIVERY

14 The Electronic Health Record and
Clinical Informatics
Emily B. Barey, Kathleen Mastrian, and Dee
McGonigle
Introduction
Setting the Stage
Components of Electronic Health Records
Advantages of Electronic Health Records
Standardized Terminology and the EHR
Ownership of Electronic Health Records
Flexibility and Expandability
Accountable Care Organizations and the EHR
The Future
Summary
References

15 Informatics Tools to Promote Patient
Safety and Quality Outcomes
Dee McGonigle and Kathleen Mastrian
Introduction
What Is a Culture of Safety?
Strategies for Developing a Safety Culture
Informatics Technologies for Patient Safety
Role of the Nurse Informaticist

Summary
References

16 Patient Engagement and Connected
Health
Kathleen Mastrian and Dee McGonigle
Introduction
Consumer Demand for Information
Health Literacy and Health Initiatives
Healthcare Organization Approaches to
Engagement
Promoting Health Literacy in School-Aged
Children
Supporting Use of the Internet for Health
Education
Future Directions for Engaging Patients
Summary
References

17 Using Informatics to Promote
Community/Population Health
Dee McGonigle, Kathleen Mastrian,
Margaret Ross Kraft, and Ida Androwich
Introduction
Core Public Health Functions
Community Health Risk Assessment: Tools for
Acquiring Knowledge
Processing Knowledge and Information to
Support Epidemiology and Monitoring Disease

Outbreaks
Applying Knowledge to Health Disaster
Planning and Preparation
Informatics Tools to Support Communication
and Dissemination
Using Feedback to Improve Responses and
Promote Readiness
Summary
References

18 Telenursing and Remote Access
Telehealth
Original contribution by Audrey Kinsella,
Kathleen Albright, Sheldon Prial, and
Schuyler F. Hoss; revised by Kathleen
Mastrian and Dee McGonigle Introduction
The Foundation of Knowledge Model and Home
Telehealth
Nursing Aspects of Telehealth
History of Telehealth
Driving Forces for Telehealth
Telehealth Care
Telenursing
Telehealth Patient Populations
Tools of Home Telehealth
Home Telehealth Software
Home Telehealth Practice and Protocols
Legal, Ethical, and Regulatory Issues

The Patient’s Role in Telehealth
Telehealth Research
Evolving Telehealth Models
Parting Thoughts for the Future and a View
Toward What the Future Holds
Summary
References

SECTION V: EDUCATION APPLICATIONS OF
NURSING INFORMATICS

19 Nursing Informatics and Nursing
Education
Heather E. McKinney, Sylvia DeSantis,
Kathleen Mastrian, and Dee McGonigle
Introduction: Nursing Education and the
Foundation of Knowledge Model
Knowledge Acquisition and Sharing
Evolution of Learning Management Systems
Delivery Modalities
Technology Tools Supporting Education
Internet-Based Tools
Promoting Active and Collaborative Learning
Knowledge Dissemination and Sharing
Exploring Information Fair Use and Copyright
Restrictions
The Future
Summary
References

20 Simulation, Game Mechanics, and Virtual
Worlds in Nursing Education
Dee McGonigle, Kathleen Mastrian, Brett
Bixler, and Nickolaus Miehl Introduction
Simulation in Nursing Informatics Education
Nursing Informatics Competencies in Nursing
Education
A Case for Simulation in Nursing Informatics
Education and Nursing Education
Incorporating EHRs into the Learning
Environment
Challenges and Opportunities
The Future of Simulation in Nursing
Informatics Education
Game Mechanics and Virtual World Simulation
for Nursing Education
Game Mechanics and Educational Games
Virtual Worlds in Education
Choosing Among Simulations, Educational
Games, and Virtual Worlds
The Future of Simulations, Games, and Virtual
Worlds in Nursing Education
Summary
References

SECTION VI: RESEARCH APPLICATIONS OF
NURSING INFORMATICS

21 Nursing Research: Data Collection,
Processing, and Analysis
Heather E. McKinney, Sylvia DeSantis,
Kathleen Mastrian, and Dee McGonigle
Introduction: Nursing Research and the
Foundation of Knowledge Model
Knowledge Generation Through Nursing
Research
Acquiring Previously Gained Knowledge
Through Internet and Library Holdings
Fair Use of Information and Sharing
Informatics Tools for Collecting Data and
Storage of Information
Tools for Processing Data and Data Analysis
The Future
Summary
References

22 Data Mining as a Research Tool
Dee McGonigle and Kathleen Mastrian
Introduction: Big Data, Data Mining, and
Knowledge Discovery
KDD and Research
Data Mining Concepts
Data Mining Techniques
Data Mining Models
Benefits of KDD
Data Mining and Electronic Health Records

Ethics of Data Mining
Summary
References

23 Translational Research: Generating
Evidence for Practice
Jennifer Bredemeyer, Ida Androwich, Dee
McGonigle, and Kathleen Mastrian
Introduction
Clarification of Terms
History of Evidence-Based Practice
Evidence
Bridging the Gap Between Research and
Practice
Barriers to and Facilitators of Evidence-Based
Practice
The Role of Informatics
Developing EBP Guidelines
Meta-Analysis and Generation of Knowledge
The Future
Summary
References

24 Bioinformatics, Biomedical Informatics,
and Computational Biology
Dee McGonigle and Kathleen Mastrian
Introduction
Bioinformatics, Biomedical Informatics, and
Computational Biology Defined

Why Are Bioinformatics and Biomedical
Informatics So Important?
What Does the Future Hold?
Summary
References

SECTION VII: IMAGINING THE FUTURE OF
NURSING INFORMATICS

25 The Art of Caring in Technology-Laden
Environments
Kathleen Mastrian and Dee McGonigle
Introduction
Caring Theories
Presence
Strategies for Enhancing Caring Presence
Reflective Practice
Summary
References

26 Nursing Informatics and the Foundation
of Knowledge
Dee McGonigle and Kathleen Mastrian
Introduction
Foundation of Knowledge Revisited
The Nature of Knowledge
Knowledge Use in Practice
Characteristics of Knowledge Workers
Knowledge Management in Organizations

Managing Knowledge Across Disciplines
The Learning Healthcare System
Summary
References

Abbreviations

Glossary

Index

Preface
The idea for this text originated with the development
of nursing informatics (NI) classes, the publication of
articles related to technology-based education, and the
creation of the Online Journal of Nursing Informatics
(OJNI), which Dee McGonigle cofounded with Renee
Eggers. Like most nurse informaticists, we fell into the
specialty; our love affair with technology and gadgets
and our willingness to be the first to try new things
helped to hook us into the specialty of informatics. The
rapid evolution of technology and its transformation of
the ways of nursing prompted us to try to capture the
essence of NI in a text.

As we were developing the first edition, we realized
that we could not possibly know all there is to know
about informatics and the way in which it supports
nursing practice, education, administration, and
research. We also knew that our faculty roles
constrained our opportunities for exposure to changes
in this rapidly evolving field. Therefore, we developed a
tentative outline and a working model of the theoretical
framework for the text and invited participation from
informatics experts and specialists around the world.
We were pleased with the enthusiastic responses we
received from some of those invited contributors and a

few volunteers who heard about the text and asked to
participate in their particular area of expertise.

In the second edition, we invited the original
contributors to revise and update their chapters. Not
everyone chose to participate in the second edition, so
we revised several of the chapters using the original
work as a springboard. The revisions to the text were
guided by the contributors’ growing informatics
expertise and the reviews provided by textbook
adopters. In the revisions, we sought to do the
following:

Expand the audience focus to include nursing
students from BS through DNP programs as well as
nurses thrust into informatics roles in clinical
agencies.
Include, whenever possible, an attention-grabbing
case scenario as an introduction or an illustrative
case scenario demonstrating why the topic is
important.
Include important research findings related to the
topic. Many chapters have research briefs
presented in text boxes to encourage the reader to
access current research.
Focus on cutting-edge innovations, meaningful use,
and patient safety as appropriate to each topic.
Include a paragraph describing what the future
holds for each topic.

New chapters that were added to the second edition
included those focusing on technology and patient
safety, system development life cycle, workflow
analysis, gaming, simulation, and bioinformatics.

In the third edition, we reviewed and updated all of the
chapters, reordered some chapters for better content
flow, eliminated duplicated content, split the education
and research content into two sections, integrated
social media content, and added two new chapters:
Data Mining as a Research Tool and The Art of Caring
in Technology-Laden Environments.

In this fourth edition, we reviewed and updated all of
the chapters based on technological advancements
and changes to the healthcare arena, including
reimbursement mechanisms for services. We have
pared this edition down to 26 chapters from the
previous edition’s 29; one chapter each was deleted
from Sections II, V, and VII. Section I includes
updates to the same five chapters on the building
blocks of nursing informatics, with extensive changes
to Chapter 3, Computer Science and the Foundation of
Knowledge Model. To improve flow, we combined
content. In Section II, the previous four chapters were
narrowed to three. New Chapters 6, History and
Evolution of Nursing Informatics and 7, Nursing
Informatics as a Specialty, were developed and
appropriate material from previous Chapters 6, 7, and
8 were assimilated. This section ends with an updated

Chapter 8, Legislative Aspects of Nursing Informatics:
HITECH and HIPAA (formerly Chapter 9). Section III
contains the same five chapters, although all were
updated and Chapter 13, Workflow and Beyond
Meaningful Use (formerly Chapter 14) now reflects the
payment models and reimbursement issues that we
are adjusting to after meaningful use has gone away.
Section IV contains the same five chapters with
updated content and some name changes to reflect the
current status of informatics and healthcare. Chapter
15 was renamed to Informatics Tools to Promote
Patient Safety and Quality Outcomes, and Chapter 16
has been changed to Patient Engagement and
Connected Health. Section V went from three chapters
to two chapters: Chapter 19 (formerly Chapter 20)
was updated, while the new Chapter 20, Simulation,
Game Mechanics, and Virtual Worlds in Nursing
Education, had content from former Chapters 21 and
22 integrated during its development. Section VI was
renamed to Research Applications of Nursing
Informatics. It still has the same four chapters, which
have been updated, but the first chapter in this section,
21, was renamed to reflect nursing research; its new
name is Nursing Research: Data Collection,
Processing, and Analysis. Section VII went from three
chapters to two chapters. Because emerging
technologies are discussed throughout the text, the
chapter focusing specifically on that was removed. The
two chapters that remain are Chapter 25, The Art of
Caring in Technology-Laden Environments, and the

new Chapter 26, Nursing Informatics and Knowledge
Management. In addition, the ancillary materials have
been updated and enhanced to include competency-
based self-assessments and mapping the content to
the current NI standards.

We believe that this text provides a comprehensive
elucidation of this exciting field. Its theoretical
underpinning is the Foundation of Knowledge model.
This model is introduced in its entirety in the first
chapter (Nursing Science and the Foundation of
Knowledge), which discusses nursing science and its
relationship to NI. We believe that humans are organic
information systems that are constantly acquiring,
processing, and generating information or knowledge
in both their professional and personal lives. It is their
high degree of knowledge that characterizes humans
as extremely intelligent, organic machines. Individuals
have the ability to manage knowledge—an ability that
is learned and honed from birth. We make our way
through life interacting with our environment and being
inundated with information and knowledge. We
experience our environment and learn by acquiring,
processing, generating, and disseminating knowledge.
As we interact in our environment, we acquire
knowledge that we must process. This processing
effort causes us to redefine and restructure our
knowledge base and generate new knowledge. We
then share (disseminate) this new knowledge and
receive feedback from others. The dissemination and

feedback initiate this cycle of knowledge over again, as
we acquire, process, generate, and disseminate the
knowledge gained from sharing and re-exploring our
own knowledge base. As others respond to our
knowledge dissemination and we acquire new
knowledge, we engage in rethinking and reflecting on
our knowledge, processing, generating, and then
disseminating anew.

The purpose of this text is to provide a set of practical
and powerful tools to ensure that the reader gains an
understanding of NI and moves from information
through knowledge to wisdom. Defining the demands
of nurses and providing tools to help them survive and
succeed in the Knowledge Era remains a major
challenge. Exposing nursing students and nurses to
the principles and tools used in NI helps to prepare
them to meet the challenge of practicing nursing in the
Knowledge Era while striving to improve patient care at
all levels.

The text provides a comprehensive framework that
embraces knowledge so that readers can develop their
knowledge repositories and the wisdom necessary to
act on and apply that knowledge. The text is divided
into seven sections.

Section I, Building Blocks of Nursing Informatics,
covers the building blocks of NI: nursing science,
information science, computer science, cognitive

science, and the ethical management of
information.
Section II, Perspectives on Nursing Informatics,
provides readers with a look at various viewpoints
on NI and NI practice as described by experts in the
field.
Section III, Nursing Informatics Administrative
Applications: Precare and Care Support, covers
important functions of administrative applications of
NI.
Section IV, Nursing Informatics Practice
Applications: Care Delivery, covers healthcare
delivery applications including electronic health
records (EHRs), clinical information systems,
telehealth, patient safety, patient and community
education, and care management.
Section V, Education Applications of Nursing
Informatics, presents subject matter on how
informatics supports nursing education.
Section VI, Research Applications of Nursing
Informatics, covers informatics tools to support
nursing research, including data mining and
bioinformatics.
Section VII, Imagining the Future of Nursing
Informatics, focuses on the future of NI,
emphasizes the need to preserve caring functions
in technology-laden environments, and reviews the
relationship of nursing informatics to organizational
knowledge management.

The introduction to each section explains the
relationship between the content of that section and the
Foundation of Knowledge model. This text places the
material within the context of knowledge acquisition,
processing, generation, and dissemination. It serves
both nursing students (BS to DNP/PhD) and
professionals who need to understand, use, and
evaluate NI knowledge. As nursing professors, our
major responsibility is to prepare the practitioners and
leaders in the field. Because NI permeates the entire
scope of nursing (practice, administration, education,
and research), nursing education curricula must
include NI. Our primary objective is to develop the most
comprehensive and user-friendly NI text on the market
to prepare nurses for current and future practice
challenges. In particular, this text provides a solid
groundwork from which to integrate NI into practice,
education, administration, and research.

Goals of this text are as follows:

Impart core NI principles that should be familiar to
every nurse and nursing student
Help the reader understand knowledge and how it
is acquired, processed, generated, and
disseminated
Explore the changing role of NI professionals
Demonstrate the value of the NI discipline as an
attractive field of specialization

Meeting these goals will help nurses and nursing
students understand and use fundamental NI principles
so that they efficiently and effectively function as
current and future nursing professionals to enhance the
nursing profession and improve the quality of health
care. The overall vision, framework, and pedagogy of
this text offer benefits to readers by highlighting
established principles while drawing out new ones that
continue to emerge as nursing and technology evolve.

Acknowledgments
We are deeply grateful to the contributors who
provided this text with a richness and diversity of
content that we could not have captured alone. Joan
Humphrey provided social media content integrated
throughout the text. We especially wish to
acknowledge the superior work of Alicia Mastrian,
graphic designer of the Foundation of Knowledge
model, which serves as the theoretical framework on
which this text is anchored. We could never have
completed this project without the dedicated and
patient efforts of the Jones & Bartlett Learning staff,
especially Amanda Martin, Emma Huggard, and
Christina Freitas, all of whom fielded our questions and
concerns in a very professional, respectful, and timely
manner.

Dee acknowledges the undying love, support, patience,
and continued encouragement of her best friend and
husband, Craig, and her son, Craig, who has made her
so very proud. She sincerely thanks her cousins
Camille, Glenn, Mary Jane, and Sonny, and her dear
friends for their support and encouragement, especially
Renee.

Kathy acknowledges the loving support of her family:
husband Chip; children Ben and Alicia; sisters Carol
and Sue; and parents Robert and Rosalie Garver. She
dedicates her work on this edition to her dad, Robert,
who died September 17, 2016. Kathy also
acknowledges those friends who understand the
importance of validation, especially Katie, Lisa, Kathy,
Maureen, Anne, Barbara, and Sally.

Authors’ Note
This text provides an overview of nursing informatics
from the perspective of diverse experts in the field, with
a focus on nursing informatics and the Foundation of
Knowledge model. We want our readers and students
to focus on the relationship of knowledge to informatics
and to embrace and maintain the caring functions of
nursing—messages all too often lost in the romance
with technology. We hope you enjoy the text!

Contributors
Ida Androwich, PhD, RN, BC, FAAN
Loyola University Chicago
School of Nursing
Maywood, IL

Emily Barey, MSN, RN
Director of Nursing Informatics
Epic Systems Corporation
Madison, WI

Lisa Reeves Bertin, BS, EMBA
Pennsylvania State University
Sharon, PA

Brett Bixler, PhD
Pennsylvania State University
University Park, PA

Jennifer Bredemeyer, RN
Loyola University Chicago
School of Nursing
Skokie, IL

Steven Brewer, PhD
Assistant Professor, Administration of Justice

Pennsylvania State University
Sharon, PA

Sylvia M. DeSantis, MA
Pennsylvania State University
University Park, PA

Judith Effken, PhD, RN, FACMI
University of Arizona
College of Nursing
Tucson, AZ

Nedra Farcus, MSN, RN
Retired from Pennsylvania State University, Altoona
Altoona, PA

Kathleen M. Gialanella, JD, RN, LLM
Law Offices
Westfield, NJ
Associate Adjunct Professor
Teachers College, Columbia University
New York, NY
Adjunct Professor
Seton Hall University, College of Nursing & School
of Law
South Orange & Newark, NJ

Denise Hammel-Jones, MSN, RN-BC, CLSSBB
Greencastle Associates Consulting
Malvern, PA

Nicholas Hardiker, PhD, RN
Senior Research Fellow
University of Salford
School of Nursing & Midwifery
Salford, UK

Glenn Johnson, MLS
Pennsylvania State University
University Park, PA

June Kaminski, MSN, RN
Kwantlen University College
Surrey, British Columbia, Canada

Julie Kenney, MSN, RNC-OB
Clinical Analyst
Advocate Health Care
Oak Brook, IL

Margaret Ross Kraft, PhD, RN
Loyola University Chicago
School of Nursing
Maywood, IL

Wendy L. Mahan, PhD, CRC, LPC
Pennsylvania State University
University Park, PA

Heather McKinney, PhD

Pennsylvania State University
University Park, PA

Nickolaus Miehl, MSN, RN
Oregon Health Sciences University
Monmouth, OR

Lynn M. Nagle, PhD, RN
Assistant Professor
University of Toronto
Toronto, Ontario, Canada

Ramona Nelson, PhD, RN-BC, FAAN, ANEF
Professor Emerita, Slippery Rock University
President, Ramona Nelson Consulting
Pittsburgh, PA

Nancy Staggers, PhD, RN, FAAN
Professor, Informatics
University of Maryland
Baltimore, MD

Jeff Swain
Instructional Designer
Pennsylvania State University
University Park, PA

Denise D. Tyler, MSN/MBA, RN-BC
Implementation Specialist
Healthcare Provider, Consulting

ACS, a Xerox Company
Dearborn, MI
The Editors also acknowledge the work of the
following first edition contributors (original
contributions edited by McGonigle and Mastrian for
second edition):

Kathleen Albright, BA, RN
Strategic Account Manager at GE Healthcare
Philadelphia, PA

Schuyler F. Hoss, BA
Northwest Healthcare Management
Vancouver, WA

Audrey Kinsella, MA, MS
Information for Tomorrow
Telehealth Planning Services
Asheville, NC

Peter J. Murray, PhD, RN, FBCS
Coachman’s Cottage
Nocton, Lincoln, UK

Susan M. Paschke, MSN, RN
The Cleveland Clinic
Cleveland, OH

Sheldon Prial, RPH, BS Pharmacy
Sheldon Prial Consultance

Melbourne, FL

Jackie Ritzko
Pennsylvania State University
Hazelton, PA

Marianela Zytkowsi, MSN, RN
The Cleveland Clinic
Cleveland, OH

SECTION I: Building
Blocks of Nursing
Informatics

Chapter 1 Nursing Science and the Foundation
of Knowledge

Chapter 2 Introduction to Information,
Information Science, and Information Systems

Chapter 3 Computer Science and the
Foundation of Knowledge Model

Chapter 4 Introduction to Cognitive Science and
Cognitive Informatics

Chapter 5 Ethical Applications of Informatics

Nursing professionals are information-dependent
knowledge workers. As health care continues to evolve
in an increasingly competitive information marketplace,
professionals—that is, the knowledge workers—must
be well prepared to make significant contributions by
harnessing appropriate and timely information. Nursing
informatics (NI), a product of the scientific synthesis of
information in nursing, encompasses concepts from
computer science, cognitive science, information
science, and nursing science. NI continues to evolve

as more and more professionals access, use, and
develop the information, computer, and cognitive
sciences necessary to advance nursing science for the
betterment of patients and the profession. Regardless
of their future roles in the healthcare milieu, it is clear
that nurses need to understand the ethical application
of computer, information, and cognitive sciences to
advance nursing science.

To implement NI, one must view it from the perspective
of both the current healthcare delivery system and
specific, individual organizational needs, while
anticipating and creating future applications in both the
healthcare system and the nursing profession. Nursing
professionals should be expected to discover
opportunities to use NI, participate in the design of
solutions, and be challenged to identify, develop,
evaluate, modify, and enhance applications to improve
patient care. This text is designed to provide the reader
with the information and knowledge needed to meet
this expectation.

Section I presents an overview of the building blocks of
NI: nursing, information, computer, and cognitive
sciences. Also included in this section is a chapter on
ethical applications of healthcare informatics. This
section lays the foundation for the remainder of the
book.

The Nursing Science and the Foundation of Knowledge

chapter describes nursing science and introduces the
Foundation of Knowledge model as the conceptual
framework for the book. In this chapter, a clinical case
scenario is used to illustrate the concepts central to
nursing science. A definition of nursing science is also
derived from the American Nurses Association’s
definition of nursing. Nursing science is the ethical
application of knowledge acquired through education,
research, and practice to provide services and
interventions to patients to maintain, enhance, or
restore their health, and to acquire, process, generate,
and disseminate nursing knowledge to advance the
nursing profession. Information is a central concept
and health care’s most valuable resource. Information
science and systems, together with computers, are
constantly changing the way healthcare organizations
conduct their business. This will continue to evolve.

To prepare for these innovations, the reader must
understand fundamental information and computer
concepts, covered in the Introduction to Information,
Information Science, and Information Systems and
Computer Science and the Foundation of Knowledge
Model chapters, respectively. Information science deals
with the interchange (or flow) and scaffolding (or
structure) of information and involves the application of
information tools for solutions to patient care and
business problems in health care. To be able to use
and synthesize information effectively, an individual
must be able to obtain, perceive, process, synthesize,

comprehend, convey, and manage the information.
Computer science deals with understanding the
development, design, structure, and relationship of
computer hardware and software. This science offers
extremely valuable tools that, if used skillfully, can
facilitate the acquisition and manipulation of data and
information by nurses, who can then synthesize these
resources into an ever-evolving knowledge and
wisdom base. This not only facilitates professional
development and the ability to apply evidence-based
practice decisions within nursing care, but, if the results
are disseminated and shared, can also advance the
profession’s knowledge base. The development of
knowledge tools, such as the automation of decision
making and strides in artificial intelligence, has altered
the understanding of knowledge and its representation.
The ability to structure knowledge electronically
facilitates the ability to share knowledge structures and
enhance collective knowledge.

As discussed in the Introduction to Cognitive Science
and Cognitive Informatics chapter, cognitive science
deals with how the human mind functions. This science
encompasses how people think, understand,
remember, synthesize, and access stored information
and knowledge. The nature of knowledge, including
how it is developed, used, modified, and shared,
provides the basis for continued learning and
intellectual growth.

The Ethical Applications of Informatics chapter focuses
on ethical issues associated with managing private
information with technology and provides a framework
for analyzing ethical issues and supporting ethical
decision making.

The material within this book is placed within the
context of the Foundation of Knowledge model (shown
in Figure I-1 and periodically throughout the book, but
more fully introduced and explained in the Nursing
Science and the Foundation of Knowledge chapter).
The Foundation of Knowledge model is used
throughout the text to illustrate how knowledge is used
to meet the needs of healthcare delivery systems,
organizations, patients, and nurses. It is through
interaction with these building blocks—the theories,
architecture, and tools—that one acquires the bits and
pieces of data necessary, processes these into
information, and generates and disseminates the
resulting knowledge. Through this dynamic exchange,
which includes feedback, individuals continue the
interaction and use of these sciences to input or
acquire, process, and output or disseminate generated
knowledge. Humans experience their environment and
learn by acquiring, processing, generating, and
disseminating knowledge. When they then share
(disseminate) this new knowledge and receive
feedback on the knowledge they have shared, the
feedback initiates the cycle of knowledge all over
again. As individuals acquire, process, generate, and

disseminate knowledge, they are motivated to share,
rethink, and explore their own knowledge base. This
complex process is captured in the Foundation of
Knowledge model. Throughout the chapters in the
Building Blocks of Nursing Informatics section, readers
are challenged to think about how the model can help
them to understand the ways in which they acquire,
process, generate, disseminate, and then receive and
process feedback on their new knowledge of the
building blocks of NI.

Figure I-1 Foundation of Knowledge Model

Designed by Alicia Mastrian

CHAPTER 1: Nursing
Science and the
Foundation of
Knowledge

Dee McGonigle and Kathleen Mastrian

Objectives
1. Define nursing science and its

relationship to various nursing roles and
nursing informatics.

2. Introduce the Foundation of Knowledge
model as the organizing conceptual
framework for the text.

3. Explain the relationships among
knowledge acquisition, knowledge
processing, knowledge generation,
knowledge dissemination, and wisdom.

Key Terms
» Borrowed theory

» Building blocks

» Clinical databases

» Clinical practice guidelines

» Conceptual framework

» Data

» Data mining

» Evidence

» Feedback

» Foundation of Knowledge model

» Information

» Knowledge

» Knowledge acquisition

» Knowledge dissemination

» Knowledge generation

» Knowledge processing

» Knowledge worker

» Nursing informatics

» Nursing science

» Nursing theory

» Relational database

» Transparent wisdom

Introduction
Nursing informatics has been traditionally defined as
a specialty that integrates nursing science, computer
science, and information science to manage and
communicate data, information, knowledge, and
wisdom in nursing practice. This chapter focuses on
nursing science as one of the building blocks of
nursing informatics. As depicted in Figure 1-1, the
traditional definition of nursing informatics is extended
to include cognitive science. The Foundation of
Knowledge model is also introduced as the organizing
conceptual framework of this text, and the model is
tied to nursing science and the practice of nursing
informatics. To lay the groundwork for this discussion,
consider the following patient scenario:

Tom H. is a registered nurse who works
in a very busy metropolitan hospital
emergency room. He has just admitted a
79-year-old man whose wife brought him
to the hospital because he is having
trouble breathing. Tom immediately clips

a pulse oximeter to the patient’s finger
and performs a very quick assessment of
the patient’s other vital signs. He
discovers a rapid pulse rate and a
decreased oxygen saturation level in
addition to the rapid and labored
breathing. Tom determines that the
patient is not in immediate danger and
that he does not require intubation. Tom
focuses his initial attention on easing the
patient’s labored breathing by elevating
the head of the bed and initiating oxygen
treatment; he then hooks the patient up to
a heart monitor. Tom continues to assess
the patient’s breathing status as he
performs a head-to-toe assessment of
the patient that leads to the nursing
diagnoses and additional interventions
necessary to provide comprehensive care
to this patient.

Consider Tom’s actions and how and why he
intervened as he did. Tom relied on the immediate data
and information that he acquired during his initial
rapid assessment to deliver appropriate care to his
patient. Tom also used technology (a pulse oximeter
and a heart monitor) to assist with and support the
delivery of care. What is not immediately apparent, and
some would argue is transparent (done without

conscious thought), is the fact that during the rapid
assessment, Tom reached into his knowledge base of
previous learning and experiences to direct his care, so
that he could act with transparent wisdom. He used
both nursing theory and borrowed theory to inform
his practice. Tom certainly used nursing process
theory, and he may have also used one of several
other nursing theories, such as Rogers’s science of
unitary human beings, Orem’s theory of self-care
deficit, or Roy’s adaptation theory. In addition, Tom
may have applied his knowledge from some of the
basic sciences, such as anatomy, physiology,
psychology, and chemistry, as he determined the
patient’s immediate needs. Information from Maslow’s
hierarchy of needs, Lazarus’s transaction model of
stress and coping, and the health belief model may
have also helped Tom practice professional nursing.
He gathered data, and then analyzed and interpreted
those data to form a conclusion—the essence of
science. Tom has illustrated the practical aspects of
nursing science.

The American Nurses Association (2016) defines
nursing in this way: “Nursing is the protection,
promotion, and optimization of health and abilities,
prevention of illness and injury, facilitation of healing,
alleviation of suffering through the diagnosis and
treatment of human response, and advocacy in the
care of individuals, families, groups, communities, and
populations” (para. 1). Thus the focus of nursing is on

human responses to actual or potential health
problems and advocacy for various clients. These
human responses are varied and may change over
time in a single case. Nurses must possess the
technical skills to manage equipment and perform
procedures, the interpersonal skills to interact
appropriately with people, and the cognitive skills to
observe, recognize, and collect data; analyze and
interpret data; and reach a reasonable conclusion that
forms the basis of a decision. At the heart of all of
these skills lies the management of data and
information. This definition of nursing science focuses
on the ethical application of knowledge acquired
through education, research, and practice to provide
services and interventions to patients to maintain,
enhance, or restore their health and to acquire,
process, generate, and disseminate nursing knowledge
to advance the nursing profession.

Figure 1-1 Building Blocks of Nursing Informatics

Nursing is an information-intensive profession. The
steps of using information, applying knowledge to a
problem, and acting with wisdom form the basis of
nursing practice science. Information is composed of
data that were processed using knowledge. For
information to be valuable, it must be accessible,
accurate, timely, complete, cost-effective, flexible,
reliable, relevant, simple, verifiable, and secure.
Knowledge is the awareness and understanding of a
set of information and ways that information can be

made useful to support a specific task or arrive at a
decision. In the case scenario, Tom used accessible,
accurate, timely, relevant, and verifiable data and
information. He compared that data and information to
his knowledge base of previous experiences to
determine which data and information were relevant to
the current case. By applying his previous knowledge
to data, he converted those data into information, and
information into new knowledge—that is, an
understanding of which nursing interventions were
appropriate in this case. Thus information is data made
functional through the application of knowledge.

Humans acquire data and information in bits and
pieces and then transform the information into
knowledge. The information-processing functions of the
brain are frequently compared to those of a computer,
and vice versa (see a discussion of cognitive
informatics for more information). Humans can be
thought of as organic information systems that are
constantly acquiring, processing, and generating
information or knowledge in their professional and
personal lives. They have an amazing ability to
manage knowledge. This ability is learned and honed
from birth as individuals make their way through life
interacting with the environment and being inundated
with data and information. Each person experiences
the environment and learns by acquiring, processing,
generating, and disseminating knowledge.

Tom, for example, acquired knowledge in his basic
nursing education program and continues to build his
foundation of knowledge by engaging in such activities
as reading nursing research and theory articles,
attending continuing education programs, consulting
with expert colleagues, and using clinical databases
and clinical practice guidelines. As he interacts in
the environment, he acquires knowledge that must be
processed. This processing effort causes him to
redefine and restructure his knowledge base and
generate new knowledge. Tom can then share
(disseminate) this new knowledge with colleagues, and
he may receive feedback on the knowledge that he
shares. This dissemination and feedback builds the
knowledge foundation anew as Tom acquires,
processes, generates, and disseminates new
knowledge as a result of his interactions. As others
respond to his knowledge dissemination and he
acquires yet more knowledge, he is engaged to rethink,
reflect on, and re-explore his knowledge acquisition,
leading to further processing, generating, and then
disseminating knowledge. This ongoing process is
captured in the Foundation of Knowledge model, which
is used as an organizing framework for this text.

At its base, the model contains bits, bytes (a computer
term used to quantify data), data, and information in a
random representation. Growing out of the base are
separate cones of light that expand as they reflect
upward; these cones represent knowledge acquisition,

knowledge generation, and knowledge dissemination.
At the intersection of the cones and forming a new
cone is knowledge processing. Encircling and cutting
through the knowledge cones is feedback that acts on
and may transform any or all aspects of knowledge
represented by the cones. One should imagine the
model as a dynamic figure in which the cones of light
and the feedback rotate and interact rather than remain
static. Knowledge acquisition, knowledge generation,
knowledge dissemination, knowledge processing, and
feedback are constantly evolving for nurse scientists.
The transparent effect of the cones is deliberate and is
intended to suggest that as knowledge grows and
expands, its use becomes more transparent—a person
uses this knowledge during practice without even being
consciously aware of which aspect of knowledge is
being used at any given moment.

Experienced nurses, thinking back to their novice
years, may recall feeling like their head was filled with
bits of data and information that did not form any type
of cohesive whole. As the model depicts, the
processing of knowledge begins a bit later (imagine a
timeline applied vertically) with early experiences on
the bottom and expertise growing as the processing of
knowledge ensues. Early on in nurses’ education,
conscious attention is focused mainly on knowledge
acquisition, and beginning nurses depend on their
instructors and others to process, generate, and
disseminate knowledge. As nurses become more

comfortable with the science of nursing, they begin to
take over some of the other Foundation of Knowledge
functions. However, to keep up with the explosion of
information in nursing and health care, they must
continue to rely on the knowledge generation of
nursing theorists and researchers and the
dissemination of their work. In this sense, nurses are
committed to lifelong learning and the use of
knowledge in the practice of nursing science.

The Foundation of Knowledge model (Figure 1-2)
permeates this text, reflecting the understanding that
knowledge is a powerful tool and that nurses focus on
information as a key building block of knowledge. The
application of the model is described to help the reader
understand and appreciate the foundation of
knowledge in nursing science and see how it applies to
nursing informatics. All of the various nursing roles
(practice, administration, education, research, and
informatics) involve the science of nursing. Nurses are
knowledge workers, working with information and
generating information and knowledge as a product.
They are knowledge acquirers, providing convenient
and efficient means of capturing and storing
knowledge. They are knowledge users, meaning
individuals or groups who benefit from valuable, viable
knowledge. Nurses are knowledge engineers,
designing, developing, implementing, and maintaining
knowledge. They are knowledge managers, capturing
and processing collective expertise and distributing it

where it can create the largest benefit. Finally, they are
knowledge developers and generators, changing and
evolving knowledge based on the tasks at hand and
the information available.

In the case scenario, at first glance one might label
Tom as a knowledge worker, a knowledge acquirer,
and a knowledge user. However, stopping here might
sell Tom short in his practice of nursing science.
Although he acquired and used knowledge to help him
achieve his work, he also processed the data and
information he collected to develop a nursing diagnosis
and a plan of care. The knowledge stores Tom used to
develop and glean knowledge from valuable
information are generative (having the ability to
originate and produce or generate) in nature. For
example, Tom may have learned something new about
his patient’s culture from the patient or his wife that he
will file away in the knowledge repository of his mind to
be used in another similar situation. As he compares
this new cultural information to what he already knows,
he may gain insight into the effect of culture on a
patient’s response to illness. In this sense, Tom is a
knowledge generator. If he shares this newly acquired
knowledge with another practitioner, and as he records
his observations and his conclusions, he is then
disseminating knowledge. Tom also uses feedback
from the various technologies he has applied to
monitor his patient’s status. In addition, he may rely on
feedback from laboratory reports or even other

practitioners to help him rethink, revise, and apply the
knowledge about this patient that he is generating.

To have ongoing value, knowledge must be viable.
Knowledge viability refers to applications (most
technology based) that offer easily accessible,
accurate, and timely information obtained from a
variety of resources and methods and presented in a
manner so as to provide the necessary elements to
generate new knowledge. In the case scenario, Tom
may have felt the need to consult an electronic
database or a clinical guidelines repository that he has
downloaded on his tablet or smartphone, or that
resides in the emergency room’s networked computer
system, to assist him in the development of a
comprehensive care plan for his patient. In this way,
Tom uses technology and evidence to support and
inform his practice. It is also possible in this scenario
that an alert might appear in the patient’s electronic
health record or the clinical information system (CIS)
reminding Tom to ask about influenza and pneumonia
vaccines. Clinical information technologies that support
and inform nursing practice and nursing administration
are an important part of nursing informatics.

Figure 1-2 Foundation of Knowledge Model

Designed by Alicia Mastrian

This text provides a framework that embraces
knowledge so that readers can develop the wisdom
necessary to apply what they have learned. Wisdom is
the application of knowledge to an appropriate
situation. In the practice of nursing science, one
expects actions to be directed by wisdom. Wisdom
uses knowledge and experience to heighten common
sense and insight to exercise sound judgment in
practical matters. It is developed through knowledge,
experience, insight, and reflection. Wisdom is
sometimes thought of as the highest form of common
sense, resulting from accumulated knowledge or
erudition (deep, thorough learning) or enlightenment

(education that results in understanding and the
dissemination of knowledge). It is the ability to apply
valuable and viable knowledge, experience,
understanding, and insight while being prudent and
sensible. Knowledge and wisdom are not synonymous:
Knowledge abounds with others’ thoughts and
information, whereas wisdom is focused on one’s own
mind and the synthesis of experience, insight,
understanding, and knowledge. Wisdom has been
called the foundation of the art of nursing.

Some nursing roles might be viewed as more focused
on some aspects rather than other aspects of the
foundation of knowledge. For example, some might
argue that nurse educators are primarily knowledge
disseminators and that nurse researchers are
knowledge generators. Although the more frequent
output of their efforts can certainly be viewed in this
way, it is important to realize that nurses use all of the
aspects of the Foundation of Knowledge model
regardless of their area of practice. For nurse
educators to be effective, they must be in the habit of
constantly building and rebuilding their foundation of
knowledge about nursing science. In addition, as they
develop and implement curricular innovations, they
must evaluate the effectiveness of those changes. In
some cases, they use formal research techniques to
achieve this goal and, therefore, generate knowledge
about the best and most effective teaching strategies.
Similarly, nurse researchers must acquire and process

new knowledge as they design and conduct their
research studies. All nurses have the opportunity to be
involved in the formal dissemination of knowledge via
their participation in professional conferences, either as
presenters or as attendees. In addition, some nurses
disseminate knowledge by formal publication of their
ideas. In the cases of conference presentation and
publication, nurses may receive feedback that
stimulates rethinking about the knowledge they have
generated and disseminated, in turn prompting them to
acquire and process data and information anew.

All nurses, regardless of their practice arena, must use
informatics and technology to inform and support that
practice. The case scenario discussed Tom’s use of
various monitoring devices that provide feedback on
the physiologic status of the patient. It was also
suggested that Tom might consult a clinical database
or nursing practice guidelines residing on a tablet or
smartphone, in the cloud (a virtual information storage
system), or on a clinical agency network as he
develops an appropriate plan of action for his nursing
interventions. Perhaps the CIS in the agency supports
the collection of data about patients in a relational
database, providing an opportunity for data mining by
nursing administrators or nurse researchers. In this
way, administrators and researchers can glean
information about best practices and determine which
improvements are necessary to deliver the best and

most effective nursing care (Swan, Lang, & McGinley,
2004).

The future of nursing science and nursing informatics is
closely associated with nursing education and nursing
research. Skiba (2007) suggested that techno-savvy
and well-informed faculty who can demonstrate the
appropriate use of technologies to enhance the
delivery of nursing care are needed. Along those lines,
Whitman-Price, Kennedy, and Godwin (2012)
conducted research among senior nursing students to
determine perceptions of personal phone use to
access healthcare information during clinical. Their
study indicated that ready access to electronic
resources enhanced clinical decision making and
confidence in patient care. Girard (2007) discussed
cutting-edge operating room technologies, such as
nanosurgery using nanorobots, smart fabrics that aid in
patient assessment during surgery, biopharmacy
techniques for the safe and effective delivery of
anesthesia, and virtual reality training. She made an
extremely provocative point about nursing education:
“Educators will need to expand their knowledge and
teach for the future and not the past. They must take
heed that the old tried-and-true nursing education
methods and curriculum that has lasted 100 years will
have to change, and that change will be mandated for
all areas of nursing” (p. 353). Bassendowski (2007)
specifically addressed the potential for the generation
of knowledge in educational endeavors as faculty apply

new technologies to teaching and the focus shifts away
from individual to group instruction that promotes
sharing and processing of knowledge.

Several key national groups continue to promote the
inclusion of informatics content in nursing education
programs. These initiatives include the Vision Series by
the National League for Nursing (NLN; 2015);
recommendations in the Quality and Safety Education
for Nurses (QSEN) learning modules (2014a); the
Technology Informatics Guiding Education Reform
(TIGER) Initiative (Healthcare Information and
Management Systems Society, 2016); and Nursing
Informatics Deep Dive by the American Association of
Colleges of Nursing (AACN; 2016). These
organizations focus on the need to integrate
informatics competencies into nursing curricula to
prepare future nurses for the tasks of managing data,
information, and knowledge; alleviating errors and
promoting safety; supporting decision making; and
improving the quality of patient care. Nurse educators
are challenged to prepare informatics-competent
nurses who can practice safely in technology-laden
settings.

The TIGER (2007) initiative identified steps toward a
10-year vision and stated a key purpose: “to create a
vision for the future of nursing that bridges the quality
chasm with information technology, enabling nurses to
use informatics in practice and education to provide

safer, higher-quality patient care” (p. 4). The pillars of
the TIGER vision include the following:

Management and Leadership: Revolutionary
leadership that drives, empowers, and executes the
transformation of health care.
Education: Collaborative learning communities that
maximize the possibilities of technology toward
knowledge development and dissemination, driving
rapid deployment and implementation of best
practices.
Communication and Collaboration: Standardized,
person-centered, technology-enabled processes to
facilitate teamwork and relationships across the
continuum of care.
Informatics Design: Evidence-based, interoperable
intelligence systems that support education and
practice to foster quality care and safety.
Information Technology: Smart, people-centered,
affordable technologies that are universal, useable,
useful, and standards based.
Policy: Consistent, incentives-based initiatives
(organizational and governmental) that support
advocacy and coalition-building, achieving and
resourcing an ethical culture of safety.
Culture: A respectful, open system that leverages
technology and informatics across multiple
disciplines in an environment where all
stakeholders trust each other to work together
toward the goal of high quality and safety (p. 4).

The Essentials of Baccalaureate Education for
Professional Nursing Practice (AACN, 2008, pp. 18–
19) includes the following technology-related outcomes
for baccalaureate nursing graduates:

1. Demonstrate skills in using patient care
technologies, information systems, and
communication devices that support safe
nursing practice.

2. Use telecommunication technologies to assist in
effective communication in a variety of
healthcare settings.

3. Apply safeguards and decision-making support
tools embedded in patient care technologies and
information systems to support a safe practice
environment for both patients and healthcare
workers.

4. Understand the use of CIS to document
interventions related to achieving nurse-sensitive
outcomes.

5. Use standardized terminology in a care
environment that reflects nursing’s unique
contribution to patient outcomes.

6. Evaluate data from all relevant sources,
including technology, to inform the delivery of
care.

7. Recognize the role of information technology in
improving patient care outcomes and creating a
safe care environment.

8. Uphold ethical standards related to data security,
regulatory requirements, confidentiality, and
clients’ right to privacy.

9. Apply patient care technologies as appropriate
to address the needs of a diverse patient
population.

10. Advocate for the use of new patient care
technologies for safe, quality care.

11. Recognize that redesign of workflow and care
processes should precede implementation of
care technology to facilitate nursing practice.

12. Participate in the evaluation of information
systems in practice settings through policy and
procedure development.

The report suggests the following sample content for
achieving these student outcomes (AACN, 2008, pp.
19–20):

Use of patient care technologies (e.g., monitors,
pumps, computer-assisted devices)
Use of technology and information systems for
clinical decision making
Computer skills that may include basic software,
spreadsheet, and healthcare databases
Information management for patient safety
Regulatory requirements through electronic data-
monitoring systems
Ethical and legal issues related to the use of
information technology, including copyright, privacy,

and confidentiality issues
Retrieval information systems, including access,
evaluation of data, and application of relevant data
to patient care
Online literature searches
Technological resources for evidence-based
practice
Web-based learning and online literature searches
for self and patient use
Technology and information systems safeguards
(e.g., patient monitoring, equipment, patient
identification systems, drug alerts and IV systems,
and bar coding)
Interstate practice regulations (e.g., licensure,
telehealth)
Technology for virtual care delivery and monitoring
Principles related to nursing workload measurement
and resources and information systems
Information literacy
Electronic health record and physician order entry
Decision support tools
Role of the nurse informaticist in the context of
health informatics and information systems

The Informatics and Healthcare Technologies
Essentials of Master’s Education in Nursing includes
the following elements:

Essential V: Informatics and Healthcare
Technologies

Rationale

Informatics and healthcare technologies
encompass five broad areas:

Use of patient care and other technologies to
deliver and enhance care

Communication technologies to integrate and
coordinate care

Data management to analyze and improve
outcomes of care

Health information management for evidence-
based care and health education

Facilitation and use of electronic health records
to improve patient care (AACN, 2011, pp. 17–
18)

Quality and Safety Education
for Nurses
As nursing science evolves, it is critical that patient
care improves. Sometimes, unfortunately, patient care
is less-than-adequate and is unsafe. Therefore, quality
and safety have become paramount. The QSEN
Institute project seeks to prepare future nurses who will
have the knowledge, skills, and attitudes (KSAs)
necessary to continuously improve the quality and

safety of the healthcare systems within which they
work.

Prelicensure informatics KSAs include the following
(QSEN Institute, 2014c):

INFORMATICS

Knowledge Skills Attitudes

Explain why information

and technology skills are

essential for safe patient

care

Seek

education

about how

information is

managed in

care settings

before

providing care

Apply

technology

and

information

management

tools to

support safe

processes of

care

Appreciate the

necessity for all

health professionals

to seek lifelong,

continuous learning

of information

technology skills

Identify essential

information that must be

available in a common

database to support

patient care

Contrast benefits and

Navigate the

electronic

health record

Document and

plan patient

care in an

Value technologies

that support clinical

decision making,

error prevention, and

care coordination

Protect the

limitations of different

communication

technologies and their

impact on safety and

quality

electronic

health record

Employ

communication

technologies to

coordinate

care for

patients

confidentiality of

protected health

information in

electronic health

records

Describe examples of

how technology and

information management

are related to the quality

and safety of patient care

Recognize the time,

effort, and skill required

for computers,

databases, and other

technologies to become

reliable and effective tools

for patient care

Respond

appropriately

to clinical

decision-

making

supports and

alerts

Use

information

management

tools to

monitor

outcomes of

care

processes

Use high

quality

electronic

sources of

healthcare

information

Value nurses’

involvement in

design, selection,

implementation, and

evaluation of

information

technologies to

support patient care

Definition: Use information and technology to communicate, manage
knowledge, mitigate error, and support decision making.

Reproduced from Cronenwett, L., Sherwood, G., Barnsteiner J.,

Disch, J., Johnson, J., Mitchell, P., . . . Warren, J. (2007). Quality and

safety education for nurses. Nursing Outlook, 55(3), 122–131.

Copyright 2007, with permission from Elsevier.

Graduate-level informatics KSAs include the following
(QSEN Institute, 2014b):

INFORMATICS

Knowledge Skills Attitudes

Contrast benefits and

limitations of common

information technology

strategies used in the

delivery of patient care

Evaluate the strengths

and weaknesses of

information systems

used in patient care

Participate in the

selection, design,

implementation,

and evaluation of

information

systems

Communicate the

integral role of

information

technology in

nurses’ work

Model behaviors

that support

implementation

and appropriate

use of electronic

health records

Assist team

members to adopt

information

technology by

piloting and

Value the use of

information and

communication

technologies in

patient care

evaluating

proposed

technologies

Formulate essential

information that must

be available in a

common database to

support patient care in

the practice specialty

Evaluate benefits and

limitations of different

communication

technologies and their

impact on safety and

quality

Promote access to

patient care

information for all

professionals who

provide care to

patients

Serve as a

resource for how to

document nursing

care at basic and

advanced levels

Develop

safeguards for

protected health

information

Champion

communication

technologies that

support clinical

decision making,

error prevention,

care coordination,

and protection of

patient privacy

Appreciate the

need for consensus

and collaboration in

developing systems

to manage

information for

patient care

Value the

confidentiality and

security of all

patient records

Describe and critique

taxonomic and

terminology systems

used in national efforts

to enhance

interoperability of

information systems

Access and

evaluate high

quality electronic

sources of

healthcare

information

Participate in the

Value the

importance of

standardized

terminologies in

conducting

searches for patient

information

and knowledge

management systems

design of clinical

decision-making

supports and alerts

Search, retrieve,

and manage data

to make decisions

using information

and knowledge

management

systems

Anticipate

unintended

consequences of

new technology

Appreciate the

contribution of

technological alert

systems

Appreciate the time,

effort, and skill

required for

computers,

databases, and

other technologies

to become reliable

and effective tools

for patient care

Definition: Use information and technology to communicate, manage
knowledge, mitigate error, and support decision making.

Reproduced from Cronenwett, L., Sherwood, G., Pohl, J., Barnsteiner

J., Moore, D., Sullivan, D., . . . Warren, J. (2009). Quality and safety

education for nurses. Nursing Outlook, 57(6), 338–348. Copyright

2009, with permission from Elsevier.

This text is designed to include the necessary content
to prepare nurses for practice in the ever-changing and
technology-laden healthcare environments. Informatics
competence has been recognized as necessary in
order to enhance clinical decision making and improve
patient care for many years. This is evidenced by
Goossen (2000), who reflected on the need for
research in this area and believed that the focus of

nursing informatics research should be on the
structuring and processing of patient information and
the ways that these endeavors inform nursing decision
making in clinical practice. The increased use of
technology to enhance nursing practice, nursing
education, and nursing research will open new
avenues for acquiring, processing, generating, and
disseminating knowledge.

In the future, nursing research will make significant
contributions to the development of nursing science.
Technologies and translational research will abound,
and clinical practices will continue to be evidence
based, thereby improving patient outcomes and
decreasing safety concerns. Schools of nursing will
embrace nursing science as they strive to meet the
needs of changing student populations and the
increasing complexity of healthcare environments.

Summary
Nursing science influences all areas of nursing
practice. This chapter provided an overview of nursing
science and considered how nursing science relates to
typical nursing practice roles, nursing education,
informatics, and nursing research. The Foundation of
Knowledge model was introduced as the organizing
conceptual framework for this text. Finally, the
relationship of nursing science to nursing informatics
was discussed. In subsequent chapters the reader will

learn more about how nursing informatics supports
nurses in their many and varied roles. In an ideal world,
nurses would embrace nursing science as knowledge
users, knowledge managers, knowledge developers,
knowledge engineers, and knowledge workers.

THOUGHT-PROVOKING QUESTIONS

1. Imagine you are in a social situation and
someone asks you, “What does a nurse
do?” Think about how you will capture
and convey the richness that is nursing
science in your answer.

2. Choose a clinical scenario from your
recent experience and analyze it using
the Foundation of Knowledge model. How
did you acquire knowledge? How did you
process knowledge? How did you
generate knowledge? How did you
disseminate knowledge? How did you use
feedback, and what was the effect of the
feedback on the foundation of your
knowledge?

References
American Association of Colleges of

Nursing (AACN). (2008, October 20).
The essentials of baccalaureate

education for professional nursing
practice. Retrieved from
http://www.aacn.nche.edu/education-
resources/BaccEssentials08.pdf

American Association of Colleges of
Nursing (AACN). (2011, March 21).
The essentials of master’s education in
nursing. Retrieved from
http://www.aacn.nche.edu/education-
resources/MastersEssentials11.pdf

American Association of Colleges of
Nursing (AACN). (2016). Background
and overview: Nursing informatics
Deep Dive. Retrieved from
http://www.aacn.nche.edu/qsen-
informatics/background-overview

American Nurses Association. (2016).
What is nursing? Retrieved from
http://www.nursingworld.org/EspeciallyForYou/What-
is-Nursing

Bassendowski, S. (2007). NursingQuest:
Supporting an analysis of nursing
issues. Journal of Nursing Education,

46(2), 92–95. Retrieved from
Education Module database [document
ID: 1210832211].

Cronenwett, L., Sherwood, G., Barnsteiner
J., Disch, J., Johnson, J., Mitchell, P., .
. . Warren, J. (2007). Quality and
safety education for nurses. Nursing
Outlook, 55(3), 122–131.

Girard, N. (2007). Science fiction comes to
the OR. Association of Operating
Room Nurses. AORN Journal, 86(3),
351–353. Retrieved from Health
Module database [document ID:
1333149261].

Goossen, W. (2000). Nursing informatics
research. Nurse Researcher, 8(2), 42.
Retrieved from ProQuest Nursing &
Allied Health Source database
[document ID: 67258628].

Healthcare Information and Management
Systems Society. (2016). The TIGER
initiative. Retrieved from

http://www.himss.org/professional-
development/tiger-initiative

National League for Nursing (NLN).
(2015). A vision for the changing
faculty role: Preparing students for the
technological world of health care.
Retrieved from
https://www.nln.org/docs/default-
source/about/nln-vision-series-
(position-statements)/a-vision-for-
the-changing-faculty-role-preparing-
students-for-the-technological-
world-of-health-care.pdf?sfvrsn=0

Quality and Safety Information for Nurses
(QSEN) Institute. (2014a). Courses:
Learning modules. Retrieved from
http://www.qsen.org/courses/learning-
modules

QSEN Institute. (2014b). Graduate KSAs.
Retrieved from
http://www.qsen.org/competencies/graduate-
ksas

QSEN Institute. (2014c). Pre-licensure
KSAs. Retrieved from
http://www.qsen.org/competencies/pre-
licensure-ksas

Skiba, D. (2007). Faculty 2.0: Flipping the
novice to expert continuum. Nursing
Education Perspectives, 28(6), 342–
344. Retrieved from ProQuest Nursing
& Allied Health Source database
[document ID: 1401240241].

Swan, B., Lang, N., & McGinley, A.
(2004). Access to quality health care:
Links between evidence, nursing
language, and informatics. Nursing
Economic$, 22(6), 325–332. Retrieved
from Health Module database
[document ID: 768191851].

Technology Informatics Guiding Education
Reform. (2007). Evidence and
informatics transforming nursing: 3-
year action steps toward a 10-year
vision. Retrieved from
http://www.aacn.nche.edu/education-
resources/TIGER.pdf

Whitman-Price, R., Kennedy, L., &
Godwin, C. (2012). Use of personal
phones by senior nursing students to
access health care information during
clinical education: Staff nurses’ and
students’ perceptions. Journal of
Nursing Education, 51(11), 642–646.

CHAPTER 2: Introduction
to Information,
Information Science, and
Information Systems

Kathleen Mastrian and Dee McGonigle

Objectives
1. Reflect on the progression from data to

information to knowledge.
2. Describe the term information.
3. Assess how information is acquired.
4. Explore the characteristics of quality

information.
5. Describe an information system.
6. Explore data acquisition or input and

processing or retrieval, analysis, and
synthesis of data.

7. Assess output or reports, documents,
summaries, alerts, and outcomes.

8. Describe information dissemination and
feedback.

9. Define information science.
10. Assess how information is processed.
11. Explore how knowledge is generated in

information science.

Key Terms
» Acquisition

» Alert

» Analysis

» Chief information officers

» Chief technical officers

» Chief technology officers

» Cloud computing

» Cognitive science

» Communication science

» Computer-based information systems

» Computer science

» Consolidated Health Informatics

» Data

» Dissemination

» Document

» Electronic health records

» Federal Health Information Exchange

» Feedback

» Health information exchange

» Health Level Seven

» Indiana Health Information Exchange

» Information

» Information science

» Information systems

» Information technology

» Input

» Interfaces

» Internet2

» Internet of Things (IoT)

» Knowledge

» Knowledge worker

» Library science

» Massachusetts Health Data Consortium

» National Health Information
Infrastructure

» National Health Information Network

» New England Health EDI Network

» Next-Generation Internet

» Outcome

» Output

» Processing

» Rapid Syndromic Validation Project

» Report

» Social sciences

» Stakeholders

» Summaries

» Synthesis

» Telecommunications

Introduction
This chapter explores information, information systems
(ISs), and information science as one of the building
blocks of informatics. (Refer to Figure 2-1.) The key
word here, of course, is information. Information and

information processing are central to the work of health
care. A healthcare professional is known as a
knowledge worker because he or she deals with and
processes information on a daily basis to make it
meaningful and inform his or her practice.

Figure 2-1 Building Blocks of Nursing Informatics

Healthcare information is complex, and many concerns
and issues arise with healthcare information, such as
ownership, access, disclosure, exchange, security,
privacy, disposal, and dissemination. The widespread

implementation of electronic health records (EHRs)
has promoted collaboration among public- and private-
sector stakeholders on a wide-ranging variety of
healthcare information solutions. Some of these
initiatives include Health Level Seven (HL7), the eGov
initiative by Consolidated Health Informatics (CHI),
the National Health Information Infrastructure
(NHII), the National Health Information Network
(NHIN), Next-Generation Internet (NGI), Internet2,
and iHealth record. There are also health information
exchange (HIE) systems, such as Connecting for
Health, the eHealth initiative, the Federal Health
Information Exchange (FHIE), the Indiana Health
Information Exchange (IHIE), the Massachusetts
Health Data Consortium (MHDC), the New England
Health EDI Network (NEHEN), the State of New
Mexico Rapid Syndromic Validation Project (RSVP),
the Southeast Michigan e-Prescribing Initiative, and the
Tennessee Volunteer eHealth Initiative (Goldstein,
Groen, Ponkshe, & Wine, 2007). Many of these were
sparked by the HITECH Act of 2011, which set the
2014 deadline for implementing EHRs and provided
the impetus for HIE initiatives.

It is quite evident from the previous brief listing that
there is a need to remedy healthcare information
technology (IT) concerns, challenges, and issues
faced today. One of the main issues deals with how
healthcare information is managed to make it
meaningful. It is important to understand how people

obtain, manipulate, use, share, and dispose of
information. This chapter deals with the information
piece of this complex puzzle.

Information
Suppose someone states the number 99.5. What does
that mean? It could be a radio station or a score on a
test. Now suppose someone says that Ms. Howsunny’s
temperature is 99.5°F—what does that convey? It is
then known that 99.5 is a person’s temperature. The
data (99.5) were processed to the information that
99.5° is a specific person’s temperature. Data are raw
facts. Information is processed data that has meaning.
Healthcare professionals constantly process data and
information to provide the best possible care for their
patients.

Many types of data exist, such as alphabetic, numeric,
audio, image, and video data. Alphabetic data refer to
letters, numeric data refer to numbers, and
alphanumeric data combine both letters and numbers.
This includes all text and the numeric outputs of digital
monitors. Some of the alphanumeric data encountered
by healthcare professionals are in the form of patients’
names, identification numbers, or medical record
numbers. Audio data refer to sounds, noises, or tones
—for example, monitor alerts or alarms, taped or
recorded messages, and other sounds. Image data
include graphics and pictures, such as graphic monitor

displays or recorded electrocardiograms, radiographs,
magnetic resonance imaging (MRI) outputs, and
computed tomography (CT) scans. Video data refer to
animations, moving pictures, or moving graphics. Using
these data, one may review the ultrasound of a
pregnant patient, examine a patient’s echocardiogram,
watch an animated video for professional development,
or learn how to operate a new technology tool, such as
a pump or monitoring system. The data we gather,
such as heart and lung sounds or X-rays, help us
produce information. For example, if a patient’s X-rays
show a fracture, it is interpreted into information such
as spiral, compound, or hairline. This information is
then processed into knowledge and a treatment plan is
formulated based on the healthcare professional’s
wisdom.

The integrity and quality of the data, rather than the
form, are what matter. Integrity refers to whole,
complete, correct, and consistent data (Figure 2-2).
Data integrity can be compromised through human
error; viruses, worms, or other computer bugs;
hardware failures or crashes; transmission errors; or
hackers entering the system. Figure 2-3 illustrates
some ways that data can be compromised. Information
technologies help to decrease these errors by putting
into place safeguards, such as backing up files on a
routine basis, error detection for transmissions, and
user interfaces that help people enter the data
correctly. High-quality data are relevant and accurately

represent their corresponding concepts. Data are dirty
when a database contains errors, such as duplicate,
incomplete, or outdated records. One author (D.M.)
found 50 cases of tongue cancer in a database she
examined for data quality. When the records were
tracked down and analyzed, and the dirty data were
removed, only one case of tongue cancer remained. In
this situation, the data for the same person had been
entered erroneously 49 times. The major problem was
with the patient’s identification number and name: The
number was changed or his name was misspelled
repeatedly. If researchers had just taken the number of
cases in that defined population as 50, they would
have concluded that tongue cancer was an epidemic,
resulting in flawed information that is not meaningful.
As this example demonstrates, it is imperative that data
be clean if the goal is quality information. The data that
are processed into information must be of high quality
and integrity to create meaning to inform assessments
and decision making.

Figure 2-2 Data Integrity

Figure 2-3 Threats to Data Integrity

To be valuable and meaningful, information must be of
good quality. Its value relates directly to how the
information informs decision making. Characteristics of
valuable, quality information include accessibility,
security, timeliness, accuracy, relevancy,
completeness, flexibility, reliability, objectivity, utility,
transparency, verifiability, and reproducibility.

Accessibility is a must; the right user must be able to
obtain the right information at the right time and in the
right format to meet his or her needs. Getting
meaningful information to the right user at the right time
is as vital as generating the information in the first
place. The right user refers to an authorized user who
has the right to obtain the data and information he or
she is seeking. Security is a major challenge because
unauthorized users must be blocked while the
authorized user is provided with open, easy access
(see the Electronic Security chapter).

Timely information means that the information is
available when it is needed for the right purpose and at
the right time. Knowing who won the lottery last week
does not help one to know if the person won it today.
Accurate information means that there are no errors in
the data and information. Relevant information is a
subjective descriptor, in that the user must have
information that is relevant or applicable to his or her
needs. If a healthcare provider is trying to decide
whether a patient needs insulin and only the patient’s

CT scan information is available, this information is not
relevant for that current need. However, if one needed
information about the CT scan, the information is
relevant.

Complete information contains all of the necessary
essential data. If the healthcare provider needs to
contact the only relative listed for the patient and his or
her contact information is listed but the approval for
that person to be a contact is missing, this information
is considered incomplete. Flexible information means
that the information can be used for a variety of
purposes. Information concerning the inventory of
supplies on a nursing unit, for example, can be used by
nurses who need to know if an item is available for use
for a patient. The nurse manager accesses this
information to help decide which supplies need to be
ordered, to determine which items are used most
frequently, and to do an economic assessment of any
waste.

Reliable information comes from reliable or clean data
gathered from authoritative and credible sources.
Objective information is as close to the truth as one
can get; it is not subjective or biased, but rather is
factual and impartial. If someone states something, it
must be determined whether that person is reliable and
whether what he or she is stating is objective or tainted
by his or her own perspective.

Utility refers to the ability to provide the right
information at the right time to the right person for the
right purpose. Transparency allows users to apply their
intellect to accomplish their tasks while the tools
housing the information disappear into the background.
Verifiable information means that one can check to
verify or prove that the information is correct.
Reproducibility refers to the ability to produce the same
information again.

Information is acquired either by actively looking for it
or by having it conveyed by the environment. All of the
senses (vision, hearing, touch, smell, and taste) are
used to gather input from the surrounding world, and
as technologies mature, more and more input will be
obtained through the senses. Currently, people receive
information from computers (output) through vision,
hearing, or touch (input); and the response (output) to
the computer (input) is the interface with technology.
Gesture recognition is increasing, and interfaces that
incorporate it will change the way people become
informed. Many people access the Internet on a daily
basis seeking information or imparting information.
Individuals are constantly becoming informed,
discovering, or learning; becoming reinformed,
rediscovering, or relearning; and purging what has
been acquired. The information acquired through these
processes is added to the personal knowledge base.
Knowledge is the awareness and understanding of a
set of information and ways that information can be

made useful to support a specific task or arrive at a
decision. This knowledge building is an ongoing
process engaged in while a person is conscious and
going about his or her normal daily activities.

Information Science
Information science has evolved over the last 50 or so
years as a field of scientific inquiry and professional
practice. It can be thought of as the science of
information, studying the application and usage of
information and knowledge in organizations and the
interface or interaction between people, organizations,
and ISs. This extensive, interdisciplinary science
integrates features from cognitive science,
communication science, computer science, library
science, and the social sciences. Information science
is primarily concerned with the input, processing,
output, and feedback of data and information through
technology integration with a focus on comprehending
the perspective of the stakeholders involved and then
applying IT as needed. It is systemically based, dealing
with the big picture rather than individual pieces of
technology.

Information science can also be related to determinism.
Specifically, it is a response to technologic determinism
—the belief that technology develops by its own laws,
that it realizes its own potential, limited only by the
material resources available, and must therefore be

regarded as an autonomous system controlling and
ultimately permeating all other subsystems of society
(Web Dictionary of Cybernetics and Systems, 2007,
para. 1).

This approach sets the tone for the study of information
as it applies to itself, the people, the technology, and
the varied sciences that are contextually related
depending on the needs of the setting or organization;
what is important is the interface between the
stakeholders and their systems, and the ways they
generate, use, and locate information. According to
Cornell University (2010), “Information Science brings
together faculty, students and researchers who share
an interest in combining computer science with the
social sciences of how people and society interact with
information” (para. 1). Information science is an
interdisciplinary, people-oriented field that explores and
enhances the interchange of information to transform
society, communication science, computer science,
cognitive science, library science, and the social
sciences. Society is dominated by the need for
information, and knowledge and information science
focus on systems and individual users by fostering
user-centered approaches that enhance society’s
information capabilities, effectively and efficiently
linking people, information, and technology. This
impacts the configuration and mix of organizations and
influences the nature of work—namely, how knowledge

workers interact with and produce meaningful
information and knowledge.

Information Processing
Information science enables the processing of
information. This processing links people and
technology. Humans are organic ISs, constantly
acquiring, processing, and generating information or
knowledge in their professional and personal lives. This
high degree of knowledge, in fact, characterizes
humans as extremely intelligent organic machines. The
premise of this text revolves around this concept, and
the text is organized on the basis of the Foundation of
Knowledge model: knowledge acquisition, knowledge
processing, knowledge generation, and knowledge
dissemination.

Information is data that are processed using
knowledge. For information to be valuable or
meaningful, it must be accessible, accurate, timely,
complete, cost-effective, flexible, reliable, relevant,
simple, verifiable, and secure. Knowledge is the
awareness and understanding of an information set
and ways that information can be made useful to
support a specific task or arrive at a decision. As an
example, if an architect were going to design a
building, part of the knowledge necessary for
developing a new building is understanding how the
building will be used, what size of building is needed

compared to the available building space, and how
many people will have or need access to this building.
Therefore, the work of choosing or rejecting facts
based on their significance or relevance to a particular
task, such as designing a building, is also based on a
type of knowledge used in the process of converting
data into information. Information can then be
considered data made functional through the
application of knowledge. The knowledge used to
develop and glean knowledge from valuable
information is generative (having the ability to originate
and produce or generate) in nature. Knowledge must
also be viable. Knowledge viability refers to
applications that offer easily accessible, accurate, and
timely information obtained from a variety of resources
and methods and presented in a manner so as to
provide the necessary elements to generate
knowledge.

Information science and computational tools are
extremely important in enabling the processing of data,
information, and knowledge in health care. In this
environment, the hardware, software, networking,
algorithms, and human organic ISs work together to
create meaningful information and generate
knowledge. The links between information processing
and scientific discovery are paramount. However,
without the ability to generate practical results that can
be disseminated, the processing of data, information,
and knowledge is for naught. It is the ability of

machines (inorganic ISs) to support and facilitate the
functioning of people (human organic ISs) that refines,
enhances, and evolves nursing practice by generating
knowledge. This knowledge represents five rights: the
right information, accessible by the right people in the
right settings, applied the right way at the right time.

An important and ongoing process is the struggle to
integrate new knowledge and old knowledge so as to
enhance wisdom. Wisdom is the ability to act
appropriately; it assumes actions directed by one’s own
wisdom. Wisdom uses knowledge and experience to
heighten common sense, and uses insight to exercise
sound judgment in practical matters. It is developed
through knowledge, experience, insight, and reflection.
Wisdom is sometimes thought of as the highest form of
common sense, resulting from accumulated knowledge
or erudition (deep, thorough learning) or enlightenment
(education that results in understanding and the
dissemination of knowledge). It is the ability to apply
valuable and viable knowledge, experience,
understanding, and insight while being prudent and
sensible. Knowledge and wisdom are not synonymous,
because knowledge abounds with others’ thoughts and
information, whereas wisdom is focused on one’s own
mind and the synthesis of one’s own experience,
insight, understanding, and knowledge.

If clinicians are inundated with data without the ability
to process it, the situation results in too much data and

too little wisdom. Consequently, it is crucial that
clinicians have viable ISs at their fingertips to facilitate
the acquisition, sharing, and use of knowledge while
maturing wisdom; this process leads to empowerment.

Information Science and the
Foundation of Knowledge
Information science is a multidisciplinary science that
encompasses aspects of computer science, cognitive
science, social science, communication science, and
library science to deal with obtaining, gathering,
organizing, manipulating, managing, storing, retrieving,
recapturing, disposing of, distributing, and broadcasting
information. Information science studies everything that
deals with information and can be defined as the study
of ISs. This science originated as a subdiscipline of
computer science, as practitioners sought to
understand and rationalize the management of
technology within organizations. It has since matured
into a major field of management and is now an
important area of research in management studies.
Moreover, information science has expanded its scope
to examine the human–computer interaction,
interfacing, and interaction of people, ISs, and
corporations. It is taught at all major universities and
business schools worldwide.

Modern-day organizations have become intensely
aware of the fact that information and knowledge are
potent resources that must be cultivated and honed to
meet their needs. Thus information science or the
study of ISs—that is, the application and usage of
knowledge—focuses on why and how technology can
be put to best use to serve the information flow within
an organization.

Information science impacts information interfaces,
influencing how people interact with information and
subsequently develop and use knowledge. The
information a person acquires is added to his or her
knowledge base. Knowledge is the awareness and
understanding of an information set and ways that
information can be made useful to support a specific
task or arrive at a decision.

Healthcare organizations are affected by and rely on
the evolution of information science to enhance the
recording and processing of routine and intimate
information while facilitating human-to-human and
human-to-systems communications, delivery of
healthcare products, dissemination of information, and
enhancement of the organization’s business
transactions. Unfortunately, the benefits and
enhancements of information science technologies
have also brought to light new risks, such as glitches
and loss of information and hackers who can steal
identities and information. Solid leadership, guidance,

and vision are vital to the maintenance of cost-effective
business performance and cutting-edge, safe
information technologies for the organization. This field
studies all facets of the building and use of information.
The emergence of information science and its impact
on information have also influenced how people
acquire and use knowledge.

Information science has already had a tremendous
impact on society and will undoubtedly expand its
sphere of influence further as it continues to evolve and
innovate human activities at all levels. What visionaries
only dreamed of is now possible and part of reality. The
future has yet to fully unfold in this important arena.

Introduction to Information
Systems
Consider the following scenario: You have just been
hired by a large healthcare facility. You enter the
personnel office and are told that you must learn a new
language to work on the unit where you have been
assigned. This language is used just on this unit. If you
had been assigned to a different unit, you would have
to learn another language that is specific to that unit,
and so on. Because of the differences in various units’
languages, interdepartmental sharing and information
exchange (known as interoperability) are severely
hindered.

This scenario might seem far-fetched, but it is actually
how workers once operated in health care—in silos.
There was a system for the laboratory, one for finance,
one for clinical departments, and so on. As healthcare
organizations have come to appreciate the importance
of communication, tracking, and research, however,
they have developed integrated information systems
that can handle the needs of the entire organization.

Information and IT have become major resources for
all types of organizations, and health care is no
exception (see Box 2-1). Information technologies help
to shape a healthcare organization, in conjunction with
personnel, money, materials, and equipment. Many
healthcare facilities have hired chief information
officers (CIOs) or chief technical officers (CTOs),
also known as chief technology officers. The CIO is
involved with the IT infrastructure, and this role is
sometimes expanded to include the position of chief
knowledge officer. The CTO is focused on
organizationally based scientific and technical issues
and is responsible for technological research and
development as part of the organization’s products and
services. The CTO and CIO must be visionary leaders
for the organization, because so much of the business
of health care relies on solid infrastructures that
generate potent and timely information and knowledge.
The CTO and CIO are sometimes interchangeable
positions, but in some organizations the CTO reports to
the CIO. These positions will become critical roles as

companies continue to shift from being product
oriented to knowledge oriented, and as they begin
emphasizing the production process itself rather than
the product. In health care, ISs must be able to handle
the volume of data and information necessary to
generate the needed information and knowledge for
best practices, because the goal is to provide the
highest quality of patient care.

BOX 2-1 EXAMPLES OF INFORMATION

SYSTEMS

Information
System

How It Is Used

Clinical

Information

System

(CIS)

Comprehensive and integrative system that

manages the administrative, financial, and

clinical aspects of a clinical facility; a CIS

should help to link financial and clinical

outcomes. An example is the EHR.

Decision

Support

System

(DSS)

Organizes and analyzes information to help

decision makers formulate decisions when

they are unsure of their decision’s possible

outcomes. After gathering relevant and

useful information, develops “what if”

models to analyze the options or choices

and alternatives.

Executive

Support

System

Collects, organizes, analyzes, and

summarizes vital information to help

executives or senior management with

strategic decision making. Provides a quick

view of all strategic business activities.

Geographic

Information

System

(GIS)

Collects, manipulates, analyzes, and

generates information related to geographic

locations or the surface of the earth;

provides output in the form of virtual models,

maps, or lists.

Management

Information

Systems

(MIS)

Provides summaries of internal sources of

information, such as information from the

transaction processing system, and

develops a series of routine reports for

decision making.

Office

Systems

Facilitates communication and enhances

the productivity of users needing to process

data and information.

Transaction

Processing

System

(TPS)

Processes and records routine business

transactions, such as billing systems that

create and send invoices to customers, and

payroll systems that generate employees’

pay stubs and wage checks and calculate

tax payments.

Hospital

Information

System

(HIS)

Manages the administrative, financial, and

clinical aspects of a hospital enterprise. It

should help to link financial and clinical

outcomes.

Information Systems

ISs can be manually based, but for the purposes of this
text, the term refers to computer-based information
systems (CBISs). According to Jessup and Valacich
(2008), CBISs “are combinations of hardware, software
and telecommunications networks that people build
and use to collect, create, and distribute useful data,
typically in organizational settings” (p. 10). Along the
same lines, ISs are also defined as “a collection of
interconnected elements that gather, process, store
and distribute data and information while providing a
feedback structure to meet an objective” (Stair &
Reynolds, 2016, p. 4). ISs are designed for specific
purposes within organizations. They are only as
functional as the decision-making capabilities, problem-
solving skills, and programming potency built in and the
quality of the data and information input into them. The
capability of the IS to disseminate, provide feedback,
and adjust the data and information based on these
dynamic processes is what sets them apart. The IS
should be a user-friendly entity that provides the right
information at the right time and in the right place.

An IS acquires data or inputs; processes data through
the retrieval, analysis, or synthesis of those data;
disseminates or outputs information in the form of
reports, documents, summaries, alerts, prompts, or
outcomes; and provides for responses or feedback.
Input or data acquisition is the activity of collecting and
acquiring raw data. Input devices include combinations
of hardware, software, and telecommunications,

including keyboards, light pens, touch screens, mice or
other pointing devices, automatic scanners, and
machines that can read magnetic ink characters or
lettering. To watch a pay-per-view movie, for example,
the viewer must first input the chosen movie, verify the
purchase, and have a payment method approved by
the vendor. The IS must acquire this information before
the viewer can receive the movie.

Processing—the retrieval, analysis, or synthesis of
data—refers to the alteration and transformation of the
data into helpful or useful information and outputs. The
processing of data can range from storing it for future
use; to comparing the data, making calculations, or
applying formulas; to taking selective actions.
Processing devices consist of combinations of
hardware, software, and telecommunications and
include processing chips where the central processing
unit (CPU) and main memory are housed. Some of
these chips are quite ingenious. According to Schupak
(2005), the bunny chip could save the pharmaceutical
industry money while sparing “millions of furry
creatures, with a chip that mimics a living organism”
(para. 1). The HµREL Corporation has developed
environments or biologic ISs that reside on chips and
actually mimic the functioning of the human body.
Researchers can use these environments to test for
both the harmful and beneficial effects of drugs,
including those that are considered experimental and
that could be harmful if used in human and animal

testing. Such chips also allow researchers to monitor a
drug’s toxicity in the liver and other organs.

One patented HµREL microfluidic “biochip” comprises
an arrangement of separate but fluidically
interconnected “organ” or “tissue” compartments. Each
compartment contains a culture of living cells drawn
from, or engineered to mimic the primary functions of,
the respective organ or tissue of a living animal.
Microfluidic channels permit a culture medium that
serves as a “blood surrogate” to recirculate just as in a
living system, driven by a microfluidic pump. The
geometry and fluidics of the device are fashioned to
simulate the values of certain related physiologic
parameters found in the living creature. Drug
candidates or other substrates of interest are added to
the culture medium and allowed to recirculate through
the device. The effects of drug compounds and their
metabolites on the cells within each respective organ
compartment are then detected by measuring or
monitoring key physiologic events. The cell types used
may be derived from either standard cell culture lines
or primary tissues (HµREL Corporation, 2010, para.
2–3). As new technologies such as the HµREL chips
continue to evolve, more and more robust ISs that can
handle a variety of biological and clinical applications
will be seen.

Returning to the movie rental example, the IS must
verify the data entered by the viewer and then process

the request by following the steps necessary to provide
access to the movie that was ordered. This processing
must be instantaneous in today’s world, where
everyone wants everything now. After the data are
processed, they are stored. In this case, the rental
must also be processed so the vendor receives
payment for the movie, whether electronically, via a
credit card or checking account withdrawal, or by
generating a bill for payment.

Output or dissemination produces helpful or useful
information that can be in the form of reports,
documents, summaries, alerts, or outcomes. A report
is designed to inform and is generally tailored to the
context of a given situation or user or user group.
Reports may include charts, figures, tables, graphics,
pictures, hyperlinks, references, or other
documentation necessary to meet the needs of the
user. A documentrepresents information that can be
printed, saved, emailed, or otherwise shared, or
displayed. Summaries are condensed versions of the
original information designed to highlight the major
points. An alert is comprised of warnings, feedback, or
additional information necessary to assist the user in
interacting with the system. An outcome is the
expected result of input and processing. Output
devices are combinations of hardware, software, and
telecommunications and include sound and speech
synthesis outputs, printers, and monitors.

Continuing with the movie rental example, the IS must
be able to provide the consumer with the movie
ordered when it is wanted and somehow notify the
purchaser that he or she has, indeed, purchased the
movie and is granted access. The IS must also be able
to generate payment either electronically or by
generating a bill, while storing the transactional record
for future use.

Feedback or responses are reactions to the inputting,
processing, and outputs. In ISs, feedback refers to
information from the system that is used to make
modifications in the input, processing actions, or
outputs. In the movie rental example, what if the
consumer accidentally entered the same movie order
three times, but really wanted to order the movie only
once? The IS would determine that more than one
movie order is out of range for the same movie order at
the same time and provide feedback. Such feedback is
used to verify and correct the input. If undetected, the
viewer’s error would result in an erroneous bill and
decreased customer satisfaction while creating more
work for the vendor, which would have to engage in
additional transactions with the customer to resolve this
problem. The Nursing Informatics Practice
Applications: Care Delivery section of this text provides
detailed descriptions of clinical ISs that operate on
these same principles to support healthcare delivery.

Summary
Information systems deal with the development, use,
and management of an organization’s IT infrastructure.
An IS acquires data or inputs; processes data through
the retrieval, analysis, or synthesis of those data;
disseminates or outputs in the form of reports,
documents, summaries, alerts, or outcomes; and
provides for responses or feedback. Quality decision-
making and problem-solving skills are vital to the
development of effective, valuable ISs. Today’s
organizations now recognize that their most precious
asset is their information, as represented by their
employees, experience, competence or know-how, and
innovative or novel approaches, all of which are
dependent on a robust information network that
encompasses the information technology
infrastructure.

In an ideal world, all ISs would be fluid in their ability to
adapt to any and all users’ needs. They would be
Internet oriented and global, where resources are
available to everyone. Think of cloud computing—it is
just the beginning point from which ISs will expand and
grow in their ability to provide meaningful information to
their users. As technologies advance, so will the skills
and capabilities to comprehend and realize what ISs
can become. As wearable tracking technologies and
other health-related mobile applications expand, more
robust and timely health data will be generated, and

this data will need to be processed into meaningful
information. “Practitioners and medical researchers can
look forward to technologies that enable them to apply
data analysis to develop new insights into finding cures
for difficult diseases. Healthcare CIOs and other IT
leaders can expect to be called upon to manage all the
new data and devices that will be transforming
healthcare as we know it” (Schindler, 2015, para. 2).
Devices with sensors communicating with each other is
known as the Internet of Things (IoT) and the future
possibilities for health care are tremendous. “The IoT
raises the bar—enabling connection and
communication from anywhere to anywhere—and
allows analytics to replace the human decision-maker”
(Glasser, 2015, para. 3). Essentially, the sensor-
collected data are transmitted to another technology,
triggering an action or an alert that prompts feedback
for an action. For example, “imagine a miniaturized,
implanted device or skin patch that monitors a
diabetic’s blood sugar, movement, skin temperature
and more, and informs an insulin pump to adjust the
dosage” (para. 8).

It is important to continue to develop and refine
functional, robust, visionary ISs that meet the current
meaningful information needs while evolving systems
that are even better prepared to handle future
information and knowledge needs of the healthcare
industry.

THOUGHT-PROVOKING QUESTIONS

1. How do you acquire information? Choose
2 hours out of your busy day and try to
notice all of the information that you
receive from your environment. Keep
diaries indicating where the information
came from and how you knew it was
information and not data.

2. Reflect on an IS with which you are
familiar, such as the automatic banking
machine. How does this IS function?
What are the advantages of using this
system (i.e., why not use a bank teller
instead)? What are the disadvantages?
Are there enhancements that you would
add to this system?

3. In health care, think about a typical day of
practice and describe the setting. How
many times does the nurse interact with
ISs? What are the ISs that we interact
with, and how do we access them? Are
they at the bedside, handheld, or station
based? How do their location and ease of
access impact nursing care?

4. Briefly describe an organization and
discuss how our need for information and
knowledge impacts the configuration and
interaction of that organization with other
organizations. Also discuss how the need

for information and knowledge influences
the nature of work or how knowledge
workers interact with and produce
information and knowledge in this
organization.

5. If you could meet only four of the rights
discussed in this chapter, which one
would you omit and why? Also, provide
your rationale for each right you chose to
meet.

References
Cornell University. (2010). Information

science. Retrieved from
http://www.infosci.cornell.edu

Goldstein, D., Groen, P., Ponkshe, S., &
Wine, M. (2007). Medical informatics
20/20. Sudbury, MA: Jones and
Bartlett.

Glasser, J. (2015). How the Internet of
Things will affect health care. Hospitals
and Health Networks. Retrieved from
http://www.hhnmag.com/articles/3438-

how-the-internet-of-things-will-
affect-health-care

HµREL Corporation. (2010). Human-
relevant: HµREL. Technology
overview. Retrieved from
http://www.hurelcorp.com/overview.php

Jessup, L., & Valacich, J. (2008).
Information systems today (3rd ed.).
Upper Saddle River, NJ: Pearson
Prentice Hall.

Schindler, E. (2015). Healthcare IT: Hot
Trends for 2016, Part 1.
InformationWeek. Retrieved from
http://www.informationweek.com/healthcare/leadership/healthcare-
it-hot-trends-for-2016-part-1/d/d-
id/1323722

Schupak, A. (2005). Technology: The
bunny chip. Forbes. Retrieved from
http://www.forbes.com/forbes/2005/0815/053.html

Stair, R., & Reynolds, G. (2016).
Principles of information systems (12th

ed.). Boston, MA: Cengage Learning.

Web Dictionary of Cybernetics and
Systems. (2007). Technological
determinism. Retrieved from
http://pespmc1.vub.ac.be/ASC/TECHNO_DETER.html

CHAPTER 3: Computer
Science and the
Foundation of
Knowledge Model

Dee McGonigle, Kathleen Mastrian, and June Kaminski

Objectives
1. Describe the essential components of

computer systems, including both
hardware and software.

2. Recognize the rapid evolution of
computer systems and the benefit of
keeping up-to-date with current trends
and developments.

3. Analyze how computer systems function
as tools for managing information and
generating knowledge.

4. Define the concept of human–technology
interfaces.

5. Assess how computers can support
collaboration, networking, and
information exchange.

Key Terms
» Acquisition

» AMOLED (Active Matrix Organic Light-
Emitting Diode)

» Applications

» Arithmetic logic units

» Basic input/output system (BIOS)

» Binary system

» Bit

» Bus

» Byte

» Cache memory

» Central processing unit (CPU)

» Cloud computing

» Cloud storage

» Communication software

» Compact disc read-only memory (CD-
ROM)

» Compact disc-recordable (CD-R)

» Compact disc-rewritable (CD-RW)

» Compatibility

» Computer

» Computer science

» Conferencing software

» Creativity software

» Database

» Desktop

» Digital video disc (DVD)

» Digital video disc-recordable (DVD-R)

» Digital video disc-rewritable (DVD-RW)

» Dissemination

» Dots per inch (DPI) switch

» Double data rate synchronous dynamic
random-access memory (DDR SDRAM)

» Dynamic random access memory
(DRAM)

» Email

» Email client

» Electronically erasable programmable
read-only memory (EEPROM)

» Embedded device

» Exabyte (EB)

» Executes

» Extensibility

» FireWire

» Firmware

» Flash memory

» Gigabyte (GB)

» Gigahertz

» Graphical user interface

» Graphics card

» Haptic

» Hard disk

» Hard drive

» Hardware

» High-definition multimedia interface
(HDMI)

» Information

» Information Age

» Infrastructure as a service (IaaS)

» Instant message (IM)

» Integrated drive electronics (IDE)

» Internet browser

» IPS LCD (In-Plane Switching Liquid
Crystal Display)

» Keyboard

» Knowledge

» Laptop

» Main memory

» Mainframes

» Megabyte (MB)

» Megahertz

» Memory

» Microprocessor

» Microsoft Surface

» Millions of instructions per second
(MIPS)

» Mobile device

» Modem

» Monitor

» Motherboard

» Mouse

» MPEG-1 Audio Layer-3 (MP3)

» Networks

» Office suite

» Open source

» Operating system (OS)

» Parallel port

» Peripheral component interconnection
(PCI)

» Personal computer (PC)

» Petabytes (PB)

» Platform as a service (PaaS)

» Plug and play

» Port

» Portability

» Portable operating system interface for
UNIX (POSIX)

» Power supply

» Presentation

» Private cloud

» Processing

» Processor

» Productivity software

» Professional development

» Programmable read-only memory
(PROM)

» Public cloud

» Publishing

» Quantum bits (Qubits)

» Quantum computing

» QWERTY

» Random-access memory (RAM)

» Read-only memory (ROM)

» Security

» Serial port

» Small Computer System Interface
(SCSI)

» Software

» Software as a service (SaaS)

» Sound card

» Spreadsheet

» Supercomputers

» Synchronous dynamic random-access
memory (SDRAM)

» Technology

» Terabytes (TB)

» Throughput

» Touch pad

» Touch screen

» Universal serial bus (USB)

» USB flash drive

» User friendly

» User interface

» Video adapter card

» Virtual memory

» Wearable technology

» Wi-Fi

» Wisdom

» Word processing

» World Wide Web (WWW)

» Yottabyte (YB)

» Zettabyte (ZB)

Introduction
In this chapter, the discipline of computer science is
introduced through a focus on computers and the
hardware and software that make up these evolving
systems; computer science is one of the building
blocks of nursing informatics (refer to Figure 3-1).
Computer science offers extremely valuable tools
that, if used skillfully, can facilitate the acquisition and
manipulation of data and information by nurses, who
can then synthesize these into an evolving knowledge
and wisdom base. This process can facilitate
professional development and the ability to apply
evidence-based practice decisions within nursing care,
and if the results are disseminated and shared, can
also advance the professional knowledge base.

Figure 3-1 Building Blocks of Nursing Informatics

This chapter begins with a look at common computer
hardware, followed by a brief overview of operating,
productivity, creativity, and communication software. It
concludes with a glimpse at how computer systems
help to shape knowledge and collaboration and an
introduction to human–technology interface dynamics.

The Computer as a Tool for
Managing Information and

Generating Knowledge
Throughout history, various milestones have signaled
discoveries, inventions, or philosophic shifts that
spurred a surge in knowledge and understanding
within the human race. The advent of the computer is
one such milestone, which has sparked an intellectual
metamorphosis whose boundaries have yet to be fully
understood. Computer technology has ushered in
what has been called the Information Age, an age
when data, information, and knowledge are both
accessible and able to be manipulated by more people
than ever before in history. How can a mere machine
lead to such a revolutionary state of knowledge
potential? To begin to answer this question, it is best to
examine the basic structure and components of
computer systems.

Essentially, a computer is an electronic information-
processing machine that serves as a tool with which to
manipulate data and information. The easiest way to
begin to understand computers is to realize they are
input–output systems. These unique machines accept
data input via a variety of devices, process data
through logical and arithmetic rendering, store the data
in memory components, and output data and
information to the user.

Since the advent of the first electronic computer in the
mid-1940s, computers have evolved to become

essential tools in every walk of life, including the
profession of nursing. The complexity of computers has
increased dramatically over the years, and will continue
to do so. “Computing has changed the world more than
any other invention of the past hundred years, and has
come to pervade nearly all human endeavors. Yet, we
are just at the beginning of the computing revolution;
today’s computing offers just a glimpse of the potential
impact of computers” (Evans, 2010, p. 3). Major
computer manufacturers and researchers, such as
Intel, have identified the need to design computers to
mask this growing complexity. The sophistication of
computers is evolving at amazing speed, yet ease of
use or user-friendly aspects are also increasing
accordingly. This is achieved by honing hardware and
software capabilities until they work seamlessly
together to ensure user-friendly, intuitive tools for users
of all levels of expertise. Box 3-1 provides information
about haptic technology, computing surfaces, and
multi-touch interfaces, which are evolving technologies.

BOX 3-1 IMMERSION, MICROSOFT,

AND PQ LABS INTERFACES

Dee McGonigle

Do not get too attached to your mouse and
keyboard, because they will be outdated soon if
Immersion, Microsoft, and PQ Labs have their
way. From Immersion’s (2016) haptic

technology, the Microsoft Surface (Microsoft
Corporation, 2016), and PQ Labs (2016) multi-
touch capabilities, have you ever thought of
digital information you can touch and grab? The
sense of touch is a powerful sense that we use
daily. Haptic technology continues to advance
and “brings the sense of touch to digital content”
(Immersion, 2016, para. 4). Haptic technology
combined with a visual display can be used to
prepare users for tasks necessitating hand–eye
coordination, such as surgical procedures.
Microsoft and PQ Labs are leading us into and
evolving the next generation of computing,
known as surface or table computing. Surface or
table computing consists of a multi-touch,
multiuser interface that allows one to “grab”
digital information and then collaborate, share,
and store that information, without using a
mouse or keyboard—just the hands and fingers
and devices such as a digital camera or
smartphone. These interfaces can actually
sense objects, touch, and gestures from many
users.

We can enter a restaurant and interact with the
menu through the surface of the table where you
sit to eat. Once you have completed your order,
you can begin computing by using the
capabilities built into the surface or using your
own device, such as a smartphone. You can set

a smartphone on the table’s surface and
download images, graphics, and text to the
surface. You can even communicate with others
using full audio and video while waiting for your
order. When you have finished eating, you
simply set your credit card on the surface and it
is automatically charged; you pick up your credit
card and leave. This is a different kind of eating
experience—but one that will become
commonplace for the next generation of users.
You can routinely experience this in Las Vegas,
as well as in selected casinos, banks,
restaurants, and hotels throughout the world.

You should seek to explore this new interface,
which will forever change how we interact and
compute. Think of the ramifications for health
care especially as it relates to the haptic
experience and wearables. Explore the
Immersion reference provided for you.

REFERENCES

Immersion. (2016). Touch. Feel.
Engage. Retrieved from
http://www.immersion.com/wearables

Microsoft Corporation. (2016).
Designed on Surface: A global
art project. Retrieved from

https://www.microsoft.com/surface/en-
us/art

PQ Labs. (2016). Introducing G5: 4K
Touch Fidelity. Retrieved from
http://multitouch.com/product.html

As our capabilities evolve, so does the complexity of
computer operations. The goal for vendors that provide
computer systems and software is to decrease the
learning curve for the user while enhancing the user’s
capacity to manipulate the system to meet their
computing needs. Therefore, the complexity of the
operation is concealed by the ease of use.

One example of this type of complexity masked in
simplicity is the evolution of “plug and play” computer
add-ons, where a peripheral, such as an iPod or game
console, can be simply plugged into a serial or other
port and instantly used.

Computers are universal machines, because they are
general-purpose, symbol-manipulating devices that can
perform any task represented in specific programs. For
instance, they can be used to draw an image, calculate
statistics, write an essay, or record nursing care data.

In a nutshell, computers can be used for data and
information storage, retrieval, analysis, generation, and
transformation.

Most computers are based on scientist John Von
Neumann’s model of a processor–memory–input–
output architecture. In this model, the logic unit and
control unit are parts of the processor, the memory is
the storage region, and the input and output segments
are provided by the various computer devices, such as
the keyboard, mouse, monitor, and printer. Recent
developments have provided alternative configurations
to the Von Neumann model—for example, the parallel
computing model, where multiple processors are set up
to work together. Nevertheless, today’s computer
systems share the same basic configurations and
components inherent in the earliest computers.

Components

Hardware
Computer hardware refers to the actual physical body
of the computer and its components. Several key
components in the average computer work together to
shape a complex yet highly usable machine that serves
as a tool for knowledge management, communication,
and creativity.

Protection: The Casing

The most noticeable component of any computer is the
outer case. Desktop personal computers have either a
desktop case, which lies horizontally (flat) on a desk,
often with the computer monitor positioned on top of it;
or a tower case, which stands vertically, and usually
sits beside the monitor or on a lower shelf or the floor.
Most cases come equipped with a case fan, which is
extremely critical for keeping the computer components
cool when in use. Laptop and surface computers
combine the components into a flat rectangular casing
that is attached to the hinged or foldable monitor.
Smartphones also have a protective outer plastic or
metal case with a display screen.

Central Processing Unit (CPU)/Processor

The central processing unit (CPU) is an older term
for the processor and microprocessor. Sometimes
conceptualized as the “brain” of the computer, the
processor is the computer component that actually
executes, calculates, and processes the binary
computer code (which consists of various
configurations of 0s and 1s), instigated by the
operating system (OS) and other applications on the
computer. The processor and microprocessor serve as
the command center that directs the actions of all other
computer components, and they manage both
incoming and outgoing data that are processed across
components. Some of the best processors include the

AMD FX-9590, AMD FX-8320, AMD FX-6300, Intel
Core i7-5820K, Intel Core i7- 4930K, Intel Core i7-
5960X, Intel Core i5-6600K, and Intel Xeon processor
(Futuremark, 2016).

The processor contains specific mechanical units,
including registers, arithmetic logic units, a floating
point unit, control circuitry, and cache memory.
Together, these inner components form the computer’s
central processor. Registers consist of data-storing
circuits whose contents are processed by the adjacent
arithmetic and logic units or the floating point unit.
Cache memory is extremely quick memory that holds
whatever data and code are being used at any one
time. The processor uses the cache to store in-process
data so that it can be quickly retrieved as needed. The
processor is protected by a heat sink, a copper or
aluminum metal block that cools the processor (often
with the help of a fan) to prevent overheating (refer to
Figure 3-2).

Figure 3-2 Computer Components

Keyboard © Undrey/Shutterstock; mouse © Pressmaster/Shutterstock;

microphone © VectorShow/Shutterstock; touch pad ©

donfiore/Shutterstock; pen drawing a diagram © Syda

Productions/Shutterstock; USB drive © DecemberDah/Shutterstock; CPU

© Péter Gudella/Dreamstime.com; RAM © NorGal/Shutterstock; hard

drive © mike mols/Shutterstock; monitor © Leone_V/Shutterstock; printer

© Billion Photos/Shutterstock; speakers © Krailurk Warasup/Shutterstock;

TV © JTal/Shutterstock; flash drive © Ksander/Shutterstock

In the past, the speed and power of a processor were
measured in units of megahertz and was written as a

value in MHz (e.g., 400 MHz, meaning the
microprocessor ran at 400 MHz, executing 400 million
cycles per second). Today, it is more common to see
the speed measured in gigahertz (1 GHz is equal to
1,000 MHz); thus a processor that operates at 4 GHz is
1,000 times faster than an older one that operated at 4
MHz. The more cycles a processor can complete per
second, the faster computer programs can run.
However, according to Anderson (2016),

Intel has said that new technologies in
chip manufacturing will favour better
energy consumption over faster
execution times—effectively calling an
end to “Moore’s Law,” which successfully
predicted the doubling of density in
integrated circuits, and therefore speed,
every two years. (para. 1)

For example, the Intel Xeon processor E5-2699 v4 has
a speed of 2.20 Ghz with 55 MB cache (Intel
Corporation, 2016), making it more efficient at a lower
speed.

In recent years, processor manufacturers, such as
Intel, have moved to multicore microprocessors, which
are chips that combine two or more processors. In fact,
multiple microprocessors have become a standard in
both personal and professional-level computers.

Minicomputers were replaced by servers using
microprocessors and multiprocessors have replaced
most mainframes.

As mobile devices and embedded devices are being
integrated into our daily routines, mainframes can
create secure transactions with the analytics necessary
for organizations to improve their business processes.
IBM has found its niche and continues to build
mainframes. According to Alba (2015),

The concept of a “mobile transaction” is a
bit of marketing-speak. Tons of
transactions take place via mobile
devices, and the mainframe is good at
transaction processing. Put them
together, and voilà: a computer the size
of a backyard shed becomes a mobile
product. (para. 6)

Powerful supercomputers are also using collections
of microprocessors.

Motherboard

The motherboard has been called the “central
nervous system” of the computer because it facilitates
communication among all of the different computer
components. This makes it a key foundational
component because all other components are

connected to it in some way (either directly via local
sockets, attached directly to it, or connected via
cables). This includes universal serial bus (USB)
controllers, Ethernet network controllers, integrated
graphics controllers, and so forth. The essential
structures of the motherboard include the major
chipset, Super Input/Output chip, basic input/output
system read-only memory, bus communications
pathways, and a variety of sockets that allow
components to plug into the board. The chipset (often a
pair of chips) determines the computer’s CPU type and
memory. It also houses the north bridge and south
bridge controllers that allow the buses to transfer data
from one to another.

Power Supply

The power supply is a critical component of any
computer, because it provides the essential electrical
energy needed to allow a computer to operate. The
power supply unit converts the 120-volt AC main power
(provided via the power cable from the wall socket into
which the computer is plugged) into low-voltage DC
power. Computers depend on a reliable, steady supply
of DC power to function properly. The more devices
and programs used on a computer, the larger the
power supply should be to avoid damage and
malfunctioning. Power supplies normally range from
160 to 700 watts, with an average of 300 to 400 watts.
Most contemporary power supply units come equipped

with at least one fan to cool the unit under heavy use.
The power supply is controlled by pressing the on and
off switch, as well as the reset switch (which restarts
the system) of a computer.

Laptop and other portable computing machines, such
as electronic readers and tablet computers, are
equipped with a both rechargeable battery power
supply and the standard plug-in variety.

Hard Disk

This component is so named because of the rigid hard
disks that reside in it, which are mounted to a spindle
that is spun by a motor when in use. Drive heads (most
computers have two or more heads) produce a
magnetic field through their transducers that
magnetizes the disk surface as a voltage is applied to
the disk. The hard disk acts as a permanent data
storage area that holds gigabytes (GB) or even
terabytes (TB) worth of data, information, documents,
and programs saved on the computer, even when the
computer is shut off. Disk drives are not infallible,
however, so backing up important data is imperative.

The computer writes binary data to the hard drive by
magnetizing small areas of its surface. Each drive head
is connected to an actuator that moves along the disk
to hover over any point on the disk surface as it spins.
The parts of the hard disk are encased in a sealed unit.

The hard drive is managed by a disk controller, which
is a circuit board that controls the motor and actuator
arm assembly. The hard drive produces the voltage
waveform that contacts the heads to write and read
data, and handles communications with the
motherboard. It is usually located within the computer’s
hard outer casing. Some people also attach a second
hard drive externally, to increase available memory or
to back up data.

Main Memory or Random-Access Memory

Random-access memory (RAM) is considered to be
volatile memory because it is a temporary storage
system that allows the processor to access program
codes and data while working on a task. The contents
of RAM are lost once the system is rebooted, is shut
off, or loses power.

The memory is actually situated on small chip boards,
which sport rows of pins along the bottom edge and
are plugged into the motherboard of the computer.
These memory chips contain complex arrays of tiny
memory circuits that can be either set by the processor
during write operations (puts them into storage) or read
during data retrieval. The circuits store the data in
binary form as either a low (on) voltage stage,
expressed as a 0, or a high (off) voltage stage,
expressed as a 1. All of the work being done on a
computer resides in RAM until it is saved onto the hard

drive or other storage drive. Computers generally come
with 2 GB of RAM or more, and some offer more RAM
via graphics cards and other expansion cards.

A certain portion of the RAM, called the main memory,
serves the hard disk and facilitates interactions
between the hard disk and central processor. Main
memory is provided by dynamic random access
memory (DRAM) and is attached to the processor
using specific addresses and data buses.

Synchronous dynamic random-access memory
(SDRAM) (also known as static dynamic RAM)
protects its data bits. The newer chip is double data
rate synchronous dynamic random-access memory
(DDR SDRAM) that allows for greater bandwidth and
twice the transfers per the computer’s internal clock’s
unit of time.

Read-Only Memory

Read-only memory (ROM) is essential permanent or
semipermanent nonvolatile memory that stores saved
data and is critical in the working of the computer’s OS
and other activities. ROM is stored primarily in the
motherboard, but it may also be available through the
graphics card, other expansion cards, and peripherals.
In recent years, rewritable ROM chips that may include
other forms of ROM, such as programmable read-
only memory (PROM), erasable ROM, electronically

erasable programmable read-only memory
(EEPROM), and flash memory (a variation of
electronically erasable programmable ROM), have
become available.

Basic Input/Output System

The basic input/output system (BIOS) is a specific
type of ROM used by the computer when it first boots
up to establish basic communication between the
processor, motherboard, and other components. Often
called boot firmware, it controls the computer from the
time the machine is switched on until the primary OS
(e.g., Windows, Mac OS X, or Linux) takes over. The
firmware initializes the hardware and boots (loads and
executes) the primary OS.

Virtual Memory

Virtual memory is a special type of memory that is
stored on the hard disk to provide temporary data
storage so data can be swapped in and out of the RAM
as needed. This capability is particularly handy when
working with large data-intensive programs, such as
games and multimedia.

Integrated Drive Electronics Controller

The integrated drive electronics (IDE) controller
component is the primary interface for the hard drive,
compact disk read-only memory (CD-ROM), digital

video disk (DVD) drive, and the floppy disk drive
(found largely on pre-2010 computers).

Peripheral Component Interconnection Bus

This component is important for connecting additional
plug-in components to the computer. It uses a series of
slots on the motherboard to allow peripheral
component interconnection (PCI) card plug-in.

Small Computer System Interface

The Small Computer System Interface (SCSI)
component provides the means to attach additional
devices, such as scanners and extra hard drives, to the
computer.

DVD/CD Drive

The CD-ROM drive reads and records data to portable
CDs, using a laser diode to emit an infrared light beam
that reflects onto a track on the CD using a mirror
positioned by a motor. The light reflected on the disk is
directed by a system of lenses to a photodetector that
converts the light pulses into an electrical signal; this
signal is then decoded by the drive electronics to the
motherboard. There are compact disk-recordable
(CD-R) and compact disk-rewritable (CD-RW),
digital video disk-recordable (DVD-R), and digital
video disk-rewritable (DVD-RW) drives. A DVD drive
can do everything a CD drive can do, plus it can play

the content of disks and, if it is a recordable unit, can
record data on blank DVDs.

Flash or USB Flash Drive

This portable memory device uses electronically
erasable programmable ROM to provide fast
permanent memory. The USB flash drive is typically a
removable and rewritable device that includes flash
memory and an integrated USB interface. They are
easily portable due to their small size and are durable
and dependable, and obtain their power from the
device they are connected to via the USB port.

Modem

A modem is a component that can be situated either
externally (external modem) or internally (internal
modem) relative to the computer and enables Internet
connectivity via a cable connection through network
adapters situated within the computer apparatus.

Connection Ports

All computers have connection ports made to fit
different types of plug-in devices. These ports include a
monitor cable port, keyboard and mouse ports, a
network cable port, microphone/speaker/auxiliary input
ports, USB ports, and printer ports (SCSI or parallel).
These ports allow data to move to and from the

computer via peripheral or storage devices. Specific
ports include the following:

Parallel port: Connects to a printer
Serial port: Connects to an external modem
USB: Connects to a myriad of plug-in devices, such
as portable flash drives, digital cameras, MPEG-1
Audio Layer-3 (MP3) players, graphics tablets, and
light pens, using a plug-and-play connection (the
ability to add devices automatically). The
development of the USB Type-C–to–high
definition multimedia interface (HDMI) adapter
(Sexton, 2016) has expanded connectivity and
transfer. HDMI is replacing analog video standards
as an audio/video interface that can transfer
compressed and uncompressed video and digital
audio data from any device that is HDMI-compliant
to compatible monitors, televisions, video
projectors, and audio devices.
FireWire (IEEE 1394): Often used to connect
digital-video devices to the computer
Ethernet: Connects networking apparatus, such as
Internet and modem cables

Graphics Card

Most computers come equipped with a graphics
accelerator card slotted in the microprocessor of a
computer to process image data and output those data
to the monitor. These in situ graphic cards provide

satisfactory graphics quality for two-dimensional art
and general text and numerical data. However, if a user
intends to create or view three-dimensional images or
is an active game user, one or more graphics
enhancement cards are often installed.

Video Adapter Cards

Video adapter cards provide video memory, a video
processor, and a digital-to-analog converter that works
with the processor to output higher quality video
images to the monitor.

Sound Card

The sound card converts digital data into an analog
signal that is then output to the computer’s speakers or
headphones. The reverse is also accomplished by
inputting a signal from a microphone or other audio
recording equipment, which then converts the analog
signal to a digital signal.

Bit

A bit is the smallest possible chunk of data memory
used in computer processing and is depicted as either
a 1 or a 0. Bits make up the binary system of the
computer.

Byte

A byte is a chunk of memory that consists of 8 bits; it is
considered to be the best way to indicate computer
memory or storage capacity. In modern computers,
bytes are described in units of megabytes (MB);
gigabytes (GB), where 1 GB equals 1,000 MB; or
terabytes (TB), where 1 TB equals 1 trillion bytes or
1,000 GB. Box 3-2 discusses storage capacities.

BOX 3-2 STORAGE CAPACITIES

Dee McGonigle and Kathleen Mastrian

Storage and memory capacities are evolving. In
the past few decades, there have been great
leaps in data storage. It all begins with the bit,
the basic unit of data storage, composed of 0s
and 1s, also known as binary digits. A byte is
generally considered to be equal to 8 bits. The
files on a computer are stored as binary files.
The software that is used translates these binary
files into words, numbers, pictures, images, or
video. Using this binary code in the binary
numbering system, measurement is counted by
factors of 2, such as 1, 2, 4, 8, 16, 32, 64, and
128. These multiples of the binary system in
computer usage are also prefixed based on the
metric system. Therefore, a kilobyte (KB) is
actually 2 to the 10th power (210) or 1,024
bytes, but is typically considered to be 1,000
bytes. This is why one sees 1,024 or multiples of

that number instead of an even 1,000 mentioned
at times in relation to kilobytes.

In the early 1980s, kilobytes were the norm as
far as computer capacity went, and 128 KB
machines were launched for personal use.
Subsequent decades, however, have seen
advanced computing power and storage
capacity. As capabilities soared, so did the
ability to save and store what was used and
created. Megabytes (MB) emerged as a
common unit of measure; 1 megabyte is
1,048,576 bytes but is considered to be roughly
equivalent to 1 million bytes. The next leap in
computer capacity was one that some people
could not even imagine: gigabytes (GB). A
gigabyte is 1,073,741,824 bytes but is generally
rounded to 1 billion bytes. Some computing
experts are very concerned that valuable bytes
are lost when these measurements are rounded,
whereas hard drive manufacturers use the
decimal system so their capacity is expressed
as an even 1 billion bytes per gigabyte.

Computer capacity has moved into and beyond
the range of terabytes, with capacities moving
into the range of petabytes (PB), exabytes
(EB), zettabytes (ZB), and yottabytes (YB).
These terms for storage capacity are defined as
follows:

1 TB = 1,000 GB

1 PB = 1,000,000 GB

1 EB = 1,000 PB

1 ZB = 1,000 EB

1 YB = 1,000 ZB

To put all of this in perspective, Lyman and
Varian describe the data powers of 10:

2 KB: A typewritten page

2 MB: A high-resolution photograph

10 MB: A minute of high-fidelity sound or a
digital chest X-ray

50 MB: A digital mammogram

1 GB: A symphony in high-fidelity sound or a
movie at TV quality

1 TB: All the X-ray films in a large,
technologically advanced hospital

2 PB: The contents of all U.S. academic
research libraries

5 EB: All words ever spoken by human
beings

We have not even addressed ZB and YB. Stay
tuned . . .

REFERENCE

Lyman, P., & Varian, H. R. (2003).
How much information?
Retrieved from
http://groups.ischool.berkeley.edu/archive/how-
much-info-2003/

Software
Software comprises the application programs
developed to facilitate various user functions, such as
writing, artwork, organizing meetings, surfing the
Internet, communicating with others, and so forth. For
the purposes of this overview, the various types of
software have been divided into four categories: (1) OS
software, (2) productivity software, (3) creativity
software, and (4) communication software.

User friendliness is a critical condition for effective
software adoption. The easier and more intuitive a
software package seems to be to a user influences that
user’s perception of how clear the package is to
understand and to use. The rapid evolution of
hardware mentioned previously has been equally
matched by the phenomenal development in software
over the past three or four decades.

Commercial Software

Several large commercial software companies, such as
Apple, Microsoft, IBM, and Adobe, dominate the
market for software, and have done so since the
advent of the personal computer (PC). Licensed
software has evolved over time; hence, most products
have a long version history. Many software packages,
such as office suites, are expensive to purchase; in
turn, there is a “digital divide” as far as access and
affordability go across societal spheres, especially
when viewed from a global perspective.

Open Source Software

The open source initiative began in the late 1990s and
has become a powerful movement that is changing the
software production and consumer market. In addition
to commercially available software, a growing number
of open source software packages are being
developed in all four of the categories addressed in this
chapter. The open source movement was begun by
developers who wished to offer their creations to others
for the good of the community and encouraged them to
do the same. Users who modify or contribute to the
evolution of open source software are obligated to
share their new code, but essentially the software is
free to all. Apache OpenOffice, Google Docs, and
NeoOffice are examples of open source productivity
software (refer to Figure 3-3).

OS Software

The OS is the most important software on any
computer. It is the very first program to load on
computer start-up and is fundamental for the operation
of all other software and the computer hardware.
Examples of commonly used OSs include the Microsoft
Windows family, Linux, and Mac OS X. The OS
manages both the hardware and the software and
provides a reliable, consistent interface for the software
applications to work with the computer’s hardware. An
OS must be both powerful and flexible to adapt to the
myriad of types of software available, which are made
by a variety of development companies. New versions
of the major OSs are equipped to deal with multiple
users and handle multitasking with ease. For example,
a user can work on a word processing document while
listening for an “email received” signal, have an
Internet browser window open to look for references
on the Internet as needed, listen to music in the CD
drive, and download a file—all at the same time.

OS tasks can be described in terms of six basic
processes:

Memory management
Device management
Processor management
Storage management
Application interface

User interface (usually a graphical user interface
[GUI])

A GUI (pronounced “gooey”) is used by OSs to display
a combination of graphics and text such as icons, drop-
down menus, and buttons; it allows you to use input
and output devices as well as icons that represent files,
programs, actions, and processes.

OSs should be convenient to use, easy to learn,
reliable, safe, and fast. They should also be easy to
design, implement, and maintain and should be
flexible, reliable, error free, and efficient. For example,
Silbershatz, Baer Galvin, and Gagne (2013) described
how “Microsoft’s design goals for Windows included
security, reliability, Windows and POSIX application
compatibility, high performance, extensibility, portability,
and international support” (p. 831). The following goals
were established by Microsoft:

Figure 3-3 Open Source Software

Portability: The OS can be moved from one
hardware architecture to another with few changes
needed.
Security: The OS incorporates hardware protection
for virtual memory and software protection
mechanisms for OS resources, including encryption
and digital signature capabilities.
Portable operating system interface for Unix
(POSIX) compliance: Applicationsdesigned to follow
the POSIX (IEEE 1003.1) standard can be compiled
to run on Windows without changing the source

code. Windows OSs have varying levels of
compatibility with the applications that ran on earlier
versions of Windows OSs.
Multiprocessor support: The OS is designed for
symmetrical multiprocessing.
Extensibility: This capability is provided by using a
layered architecture with a protected executive
layer for basic system services, several server
subsystems that operate in user mode, and a
modular structure that allows additional
environmental subsystems to be added without
affecting the executive layer.
International support: The Windows OS supports
different locales via the national language support
application programming interface (API).
Compatibility with MS-DOS and MS-Windows
applications.

Productivity Software

Productivity software, such as an office suite, is the
type of software most commonly used both in the
workplace and on personal computers. Several
software companies produce this type of multiple-
program software, which usually bundles together
word processing, spreadsheet, database,
presentation, Web development, and email programs.

The intent of office suites is generally to provide all of
the basic programs that office or knowledge workers

need to do their work. The bundled programs within the
suite are organized to be compatible with one another,
are designed to look similar to one another for ease of
use, and provide a powerful array of tools for data
manipulation, information gathering, and knowledge
generation. Some office suites add other programs,
such as database creation software, mathematical
editors, drawing, and desktop publishing programs.
Table 3-1 summarizes the application of programs
included in some of the popular office suites: Microsoft
Office, Apache OpenOffice, NeoOffice, Corel
WordPerfect Suite, and Apple iWork.

Table 3-1 Office Suite Software Features and
Examples

Office Suite Software

Program Application Examples

Word

processing

Composition, editing,

formatting, and

producing text

documents

Microsoft Word, Open

Office Writer, KOffice

KWord, Corel Word

Perfect or Corel Write,

Apple Pages

Spreadsheets Grid-based documents in

ledger format; organizes

numbers and text;

calculates statistical

formulae

Microsoft Excel, Open

Office Calc, KOffice

KSpread, Corel Quattro

Pro, Apple Numbers

Presentations Slideshow software,

usually used for business

or classroom

presentations using text,

images, graphs, media

Microsoft Power

Point, Open Office

Impress, KOffice

KPresenter, Corel

Show, Apple Keynote

Databases Database creation for

text and numbers

Microsoft Access (in

elite packages), Open

Office Base, KOffice

Kexi, Corel Calculate,

Corel Paradox

Email Integrated email program

to send and receive

electronic mail

Microsoft Outlook,

Corel Word

Perfect Mail, Mozilla

Thunderbird

Drawing Graphics and diagram

drawing

Open Office Draw,

Corel Presentation

Graphics, KOffice Kivio,

Karbon, Krita

Math

formulas

Inserts math equations in

word processing and

presentation work

Open Office Math,

KOffice KFormula

Desktop

publishing

Page layouts and

publication-ready

documents

Microsoft Publisher (in

elite packages), Apple

Pages

Creative Software

Creative software includes programs that allow users
to draw, paint, render, record music and sound, and
incorporate digital video and other multimedia in

professional aesthetic ways to share and convey
information and knowledge (Table 3-2).

Table 3-2 Creative Software Features and Examples

Creative Software

Program and Application Software Examples

Raster graphics programs

Draw, paint, render, manipulate, and

edit images, fonts, and photographs to

create pixel-based (dot points) digital

art and graphics.

Adobe Photoshop and

Fireworks, Ulead Photo

Impact, Corel Draw, Painter,

and Paint Shop Pro, GIMP

(open source), KOffice Krita

(open source)

Vector graphics programs

Mathematically rendered, geometric

modeling is applied through shapes,

curves, lines, and points and

manipulated for shape, color, and

size. Ideal for printing and three-

dimensional (3D) modeling.

Adobe Flash, Freehand,

and Illustrator; Corel

Draw and Designer, Open

Office Draw (open source),

Mirosoft Visio, Xara Xtreme,

KOffice Karbon14 (open

source)

Desktop publishing programs

Page layout and publishing

preparation for printed and Web

documents, such as magazines,

journals, books, newsletters, and

brochures.

Adobe InDesign, Corel

Page

Maker, Microsoft Publisher,

Scribus (open source),

QuarkXPress, Apple Pages

(note that many of the

graphics programs can also

be used for DTP)

Web design programs

Create, edit, and update webpages

using specific codes, such as XML,

CSS, HTML, and Java.

Adobe Dreamweaver,

Coffee Cup, Microsoft

FrontPage, Nvu (open

source), W3C’s Amaya

(open source)

Multimedia programs

Combines text, audio, images,

animation, and video into interactive

content for electronic presentation.

Adobe Flash, Microsoft

Movie Maker, Apple Quick

Time and FinalCut Studio,

Corel VideoStudio, Ulead

VideoStudio, Real Studio,

CamStudio (open source),

Audacity (open source)

Communication Software

Networking and communication software enable
users to dialogue, share, and network with other users
via the exchange of email or instant message (IM), by
accessing the World Wide Web, or by engaging in
virtual meetings using conferencing software (Table
3-3)

Table 3-3 Communication Software Features and
Examples

Communication Software

Email client

Allows user to read, edit, forward,

and send email messages to other

users via an Internet connection.

The software can be resident on the

computer or accessed via the World

Wide Web.

Resident programsMicrosoft

Outlook and Outlook Express,

Eudora, Pegasus, Mozilla

Thunderbird, Lotus

NotesWeb-based

programsGmail, Yahoo Mail,

Hotmail

Internet browsers

Enables user to access, browse,

download, upload, and interact with

text, audio, video, and other Web-

based documents.

Mozilla Firefox, Microsoft

Internet Explorer, Google

Chrome, Apple Safari, Opera,

Microbrowser (for mobile

access)

Instant messaging (IM)

Real-time text messaging between

users, can attach images, videos,

and other documents via personal

computer, cell phone, handheld

devices.

MSN Instant Messenger,

Microsoft Live Messenger,

Yahoo Messenger, Apple

iChat

Conferencing

Enables user to communicate in a

virtual meeting room setting to share

work, discussions, planning, using

an intranet or Internet environment;

can exhibit files, video, and

screenshots of content.

Adobe Acrobat Connect,

Microsoft Live Meeting or

Meeting Space,

GoToMeeting, Meeting

Bridge, Free Conference,

RainDance, WebEx

Acquisition of Data and Information:
Input Components
Input devices include the keyboard; mouse; joysticks
(typically used for playing computer games); game
controllers or pads; Web cameras (webcams); stylus
(often used with tablets or personal digital assistants);
image scanners for copying a digital image of a
document or picture; touch pads; or other plug-and-
play input devices, such as digital cameras, digital
video recorders (camcorders), MP3 players, electronic
musical instruments, and physiologic monitors. These
devices are the origin or medium used to input text,
visual, audio, or multimedia data into the computer
system for viewing, listening, manipulating, creating, or
editing. The primary input devices on a computer are
the keyboard, mouse, touch pad, and touch screen.

Keyboard

A computer keyboard is very similar to the typewriter
keyboards of earlier days and usually serve as the
prime input device that enables the user to type words,
numbers, and commands into the computer’s
programs. Standard computer keyboards have 110
keys and are organized to facilitate Latin-based
languages using a QWERTY layout (so named
because these letters appear on the first six keys in the
first row of letters).

Certain keys are used as command keys, particularly
the control (CTRL), alternate (Alt), delete (Del), and
shift keys, which can all be used to activate useful
commands. The escape (ESC) key allows the user
instantly to exit a process or program. The F keys,
numbered F1 through F12, are function keys. They are
used in different ways by particular programs. If a
program instructs users to press the “F8” key, they
would do so by pressing F8. The print screen (PrtSc)
key sends a graphical picture or screen shot of a
computer screen to the clipboard. This copied screen
shot can then be pasted in any graphic program that
can work with bitmap files.

Some keyboards have a wire and plug in, while others
are wireless or cordless. Touch screen or virtual
keyboards are those being incorporated into the touch
screens of phones, gaming machines, and tablets, and
they are also available through ease-of-access tools on
laptops.

Mouse

The mouse is the second-most-commonly used input
device. It is manipulated by the user’s hand to point,
click, and move objects around on the computer
screen. A mouse can come in a number of different
configurations, including a standard mechanical
trackball serial mouse, bus mouse, PS/2 mouse, USB-
connected mouse, optical lens mouse, cordless

mouse, and optomechanical mouse. Even though “the
mouse may be a simple device in concept,” it has
evolved and increased in complexity and capability
over time (Bagaza & Westover, 2016, para. 2). For
example, “[g]aming mice take the basic mouse concept
and amplify every element to extremes” (Bagaza &
Westover, para. 4). Some manufacturers offer
specialized features, but there is a common
“combination of high-performance parts—laser
sensors, light-click buttons, and gold-plated USB
connectors—and customization, like adjustable weight,
programmable macro commands, and on-the-fly DPI
switching. For non-gamers, these features are overkill;
for dedicated gamers, they provide a competitive edge”
(Bagaza & Westover, para. 4). The dots per inch
(DPI) switch is an actual switch on a computer mouse
that allows you to adjust the mouse’s sensitivity to
movement, as in faster or slower mouse pointer
speeds. Having the ability to do this on the fly or as
needed without pausing could enhance the computing
or gaming experience.

Touch Pad

The touch pad is a device that senses the pressure of
the user’s finger along with the movement of the finger
on the touch pad to control input positioning. It is an
alternative to using a mouse.

Touch Screen

The touch screen is a display used as an input device
for interacting with or relating to the display’s materials
or content. The user can touch or press on the
designated display area to respond, execute, or
request information or output.

Processing of Data and Information:
Throughput/Processing Components
All of the hardware discussed earlier in this chapter is
involved in the throughput or processing of input
data and in the preparation of output data and
information. Specific software is used, depending on
the application and data involved. One key hardware
component, the computer monitor, is a unique example
of a visible throughput component—it is the part of the
computer that users focus on the most when they are
working on a computer. Input data can be visualized
and accessed by manipulating the mouse and
keyboard input devices, but it is the monitor that
receives the user’s attention. The monitor is critical for
the efficient rendering during this part of the cycle,
because it facilitates user access and control of the
data and information.

Monitor

The monitor is the visual display that serves as the
landscape for all interactions between user and
machine. It typically resembles a television screen, and

comes in various sizes (usually ranging from 15 to 21
inches) and configurations. Monitors either are based
on cathode ray tubes (the conventional monitor with a
large section behind the screen) or are thinner, flat-
screen liquid crystal display devices. Some computer
monitors also have a touch screen that can serve as an
input device when the user touches specific areas of
the screen.

Monitors vary in their refresh rate (usually measured in
megahertz) and dot pitch. Both of these characteristics
are important for user comfort. The faster the refresh
rate, the cleaner and clearer the image on the screen,
because the monitor refreshes the screen contents
more frequently. For example, a monitor with a 100
MHz refresh rate refreshes the screen contents 100
times per second. Similarly, the larger the dot pitch
factor, the smaller the dots that make up the screen
image, which provides a more detailed display on the
monitor and also facilitates clarity and ease of viewing.

If equipped with a touch screen, a monitor can also
serve as an input device when activated by a stylus or
finger pressure. Some users might also consider the
monitor to be an output device, because access to
input and stored documents is often performed via the
screen (e.g., reading a document that is stored on the
computer or viewable from the Internet). As we
advance to more engaged computing, larger screens

and ultra-wide monitors are evolving to provide
immersive experiences.

Smartphone displays can be a form of AMOLED
(Active Matrix Organic Light-Emitting Diode) or IPS
LCD (In-Plane Switching Liquid Crystal Display). In
the AMOLED type, the individual pixels are lit
separately (active matrix); the next-generation super
AMOLED type includes touch sensors. The IPS LCD–
type uses polarized light passing through a color filter
and all of the pixels are backlit. The liquid crystals
control the brightness and which pixels are on or off.
With the active matrix, you have crisp, vivid colors and
darker blacks.

Dissemination: Output Components
Output devices carry data in a usable form through exit
devices in or attached to a computer. Common forms
of output include printed documents, audio or video
files, physiologic summaries, scan results, and saved
files on portable disk drives, such as a CD, DVD, flash
drive, or external hard drive. Output devices literally put
data and information at the user’s fingertips, which can
then be used to develop knowledge and even wisdom.
The most commonly used output devices include
printers, speakers, and portable disk drives.

Printer

Printers are external components that can be attached
to a computer using a printer cord that is secured into
the computer’s printer port. Printers enable users to
print a hard paper copy of documents that are housed
on the computer.

The most common printer types are the inkjet and laser
printers. Inkjet printers are more economical to use and
offer good quality print; they apply ink to paper using a
jet-spray mechanism. Laser printers produce publisher-
ready quality printing if combined with good-quality
paper, but cost more in terms of printing supplies. Both
types of printers can print in black and white or in color.
Printers can be single function (print only), but typically
they are all-in-one machines or multifunction printers
that can also scan, fax, and copy. There are printers
that can be accessed via the Internet using Wi-Fi.
There are also three-dimensional (3D) printers that can
create a 3D solid object produced layer by layer from a
3D software digital file.

Speakers

All computers have some sort of speaker setup, usually
small speakers embedded in the monitor, in the case,
or, if a laptop, close to the keyboard. Often, external
speakers are added to a computer system using
speaker connectors; these devices provide enhanced
sound and a more enjoyable listening experience.

What Is the Relationship of
Computer Science to
Knowledge?
Scholars and researchers are beginning to understand
the effects that computer systems, architecture,
applications, and processes have on the potential for
knowledge acquisition and development. Users who
have access to contemporary computers equipped with
full Internet access have resources at their fingertips
that were only dreamed of before the 21st century.
Entire library collections are accessible, with many
documents available in full printable form. Users are
also able to contribute to the development of
knowledge through the use of productivity, creativity,
and communication software. In addition, using the
World Wide Web (WWW) interface, users are able to
disseminate knowledge on a grand scale with other
users. This deluge of information available via
computers must be mastered and organized by the
user if knowledge is to emerge. Discernment and the
ability to critique and filter this information must also be
present to facilitate the further development of wisdom.

The development of an understanding of computer
science principles as they apply to technology used in
nursing can facilitate optimal usage of the technology
for knowledge development in the profession. The
maxim that “knowledge is power” and that the skillful

use of computers lies at the heart of this power is a
presumption. Once nurses become comfortable with
the various technologies, they can shape them, refine
them, and apply them in new and different ways, just
as they have always adapted earlier equipment and
technologies. Nurses must harness the power of data
and information through the use of computer
technologies to build knowledge and gain wisdom.

How Does the Computer
Support Collaboration and
Information Exchange?
Computers can be linked to other computers through
networking software and hardware to promote
communication, information exchange, work sharing,
and collaboration. Such networks can be local or
organizationally based, with computers joined together
into a local area network; organized on a wider area
scope (e.g., a city or district) using a metropolitan area
network; or encompassing computers at an even
greater distance (e.g., a whole country or continent, or
the Internet itself) using a wide area network
configuration (Sarkar, 2006). Network interface cards
are used to connect a computer and its modem to a
network.

Networks within health care can manifest in several
different configurations, including client-focused

networks, such as in telenursing, e-health, and client
support networks; work-related networks, including
virtual work and virtual social networks; and learning
and research networks, as in communities of practice.
These trends are still evolving in most nursing work
environments (and most nurses’ personal lives), but
they are predicted to continue to grow dramatically. We
are experiencing one of the greatest upsurges in
shared information and our ability to access, exchange,
and utilize this information to enhance knowledge.

Virtual social networks are another form of professional
network that have expanded phenomenally since the
advent of the Internet and other computer software and
hardware. Nursing-related virtual social networks
provide a cyberspace for nurses to make contacts,
share information and ideas, and build a sense of
community.

Social communication software is used to provide a
dynamic virtual environment, and often virtual social
networks provide communicative capabilities through
posting tools, such as blogs, forums, and wikis; email
for sharing ideas on a smaller scale; collaborative
areas for interaction, creating, and building digital
artifacts or planning projects; navigation tools for
moving through the virtual network landscape; and
profiles to provide a space for each member to disclose
personal information with others. Nurses who have to
engage in shift work often find that virtual social

networks can provide a sense of connection with other
professionals that is available around the clock.
Because time is often a factor in any social
interchange, virtual communication offers an alternative
for practicing nurses, who can access information and
engage in interchanges at any time of day. With active
participation, the interchanges and shared information
and ideas of the network can culminate in valuable
social and cultural capital, available to all members of
that network. Often, nursing virtual social networks are
created for the purpose of exchanging ideas on
practice issues and best practices; to become more
knowledgeable about new trends, research, and
innovations in health care; or to participate in
advocacy, activist, and educational initiatives.

Through the use of portable disk devices, such as flash
drives, CDs, and DVDs, as well as Web-based and
cloud spaces, people can share information,
documents, and communications by exchanging files.
Since the advent of the Internet in the mid-1980s, the
World Wide Web has evolved to become a viable and
user-friendly way for people to collaborate and
exchange information, projects, and other knowledge-
based files, such as websites, email, social networking
applications, and webinar logs. Box 3-3 provides
information on Web 2.0, the latest iteration of the World
Wide Web, and beyond.

BOX 3-3 WEB 2.0 AND BEYOND TOOLS

Dee McGonigle, Kathleen Mastrian, and Wendy
Mahan

Web 2.0—the name given to the new World
Wide Web tools—enables users to collaborate,
network socially, and disseminate knowledge
with other users on a scale that was once not
even comprehensible. These programs promote
data and information exchange, feedback, and
knowledge development and dissemination.

To facilitate a selective review of the Web 2.0
tools available, they have been categorized into
three areas here: (1) tools for creating and
sharing information, (2) tools for collaborating,
and (3) tools for communicating. Examples of
tools for creating and sharing information
include blogs, podcasts, Flickr, YouTube,
Hellodeo, Jing, Screencast-o-matic, Facebook,
MySpace, Box, Samepage, Wrike, Snapchat,
and MakeBeliefsComix. Examples of tools for
collaborating with others include Google Docs,
Zoho, wikis, Del.icio.us, and Gliffy. Finally, some
tools for communicating with others include
Adobe Connect, GoToMeeting, BlueJeans,
WebEx Meeting Center, Vyew, Skype, Twitter,
and instant messaging.

The application of the creating and sharing
information tools has led to an explosion of
social networking on the Web. YouTube has
promoted the “broadcast yourself” proliferation.
Anyone can post a video onto YouTube that is
shared with others over the Web. Similarly,
Flickr allows users to upload and tag personal
photos to share either privately or publicly.
Facebook and MySpace both promote
socializing on the Web. Facebook is a social
utility and MySpace is a place for friends,
according to the descriptions found on these
websites. Other tools let users create and share
recorded messages, diagrams, screen captures,
and even custom comic strips.

Collaborating over the Web has become easier.
Indeed, it is a way of life for many people.
Google Docs and Zoho allow users to create
online and share and collaborate in real time.
Wikis are server-based software programs that
enable users to generate and edit webpage
content using any browser. Del.icio.us is a social
bookmarking manager that uses tags to identify
or describe the bookmarks that can be shared
with others.

Communicating with others includes audio- and
videoconferencing in real time. Adobe Connect
is a comprehensive Web communications
solution. Although a fee-based service, it does

provide a free trial. Users should read all of the
documentation on Adobe’s site before
downloading, installing, and using this software.
Vyew is free, always-on collaboration plus live
webinars. Skype allows users to make calls in
audio only or with video. Users can download
Skype for free but depending on the type of calls
made, fees or charges could be assessed.
Individuals should read through all of the
information before downloading, installing, and
using this software. Twitter allows participants to
answer the question “What are you doing?” with
messages containing 140 or fewer characters.
Although Twitter can be used to keep the friends
in a person’s network updated on daily activities,
it can also be used for other purposes, such as
asking questions or expressing thoughts. In
addition, Twitter can be accessed by cell
phones, so users can stay in touch on the go.

Along with all of the advantages and intellectual
harvesting capabilities from the use of these
tools come serious security issues. Wagner
(2007) warned the user to “bear in mind before
you jump in that you’re giving information to a
third-party company to store” (para. 5). He also
states that “you should talk to your company’s
legal and compliance offices to be sure you’re
obeying the law and regulations with regard to
managing company’s information” (para. 5). One

suggestion that Wagner offers is that if you do
not want to involve a third party, “Wikis provide a
good alternative for organizations looking to
maintain control of their own software.
Organizations can install wiki software on their
own, internal servers” (para. 6).

This new wave of Web-based tools facilitates
the ability to interact, exchange, collaborate,
communicate, and share in ways that have only
begun to be realized. As the tools and their
innovative uses continue to expand, users need
to stay vigilant to handle the associated security
challenges. These Web 2.0 and beyond tools
are providing a new cyber-playground that is
limited only by users’ own imaginations and
intelligence. We encourage you to explore these
tools.

REFERENCE

Wagner, M. (2007). Nine easy Web-
based collaborative tools.
Forbes. Retrieved from
http://www.forbes.com/2007/02/26/google-
microsoft-bluetie-enttech-
cx_mw_0226smallbizresource.html

Cloud Computing
Cloud computing has Web browser–based login-
accessible data, software, and hardware that you can
access and use. Using the cloud, you could link
systems together and reduce costs (Figure 3-4).
According to Griffith (2016), “cloud computing means
storing and accessing data and programs over the
Internet instead of [on] your computer’s hard drive. The
cloud is just a metaphor for the Internet” (para. 2). IBM
(2016) stated that cloud computing, “referred to as
simply ‘the cloud,’ is the delivery of on-demand
computing resources—everything from applications to
data centers—over the Internet on a pay-for-use basis”
(para. 1). IBM described services as elastic resources,
either metered or self-service. Elastic resources refer
to those that are able to be scaled up or down to meet
the consumer’s needs. Metered services allow you to
pay only for what you use, and self-service refers to
having self-service access to all of the IT resources the
consumer needs. Woodford (2016) stated that cloud
computing is different because it is managed; on-
demand; and can be public, private, or a hybrid of both.
The public cloud is owned and operated by
companies offering public access to computing
resources. It is believed to be more affordable and
economically sound because the user does not need to
purchase the hardware, software, or supporting
infrastructure, as these are managed and owned by the
cloud provider (IBM, 2016). The private cloud is

operated for a single organization with the
infrastructure being managed and/or hosted internally
or outsourced to a third party; it provides added control
and avoids multi-tenancy (IBM).

As we explore Web-based apps and computing over
the Internet, we are cloud computing. Griffith (2016)
described some common major examples of cloud
computing that you might be using right now: Google
Drive, Microsoft Office Online, Microsoft OneDrive,
Apple iCloud, Amazon Cloud Drive, Box, Dropbox, and
SugarSync. There is also cloud hardware; the primary
example of a device that is completely cloud-centric is
the Chromebook, a laptop that has just enough local
storage and power to run the Chrome OS, which
essentially turns the Google Chrome Web browser into
an operating system. “With a Chromebook, most
everything you do is online: apps, media, and storage
are all in the cloud” (Griffith, 2016, para. 16).

Figure 3-4 Cloud Computing

Cloud storage is data storage provided by networked
online servers that are typically outside of the institution
whose data are being housed.

There are also additional services based in the cloud
that are mainly business related: software as a
service (SaaS), platform as a service (PaaS), and
infrastructure as a service (IaaS) (Figure 3-5). SaaS,
such as Salesforce.com refers to cloud-based
applications with the following benefits: quickly start
using innovative or specific business apps that are
scalable to your needs, any connected computer can
access the apps and data, and data is not lost if your
hard drive crashes because the data is stored in the

cloud (Griffith, 2016; IBM, 2016). PaaS provides
everything needed to support the cloud application’s
building and delivery, enabling users to develop and
launch custom Web applications rapidly to the cloud
(Griffith, 2016; IBM, 2016). IaaS such as Amazon,
Microsoft, Google, and Rackspace provide a rentable
backbone to companies, enabling the scalable, on-
demand infrastructure they need to support their
dynamic workloads; the user pays only for what they
use and he or she does not have to invest in hardware
such as networks, storage, and data center space
(Griffith, 2016; IBM, 2016). You can access and
receive services from Netflix and Pinterest because
they are customers of Amazon’s cloud services.
According to Griffith (2016), cloud computing is truly
big business and could generate 500 billion dollars
within the next 5 years.

Figure 3-5 Software as a Service (SaaS), Platform as
a Service (PaaS), and Infrastructure as a Service
(IaaS)

Cloud computing is Internet computing, and it has the
same pitfalls and benefits as using the Internet. Some
are not sold on the claims that it is totally reliable, safe,
and/or secure. Others believe it is a more
environmentally friendly option because it uses fewer
resources and less energy, and yet many people can
share efficiently managed, centralized cloud-based
systems (Woodford, 2016). One of the driving forces
behind the initiation of cloud computing was the need
for scalable resources that are affordable. As with
anything on the Internet, these resources can be
shared or privately held. Cloud computing will continue

to grow as long as there is demand and it can meet the
scalability requirements while maintaining secure,
reliable spaces.

In an ideal world, nurses would be able to use and
interact with computer technologies effectively to
enhance patient care. They would understand
computer science and know how to harness its
capabilities to benefit the profession and ultimately
their patients.

Looking to the Future
The use of the cloud will continue to expand. The
market for wearable technology, which is comprised
of smaller and faster handheld and portable computer
systems, and high-quality voice-activated inventions
will further facilitate the use of computers in nursing
practice and professional development. The field of
computer science will continue to contribute to the
evolving art and science of nursing informatics. New
trends promise to bring wide-sweeping and (it is
hoped) positive changes to the practice of nursing.
Computers and other technologies have the potential
to support a more client-oriented healthcare system in
which clients truly become active participants in their
own healthcare planning and decisions. Mobile health
technology, telenursing, sophisticated electronic health
records, and next-generation technology are predicted
to contribute to high-quality nursing care and

consultation within healthcare settings, including
patients’ homes and communities.

Computers are becoming more powerful, yet more
compact, which will contribute to the development of
several technologic initiatives that are currently still in
their infancy, such as quantum computing. Some of
these initiatives are described here. These predicted
innovations are only some of the many computer and
technologic applications being developed. As nurses
gain proficiency in capitalizing on the creative,
timesaving, and interactive capabilities emerging from
information technology research, the field of nursing
informatics will grow in similar proportions.

Quantum Computing
Quantum bits (qubits) are three-dimensional arrays of
atoms in quantum states. A quantum computer is a
proposed machine that is not based on the binary
system, but instead performs calculations based on the
behavior of subatomic particles or qubits. It is
estimated that if quantum computing, the act of using a
quantum computer, is ever realized, we will be able to
execute millions of instructions per second (MIPS)
due to the qubits existing in more than one state at a
time or having the ability to simultaneously execute and
process. According to Kennedy (2016), “the era of
quantum computers is one step closer” (para. 1) due to
the creation of qubits by David Weiss’s research team.

Voice-Activated Communicators
Voice-activated communicators are already on the
market, with new iterations being developed by a
variety of companies, including Vocera
Communications. Vocera (2015) developed the Vocera
B3000n Communication Badge, which

is a lightweight, voice-controlled,
wearable device that enables instant two-
way or one to many conversations using
intuitive and simple commands. The
Vocera Badge is widely used by mobile
workers who need wearable devices that
provide the convenience and expedience
of being able to respond to calls without
pressing a button (i.e. sterile operating
rooms, nuclear power plants, hotel staff,
security personnel). (para. 1)

These new technologies will permit nurses to use
wireless, hands-free devices to communicate with one
another and to record data. This technology is
becoming a user-friendly and cost-effective way to
increase clinical productivity.

Game and Simulation Technology
Game and simulation technology is offering realistic,
innovative ways to teach content in general, including

healthcare informatics concepts and skills. The same
technology that powers video games is being used to
create dynamic educational interfaces to help students
learn about pathophysiology, care guidelines, and a
host of other topics. Such applications are also very
valuable for client education and health promotion
materials. The “serious games” industry is growing now
that video game producers are looking beyond mere
entertainment to address public and private policy,
management, and leadership issues and topics,
including those related to health care. For example, the
Games for Health Project, initiated by the Robert Wood
Johnson Foundation (2015), is working on developing
best practices to support innovation in healthcare
training, messaging, and illness management. The
Serious Games & VE Arcade & Showcase is presented
at the annual meetings of the Society for Simulation in
Healthcare and is continuing to flourish with numerous
products available to demonstrate.

Virtual Reality
Virtual reality is another technological breakthrough
that is and will continue to influence healthcare
education and professional development. Virtual reality
is a three-dimensional, computer-generated “world”
where a person (with the right equipment) can move
about and interact as if he or she was actually in the
visualized location. The person’s senses are immersed
in this virtual reality world using special gadgetry, such

as head-mounted displays, data gloves, joysticks, and
other hand tools. The equipment and special
technology provide a sense of presence that is lacking
in multimedia and other complex programs. According
to Smith (2015), “It’s crazy but true: Virtual reality will
be a real thing in people’s homes by this time next
year” (para. 1). There are numerous products
available. Virtual Realities (2015) stated that they
provide “head mounted displays, head trackers, motion
trackers, data gloves, 3D controllers, haptic devices,
stereoscopic 3D displays, VR domes and virtual reality
software. Virtual Realities’ products are used by
government, educational, industrial, medical and
entertainment markets worldwide” (para. 1). Oculus VR
(2015) developed Rift, which is the next generation of
virtual reality products, and they are currently
distributing the developer kits. HTC (2015)
manufactures consumer electronics and developed the
Vive headset. The Morpheus headset is used with
PlayStation 4.

Mobile Devices
Mobile devices will be used more by nurses both at the
point of care and in planning, documenting, interacting
with the interprofessional healthcare team, and
research. Nurses also will be using such powerful
wearable technologies as nano-based diagnostic
sensors in their personal lives, and will be generating
their own data streams and receiving data from the

wearable and mobile devices their patients use.
Silbershatz et al. (2013) stated that Apple iOS and
Google Android are “currently dominating mobile
computing” (p. 37). Perry (2015) stated that it is
“estimated more than 177 million wearable devices will
be in use by 2018” (para. 5). Cisco (2014) reported that
“by the year 2020, the majority of Generation X and Y
professionals believe that smartphones and wearable
devices will be the workforce’s most important
‘connected’ device—while the laptop remains the
workplace device of choice” (para. 1). Data are truly at
our fingertips.

Summary
The field of computer science is one of the fastest-
growing disciplines. Astonishing innovations in
computer hardware, software, and architecture have
occurred over the past few decades, and there are no
indications that this trend will come to a halt anytime
soon. Computers have increased in speed, accuracy,
and efficiency, yet now cost less and have reduced
physical size compared to their forebears. These
trends are predicted to continue. Current computer
hardware and software serve as vital and valuable
tools for both nurses and patients to engage in on-
screen and online activities that provide rich access to
data and information. Productivity, creativity, and
communication software tools also enable nurses to
work with computers to further foster knowledge

acquisition and development. Wide access to vast
stores of information and knowledge shared by others
facilitates the emergence of wisdom in users, which
can then be applied to nursing in meaningful and
creative ways. It is imperative that nurses become
discerning, yet skillful users of computer technology to
apply the principles of nursing informatics to practice to
improve patient care and to contribute to the
profession’s ever-growing body of knowledge.

Working Wisdom
Since the beginning of the profession, nurses have
applied their ingenuity, resourcefulness, and
professional awareness of what works to adapt
technology and objects to support nursing care, usually
with the intention of promoting efficiency but also in
support of client comfort and healing. This
resourcefulness could also be applied effectively to the
adaptation of information technology within the care
environment, to ensure that the technology truly does
serve clients and nurses and the rest of the
interprofessional team.

Consider this question: “How can you develop
competency in using the various computer hardware
and software not only to promote efficient, high-quality
nursing care and to develop yourself professionally, but
also to further the development of the profession’s
body of knowledge?”

Application Scenario
Dan P. is a first-year student in graduate studies in
nursing. In the past, he has learned to use his family’s
personal computer to surf the World Wide Web,
exchange email with friends, and play some computer
games. Now, however, Dan realizes that the computer
is a vital tool for his academic success. He has saved
up enough money to purchase a laptop computer. He
has decided on an Intel processor with 1 TB of storage
and 8 GB of RAM. Dan also wishes to choose
appropriate software for his system. He is on a limited
budget but wants to make the most of his investment.

1. Dan still wants to learn more about computers.
You recommend that he review the following
information: Domingo (2016), Knapp (2016), and
PCMag Digital Group (2016).

2. Which of the four categories of software
discussed in this chapter would benefit Dan the
most in his studies (OS, productivity, creativity,
or communication)? Dan definitely needs an OS
—this is critical. He would also directly benefit
from productivity software and at least
connective email and web browser software
from the communication group so he can access
the Internet for research, to collaborate with
peers, and to communicate with his teachers.

3. How could Dan afford to install software from all
four groups on his new laptop? If Dan accessed

some open source software (e.g., Apache
OpenOffice for his productivity software), he
could save money to put toward creativity
software.

THOUGHT-PROVOKING QUESTIONS

1. How can knowledge of computer
hardware and software help nurses to
participate in information technology
adoption decisions in the practice area?

2. How can new computer software help
nurses engage in professional
development, collaboration, and
knowledge dissemination activities at their
own pace and leisure?

References
Alba, D. (2015). Why on earth is IBM still

making mainframes? Wired. Retrieved
from
http://www.wired.com/2015/01/z13-
mainframe

Anderson, M. (2016). Intel says chips to
become slower but more energy
efficient. Retrieved from

https://thestack.com/iot/2016/02/05/intel-
william-holt-moores-law-slower-
energy-efficient-chips

Bagaza, L., & Westover, B. (2016). The 10
best computer mice of 2016. PC
Magazine. Retrieved from
http://www.pcmag.com/article2/0,2817,2374831,00.asp

Bandura, A. (2002). Growing primacy of
human agency in adaptation and
change in the electronic era. European
Psychologist, 7(1), 2–16.

Cisco. (2014). Working from Mars with an
Internet brain implant: Cisco study
shows how technology will shape the
“Future of Work.” Retrieved from
http://newsroom.cisco.com/press-
release-content?
type=webcontent&articleId=1528226

Domingo, J. (2016). The 10 best desktop
PCs of 2016. PC Magazine. Retrieved
from
http://www.pcmag.com/article2/0,2817,2372609,00.asp

Evans, D. (2010). Introduction to
computing: Explorations in language,
logic, and machines. University of
Virginia. Retrieved from
http://www.computingbook.org

Futuremark. (2016). Best processors May
– 2016. Retrieved from
http://www.futuremark.com/hardware/cpu

Griffith, E. (2016). What is cloud
computing? PC Magazine. Retrieved
from
http://www.pcmag.com/article2/0,2817,2372163,00.asp

HTC. (2015). HTC’s VR vision. Finally, the
future. Retrieved from
http://www.htcvr.com

IBM. (2016). What is cloud computing?
Retrieved from
https://www.ibm.com/cloud-
computing/what-is-cloud-computing

Intel Corporation. (2016). Intel Xeon
processor E5 family: Product

specifications. Retrieved from
http://www.intel.com/content/www/us/en/processors/xeon/xeon-
processor-e5-family.html

Kennedy, B. (2016). New, better way to
build circuits for the world’s first useful
quantum computers. Phys.org.
Retrieved from
http://phys.org/news/2016-06-
circuits-world-quantum.html#jCp

Knapp, M. (2016). 9 key things to know
before you buy a computer. Gear &
Style Cheat Sheet. Retrieved from
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tips-for-picking-your-machine-
computer-shopping-cheat-
sheet.html/?a=viewall

Oculus VR. (2015). Step into the Rift.
Retrieved from
https://www.oculus.com/en-us/rift

PCMag Digital Group. (2016). Laptops
and notebooks. PC Magazine.
Retrieved from

http://www.pcmag.com/reviews/laptop-
computers

Perry, L. (2015). Evolving millennial
connections using wearables. Cisco.
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http://blogs.cisco.com/tag/wearable-
technology

Robert Wood Johnson Foundation.
(2015). Games for health. Retrieved
from
http://gamesforhealth.org/about

Sarkar, N. (2006). Tools for teaching
computer networking and hardware
concepts. Hershey, PA: Idea Group.

Sexton, M. (2016). StarTech unveils USB
type-C to HDMI adapter. Retrieved
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usb-typec-hdmi-adapter,31067.html

Silbershatz, A., Baer Galvin, P., & Gagne,
G. (2013). Operating system concepts

(9th ed.). Hoboken, NJ: John Wiley &
Sons.

Smith, D. (2015). 3 virtual reality products
will dominate our living rooms by this
time next year. Business Insider.
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reality-is-getting-real-2015-5

Virtual Realities. (2015). Worldwide
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badge

Woodford, C. (2016). Cloud computing.
Retrieved from
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computing-introduction.html

CHAPTER 4: Introduction
to Cognitive Science and
Cognitive Informatics

Kathleen Mastrian and Dee McGonigle

Objectives
1. Describe cognitive science.
2. Assess how the human mind processes

and generates information and
knowledge.

3. Explore cognitive informatics.
4. Examine artificial intelligence and its

relationship to cognitive science and
computer science.

Key Terms
» Artificial intelligence

» Brain

» Cognitive informatics

» Cognitive science

» Computer science

» Connectionism

» Decision making

» Empiricism

» Epistemology

» Human Mental Workload (MWL)

» Intelligence

» Intuition

» Knowledge

» Logic

» Memory

» Mind

» Neuroscience

» Perception

» Problem solving

» Psychology

» Rationalism

» Reasoning

» Wisdom

Introduction
Cognitive science is the fourth of four basic building
blocks used to understand informatics (Figure 4-1).
The Building Blocks of Nursing Informatics section
began by examining nursing science, information
science, and computer science, and considering how
each relates to and helps one understand the concept
of informatics. This chapter explores the building
blocks of cognitive science, cognitive informatics
(CI), and artificial intelligence (AI).

Figure 4-1 Building Blocks of Nursing Informatics

Throughout the centuries, cognitive science has
intrigued philosophers and educators alike. Beginning
in Greece, the ancient philosophers sought to
comprehend how the mind works and what the nature
of knowledge is. This age-old quest to unravel the
processes inherent in the working brain has been
undertaken by some of the greatest minds in history.
However, it was only about 50 years ago that computer
operations and actions were linked to cognitive
science, meaning theories of the mind, intellect, or

brain. This association led to the expansion of cognitive
science to examine the complete array of cognitive
processes, from lower-level perceptions to higher-level
critical thinking, logical analysis, and reasoning.

The focus of this chapter is the impact of cognitive
science on nursing informatics (NI). This section
provides the reader with an introduction and overview
of cognitive science, the nature of knowledge, wisdom,
and AI as they apply to the Foundation of Knowledge
model and NI. The applications to NI include problem
solving, decision support systems, usability issues,
user-centered interfaces and systems, and the
development and use of terminologies.

Cognitive Science
The interdisciplinary field of cognitive science studies
the mind, intelligence, and behavior from an
information-processing perspective. H. Christopher
Longuet-Higgins originated the term “cognitive science”
in his 1973 commentary on the Lighthill report, which
pertained to the state of AI research at that time. The
Cognitive Science Society and the Cognitive Science
Journal date back to 1980 (Cognitive Science
Society, 2005). Their interdisciplinary base arises from
psychology, philosophy, neuroscience, computer
science, linguistics, biology, and physics; covers
memory, attention, perception, reasoning, language,
mental ability, and computational models of cognitive

processes; and explores the nature of the mind,
knowledge representation, language, problem solving,
decision making, and the social factors influencing the
design and use of technology. Simply put, cognitive
science is the study of the mind and how information is
processed in the mind. As described in the Stanford
Encyclopedia of Philosophy (2010):

The central hypothesis of cognitive
science is that thinking can best be
understood in terms of representational
structures in the mind and computational
procedures that operate on those
structures. While there is much
disagreement about the nature of the
representations and computations that
constitute thinking, the central hypothesis
is general enough to encompass the
current range of thinking in cognitive
science, including connectionist theories
which model thinking using artificial
neural networks. (para. 9)

Connectionism is a component of cognitive science
that uses computer modeling through artificial neural
networks to explain human intellectual abilities. Neural
networks can be thought of as interconnected simple
processing devices or simplified models of the brain
and nervous system that consist of a considerable

number of elements or units (analogs of neurons)
linked together in a pattern of connections (analogs of
synapses). A neural network that models the entire
nervous system would have three types of units: (1)
input units (analogs of sensory neurons), which receive
information to be processed; (2) hidden units (analogs
to all of the other neurons, not sensory or motor), which
work in between input and output units; and (3) output
units (analogs of motor neurons), where the outcomes
or results of the processing are found.

Connectionism (Figure 4-2) is rooted in how
computation occurs in the brain and nervous system or
biologic neural networks. On their own, single neurons
have minimal computational capacity. When
interconnected with other neurons, however, they have
immense computational power. The connectionism
system or model learns by modifying the connections
linking the neurons. Artificial neural networks are
unique computer programs designed to model or
simulate their biologic analogs, the neurons of the
brain.

Figure 4-2 Connectionism

The mind is frequently compared to a computer, and
experts in computer science strive to understand how
the mind processes data and information. In contrast,
experts in cognitive science model human thinking
using artificial networks provided by computers—an
endeavor sometimes referred to as AI. How does the
mind process all of the inputs received? Which items
and in which ways are things stored or placed into
memory, accessed, augmented, changed,

reconfigured, and restored? Cognitive science provides
the scaffolding for the analysis and modeling of
complicated, multifaceted human performance and has
a tremendous effect on the issues impacting
informatics.

The end user is the focus of this activity because the
concern is with enhancing the performance in the
workplace; in nursing, the end user could be the actual
clinician in the clinical setting, and cognitive science
can enhance the integration and implementation of the
technologies being designed to facilitate this
knowledge worker with the ultimate goal of improving
patient care delivery. Technologies change rapidly, and
this evolution must be harnessed for the clinician at the
bedside. To do this at all levels of nursing practice, one
must understand the nature of knowledge, the
information and knowledge needed, and the means by
which the nurse processes this information and
knowledge in the situational context.

Sources of Knowledge
Just as philosophers have questioned the nature of
knowledge, so they have also strived to determine how
knowledge arises, because the origins of knowledge
can help one understand its nature. How do people
come to know what they know about themselves,
others, and their world? There are many viewpoints on
this issue, both scientific and nonscientific.

According to Holt (2006), “There are two competing
traditions concerning the ultimate source of our
knowledge: empiricism and rationalism” (para. 3).
Empiricism is based on knowledge being derived from
experiences or senses, whereas rationalism contends
that “some of our knowledge is derived from reason
alone and that reason plays an important role in the
acquisition of all of our knowledge” (para. 5).
Empiricists do not recognize innate knowledge,
whereas rationalists believe that reason is more
essential in the acquisition of knowledge than the
senses.

Three sources of knowledge have been identified: (1)
instinct, (2) reason, and (3) intuition. Instinct is when
one reacts without reason, such as when a car is
heading toward a pedestrian and he jumps out of the
way without thinking. Instinct is found in both humans
and animals, whereas reason and intuition are found
only in humans. Reason “[c]ollects facts, generalizes,
reasons out from cause to effect, from effect to cause,
from premises to conclusions, from propositions to
proofs” (Sivananda, 2004, para. 4). Intuition is a way
of acquiring knowledge that cannot be obtained by
inference, deduction, observation, reason, analysis, or
experience. Intuition was described by Aristotle as “[a]
leap of understanding, a grasping of a larger concept
unreachable by other intellectual means, yet
fundamentally an intellectual process” (Shallcross &
Sisk, 1999, para. 4).

Some believe that knowledge is acquired through
perception and logic. Perception is the process of
acquiring knowledge about the environment or situation
by obtaining, interpreting, selecting, and organizing
sensory information from seeing, hearing, touching,
tasting, and smelling. Logic is “[a] science that deals
with the principles and criteria of validity of inference
and demonstration: the science of the formal principles
of reasoning” (Merriam-Webster Online Dictionary,
2007, para. 1). Acquiring knowledge through logic
requires reasoned action to make valid inferences.

The sources of knowledge provide a variety of inputs,
throughputs, and outputs through which knowledge is
processed. No matter how one believes knowledge is
acquired, it is important to be able to explain or
describe those beliefs, communicate those thoughts,
enhance shared understanding, and discover the
nature of knowledge.

Nature of Knowledge
Epistemology is the study of the nature and origin of
knowledge—that is, what it means to know. Everyone
has a conception of what it means to know based on
their own perceptions, education, and experiences;
knowledge is a part of life that continues to grow with
the person. Thus a definition of knowledge is
somewhat difficult to agree on because it reflects the

viewpoints, beliefs, and understandings of the person
or group defining it. Some people believe that
knowledge is part of a sequential learning process
resembling a pyramid, with data on the bottom, rising
to information, then knowledge, and finally wisdom.
Others believe that knowledge emerges from
interactions and experience with the environment, and
still others think that it is religiously or culturally bound.
Knowledge acquisition is thought to be an internal
process derived through thinking and cognition or an
external process from senses, observations, studies,
and interactions. Descartes’s important premise “called
‘the way of ideas’ represents the attempt in
epistemology to provide a foundation for our
knowledge of the external world (as well as our
knowledge of the past and of other minds) in the
mental experiences of the individual” (Encyclopedia
Britannica, 2007, para. 4).

For the purpose of this text, knowledge is defined as
the awareness and understanding of a set of
information and ways that information can be made
useful to support a specific task or arrive at a decision.
It abounds with others’ thoughts and information or
consists of information that is synthesized so that
relationships are identified and formalized.

How Knowledge and Wisdom
Are Used in Decision Making

The reason for collecting and building data,
information, and knowledge is to be able to make
informed, judicious, prudent, and intelligent decisions.
When one considers the nature of knowledge and its
applications, one must also examine the concept of
wisdom. Wisdom has been defined in numerous ways:

Knowledge applied in a practical way or translated
into actions
The use of knowledge and experience to heighten
common sense and insight to exercise sound
judgment in practical matters
The highest form of common sense resulting from
accumulated knowledge or erudition (deep,
thorough learning) or enlightenment (education that
results in understanding and the dissemination of
knowledge)
The ability to apply valuable and viable knowledge,
experience, understanding, and insight while being
prudent and sensible
Focused on our own minds
The synthesis of our experience, insight,
understanding, and knowledge
The appropriate use of knowledge to solve human
problems

In essence, wisdom entails knowing when and how to
apply knowledge. The decision-making process
revolves around knowledge and wisdom. It is through
efforts to understand the nature of knowledge and its

evolution to wisdom that one can conceive of, build,
and implement informatics tools that enhance and
mimic the mind’s processes to facilitate decision
making and job performance.

Cognitive Informatics
Wang (2003) described CI as an emerging
transdisciplinary field of study that bridges the gap in
understanding regarding how information is processed
in the mind and in the computer. Computing and
informatics theories can be applied to help elucidate
the information processing of the brain, and cognitive
and neurologic sciences can likewise be applied to
build better and more efficient computer processing
systems. Wang suggested that the common issue
among the human knowledge sciences is the drive to
develop an understanding of natural intelligence and
human problem solving.

Pacific Northwest National Laboratory (PNNL), an
organization operated on behalf of the U.S.
Department of Energy, suggested the disciplines of
neuroscience, linguistics, AI, and psychology constitute
this field. PNNL (2008) defined CI as “the
multidisciplinary study of cognition and information
sciences, which investigates human information
processing mechanisms and processes and their
engineering applications in computing” (para. 1). CI
helps to bridge this gap by systematically exploring the

mechanisms of the brain and mind and exploring
specifically how information is acquired, represented,
remembered, retrieved, generated, and communicated.
This dawning of understanding can then be applied
and modeled in AI situations resulting in more efficient
computing applications.

Wang (2003) explained further:

Cognitive informatics attempts to solve
problems in two connected areas in a
bidirectional and multidisciplinary
approach. In one direction, CI uses
informatics and computing techniques to
investigate cognitive science problems,
such as memory, learning, and
reasoning; in the other direction, CI uses
cognitive theories to investigate the
problems in informatics, computing, and
software engineering. (p. 120)

Principles of cognitive informatics and an
understanding of how humans interact with computers
can be used to build information technology (IT)
systems that better meet the needs of users (Figure 4-
3). If a system is too complex or too taxing for a user,
he or she is likely to resist its use. The National Center
for Cognitive Informatics and Decision Making in
Healthcare (NCCD) was established to respond to “the

urgent and long-term cognitive challenges in health IT
adoption and meaningful use. NCCD’s vision is to
become a national resource that provides strategic
leadership in patient-centered cognitive support
research and applications in health care”
(HealthIT.gov, 2013, para. 1). Similarly, Longo (2015)
emphasized Human Mental Workload (MWL) as a
key component in effective system design (Figure 4-4).
He stated,

Figure 4-3 Cognitive Informatics Leads to Usable
Systems

Figure 4-4 Human Mental Workload

At a low level of MWL, people may often
experience annoyance and frustration
when processing information. On the
other hand, a high level can also be both
problematic and even dangerous, as it
leads to confusion, decreases
performance in information processing
and increases the chances of errors and
mistakes. (p. 758)

Cognitive Informatics and

Nursing Practice
According to Mastrian (2008), the recognition of the
potential application of principles of cognitive science
to NI is relatively new. The traditional and widely
accepted definition of NI advanced by Graves and
Corcoran (1989) is that NI is a combination of nursing
science, computer science, and information science
used to describe the processes nurses use to manage
data, information, and knowledge in nursing practice.
Turley (1996) proposed the addition of cognitive
science to this mix, as nurse scientists are seen to
strive to capture and explain the influence of the
human brain on data, information, and knowledge
processing and to elucidate how these factors in turn
affect nursing decision making. The need to include
cognitive sciences is imperative as researchers attempt
to model and support nursing decision making in
complex computer programs.

In 2003, Wang proposed the term cognitive informatics
to signify the branch of information and computer
sciences that investigates and explains information
processing in the human brain. The science of CI grew
out of interest in AI, as computer scientists developed
computer programs that mimic the information
processing and knowledge generation functions of the
human brain. CI bridges the gap between artificial and
natural intelligence and enhances the understanding of
how information is acquired, processed, stored, and

retrieved so that these functions can be modeled in
computer software.

What does this have to do with nursing? At its very
core, nursing practice requires problem solving and
decision making. Nurses help people manage their
responses to illnesses and identify ways that patients
can maintain or restore their health. During the nursing
process, nurses must first recognize that there is a
problem to be solved, identify the nature of the
problem, pull information from knowledge stores that is
relevant to the problem, decide on a plan of action,
implement the plan, and evaluate the effectiveness of
the interventions. When a nurse has practiced the
science of nursing for some time, he or she tends to do
these processes automatically; it is instinctively known
what needs to be done to intervene in the problem.
What happens, however, if the nurse faces a situation
or problem for which he or she has no experience on
which to draw? The ever-increasing acuity and
complexity of patient situations coupled with the
explosion of information in health care has fueled the
development of decision support software embedded in
the electronic health record. This software models the
human and natural decision-making processes of
professionals in an artificial program. Such systems
can help decision makers to consider the
consequences of different courses of action before
implementing the action. They also provide stores of
information that the user may not be aware of and can

use to choose the best course of action and ultimately
make a better decision in unfamiliar circumstances.

Decision support programs continue to evolve as
research in the fields of cognitive science, AI, and CI is
continuously generated and then applied to the
development of these systems. Nurses must embrace
—not resist—these advances as support and
enhancement of the practice of nursing science.

What Is AI?
The field of AI deals with the conception, development,
and implementation of informatics tools based on
intelligent technologies. This field captures the complex
processes of human thought and intelligence.

Herbert Simon believes that the field of AI could have
two functions: “One is to use the power of computers to
augment human thinking, just as we use motors to
augment human or horse power. . . . The other is to
use a computer’s artificial intelligence to understand
how humans think. In a humanoid way” (Stewart,
1994, para. 13). According to the AAAI (2014), AI is the
“scientific understanding of the mechanisms underlying
thought and intelligent behavior and their embodiment
in machines” (para. 1).

John McCarthy, one of the men credited with founding
the field of AI in the 1950s, stated that AI “is the

science and engineering of making intelligent
machines, especially intelligent computer programs. It
is related to the similar task of using computers to
understand human intelligence, but AI does not have to
confine itself to methods that are biologically
observable” (2007, p. 2).

Lamont (2007) interviewed Ray Kurzweil, a visionary
who defined AI as “the ability to perform a task that is
normally performed by natural intelligence, particularly
human natural intelligence. We have in fact artificial
intelligence that can perform many tasks that used to
require—and could only be done by—human
intelligence” (para. 6). The intelligence factor is
extremely important in AI and has been defined by
McCarthy as “the computational part of the ability to
achieve goals in the world. Varying kinds and degrees
of intelligence occur in people, many animals, and
some machines” (2007, p. 2).

The challenge of this field rests in capturing, mimicking,
and creating the complex processes of the mind in
informatics tools, including software, hardware, and
other machine technologies, with the goal that the tool
be able to initiate and generate its own mechanical
thought processing. The brain’s processing is highly
intricate and complicated. This complexity is reflected
in Cohn’s (2006) comment that “Artificial intelligence is
50 years old this summer, and while computers can
beat the world’s best chess players, we still can’t get

them to think like a 4-year-old” (para. 1). AI uses
cognitive science and computer science to replicate
and generate human intelligence. This field will
continue to evolve and produce artificially intelligent
tools to enhance nurses’ personal and professional
lives.

AI in the Future
As electronic health records become more ubiquitous
and we have access to physiologic data streamed in
real time, we will have the potential to process large
amounts of data using AI tools and we will begin to see
data analytics that will enable machine processing that
far exceeds the capabilities of the human mind.
According to Neill (2013),

Perhaps the next great challenge for AI in
healthcare is to develop approaches that
can be applied to the entire population of
patients monitoring huge quantities of
data to automatically detect threats to
patient safety (including patterns of
suboptimal care, as well as outbreaks of
hospital acquired illness), and to discover
new best practices of patient care. (p. 93)

Summary

Cognitive science is the interdisciplinary field that
studies the mind, intelligence, and behavior from an
information-processing perspective. CI is a field of
study that bridges the gap in understanding regarding
how information is processed in the mind and in the
computer. Computing and informatics theories can be
applied to help elucidate the information processing of
the brain, and cognitive and neurologic sciences can
likewise be applied to build better and more efficient
computer processing systems.

AI is the field that deals with the conception,
development, and implementation of informatics tools
based on intelligent technologies. This field captures
the complex processes of human thought and
intelligence. AI uses cognitive science and computer
science to replicate and generate human intelligence.

The sources of knowledge, nature of knowledge, and
rapidly changing technologies must be harnessed by
clinicians to enhance their bedside care. Therefore, we
must understand the nature of knowledge, the
information and knowledge needed, and the means by
which nurses process this information and knowledge
in their own situational context. The reason for
collecting and building data, information, and
knowledge is to be able to build wisdom—that is, the
ability to apply valuable and viable knowledge,
experience, understanding, and insight while being
prudent and sensible. Wisdom is focused on our own

minds, the synthesis of our experience, insight,
understanding, and knowledge. Nurses must use their
wisdom and make informed, judicious, prudent, and
intelligent decisions while providing care to patients,
families, and communities. Cognitive science, CI, and
AI will continue to evolve to help build knowledge and
wisdom.

THOUGHT-PROVOKING QUESTIONS

1. How would you describe CI? Reflect on a
plan of care that you have developed for
a patient. How could CI be used to create
tools to help with or support this important
work?

2. Think of a clinical setting with which you
are familiar and envision how AI tools
might be applied in this setting. Are there
any current tools in use? Which current or
emerging tools would enhance practice in
this setting and why?

3. Use your creative mind to think of a tool
of the future based on cognitive
informatics that would support your
practice.

References

Association for the Advancement of
Artificial Intelligence (AAAI). (2014).
Homepage. Retrieved from
http://www.aaai.org

Cognitive Science Society. (2005). CSJ
archive. Retrieved from
http://www.cogsci.rpi.edu/CSJarchive/1980v04/index.html

Cohn, D. (2006). AI reaches the golden
years. Wired. Retrieved from
http://archive.wired.com/science/discoveries/news/2006/07/71389

Encyclopedia Britannica. (2007).
Epistemology. Retrieved from
http://www.britannica.com/eb/article-
247960/epistemology

Graves, J., & Corcoran, S. (1989). The
study of nursing informatics. Image:
Journal of Nursing Scholarship, 21(4),
227–230.

HealthIT.gov. (2013). National center for
cognitive informatics and decision
making in healthcare. Retrieved from

https://www.healthit.gov/policy-
researchers-implementers/national-
center-cognitive-informatics-and-
decision-making-healthcare

Holt, T. (2006). Sources of knowledge.
Retrieved from
http://www.theoryofknowledge.info/sourcesofknowledge.html

Lamont, I. (2007). The grill: Ray Kurzweil
talks about “augmented reality” and the
singularity. Computer World. Retrieved
from
http://www.computerworld.com/action/article.do?
command=viewArticleBasic&articleId=306176

Longo, L. (2015). A defeasible reasoning
framework for human mental workload
representation and assessment.
Behaviour & Information Technology,
34(8), 758–786.
doi:10.1080/0144929X.2015.1015166

Longuet-Higgins, H. C. (1973). Comments
on the Lighthill report and the
Sutherland reply. Artificial Intelligence:
A Paper Symposium, 35–37.

Mastrian, K. (2008, February). Invited
editorial: Cognitive informatics and
nursing practice. Online Journal of
Nursing Informatics, 12(1). Retrieved
from http://ojni.org/12_1/kathy.html

McCarthy, J. (2007). What is artificial
intelligence? Retrieved from
http://www.formal.stanford.edu/jmc/whatisai.pdf

Merriam-Webster Online Dictionary.
(2007). Logic. Retrieved from
http://www.merriam-
webster.com/dictionary/logic

Neill, D. (2013). Using artificial intelligence
to improve hospital inpatient care.
IEEE Intelligent Systems, 92–95.

Pacific Northwest National Laboratory,
U.S. Department of Energy. (2008).
Cognitive informatics. Retrieved from
http://www.pnl.gov/coginformatics

Shallcross, D. J., & Sisk, D. A. (1999).
What is intuition? In T. Arnold (Ed.),
Hyponoesis glossary: Intuition.
Retrieved from
http://www.hyponoesis.org/Glossary/Definition/Intuition

Sivananda, S. (2004). Four sources of
knowledge. The Divine Life Society.
Retrieved from
http://www.dlshq.org/messages/knowledge.htm

Stanford Encyclopedia of Philosophy.
(2010). Cognitive science. Retrieved
from
http://plato.stanford.edu/entries/cognitive-
science

Stewart, D. (1994). The creator of the first
thinking machine on the future of
artificial intelligence: Herbert Simon on
the mind in the machine. OMNI Q&A.
Retrieved from
http://www.omnimagazine.com/archives/interviews/simon/index.html

Turley, J. (1996). Toward a model for
nursing informatics. Image: Journal of
Nursing Scholarship, 28(4), 309–313.

Wang, Y. (2003). Cognitive informatics: A
new transdisciplinary research field.
Brain and Mind, 4(2), 115–127.

CHAPTER 5: Ethical
Applications of
Informatics

Dee McGonigle, Kathleen Mastrian, and Nedra Farcus

Objectives
1. Recognize ethical dilemmas in nursing

informatics.
2. Examine ethical implications of nursing

informatics.
3. Evaluate professional responsibilities for

the ethical use of healthcare informatics
technology.

4. Explore the ethical model for ethical
decision making.

5. Analyze practical ways of applying the
ethical model for ethical decision making
to manage ethical dilemmas in nursing
informatics.

Key Terms
» Alternatives

» Antiprinciplism

» Applications (Apps)

» Autonomy

» Beneficence

» Bioethics

» Bioinformatics

» Care ethics

» Casuist approach

» Confidentiality

» Consequences

» Courage

» Decision making

» Decision support

» Duty

» Ethical decision making

» Ethical dilemma

» Ethical, social, and legal implications

» Ethicists

» Ethics

» Eudaemonistic

» Fidelity

» Good

» Google Glass

» Harm

» Justice

» Liberty

» Moral dilemmas

» Moral rights

» Morals

» Negligence

» Nicomachean

» Nonmaleficence

» Principlism

» Privacy

» Rights

» Security

» Self-control

» Smartphones

» Social media

» Standards

» Truth

» Uncertainty

» Values

» Veracity

» Virtue

» Virtue ethics

» Wisdom

Introduction
Those who followed the actual events of Apollo 13, or
who were entertained by the movie (Howard, 1995),
watched the astronauts strive against all odds to bring
their crippled spaceship back to Earth. The speed of
their travel was incomprehensible to most viewers, and
the task of bringing the spaceship back to Earth
seemed nearly impossible. They were experiencing a
crisis never imagined by the experts at NASA, and they
made up their survival plan moment by moment. What
brought them back to Earth safely? Surely, credit must
be given to the technology and the spaceship’s ability

to withstand the trauma it experienced. Most amazing,
however, were the traditional nontechnological tools,
skills, and supplies that were used in new and different
ways to stabilize the spacecraft’s environment and
keep the astronauts safe while traveling toward their
uncertain future.

This sense of constancy in the midst of change serves
to stabilize experience in many different life events and
contributes to the survival of crisis and change. This
rhythmic process is also vital to the healthcare
system’s stability and survival in the presence of the
rapidly changing events of the Knowledge Age. No one
can dispute the fact that the Knowledge Age is
changing health care in ways that will not be fully
recognized and understood for years. The change is
paradigmatic, and every expert who addresses this
change reminds healthcare professionals of the need
to go with the flow of rapid change or be left behind.

As with any paradigm shift, a new way of viewing the
world brings with it some of the enduring values of the
previous worldview. As health care continues its
journey into digital communications, telehealth, and
wearable technologies, it brings some familiar tools
and skills recognized in the form of values, such as
privacy, confidentiality, autonomy, and
nonmaleficence. Although these basic values remain
unchanged, the standards for living out these values
will take on new meaning as health professionals

confront new and different moral dilemmas brought on
by the adoption of technological tools for information
management, knowledge development, and evidence-
based changes in patient care. Ethical decision-making
frameworks will remain constant, but the context for
examining these moral issues or ethical dilemmas will
become increasingly complex.

This chapter highlights some familiar ethical concepts
to consider on the challenging journey into the
increasingly complex future of healthcare informatics.
Ethics and bioethics are briefly defined, and the
evolution of ethical approaches from the Hippocratic
ethic era, to principlism, to the current antiprinciplism
movement of ethical decision making is examined.
New and challenging ethical dilemmas are surfacing in
the venture into the unfolding era of healthcare
informatics (Figure 5-1). Also presented in this chapter
are findings from some of the more recent literature
related to these issues. Readers are challenged to
think constantly and carefully about ethics as they
become involved in healthcare informatics and to stay
abreast of new developments in ethical approaches.

Figure 5-1 Ethics in Health Care

Ethics
Ethics is a process of systematically examining
varying viewpoints related to moral questions of right
and wrong. Ethicists have defined the term in a variety
of ways, with each reflecting a basic theoretical
philosophic perspective.

Beauchamp and Childress (1994) referred to ethics as
a generic term for various ways of understanding and
examining the moral life. Ethical approaches to this
examination may be normative, presenting standards
of right or good action; descriptive, reporting what

people believe and how they act; or explorative,
analyzing the concepts and methods of ethics.

Husted and Husted (1995) emphasized a practice-
based ethics, stating “ethics examines the ways men
and women can exercise their power in order to bring
about human benefit—the ways in which one can act in
order to bring about the conditions of happiness” (p. 3).

Velasquez, Andre, Shanks, and Myer (1987) posed the
question, “What is ethics?”, and answered it with the
following two-part response: “First, ethics refers to well-
based standards of right and wrong that prescribe what
humans ought to do, usually in terms of rights,
obligations, benefits to society, fairness, or specific
virtues” (para. 10), and “Secondly, ethics refers to the
study and development of one’s ethical standards”
(para. 11).

Regardless of the theoretical definition, common
characteristics regarding ethics are its dialectical, goal-
oriented approach to answering questions that have
the potential for multiple acceptable answers.

Bioethics
Bioethics is defined as the study and formulation of
healthcare ethics. Bioethics takes on relevant ethical
problems experienced by healthcare providers in the
provision of care to individuals and groups. Husted and

Husted (1995) state the fundamental background of
bioethics that forms its essential nature is:

1. The nature and needs of humans as living,
thinking beings

2. The purpose and function of the healthcare
system in a human society

3. An increased cultural awareness of human
beings’ essential moral status (p. 7)

Bioethics emerged in the 1970s as health care began
to change its focus from a mechanistic approach of
treating disease to a more holistic approach of treating
people with illnesses. As technology advanced,
recognition and acknowledgment of the rights and the
needs of individuals and groups receiving this high-
tech care also increased.

In today’s technologically savvy healthcare
environment, patients are being prescribed
applications (apps) for their smartphones instead of
medications in some clinical practices. Patients’
smartphones are being used to interact with them in
new ways and to monitor and assess their health in
some cases. With apps and add-ons, for example, a
provider can see the patient’s ECG immediately, or the
patient can monitor his or her ECG and send it to the
provider as necessary. Another example would be a
sensor attached to the patient’s mobile device that
could monitor blood glucose levels. We are just

beginning to realize the vast potential of these mobile
devices—and the threats they sometimes pose.
Google Glass, for example, can take photos and
videos (Stern, 2013) without anyone knowing that this
is occurring; in the healthcare environment, such a
technological advancement can violate patients’
privacy and confidentiality. Wearable technologies
provide a data-rich environment for diagnosing,
addressing, and monitoring health issues. As we
analyze huge patient datasets, concerns arise about
privacy, confidentiality, and data sharing (Johns
Hopkins, Berman Institute of Bioethics, n.d.). Add these
evolving developments to healthcare providers’
engagement in social media use with their patients,
and it becomes clear that personal and ethical
dilemmas abound for nurses in the new über-
connected world.

Ethical Issues and Social
Media
As connectivity has improved owing to emerging
technologies, a rapid explosion in the phenomenon
known as social media has occurred. Social media is
defined as “a group of Internet-based applications that
build on the ideological and technological foundations
of Web 2.0 and that allow the creation and exchange of
user-generated content” (Spector & Kappel, 2012, p.
1). Just as the electronic health record serves as a

real-time event in recording patient–provider contact,
so the use of social media represents an instantaneous
form of communication. Healthcare providers—
particularly nurses—can enhance the patient care
delivery system, promote professional collegiality, and
provide timely communication and education regarding
health-related matters by using this forum (National
Council of State Boards of Nursing [NCSBN], 2011,
p. 1). In all cases, however, nurses must exercise
judicious use of social media to protect patients’ rights.
Nurses must understand their obligation to their chosen
profession, particularly as it relates to personal
behavior and the perceptions of their image as
portrayed through social media. Above all, nurses must
be mindful that once communication is written and
posted on the Internet, there is no way to retract what
was written; it is a permanent record that can be
tracked, even if the post is deleted (Englund, Chappy,
Jambunathan, & Gohdes, 2012, p. 242).

Social media platforms include such electronic
communication outlets as Facebook, Twitter, LinkedIn,
Snapchat, and YouTube. Other widely used means of
instantaneous communications include wikis, blogs,
tweeting, Skype, and the “hangout” feature on
Google+. Even as recently as 5 years ago, some of
these means of exchanging information were unknown
(Spector & Kappel, 2012, p. 1).

Use of social networking has increased dramatically

among all age groups. Zephoria (2016) reported that,
in 2016, Facebook had over 1.65 billion active monthly
users worldwide as compared to 955 million active
monthly users in 2012, and users spend an average of
20 minutes on Facebook per visit. Twitter’s influence
on health care continues to grow, with Symplur (2016)
reporting 1,603,327,260 tweets, including healthcare-
related Tweet chats, conferences, and diseases such
as breast cancer, diabetes, and irritable bowel
syndrome.

The rapid growth of social media has found many
healthcare professionals unprepared to face the new
challenges or to exploit the opportunities that exist with
these forums. The need to maintain confidentiality
presents a major obstacle to the healthcare industry’s
widespread adoption of such technology; thus social
networking has not yet been fully embraced by many
health professionals (Anderson, 2012, p. 22). Englund
and colleagues (2012) noted that undergraduate
nursing students may face ambiguous and
understudied professional and ethical implications
when using social networking venues.

Another confounding factor is the increased use of
mobile devices by health professionals as well as the
public (Swartz, 2011, p. 345). Smartphones have the
capability to take still pictures as well as live
recordings; they have found their way into treatment
rooms around the globe.

As a consequence of more stringent confidentiality
laws and more widespread availability and use of
social and mobile media, numerous ethical and legal
dilemmas have been posed to nurses. What are not
well defined are the expectations of healthcare
providers regarding this technology. In some cases,
nurses employed in the emergency department (ED)
setting have been subjected to video and audio
recordings by patients and families when they perform
procedures and give care during the ED visit. Nurses
would be wise to inquire—before an incident occurs—
about the hospital policy regarding audio/video
recording by patients and families, as well as the state
laws governing two-party consent. Such laws require
consent of all parties to any recording or
eavesdropping activity (Lyons & Reinisch, 2013, p.
54).

Sometimes the enthusiasm for patient care and
learning can lead to ethics violations. In one case, an
inadvertent violation of privacy laws occurred when a
nurse in a small town blogged about a child in her care
whom she referred to as her “little handicapper.” The
post also noted the child’s age and the fact that the
child used a wheelchair. A complaint about this breach
of confidentiality was reported to the Board of Nursing.
A warning was issued to the nurse blogging this
information, although a more stringent disciplinary

action could have been taken (Spector & Kappel,
2012, p. 2).

In another case cited by Spector and Kappel (2012), a
student nurse cared for a 3-year-old leukemia patient
whom she wanted to remember after finishing her
pediatric clinical experience. She took the child’s
picture, and in the background of the photo the
patient’s room number was clearly displayed. The
child’s picture was posted on the student nurse’s
Facebook page, along with her statement of how much
she cared about this child and how proud she was to
be a student nurse. Someone forwarded the picture to
the nurse supervisor of the children’s hospital. Not only
was the student expelled from the program, but the
clinical site offer made by the children’s hospital to the
nursing school was rescinded. In addition, the hospital
faced citations for violations of the Health Insurance
Portability and Accountability Act (HIPAA) owing to the
student nurse’s transgression (p. 3).

Nurses sometimes use social network sites or blog
about the patients they care for believing that if they
omit the patient’s name, they are not violating the
patient’s privacy and confidentiality. “A nurse who posts
about caring for an 85-year-old female in her city could
cause the patient to be identified by content in the post.
This action does not protect the patient” (Henderson &
Dahnke, 2015, p. 63). A white paper published by the

NCSBN (2011) provides a thorough discussion of the
issues associated with nurses’ use of social media.

Ethical Dilemmas and Morals
An ethical dilemma arises when moral issues raise
questions that cannot be answered with a simple,
clearly defined rule, fact, or authoritative view. Morals
refer to social convention about right and wrong human
conduct that is so widely shared that it forms a stable
(although usually incomplete) communal consensus
(Beauchamp & Childress, 1994). Moral dilemmas
arise with uncertainty, as is the case when some
evidence a person is confronted with indicates an
action is morally right and other evidence indicates that
this action is morally wrong. Uncertainty is stressful
and, in the face of inconclusive evidence on both sides
of the dilemma, causes the person to question what he
or she should do. Sometimes the individual concludes
that based on his or her moral beliefs, he or she cannot
act. Uncertainty also arises from unanticipated effects
or unforeseeable behavioral responses to actions or
the lack of action. Adding uncertainty to the situational
factors and personal beliefs that must be considered
creates a need for an ethical decision-making model to
help one choose the best action.

Ethical Decision Making

Ethical decision making refers to the process of
making informed choices about ethical dilemmas
based on a set of standards differentiating right from
wrong. This type of decision making reflects an
understanding of the principles and standards of ethical
decision making, as well as the philosophic
approaches to ethical decision making, and it requires
a systematic framework for addressing the complex
and often controversial moral questions.

As the high-speed era of digital communications
evolves, the rights and the needs of individuals and
groups will be of the utmost concern to all healthcare
professionals. The changing meaning of
communication, for example, will bring with it new
concerns among healthcare professionals about
protecting patients’ rights of confidentiality, privacy, and
autonomy. Systematic and flexible ethical decision-
making abilities will be essential for all healthcare
professionals.

Notably, the concept of nonmaleficence (“do no harm”)
will be broadened to include those individuals and
groups whom one may never see in person, but with
whom one will enter into a professional relationship of
trust and care. Mack (2000) has discussed the
popularity of individuals seeking information online
instead of directly from their healthcare providers and
the effects this behavior has on patient–provider
relationships. He is emphatic in his reminder that

“organizations and individuals that provide health
information on the Internet have obligations to be
trustworthy, provide high-quality content, protect users’
privacy, and adhere to standards of best practices for
online commerce and online professional services in
healthcare” (p. 41).

RESEARCH BRIEF

Using an online survey of 1,227 randomly
selected respondents, Bodkin and Miaoulis
(2007) sought to describe the characteristics of
information seekers on e-health websites, the
types of information they seek, and their
perceptions of the quality and ethics of the
websites. Of the respondents, 74% had sought
health information on the Web, with women
accounting for 55.8% of the health information
seekers. A total of 50% of the seekers were
between 35 and 54 years of age. Nearly two
thirds of the users began their searches using a
general search engine rather than a health-
specific site, unless they were seeking
information related to symptoms or diseases.
Top reasons for seeking information were
related to diseases or symptoms of medical
conditions, medication information, health news,
health insurance, locating a doctor, and
Medicare or Medicaid information. The level of
education of information seekers was related to

the ratings of website quality, in that more
educated seekers found health information
websites more understandable, but were more
likely to perceive bias in the website information.
The researchers also found that the ethical
codes for e-health websites seem to be
increasing consumers’ trust in the safety and
quality of information found on the Web, but that
most consumers are not comfortable purchasing
health products or services online.

The full article appears in Bodkin, C., & Miaoulis, G. (2007).

eHealth information quality and ethics issues: An exploratory

study of consumer perceptions. International Journal of

Pharmaceutical and Healthcare Marketing, 1(1), 27–42.

Retrieved from ABI/INFORM Global (Document ID:

1515583081).

Makus (2001) suggests that both autonomy and justice
are enhanced with universal access to information, but
that tensions may be created in patient–provider
relationships as a result of this access to outside
information. Healthcare workers need to realize that
they are no longer the sole providers and gatekeepers
of health-related information; ideally, they should
embrace information empowerment and suggest
websites to patients that contain reliable, accurate, and
relevant information (Resnick, 2001).

It is clear that patients’ increasing use of the Internet
for healthcare information may prompt entirely new
types of ethical issues, such as who is responsible if a
patient is harmed as a result of following online health
advice. Derse and Miller (2008) discuss this issue
extensively and conclude that a clear line separates
information and practice. Practice occurs when there is
direct or personal communication between the provider
and the patient, when the advice is tailored to the
patient’s specific health issue, and when there is a
reasonable expectation that the patient will act in
reliance on the information.

A summit sponsored by the Internet Healthcare
Coalition (www.ihealthcoalition.org) in 2000
developed the E-Health Code of Ethics (eHealth code,
n.d.), which includes eight standards for the ethical
development of health-related Internet sites: (1)
candor, (2) honesty, (3) quality, (4) informed consent,
(5) privacy, (6) professionalism, (7) responsible
partnering, and (8) accountability. For more information
about each of these standards, access the full
discussion of the E-Health Code of Ethics
(http://www.ihealthcoalition.org/ehealth-code-of-
ethics).

It is important to realize that the standards for ethical
development of health-related Internet sites are
voluntary; there is no overseer perusing these sites
and issuing safety alerts for users. Although some sites

carry a specific symbol indicating that they have been
reviewed and are trustworthy (HONcode and Trust-e),
the healthcare provider cannot control which
information patients access or how they perceive and
act related to the health information they find online.
The research brief on the previous page describes one
study of consumer perceptions of health information on
the Web.

Theoretical Approaches to
Healthcare Ethics
Theoretical approaches to healthcare ethics have
evolved in response to societal changes. In a 30-year
retrospective article for the Journal of the American
Medical Association, Pellegrino (1993) traced the
evolution of healthcare ethics from the Hippocratic
ethic, to principlism, to the current antiprinciplism
movement.

The Hippocratic tradition emerged from relatively
homogenous societies where beliefs were similar and
most societal members shared common values. The
emphasis was on duty, virtue, and gentlemanly
conduct.

Principlism arose as societies became more
heterogeneous and members began experiencing a
diversity of incompatible beliefs and values; it emerged

as a foundation for ethical decision making. Principles
were expansive enough to be shared by all rational
individuals, regardless of their background and
individual beliefs. This approach continued into the
1900s and was popularized by two bioethicists,
Beauchamp and Childress (1977; 1994), in the last
quarter of the 20th century. Principles are considered
broad guidelines that provide guidance or direction but
leave substantial room for case-specific judgment.
From principles, one can develop more detailed rules
and policies.

Beauchamp and Childress (1994) proposed four
guiding principles: (1) respect for autonomy, (2)
nonmaleficence, (3) beneficence, and (4) justice.

Autonomy refers to the individual’s freedom from
controlling interferences by others and from
personal limitations that prevent meaningful
choices, such as adequate understanding. Two
conditions are essential for autonomy: liberty,
meaning the independence from controlling
influences, and the individual’s capacity for
intentional action.
Nonmaleficence asserts an obligation not to inflict
harm intentionally and forms the framework for the
standard of due care to be met by any professional.
Obligations of nonmaleficence are obligations of not
inflicting harm and not imposing risks of harm.
Negligence—a departure from the standard of due

care toward others—includes intentionally imposing
risks that are unreasonable and unintentionally but
carelessly imposing risks.
Beneficence refers to actions performed that
contribute to the welfare of others. Two principles
underlie beneficence: Positive beneficence requires
the provision of benefits, and utility requires that
benefits and drawbacks be balanced. One must
avoid negative beneficence, which occurs when
constraints are placed on activities that, even
though they might not be unjust, could in some
situations cause detriment or harm to others.
Justice refers to fair, equitable, and appropriate
treatment in light of what is due or owed to a
person. Distributive justice refers to fair, equitable,
and appropriate distribution in society determined
by justified norms that structure the terms of social
cooperation.

Beauchamp and Childress also suggest three types of
rules for guiding actions: substantive, authority, and
procedural. (Rules are more restrictive in scope than
principles and are more specific in content.)
Substantive rules are rules of truth telling,
confidentiality, privacy, and fidelity, and those
pertaining to the allocation and rationing of health care,
omitting treatment, physician-assisted suicide, and
informed consent. Authority rules indicate who may
and should perform actions. Procedural rules establish
procedures to be followed.

The principlism advocated by Beauchamp and
Childress has since given way to the antiprinciplism
movement, which emerged in the 21st century with the
expansive technological changes and the tremendous
rise in ethical dilemmas accompanying these changes.
Opponents of principlism include those who claim that
its principles do not represent a theoretical approach
as well as those who claim that its principles are too far
removed from the concrete particularities of everyday
human existence; are too conceptual, intangible, or
abstract; or disregard or do not take into account a
person’s psychological factors, personality, life history,
sexual orientation, or religious, ethnic, and cultural
background. Different approaches to making ethical
decisions are next briefly explored, providing the
reader with an understanding of the varied methods
professionals may use to arrive at an ethical decision.

The casuist approach to ethical decision making grew
out of the call for more concrete methods of examining
ethical dilemmas. Casuistry is a case-based ethical
reasoning method that analyzes the facts of a case in a
sound, logical, and ordered or structured manner. The
facts are compared to decisions arising out of
consensus in previous paradigmatic or model cases.
One casuist proponent, Jonsen (1991), prefers
particular and concrete paradigms and analogies over
the universal and abstract theories of principlism.

The Husted bioethical decision-making model centers
on the healthcare professional’s implicit agreement
with the patient or client (Husted & Husted, 1995). It is
based on six contemporary bioethical standards: (1)
autonomy, (2) freedom, (3) veracity, (4) privacy, (5)
beneficence, and (6) fidelity.

The virtue ethics approach emphasizes the virtuous
character of individuals who make the choices. A
virtue is any characteristic or disposition desired in
others or oneself. It is derived from the Greek word
aretai, meaning “excellence,” and refers to what one
expects of oneself and others. Virtue ethicists
emphasize the ideal situation and attempt to identify
and define ideals. Virtue ethics dates back to Plato and
Socrates. When asked “whether virtue can be taught or
whether virtue can be acquired in some other way,
Socrates answers that if virtue is knowledge, then it
can be taught. Thus, Socrates assumes that whatever
can be known can be taught” (Scott, 2002, para. 9).
According to this view, the cause of any moral
weakness is not a matter of character flaws but rather
a matter of ignorance. In other words, a person acts
immorally because the individual does not know what
is really good for him or her. A person can, for example,
be overpowered by immediate pleasures and forget to
consider the long-term consequences. Plato
emphasized that to lead a moral life and not succumb
to immediate pleasures and gratification, one must
have a moral vision. He identified four cardinal virtues:

(1) wisdom, (2) courage, (3) self-control, and (4)
justice.

Aristotle’s (350 BC) Nicomachean principles also
contribute to virtue ethics. According to this
philosopher, virtues are connected to will and motive
because the intention is what determines if one is or is
not acting virtuously. Ethical considerations, according
to his eudaemonistic principles, address the question,
“What is it to be an excellent person?” For Aristotle,
this ultimately means acting in a temperate manner
according to a rational mean between extreme
possibilities.

Virtue ethics has experienced a recent resurgence in
popularity (Ascension Health, 2007). Two of the most
influential moral and medical authors, Pellegrino and
Thomasma (1993), have maintained that virtue theory
should be related to other theories within a
comprehensive philosophy of the health professions.
They argue that moral events are composed of four
elements (the agent, the act, the circumstances, and
the consequences), and state that a variety of theories
must be interrelated to account for different facets of
moral judgment.

Care ethics is responsiveness to the needs of others
that dictates providing care, preventing harm, and
maintaining relationships. This viewpoint has been in
existence for some time. Engster (2004) stated that

“Carol Gilligan’s In a Different Voice (1982) established
care ethics as a major new perspective in
contemporary moral and political discourse” (p. 113).
The relationship between care and virtue is complex,
however. Benjamin and Curtis (1992) base their
framework on care ethics; they propose that “critical
reflection and inquiry in ethics involves the complex
interplay of a variety of human faculties, ranging from
empathy and moral imagination on the one hand to
analytic precision and careful reasoning on the other”
(p. 12). Care ethicists are less stringently guided by
rules, but rather focus on the needs of others and the
individual’s responsibility to meet those needs. As
opposed to the aforementioned theories that are
centered on the individual’s rights, an ethic of care
emphasizes the personal part of an interdependent
relationship that affects how decisions are made. In
this theory, the specific situation and context in which
the person is embedded become a part of the decision-
making process.

The consensus-based approach to bioethics was
proposed by Martin (1999), who claims that American
bioethics harbors a variety of ethical methods that
emphasize different ethical factors, including principles,
circumstances, character, interpersonal needs, and
personal meaning. Each method reflects an important
aspect of ethical experience, adds to the others, and
enriches the ethical imagination. Thus working with
these methods provides the challenge and the

opportunity necessary for the perceptive and shrewd
bioethicist to transform them into something new with
value through the process of building ethical
consensus. Diverse ethical insights can be integrated
to support a particular bioethical decision, and that
decision can be understood as a new, ethical whole.

Applying Ethics to Informatics
With the Knowledge Age has come global closeness,
meaning the ability to reach around the globe
instantaneously through technology. Language barriers
are being broken through technologically based
translators that can enhance interaction and exchange
of data and information. Informatics practitioners are
bridging continents, and international panels,
committees, and organizations are beginning to
establish standards and rules for the implementation of
informatics. This international perspective must be
taken into consideration when informatics dilemmas
are examined from an ethical standpoint; it promises to
influence the development of ethical approaches that
begin to accept that healthcare practitioners are
working within international networks and must
recognize, respect, and regard the diverse political,
social, and human factors within informatics ethics.

The various ethical approaches can be used to help
healthcare professionals make ethical decisions in all
areas of practice. The focus of this text is on

informatics. Informatics theory and practice have
continued to grow at a rapid rate and are infiltrating
every area of professional life. New applications and
ways of performing skills are being developed daily.
Therefore, education in informatics ethics is extremely
important.

Typically, situations are analyzed using past
experience and in collaboration with others. Each
situation warrants its own deliberation and unique
approach, because each individual patient seeking or
receiving care has his or her own preferences, quality
of life, and healthcare needs in a situational milieu
framed by financial, provider, setting, institutional, and
social context issues. Clinicians must take into
consideration all of these factors when making ethical
decisions.

The use of expert systems, decision support tools,
evidence-based practice, and artificial intelligence in
the care of patients creates challenges in terms of who
should use these tools, how they are implemented, and
how they are tempered with clinical judgment. All
clinical situations are not the same, and even though
the result of interacting with these systems and tools is
enhanced information and knowledge, the clinician
must weigh this information in light of each patient’s
unique clinical circumstances, including that
individual’s beliefs and wishes. Patients are demanding
access to quality care and the information necessary to

control their lives. Clinicians need to analyze and
synthesize the parameters of each distinctive situation
using a specific decision-making framework that helps
them make the best decisions. Getting it right the first
time has a tremendous impact on expected patient
outcomes. The focus should remain on patient
outcomes while the informatics tools available are
ethically incorporated.

Facing ethical dilemmas on a daily basis and struggling
with unique client situations may cause many clinicians
to question their own actions and the actions of their
colleagues and patients. One must realize that
colleagues and patients may reach very different
decisions, but that does not mean anyone is wrong.
Instead, all parties reach their ethical decision based
on their own review of the situational facts and
understanding of ethics. As one deals with diversity
among patients, colleagues, and administrators, one
must constantly strive to use ethical imagination to
reach ethically competent decisions.

Balancing the needs of society, his or her employer,
and patients could cause the clinician to face ethical
challenges on an everyday basis. Society expects
judicious use of finite healthcare resources. Employers
have their own policies, standards, and practices that
can sometimes inhibit the practice of the clinician. Each
patient is unique and has life experiences that affect
his or her healthcare perspective, choices, motivation,

and adherence. Combine all of these factors with the
challenges posed by informatics, and it is clear that the
evolving healthcare arena calls for an informatics-
competent, politically active, consumer-oriented,
business-savvy, ethical clinician to rule this ever-
changing landscape known as health care.

The goal of any ethical system should be that a
rational, justifiable decision is reached. Ethics is always
there to help the practitioner decide what is right.
Indeed, the measure of an adequate ethical system,
theory, or approach is, in part, its ability to be useful in
novel contexts. A comprehensive, robust theory of
ethics should be up to the task of addressing a broad
variety of new applications and challenges at the
intersection of informatics and health care.

The information concerning an ethical dilemma must
be viewed in the context of the dilemma to be useful.
Bioinformatics could gather, manipulate, classify,
analyze, synthesize, retrieve, and maintain databases
related to ethical cases, the effective reasoning applied
to various ethical dilemmas, and the resulting ethical
decisions. This input would certainly be potent—but the
resolution of dilemmas cannot be achieved simply by
examining relevant cases from a database. Instead,
clinicians must assess each situational context and the
patient’s specific situation and needs and make their
ethical decisions based on all of the information they
have at hand.

Ethics is exciting, and competent clinicians need to
know about ethical dilemmas and solutions in their
professions. Ethicists have often been thought of as
experts in the arbitrary, ambiguous, and ungrounded
judgments of other people. They know that they make
the best decisions they can based on the situation and
stakeholders at hand. Just as clinicians try to make the
best healthcare decisions with and for their patients,
ethically driven practitioners must do the same. Each
healthcare provider must critically think through the
situation to arrive at the best decision.

To make ethical decisions about informatics
technologies and patients’ intimate healthcare data and
information, the healthcare provider must be competent
in informatics. To the extent that information technology
is reshaping healthcare practices or promises to
improve patient care, healthcare professionals must be
trained and competent in the use of these tools. This
competency needs to be evaluated through
instruments developed by professional groups or
societies; such assessment will help with consistency
and quality. For the healthcare professional to be an
effective patient advocate, he or she must understand
how information technology affects the patient and the
subsequent delivery of care. Information science and
its effects on health care are both interesting and
important. It follows that information technology and its

ethical, social, and legal implications should be
incorporated into all levels of professional education.

The need for confidentiality was perhaps first
articulated by Hippocrates; thus if anything is different
in today’s environment, it is simply the ways in which
confidentiality can be violated. Perhaps the use of
computers for clinical decision support and data mining
in research will raise new ethical issues. Ethical
dilemmas associated with the integration of informatics
must be examined to provide an ethical framework that
considers all of the stakeholders. Patients’ rights must
be protected in the face of a healthcare provider’s duty
to his or her employer and society at large when
initiating care and assigning finite healthcare
resources. An ethical framework is necessary to help
guide healthcare providers in reference to the ethical
treatment of electronic data and information during all
stages of collection, storage, manipulation, and
dissemination. These new approaches and means
come with their own ethical dilemmas. Often they are
dilemmas not yet faced owing to the cutting-edge
nature of these technologies.

Just as processes and models are used to diagnose
and treat patients in practice, so a model in the
analysis and synthesis of ethical dilemmas or cases
can also be applied. An ethical model for ethical
decision making (Box 5-1) facilitates the ability to
analyze the dilemma and synthesize the information

into a plan of action (McGonigle, 2000). The model
presented here is based on the letters in the word
ethical. Each letter guides and prompts the healthcare
provider to think critically (think and rethink) through
the situation presented. The model is a tool because, in
the final analysis, it allows the nurse objectively to
ascertain the essence of the dilemma and develop a
plan of action.

BOX 5-1 ETHICAL MODEL FOR

ETHICAL DECISION MAKING

Examine the ethical dilemma (conflicting
values exist).
Thoroughly comprehend the possible
alternatives available.
Hypothesize ethical arguments.
Investigate, compare, and evaluate the
arguments for each alternative.
Choose the alternative you would
recommend.
Act on your chosen alternative.
Look at the ethical dilemma and examine the
outcomes while reflecting on the ethical
decision.

APPLYING THE ETHICAL
MODEL

Examine the ethical dilemma:

Use your problem-solving, decision-
making, and critical-thinking skills.

What is the dilemma you are analyzing?
Collect as much information about the
dilemma as you can, making sure to
gather the relevant facts that clearly
identify the dilemma. You should be able
to describe the dilemma you are
analyzing in detail.

Ascertain exactly what must be decided.

Who should be involved in the decision-
making process for this specific case?

Who are the interested players or
stakeholders?

Reflect on the viewpoints of these key
players and their value systems.

What do you think each of these
stakeholders would like you to decide as
a plan of action for this dilemma?

How can you generate the greatest
good?

Thoroughly comprehend the possible
alternatives available:

Use your problem-solving, decision-

making, and critical-thinking skills.

Create a list of the possible alternatives.
Be creative when developing your
alternatives. Be open minded; there is
more than one way to reach a goal.
Compel yourself to discern at least three
alternatives.

Clarify the alternatives available and
predict the associated consequences—
good and bad—of each potential
alternative or intervention.

For each alternative, ask the following
questions:

– Do any of the principles or rules,
such as legal, professional, or
organizational, automatically nullify
this alternative?

– If this alternative is chosen, what do
you predict as the best-case and
worst-case scenarios?

– Do the best-case outcomes
outweigh the worst-case outcomes?

– Could you live with the worst-case
scenario?

– Will anyone be harmed? If so, how
will they be harmed?

– Does the benefit obtained from this
alternative overcome the risk of
potential harm that it could cause to
anyone?

Hypothesize ethical arguments:

Use your problem-solving, decision-
making, and critical-thinking skills.

Determine which of the five approaches
apply to this dilemma.

Identify the moral principles that can be
brought into play to support a conclusion
as to what ought to be done ethically in
this case or similar cases.

Ascertain whether the approaches
generate converging or diverging
conclusions about what ought to be done.

Investigate, compare, and evaluate the
arguments for each alternative:

Use your problem-solving, decision-
making, and critical-thinking skills.

Appraise the relevant facts and
assumptions prudently.

– Is there ambiguous information that
must be evaluated?

– Are there any unjustifiable factual or
illogical assumptions or debatable
conceptual issues that must be
explored?

Rate the ethical reasoning and
arguments for each alternative in terms of
their relative significance.

– 4 = extreme significance

– 3 = major significance

– 2 = significant

– 1 = minor significance

Compare and contrast the alternatives
available with the values of the key
players involved.

Reflect on these alternatives:

– Does each alternative consider all of
the key players?

– Does each alternative take into
account and reflect an interest in the
concerns and welfare of all of the key
players?

– Which alternative will produce the
greatest good or the least amount of
harm for the greatest number of
people?

Refer to your professional codes of
ethical conduct. Do they support your
reasoning?

Choose the alternative you would
recommend:

Use your problem-solving, decision-
making, and critical-thinking skills.

Make a decision about the best
alternative available.

– Remember the Golden Rule: Does
your decision treat others as you
would want to be treated?

– Does your decision take into account
and reflect an interest in the concerns
and welfare of all of the key players?

– Does your decision maximize the
benefit and minimize the risk for
everyone involved?

Become your own critic; challenge your
decision as you think others might. Use
the ethical arguments you predict they
would use and defend your decision.

– Would you be secure enough in your
ethical decision-making process to

see it aired on national television or
sent out globally over the Internet?

– Are you secure enough with this
ethical decision that you could have
allowed your loved ones to observe
your decision-making process, your
decision, and its outcomes?

Act on your chosen alternative:

Use your problem-solving, decision-
making, and critical-thinking skills.

Formulate an implementation plan
delineating the execution of the decision.

– This plan should be designed to
maximize the benefits and minimize
the risks.

– This plan must take into account all
of the resources necessary for
implementation, including personnel
and money.

Implement the plan.

Look at the ethical dilemma and examine
the outcomes while reflecting on your
ethical decision:

Use your problem-solving, decision-
making, and critical-thinking skills.

Monitor the implementation plan and its
outcomes. It is extremely important to
reflect on specific case decisions and
evaluate their outcomes to develop your
ethical decision-making ability.

If new information becomes available, the
plan must be reevaluated.

Monitor and revise the plan as necessary.

The ethical model for ethical decision making was developed by

Dr. Dee McGonigle and is the property of Educational

Advancement Associates (EAA). The permission for its use in

this text has been granted by Mr. Craig R. Goshow, Vice

President, EAA.

Case Analysis Demonstration
The following case study is intended to help readers
think through how to apply the ethical model. Review
the model and then read through the case. Try to apply
the model to this case or follow along as the model is
implemented. Readers are challenged to determine
their decision in this case and then compare and
contrast their response with the decision the authors
reached.

Allison is a charge nurse on a busy
medical–surgical unit. She is expecting

the clinical instructor from the local
university at 2:00 pm to review and
discuss potential patient assignments for
the nursing students scheduled for the
following day. Just as the university
professor arrives, one of the patients on
the unit develops a crisis requiring
Allison’s attention. To expedite the
student nurse assignments for the
following day, Allison gives her electronic
medical record access password to the
instructor.

Examine the Ethical Dilemma
Allison made a commitment to meet with the university
instructor to develop student assignments at 2:00 pm.
The patient emergency that developed prevented
Allison from living up to that commitment. Allison had
an obligation to provide patient care during the
emergency and a competing obligation to the
professor. She solved the dilemma of competing
obligations by providing her electronic medical record
access password to the university professor.

By sharing her password, Allison most likely violated
hospital policy related to the security of healthcare
information. She may also have violated the American
Nurses Association code of ethics, which states that
nurses must judiciously protect information of a

confidential nature. Because the university professor
was also a nurse and had a legitimate interest in the
protected healthcare information, there might not be a
code of ethics violation.

Thoroughly Comprehend the Possible
Alternatives Available
The possible alternatives available include the
following: (1) Allison could have asked the professor to
wait until the patient crisis was resolved; (2) Allison
could have delegated another staff member to assist
the university professor; or (3) Allison could have
logged on to the system for the professor.

Hypothesize Ethical Arguments
The utilitarian approach applies to this situation. An
ethical action is one that provides the greatest good for
the greatest number; the underlying principles in this
perspective are beneficence and nonmaleficence. The
rights to be considered are as follows: right of the
individual to choose for himself or herself (autonomy);
right to truth (veracity); right of privacy (the ethical right
to privacy avoids conflict and, like all rights, promotes
harmony); right not to be injured; and right to what has
been promised (fidelity).

Does the action respect the moral rights of everyone?
The principles to consider are autonomy, veracity, and
fidelity.

As for the fairness or justice, how fair is an action?
Does it treat everyone in the same way, or does it show
favoritism and discrimination? The principles to
consider are justice and distributive justice.

Thinking about the common good assumes one’s own
good is inextricably linked to good of the community;
community members are bound by pursuit of common
values and goals and ensure that the social policies,
social systems, institutions, and environments on which
one depends are beneficial to all. Examples of such
outcomes are affordable health care, effective public
safety, a just legal system, and an unpolluted
environment. The principle of distributive justice is
considered.

Virtue assumes that one should strive toward certain
ideals that provide for the full development of humanity.
Virtues are attitudes or character traits that enable one
to be and to act in ways that develop the highest
potential; examples include honesty, courage,
compassion, generosity, fidelity, integrity, fairness, self-
control, and prudence. Like habits, virtues become a
characteristic of the person. The virtuous person is the
ethical person. Ask yourself, what kind of person
should I be? What will promote the development of

character within myself and my community? The
principles considered are fidelity, veracity, beneficence,
nonmaleficence, justice, and distributive justice.

In this case, there is a clear violation of an institutional
policy designed to protect the privacy and
confidentiality of medical records. However, the
professor had a legitimate interest in the information
and a legitimate right to the information. Allison trusted
that the professor would not use the system password
to obtain information outside the scope of the legitimate
interest. However, Allison cannot be sure that the
professor would not access inappropriate information.
Further, Allison is responsible for how her access to the
electronic system is used. Balancing the rights of
everyone—the professor’s right to the information, the
patients’ rights to expect that their information is
safeguarded, and the right of the patient in crisis to
expect the best possible care—is important and is the
crux of the dilemma. Does the patient care obligation
outweigh the obligation to the professor? Yes, probably.
Allison did the right thing by caring for the patient in
crisis. By giving out her system access password,
Allison also compromised the rights of the other
patients on the unit to expect that their confidentiality
and privacy would be safeguarded.

Virtue ethics suggests that individuals use power to
bring about human benefit. One must consider the
needs of others and the responsibility to meet those

needs. Allison must simultaneously provide care,
prevent harm, and maintain professional relationships.

Allison may want to effect a long-term change in
hospital policy for the common good. It is reasonable to
assume that this event was not an isolated incident and
that the problem may recur in the future. Can the
institutional policy be amended to provide professors
with access to the medical records system? As
suggested in the HIPAA administrative guidelines, the
professor could receive the same staff training
regarding appropriate and inappropriate use of access
and sign the agreement to safeguard the records. If the
institution has tracking software, the professor’s access
could be monitored to watch for inappropriate use.

Identify the moral principles that can be brought into
play to support a conclusion as to what ought to be
done ethically in this case or similar cases. The
International Council of Nurses (2006) code of ethics
states that “The nurse holds in confidence personal
information and uses judgment in sharing this
information” (p. 4). The code also states, “The nurse
uses judgment in relation to individual competence
when accepting and delegating responsibilities” (p. 5).
Both of these statements apply to the current situation.

Ascertain whether the approaches generate
converging or diverging conclusions about what ought
to be done. From the analysis, it is clear that the best

immediate solution is to delegate assisting the
professor with assignments to another nurse on the
unit.

Investigate, Compare, and Evaluate
the Arguments for Each Alternative
Review and think through the items listed in Table 5-1.

Table 5-1 Detailed Analysis of Alternative Actions

Alternative Good
Consequences

Bad
Consequences

Do Any
Rules
Nullify

Expected
Outcome

1. Wait

until

crisis

was

resolved

No policy

violation

Patient rights

safeguarded

Not the best

use of the

professor’s time

No Best: Crisis

will require a

short time

Worst: Crisis

may take a

long time

2.

Delegate

to

another

staff

member

No policy

violated

Other staff may

be equally busy

or might not be

as familiar with

all patients

No Best:

Assignments

will be

completed

Worst: May

not have

benefit of

expert

advice

3. Log on

to the

system

for the

professor

Professor can

begin making

assignments

May still be a

violation of

policy regarding

system access

Rules

regarding

access to

medical

record

Best:

Assignments

can be

completed

Worst:

Abuse of

access to

information

Choose the Alternative You Would
Recommend
The best immediate solution is to delegate another
staff member to assist the professor. The best long-
term solution is to change the hospital policy to include
access for professors, as described previously.

Act on Your Chosen Alternative
Allison should delegate another staff member to assist
the professor in making assignments.

Look at the Ethical Dilemma and
Examine the Outcomes While
Reflecting on the Ethical Decision
As already indicated in the alternative analyses,
delegation may not be an ideal solution because the

staff nurse who is assigned to assist the professor may
not possess the same extensive information about all
of the patients as the charge nurse. It is, however, the
best immediate solution to the dilemma and is certainly
safer than compromising the integrity of the hospital’s
computer system. As noted previously, Allison may
want to pursue a long-term solution to a potentially
recurring problem by helping the professor gain
legitimate access to the computer system with the
professor’s own password. The system administrator
would then have the ability to track who used the
system and which types of information were accessed
during use.

This case analysis demonstration provides the authors’
perspective on this case and the ethical decision made.
If your decision did not match this perspective, what
was the basis for the difference of opinion? If you
worked through the model, you might have reached a
different decision based on your individual background
and perspective. This does not make the decision right
or wrong. A decision should reflect the best decision
one can make given review, reflection, and critical
thinking about this specific situation.

Six additional cases are provided in the online learner’s
manual for review. Apply the model to each case study,
and discuss these cases with colleagues or
classmates.

New Frontiers in Ethical Issues
The expanding use of new information technologies in
health care will bring about new and challenging ethical
issues. Consider that patients and healthcare providers
no longer have to be in the same place for a quality
interaction. How, then, does one deal with licensing
issues if the electronic consultation takes place across
a state line? Derse and Miller (2008) describe a
second-opinion medical consultation on the Internet
where the information was provided to the referring
physician and not to the patient, thus avoiding the
licensing issue. In essence, provider-to-provider
consultation does not constitute practicing in a state in
which you are not licensed. As new technologies for
healthcare delivery are developed, new ethical
challenges may arise. It is important for all healthcare
providers to be aware of the code of ethics for their
specific practices, and to understand the laws
governing their practice and private health information.

Consider also the ethical issues created by genomic
databases or by sharing of information in a health
information exchange to promote population health.
Alpert (2008) asks, “Is it wise to put genomic sequence
data into electronic medical records that are poorly
protected, that cannot adhere well to Fair Information
Practice Principles for privacy, and that can potentially
be seen by tens of thousands of people/entities, when
it is clear that we do not understand the functionality of

the genome and likely will not for several years?” (p.
382).

Further, how does one really obtain informed consent
for such data collection, when how the data will
ultimately be used is not known, but clearly that
application will be important to health research uses
that go beyond the immediate medical care of the
patient? Angst (2009) asks whether the public good
outweighs individual interests in such a case because
the information contained in these databases is
important to developing new understandings and
creating new knowledge by matching data in
aggregated pools: “Thus, science adds meaning and
context to data, but to what extent do we agree to
make the data available such that this discovery
process can take place, and are the impacts of
discovery great enough to justify the risks?” (p. 172).
Further, if a voluntary system where patients can opt
out of such data collection is adopted, then are
healthcare disparities related to incomplete electronic
health records created?

In an ideal world, healthcare professionals must not be
affected by conflicting loyalties; nothing should interfere
with judicious, ethical decision making. As the
technologically charged waters of health care are
navigated, one must hone a solid foundation of ethical
decision making and practice it consistently.

Summary
As science and technology advance, and policy
makers and healthcare providers continue to shape
healthcare practices including information
management, it is paramount that ethical decisions are
made. Healthcare professionals are typically honest,
trustworthy, and ethical, and they understand that they
are duty bound to focus on the needs and rights of their
patients. At the same time, their day-to-day work is
conducted in a world of changing healthcare
landscapes populated by new technologies, diverse
patients, varied healthcare settings, and changing
policies set by their employers, insurance companies,
and providers. The technologies themselves are not
the problem, but the misuse of the technology can
cause harm to our patients. If we use them to the
patient’s advantage while protecting the patient, they
can be beneficial tools in accessing our technologically
savvy patients to garner the data and information
necessary to address their healthcare needs, including
patient education, while impacting public health and
enhancing our relationship with our patients.
Healthcare professionals need to juggle all of these
balls simultaneously, and so the ethical considerations
must be at the forefront, a task that often results in far
too many gray areas or ethical decision-making
dilemmas with no clear correct course of action.
Patients rely on the ethical competence of their
healthcare providers, believing that their situation is

unique and will be respected and evaluated based on
their own needs, abilities, and limitations. The
healthcare professional cannot allow conflicting
loyalties to interfere with judicious, ethical decision
making. Just as in the opening example of the Apollo
mission, it is uncertain where this technologically
heightened information era will lead, but if a solid
foundation of ethical decision making is relied upon,
duties and rights will be judiciously and ethically
fulfilled.

THOUGHT-PROVOKING QUESTIONS

1. Identify moral dilemmas in healthcare
informatics that would best be
approached with the use of an ethical
decision-making framework, such as the
use of smartphones to interact with
patients as well as to monitor and assess
patient health.

2. Discuss the evolving healthcare ethics
traditions within their social and historical
contexts.

3. Differentiate among the theoretical
approaches to healthcare ethics as they
relate to the theorists’ perspectives of
individuals and their relationships.

4. Select one of the healthcare ethics
theories and support its use in examining
ethical issues in healthcare informatics.

5. Select one of the healthcare ethics
theories and argue against its use in
examining ethical issues in healthcare
informatics.

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SECTION II: Perspectives
on Nursing Informatics

Chapter 6 History and Evolution of Nursing
Informatics

Chapter 7 Nursing Informatics as a Specialty

Chapter 8 Legislative Aspects of Nursing
Informatics: HITECH and HIPAA

Nursing informatics (NI) is the synthesis of nursing
science, information science, computer science, and
cognitive science for the purpose of managing and
enhancing healthcare data, information, knowledge,
and wisdom to improve patient care and the nursing
profession. In the Building Blocks of Nursing
Informatics section, the reader learned about the four
sciences of NI, also referred to as the four building
blocks, and the ethical application of these sciences to
manage patient information. Nursing knowledge
workers must be able to understand the evolving
specialty of NI to harness and use the tools available
for managing the vast amount of healthcare data and
information. It is essential that NI capabilities be
appreciated, promoted, expanded, and advanced to
facilitate the work of the nurse, improve patient care,
and enhance the nursing profession.

This section presents the perspectives of nursing
experts on NI. The History and Evolution of Nursing
Informatics chapter begins this exploration by providing
the historical development and evolution of NI. This
transitions into the Nursing Informatics as a Specialty
chapter, where the reader learns about NI roles,
competencies, and skills. The Legislative Aspects of
Nursing Informatics: HITECH and HIPAA chapter
considers the evolving NI needs of nurses and nurse
informaticists based on the current regulations
impacting the healthcare arena.

In the History and Evolution of Nursing Informatics
chapter, interrelationships among major NI concepts
are discussed. As data are transformed into
information and information into knowledge, increasing
complexity and interrelationships ensue. The
boundaries between concepts can become blurred,
and feedback loops from one concept level to another
evolve. Structured languages and human–computer
interaction concepts, which are critical elements for NI,
are noted in this chapter. Taxonomies and other current
structured languages for nursing are listed. Human–
computer interaction concepts are briefly defined and
discussed because they are critical to the success of
informatics solutions. Importantly, the construct of
decision making is added to the traditional nursing
metaparadigms: nurse, person, health, and
environment. Decision making is not only at the crux of
nursing practice in all settings and roles, but it is a

fundamental concern of NI. The work of nursing is
centered on the concepts of NI: data, information,
knowledge, and wisdom. Information technology (IT)
per se is not the focus; it is the information that the
technology conveys that is central. Moreover, NI is no
longer the domain of experts in the IT field. More
interestingly, one does not need technology to perform
informatics. The centerpiece of informatics is the
manipulation of data, information, and knowledge,
especially related to decision making in any aspect of
nursing or in any setting. In a way, nurses are all
already informatics nurses. Note that the core concepts
and competencies of informatics are particularly well
suited to a model of interprofessional education.
Ideally, when educational programs are emulating
clinical settings, informatics knowledge should be
integrated with the processes of interprofessional
teams and decision making. Because simulation
laboratories are becoming increasingly common
fixtures in the delivery of health-related professional
education, they provide a perfect opportunity to
incorporate the electronic health records applications.
The learning laboratory for nursing education will then
more closely approximate the IT-enabled clinical
settings that are emerging in the real world. A
presumption is often made that future graduates will be
more computer literate than nurses currently in
practice. Although this may be true, computer literacy
or comfort does not equate to an understanding of the
facilitative and transformative role of information

technology. It is essential that the future curricula of
basic nursing programs embed the concepts of the role
of IT in supporting clinical care delivery. The need for
standardizing nursing terminology is also discussed in
this chapter as a way to improve the clinical support
functions of the electronic health record. The
healthcare industry employs the largest number of
knowledge workers—a fact that has resulted in the
realization that healthcare administrators must begin to
change the way they look at their employees. Nurses
and physicians are bright, highly skilled, and dedicated
to giving the best patient care. Administrators who tap
into this wealth of knowledge find that patient care
becomes safer and more efficient.

The Nursing Informatics as a Specialty chapter
discusses NI as a relatively new nursing specialty that
combines the building block sciences covered earlier in
the text. Combining these sciences results in nurses
being able to care for their patients effectively and
safely because the information that they need is readily
available. Nurses have been actively involved in NI
since computers were introduced into health care. With
the advent of electronic health records, it became
apparent that nursing needed to develop its own
language for this evolving field. NI was instrumental in
assisting in nursing language development. NI is
governed by standards established by the American
Nurses Association and is a very diverse field, which
results in many nurse informaticist specialists

becoming focused on one segment of NI. Although NI
is a recognized specialty area of practice, in the future
all nurses will be expected to have some knowledge of
the field. NI competencies have been developed to
ensure that all entry-level nurses are ready to enter a
field that is becoming more technologically advanced.
The competencies may also be used to determine the
educational needs of currently practicing nurses as well
as Level 4 nurse informatics specialists. Nurse
informatics specialists no longer have to enter the field
solely through on-the-job exposure, but can now obtain
an advanced degree in NI at many well-established
universities throughout the United States. NI has grown
tremendously as a specialty since its inception and is
predicted to continue growing.

The Legislative Aspects of Nursing Informatics:
HITECH and HIPAA chapter provides insights into
HIPAA rules and an overview of the rules associated
with technology implementation as defined by the
HITECH Act. Equally important in informatics practice
is a thorough understanding of current legislation and
regulations that shape 21st century practice. The
information provided in this text reflects current rules
that were in effect at the time of publication. The reader
should follow the rules development and evolution of
informatics legislation at the U.S. Department of Health
and Human Services website (www.hhs.gov) to obtain
the most current information related to health
information management.

There is an emerging global focus on information
technology to support clinical care and on the potential
benefits for clinicians and patients. In the future, nurses
will likely have sufficient computing power at their
disposal to aggregate and transform additional
multidimensional data and information sources (e.g.,
historical, multisensory, experiential, genetic) into a
clinical information system to engage with individuals,
families, and groups in ways not yet imagined. Every
nurse’s practice will make contributions to new nursing
knowledge in these dynamically interactive clinical
information system environments. With the right tools
to support the management of data, complex
information processing, and ready access to
knowledge, the core concepts and competencies
associated with informatics will be embedded in the
practice of every nurse, whether administrator,
researcher, educator, or practitioner. Information
technology is not a panacea, but it provides the
profession with unprecedented capacity to generate
and disseminate new knowledge more rapidly.

The material within this text is placed within the context
of the Foundation of Knowledge model (Figure II-1) to
meet the needs of healthcare delivery systems,
organizations, patients, and nurses. Through
involvement in NI and learning about this evolving
specialty, one will be able to use the current theories,
architecture, and tools, while beginning to challenge

what is known. This questioning and search for what
could be will provide the basis for the future landscape
of nursing. By using the Foundation of Knowledge
model as an organizing framework for this text, the
authors have attempted to capture this process.

Figure II-1 Foundation of Knowledge Model

Designed by Alicia Mastrian.

In this section, the reader learns about NI. Those
readers who are beginning their education will
consciously focus on input and knowledge acquisition,
trying to glean as much information and knowledge as
possible. As these readers become more comfortable
in their clinical setting and with nursing science, they
will begin to take over some of the other knowledge

functions. Experienced nurses, also known as
“seasoned nurses,” question what is known and search
for ways to enhance their knowledge and the
knowledge of others. What is not available must be
created. It is through these leaders, researchers, or
clinicians that new knowledge is generated and
disseminated and nursing science is advanced.
Sometimes, however, to keep up with the explosion of
information in nursing and health care, one must
continue to rely on the knowledge generated and
disseminated by others. In this sense, nurses are
committed to lifelong learning and the use of
knowledge in the practice of nursing science. How
nurses interact within their environment and apply what
is learned depends on their placement in the
Foundation of Knowledge model.

Readers of this section are challenged to ask how they
can (1) apply knowledge gained from the practice
setting to benefit patients and enhance their practice,
(2) help colleagues and patients understand and use
current technology, and (3) use wisdom to help create
the theories, tools, and knowledge of the future.

CHAPTER 6: History and
Evolution of Nursing
Informatics

Kathleen Mastrian and Dee McGonigle

With contributions by Ramona Nelson, Nancy
Staggers, Lynn M. Nagle, and Nicholas Hardiker

Objectives
1. Trace the evolution of nursing informatics

from concept to specialty practice.
2. Relate nursing informatics

metastructures, concepts, and tools to
the knowledge work of nursing.

3. Explore the quest for consistent
terminology in nursing and describe
terminology approaches that accurately
capture and codify the contributions of
nursing to health care.

4. Explore the concept of nurses as
knowledge workers.

5. Explore how nurses can create and
derive clinical knowledge from
information systems.

Key Terms
» Accessibility

» Cognitive activity

» Data

» Data gatherer

» Enumerative approach

» Expert systems

» Industrial Age

» Information

» Information Age

» Information user

» International Classification of Nursing
Practice

» Knowledge

» Knowledge builder

» Knowledge user

» Knowledge worker

» Ontological approach

» Reusability

» Standardized Nursing Terminology

» Technologist

» Terminology

» Ubiquity

» Wisdom

Introduction
The information and knowledge informing the 21st
century of healthcare delivery have been growing at an
unprecedented pace in recent years. Clinical research
in particular has propelled the understanding of the
efficacy of various clinical practices, treatment
regimens, and interventions. Extended and expanded
access to clinical research findings and decision
support tools has been significantly influenced by the
advent of computerization and the Internet. Indeed, the
conduct of research itself has been accelerated by
virtue of ubiquitous computing. Working in
environments of increasingly complex clinical care and

contending with the management of large volumes of
data and information, all nurses need to avail
themselves of the technological tools that can support
quality practice that is optimally safe, informed, and
knowledge based. Although the increased deployment
of information technologies within healthcare settings
presumes that nurses and other health professionals
are proficient in the use of computing devices, the
processes and potential outcomes associated with
informatics are yet to be fully realized or understood.
Nurses need to participate in the creation of those
possibilities.

Health service organizations, societies, and
governments throughout the industrialized world are
committed to ensuring that healthcare delivery is safer,
knowledge based, cost effective, seamless, and timely.
Beyond these deliverables, there are expectations of
improved efficiency and quality and of the active
engagement of consumers in their care. In particular,
given the evolving emphasis on such issues as chronic
disease management and aging at home, informatics
tools need to include the use of technologies to
empower citizens to manage their own health and
wellness more effectively.

This chapter explores the history and evolution of
nursing informatics and defines and addresses the goal
of informatics as it relates to nursing practice. The
ways in which nursing informatics supports the creation

of a culture of knowledge-based nursing practice that is
enabled and advanced through the use of information
and communication technologies are described. The
chapter also addresses some of the challenges
associated with the attainment of this knowledge-based
culture, as well as the opportunities for nurses to create
and derive knowledge from emerging health
information technologies. Finally, the chapter provides
a contemplative view of the future for nurses and
informatics.

The Evolution of a Specialty
Nurses have historically gathered and recorded data,
albeit in a paper record. For example, nurses gather
atomic-level data (e.g., blood pressure, pulse, blood
glucose, pallor), aggregate data to derive information
(e.g., impending shock), and apply knowledge (e.g.,
lowering the head of the bed to minimize the potentially
deleterious effects of impending shock). Over the
years, these data have been recorded into individuals’
hard-copy health records, thereby chronicling findings,
actions, and outcomes; these data and information
were then forever lost unless manually extracted for
research purposes. As computers were introduced into
health care, and data and information were recorded
electronically, a nursing specialty was born.

Florence Nightingale has been credited as one of the
first statisticians to collect and use data to change the

way she cared for her patients. While serving in the
Crimean War, she began to gather data regarding the
conditions in which patients were living and the
diseases they contracted and from which they died.
These data were later used to improve patient
conditions at both city and military hospitals (O’Connor
& Robertson, 2003). There is no doubt that nursing
experiences build knowledge and skill in nursing
practice, but paper-based documentation has hindered
the ability to share knowledge and to aggregate
experiences to build new knowledge.

Nursing informatics pioneers recognized early on that
computers had the potential to fundamentally change
health care and they became actively involved in
shaping how computers were used in health care. For
more specific information on nursing informatics
pioneers, and to view video recordings of the
contributions of each in the nursing informatics history
project, please visit this website:
https://www.amia.org/working-groups/nursing-
informatics/history-project/video-library-1

According to Ozbolt and Saba (2008), one very early
pioneer, Harriet Werley, a nurse researcher at Walter
Reed Army Research Institute, consulted with IBM in
the late 1950s to explore computer use in health care.
Ms. Werley recognized the need for a minimum set of
data to be collected from every patient, so that
comparisons could be made, and thus set the stage for

the development of informatics. As computers became
more commonplace in the 1970s and 1980s, more
nurses became involved with developing approaches
to use computers in health care. It is important to note
that this was also the time that nurse leaders were
writing about the need for and developing
terminologies to represent patient data and nursing
contributions to health care, were beginning to conduct
informatics research, and were advocating for
informatics education in nursing curricula (Ozbolt &
Saba, 2008).

In 1989, Graves and Cocoran offered what is widely
viewed as the seminal definition of nursing informatics
(NI). They defined NI as: “a combination of computer
science, information science, and nursing science
designed to assist in the management and processing
of nursing data, information, and knowledge to support
the practice of nursing and the delivery of nursing care”
(p. 227). In this same article, acknowledging the 1986
work of Blum, Graves and Cocoran provided the
definitions and descriptions of the concepts of data
(discrete entities described objectively without
interpretation), information (data that are interpreted,
organized, or structured), and knowledge (information
that is synthesized so that relationships are identified
and formalized) as these terms apply to the science
and practice of NI. They also described what is meant
by management and processing. “The management
component of informatics is the functional ability to

collect, aggregate, organize, move, and re-present
information in an economical, efficient way that is
useful to the users of the system. . . . In practice,
processing is considered as a transformation of data or
information from one form to another form, usually at a
more complex state of organization or meaning. There
is a progression of transformation of data into
information and of information into knowledge” (p. 227).
We will return to a discussion of these concepts later in
the chapter. For now, we continue our exploration of
the evolution of informatics as a specialty.

In the 1990s, the American Medical Informatics
Association was founded with a nursing informatics
work group, the American Nurses Association (ANA)
recognized nursing informatics as a specialty, ANA
published two documents related to informatics
practice, and the first informatics certification was
established (Ozbolt & Saba, 2008). As nursing
informatics pioneers and emerging leaders continued
to champion the use of computers in health care, the
need for computer-friendly terminologies to represent
the work of nursing was increasingly apparent. Several
different terminology schemes were developed during
this time, and there were also international efforts at
developing a standardized nursing terminology to
capture and codify the contributions of nursing to
health care. At this same time, healthcare
organizations were beginning to implement electronic
information systems. There was little coordination of

these various efforts and approaches. As Ozbolt and
Saba (2008) explain, “Faced with the bewildering array
of choices and the licensing fees required for the use of
NANDA [North American Nursing Diagnosis
Association (as it was known until 2002)], NIC [Nursing
Interventions Classification], NOC [Nursing Outcomes
Classification], and SNOMED [Systematized
Nomenclature of Medicine], many health care
organizations adopting nursing information systems
opted to use their own or vendor-provided, non-
standard terms. This approach allowed entry of data
via familiar terms, but because the terms were not
consistent in definition or usage, investigators could not
retrieve meaningful data to analyze for quality
improvement or research” (p. 202). We will discuss this
issue in more detail later in the chapter.

President Bush’s call for electronic health records in
2004 further stimulated the development of nursing
informatics, informatics competency identification, and
informatics education reform, and spawned several
national and international informatics organizations.
“While nursing informatics leaders work to transform
nursing education and practice, nursing informatics
scientists are creating the knowledge and tools that will
enable the transformation. As research in nursing
terminology and knowledge representation moves from
creation to implementation and use, other domains of
research reflect the maturation of nursing informatics
as a science” (Ozbolt & Saba, 2008 p. 204). In this

profound statement, we see the clear connection
between nursing science and nursing informatics. That
is, knowledge creation in nursing is dependent on
knowledge representation in the information
management tools that are central to nursing
informatics. As the NI pioneers recognized these
important connections and synergies, both nursing as a
science and nursing informatics as a specialty evolved.
Indeed, the evolution is not complete, as you will
experience as you read the subsequent chapters in this
text.

As the NI specialty was evolving, informatics pioneers
and other nurse leaders collaborated on several ANA
publications. As mentioned previously, NI was
identified by the ANA as a specialty in 1992. In 1994,
the first formal document identifying the scope of
practice was published, followed by a separate
standards of practice document in 1995. In 2001, a
combined scope and standards document was
published by the ANA, followed by a more robust
scope and standards publication in 2008. Finally, in
2015 the ANA released the second edition of Nursing
Informatics: Scope and Standards of Practice.

What Is Nursing Informatics?
The ANA’s Nursing Informatics: Scope and Standards
of Practice (2015) offers the following definition of NI:

Nursing informatics (NI) is the specialty
that integrates nursing science with
multiple information and analytical
sciences to identify, define, manage, and
communicate data, information,
knowledge and wisdom in nursing
practice. NI supports nurses, consumers,
patients, the interprofessional healthcare
team, and all other stakeholders in their
decision-making in all roles and settings
to achieve desired outcomes. This
support is accomplished through the use
of information structures, information
processes, and information technology.
(p. 1–2)

The definition of nursing informatics has undergone
several revisions to arrive at this current form. The
1994 ANA definition of informatics indicated that
informatics was the integration of nursing science,
computer science, and information science, and that
nursing informatics supports practice, education,
research, and knowledge development (Murphy,
2010). The 2001 version incorporated mention of the
support of decision making by patients and providers
across all roles and settings and identified information
structures, processes, and IT (information technology)
as central to informatics (Murphy, 2010). An important
change in the 2008 definition of NI is the addition of

wisdom to the key concepts of the management of
data, information, and knowledge (Murphy, 2010).
Finally, in the 2015 version, we note that the sciences
are no longer limited to nursing science, information
science, and computer science. Cognitive science is
also a very important part of nursing informatics. Other
sciences that may contribute to NI include library
science and information management, mathematics,
archival science, and the science of terminologies and
taxonomies (ANA, 2015).

Let us reflect more carefully on the current definition of
NI by deconstructing each of the statements contained
in the ANA’s (2015) definition (statements from the
definition are italicized):

Nursing informatics (NI) is the specialty that
integrates nursing science with multiple information
and analytical sciences to identify, define, manage,
and communicate data, information, knowledge and
wisdom in nursing practice. As we established
previously, there are concepts drawn from several
sciences that are integrated to support and
contribute to NI. The contributions of these sciences
become apparent in the actions of NI: identify,
define, manage, and communicate. The last part of
this statement contains the critical central concepts
of NI: the data, information, knowledge, and wisdom
that are integral to our practice. We will explore

these central concepts in more detail in the next
section.
NI supports nurses, consumers, patients, the
interprofessional healthcare team, and all other
stakeholders in their decision-making in all roles
and settings to achieve desired outcomes. This
statement refers to the information technology (IT)
tools that support our practice and help us to
collaborate and communicate with other healthcare
professionals, as well as the evolving trends and
tools related to patient engagement in managing
their own health. All of these contribute to better
health outcomes. Examples of such tools are
electronic health records, bar-code medication
administration systems, clinical decision support
and other expert systems, patient monitoring
devices, and telehealth tools. These and other NI
tools are discussed in subsequent chapters.
This support is accomplished through the use of
information structures, information processes, and
information technology. This section of the definition
clearly identifies the need for information
technologies to provide structure to the data we
collect from our patients, and allow for processing
of data and information to create knowledge and
support wisdom in nursing practice. Think about the
fact that with the advent of clinical information
systems (CISs), specifically electronic
documentation and clinical decision support (CDS)
applications, every nurse has the capacity to

contribute to the advancement of nursing
knowledge on many levels. Imagine the use of IT
solutions to capture not only discrete, quantifiable
data, but also the nurse’s experiential and intuitive
personal knowledge not typically documented in
paper records. Further add to that mix the family
history, culture, environmental and social factors,
past experiences, and perspectives from patients
and families, and it becomes clear that the
possibilities for generating new understandings
within populations and across the life span and care
continuum are endless. Many of these technologies
are covered in subsequent chapters.

The DIKW Paradigm
The conceptual framework underpinning the science
and practice of NI centers on the core concepts of
data, information, knowledge, and wisdom, also known
as the DIKW paradigm. As an aside, it is important to
note that this paradigm is not exclusive to nursing, and
is in fact used by others who work with data and
information. When we assess a patient to determine
his or her nursing needs, we gather and then analyze
and interpret data to form a conclusion. This is the
essence of nursing science. Information is composed
of data that were processed using knowledge.
Knowledge is the awareness and understanding of a
set of information and ways that information can be
made useful to support a specific task or arrive at a

decision. When we apply previous knowledge to data,
we convert those data into information, and information
into new knowledge—that is, an understanding of
which interventions are appropriate in practice. Thus
information is data made functional through the
application of knowledge. Wisdom is the appropriate
application of knowledge to a specific situation. In the
practice of nursing science, one expects actions to be
ultimately directed by wisdom. Wisdom uses
knowledge and experience to heighten common sense
and insight to exercise sound judgment in practical
matters.

Drawing on the work of Matney, Brewster, Sward,
Cloyes, and Staggers (2011), Topaz (2013) provided
these expanded definitions and examples of the DIKW
paradigm:

Data: The smallest components of the DIKW
framework. They are commonly presented as
discrete facts; product of observation with little
interpretation (Matney et al., 2011). These are the
discrete factors describing the patient or his/her
environment. Examples include patient’s medical
diagnosis (e.g. International Statistical Classification
of Diseases [ICD-9] diagnosis #428.0: Congestive
heart failure, unspecified) or living status (e.g., living
alone, living with family, living in a retirement
community, etc.). A single piece of data, known as
datum, often has little meaning in isolation.

Information: Might be thought of as “data +
meaning” (Matney et al., 2011). Information is often
constructed by combining different data points into
a meaningful picture, given certain context.
Information is a continuum of progressively
developing and clustered data; it answers questions
such as “who,” “what,” “where,” and “when.” For
example, a combination of patient’s ICD-9
diagnosis #428.0 “Congestive heart failure,
unspecified” and living status “living alone” has a
certain meaning in a context of an older adult.
Knowledge: Information that has been synthesized
so that relations and interactions are defined and
formalized; it is a build of meaningful information
constructed of discrete data points (Matney et al.,
2011). Knowledge is often affected by assumptions
and central theories of a scientific discipline and is
derived by discovering patterns of relationships
between different clusters of information.
Knowledge answers questions of “why” or “how.”
For healthcare professionals, the combination of
different information clusters, such as the ICD-9
diagnosis #428.0 “Congestive heart failure,
unspecified” + living status “living alone” with an
additional information that an older man (78 years
old) was just discharged from hospital to home with
a complicated new medication regimen (e.g., blood
thinners) might indicate that this person is at a high
risk for drug-related adverse effects (e.g., bleeding).
Wisdom: An appropriate use of knowledge to

manage and solve human problems (ANA, 2008;
Matney et al., 2011). Wisdom implies a form of
ethics, or knowing why certain things or procedures
should or should not be implemented in healthcare
practice. In nursing, wisdom guides the nurse in
recognizing the situation at hand based on patients’
values, nurse’s experience, and healthcare
knowledge. Combining all these components, the
nurse decides on a nursing intervention or action.
Benner (2000) presents wisdom as a clinical
judgment integrating intuition, emotions, and the
senses; using the previous examples, wisdom will
be displayed when the homecare nurse will
consider prioritizing the elderly heart failure patient
using blood thinners for an immediate intervention,
such as a first nursing visit within the first hours of
discharge from hospital to assure appropriate use
of medications (para. 2).

Reflect on the examples given by Topaz and create
your own application example the DIKW scenario.

In the 2015 Nursing Informatics: Scope and Standards
of Practice, Ramona Nelson offers a graphic depiction
of the DIKW paradigm in NI and how it relates to the
evolution of information systems, decision support
systems, and expert systems to support clinical
practice. Her model indicates that as one moves from
data to information to knowledge to wisdom, there is
increasing complexity (shown as the X-axis) and

increasing interactions and relationships (shown as the
Y-axis). Information systems are shown at the
intersection of data and information, decision support
systems are depicted at the intersection of information
and knowledge and expert systems, the most complex
of the systems, reside at the intersection of knowledge
and wisdom (Figure 6-1). The development of
informatics tools to support nursing practice will
continue to evolve as we develop more and better
understanding of these complex relationships. “The
addition of wisdom raises new and important research
questions, challenging the profession to develop tools
and processes for classifying, measuring, and
encoding wisdom as it relates to nursing and
informatics education. Research in these directions will
help clarify the relationship between wisdom and the
intuitive thinking of expert nurses. Such research will
be invaluable in building information systems to better
support healthcare practitioners in decision-making”
(ANA, 2015, p.6).

Figure 6-1 The Relationship of Data, Information,
Knowledge, and Wisdom

Copyright Ramona Nelson. Used with the permission of Ramona Nelson,

President, Ramona Nelson Consulting at [email protected]

All rights reserved.

Central to the development of robust expert systems is
the agreement on and use of standard terminologies
that accurately codify and capture the nature of nursing
in these electronic systems. Consider that physician
contributions to the health of a patient have been
codified for some time, i.e., ICD-10. What if we were
able to code and thus capture nursing contributions in
a similar way? This would help to highlight the specific
nursing contributions to patient outcomes.

Capturing and Codifying the
Work of Nursing
There are major efforts under way—internationally
through the International Council of Nurses’ (2013)
International Classification of Nursing Practice
(ICNP) and in many other initiatives among and within
countries—in which nurses are attempting to
standardize the language of nursing practice (Hannah,
White, Nagle, & Pringle, 2009). These efforts are
particularly important in the face of the development of
EHRs and HIE (health information exchanges)
stimulated by the HITECH Act of 2009. The capacity to
encourage and enforce consistent nomenclatures that
reflect the practice of nurses is now possible.
Standardized language gives both the nursing
profession and healthcare delivery systems the
capability to capture, codify, retrieve, and analyze the
impact of nursing care on client outcomes. For
example, with the use and documentation of
standardized client assessments, including risk
measures, interventions based on best practices, and
consistently measured outcomes within different care
settings and across the continuum of care, there will be
an ability to demonstrate more clearly the contributions
and impact of nursing care through the analysis of EHR
outputs. Additionally, clinical outcomes can be further
understood in the context of care environments,
particularly implications related to the availability of

human and material resources to support care delivery.
The standardization of clinical inputs and outputs into
EHRs will eventually provide a rich knowledge base
from which practice and research can be enhanced,
and will inform better administrative and policy
decisions (Nagle, White, & Pringle, 2010). Rutherford
(2008) echoed these same sentiments:

A standardized nursing language should
be defined so that nursing care can be
communicated accurately among nurses
and other health care providers. Once
standardized, a term can be measured
and coded. Measurement of the nursing
care through a standardized vocabulary
by way of an ED [electronic
documentation] will lead to the
development of large databases. From
these databases, evidence-based
standards can be developed to validate
the contribution of nurses to patient
outcomes. (para. 5)

Thede and Schwiran (2011) identified the benefits of
using standardized terminology as (1) better
communication among nurse and other healthcare
providers, (2) increased visibility of nursing
interventions, (3) improved patient care, (4) enhanced
data collection to evaluate nursing care outcomes, (5)

greater adherence to standards of care, and (6)
facilitation of assessment of nursing competency (para.
2).

Think about this. Some EHRs measure height in feet
and inches, others in centimeters. Weight may be
measured in pounds or kilograms. If we want to
compare patient data from multiple EHRs in several
different healthcare institutions to develop a model to
predict the onset of Type II diabetes, these disparate
measures will not translate well. Some EHRs force
data collection into coded database fields, and these
data are more easily analyzed for trends than that
same data recorded as free text. Clinicians used to
recording data (charting) as text may resist the use of
the coded data fields typically presented as dropdown
menus in the EHR. As Skrocki (2013) pointed out,
“Data interoperability is hindered when clinicians utilize
free text documentation. Although text data can be
searched with a specific word or word phases, it does
not allow for optimal data sharing. When an
organization transfers data to another organization,
standardized codified data allows for better data
interpretation” (p. 77).

Although significant progress has been made in this
standardization work, it is still evolving. Box 6-1
discusses standardizing terminologies in nursing; it
was contributed by Nicholas Hardiker (2011), a leader
in the development of standardized languages that

support clinical applications of information and
communication technology.

BOX 6-1 THE NEED FOR

STANDARDIZED TERMINOLOGIES TO

SUPPORT NURSING PRACTICE

Nicholas Hardiker

Agreement on the consistent use of a term, such
as “impaired physical mobility,” allows that term
to be used for a number of purposes: to provide
continuity of care from care provider to care
provider, to ensure care quality by facilitating
comparisons between care providers, or to
identify trends through data aggregation. Since
the early 1970s, there has been a concerted
effort to promote consistency in nursing
terminology. This work continues today, driven
by the following increasing demands placed on
health-related information and knowledge:

Accessibility: It should be easy to access
the information and knowledge needed to
deliver care or manage a health service.
Ubiquity: With changing models of
healthcare delivery, information and
knowledge should be available anywhere.
Longevity: Information should be usable
beyond the immediate clinical encounter.

Reusability: Information should be useful for
a range of purposes.

Without consistent terminology, nursing runs the
risk of becoming invisible; it will remain difficult
to quantify nursing, the unique contribution and
impact of nursing will go unrecognized, and the
nursing component of electronic health record
systems will remain at best rudimentary. Not
least, without consistent terminology, the nursing
knowledge base will suffer in terms of
development and in terms of access, thereby
delaying the integration of evidence-based
health care into nursing practice.

External pressures merely compound this
problem. For example, in the United States, the
Health Information Technology for Economic
and Clinical Health (HITECH) Act, signed in
January 2009, provides a financial incentive for
the use of electronic health records; similar
steps are being taken in other regions. The
HITECH Act mandates that EHRs are used in a
meaningful way; achieving this goal will be
problematic without consistent terminology.
Finally, the current and future landscape of
information and communication technologies
(e.g., connection anywhere, borderless
communication, Web-based applications,
collaborative working, disintermediation and

reintermediation, consumerization, ubiquitous
advanced digital content [van Eecke, da
Fonseca Pinto, & Egyedi, 2007]) and their
inevitable infiltration into health care will only
serve to reinforce the need for consistent
nursing terminology while providing an
additional sense of urgency.

This box explains what is meant by a
standardized nursing terminology and lists
several examples. It describes in detail the
different approaches taken in the development
of two example terminologies. It presents, in the
form of an international technical standard, a
means of ensuring consistency among the
plethora of contemporary standardized nursing
terminologies, with a view toward harmonization
and possible convergence. Finally, it provides a
rationale for the shared development of models
of terminology use—models that embody both
clinical and pragmatic knowledge to ensure that
contemporary nursing record systems reflect the
best available evidence and fit comfortably with
routine practice.

STANDARDIZED NURSING
TERMINOLOGIES
A term at its simplest level is a word or phrase
used to describe something concrete (e.g., leg)

or abstract (e.g., plan). A nursing terminology is
a body of the terms used in nursing. Many
nursing terminologies exist, both formal and
informal. Nursing terminologies allow nurses to
consistently capture, represent, access, and
communicate nursing data, information, and
knowledge. A standardized nursing
terminology is a nursing terminology that is in
some way approved by an appropriate authority
(de jure standardization) or by general consent
(de facto standardization).

In North America, one such authority is the ANA
(2007), which operates a process of de jure
standardization through its Committee for
Nursing Practice Information Infrastructure
(CNPII). The ANA-approved list of nursing
languages is presented in Box 6-2.

CNPII has also recognized two data element
sets: the Nursing Minimum Data Set (NMDS)
and the Nursing Management Minimum Data
Set (NMMDS). Work on a standardized data
element set for nursing, which in the United
States began in the 1980s with the NMDS
(Werley & Lang, 1988), provided an additional
catalyst for the development of many of the
aforementioned nursing terminologies that could
provide values (e.g., chronic pain) for particular
data elements in the NMDS (e.g., nursing
diagnosis). The data element sets provide a

framework for the uniform collection and
management of nursing data; the use of a
standardized nursing terminology to represent
those data serves further to enhance
consistency.

APPROACHES TO NURSING
TERMINOLOGY
From relatively humble beginnings, nursing
terminologies have evolved significantly over the
past several decades in line with best practices
in terminology work. The enumerative
approach consists of simple lists of words or
phrases represented in a list or a simple
hierarchy. In the nursing diagnosis terminology
system of the North American Nursing
Diagnosis Association (NANDA), a nursing
diagnosis has an associated name or label and
a textual definition (NANDA International, 2008).
Each nursing diagnosis may have a set of
defining characteristics and related or risk
factors. These additional features do not
constitute part of the core terminology but
instead are intended to be used as an aid to
diagnosis. What an enumerative approach to
standardizing terminology may lack in terms of
hierarchical sophistication, it makes up for in

terms of simplicity and potential ease of
implementation and use.

In contrast, the ontological approach is
compositional in nature and provides a partial
representation of the entities within a domain
and the relationships that hold between them.
The evolution of this approach to terminology
standardization has been facilitated by
advances in knowledge representation (e.g., the
refinement of the description logic that
underpins many contemporary ontologies) and
in their accompanying technologies (e.g.,
automated reasoners that can check
consistency and identify equivalence) as well as
the subsumption (i.e., subclass–superclass)
relationships within those ontologies.

ICNP version 2 is an example of an ontology.
ICNP is described as a unified nursing language
system. It seeks to provide a resource that can
be used to develop local terminologies and to
facilitate cross-mapping between terminologies
to compare and combine data from different
sources; the existence of a number of
overlapping but inconsistent standardized
nursing terminologies is problematic in terms of
data comparison and aggregation. The core of
ICNP is represented in the Web ontology
language (OWL), a recommendation of the
World Wide Web Consortium (W3C), and a de

facto standard language for representing
ontologies (McGuiness & van Harmelen, 2004).
Because it is underpinned by description logic,
OWL permits the use of automated reasoners
that can check consistency, identify equivalence,
and support classification within the ICNP
ontology.

The results of contemporary terminology work
are encouraging. Nevertheless, further work is
needed to harmonize standardized nursing
terminologies and to scale up and mainstream
the development and implementation of models
of terminology use.

In an ideal world, one would see standardized
nursing terminologies and the structures and
systems that support their implementation and
use merely as means to an end—that is, as
tools to support good nursing practice and good
patient care. Standardized nursing terminologies
are important, but they do not obviate the need
to think and work creatively, to do right by the
people in our care, and to continue to advance
nursing.

REFERENCES

American Nurses Association
(ANA). (2007). Nursing practice
information infrastructure.
Retrieved from

http://www.nursingworld.org/MainMenuCategories/Policy-
Advocacy/Positions-and-
Resolutions/ANAPositionStatements/Position-
Statements-
Alphabetically/PrivacyandConfidentiality.html

McGuiness, D. L., & van Harmelen,
F. (Eds.). (2004). OWL Web
ontology language overview.
World Wide Web Consortium.
Retrieved from
http://www.w3.org/TR/owl-
features

NANDA International. (2008).
Nursing diagnoses: Definitions
and classification 2009–2011
edition. Indianapolis, IN: Wiley-
Blackwell.

van Eecke, P., da Fonseca Pinto, P.,
& Egyedi, T., for the European
Commission. (2007). EU study
on the specific policy needs for
ICT standardisation [Final
report]. Retrieved from
http://ec.europa.eu/idabc/en/document/7040/254.html

Werley, H. H., & Lang, N. M. (Eds.).
(1988). Identification of the
Nursing Minimum Data Set. New
York, NY: Springer.

BOX 6-2 ANA-RECOGNIZED

TERMINOLOGIES THAT SUPPORT

NURSING PRACTICE (AUGUST 2012)

1. NANDA: Nursing Diagnoses, Definitions,
and Classification, 1992; website:
www.nanda.org

2. Nursing Interventions Classification
System (NIC), 1992; website:
nursing.uiowa.edu/cncce/nursing-
interventions-classification-overview

3. Clinical Care Classification (CCC), 1992;
formerly Home Health Care Classification
(HHCC); website: www.sabacare.com

4. Omaha System, 1992; website:
www.omahasystem.org

5. Nursing Outcomes Classification (NOC),
1997; Sue Moorehead, PhD, RN, Center
Director; website:

nursing.uiowa.edu/cncce/nursing-
outcomes-classification-overview

6. Nursing Management Minimum Data Set
(NMMDS), 1998; website:
www.nursing.umn.edu/sites/nursing.umn.edu/files/nmds-
monograph.pdf

7. PeriOperative Nursing Data Set (PNDS),
1999; website: www.aorn.org

8. SNOMED CT, 1999; website:
www.ihtsdo.org/snomed-ct

9. Nursing Minimum Data Set (NMDS),
1999; website:
www.nursing.umn.edu/sites/nursing.umn.edu/files/usa-
nmds.pdf

10. International Classification for Nursing
Practice (ICNP), 2000; website:
www.icn.ch/icnp.htm

11. ABC Codes, 2000; website:
www.abccodes.com

12. Logical Observation Identifiers Names
and Codes (LOINC), 2002; website:
www.loinc.org

At least two decades of work has been directed toward
articulating standardized data elements that reflect
nursing practice. The nursing profession has been
steadily moving toward consensus on the adoption of
data standards. In fact, several “consensus
conferences” have been hosted in recent years by the

University of Minnesota, with the goal of developing “a
national action plan and harmonize existing and new
efforts of multiple individuals and organizations to
expedite integration of standardized nursing data within
EHRs and ensure their availability in clinical data
repositories for secondary use” (Westra et al., 2015
para. 3). Consider that as clinical information systems
are widely implemented, as standards for nursing
documentation and reporting are adopted, and as
healthcare IT solutions continue to evolve, the
synthesis of findings from a variety of methods and
worldviews becomes much more feasible. As we move
toward a standard terminology to capture the work of
nursing, we also will have the ability to mine electronic
record data to tease out best practices and promote
care improvements. Information technology is not a
panacea for all of the challenges found in health care,
but it will provide the nursing profession with an
unprecedented capacity to generate and disseminate
new knowledge at rapid speed, thus supporting the
knowledge work of nursing.

The Nurse as a Knowledge
Worker
As we have already established, all nurses use data
and information. This information is then converted to
knowledge. The nurse then acts on this knowledge by
initiating a plan of care, updating an existing one, or

maintaining status quo. Does this use of knowledge
make the nurse a knowledge worker?

The term knowledge worker was first coined by Peter
Drucker in his 1959 book, Landmarks of Tomorrow
(Drucker, 1994). Knowledge work is defined as
nonrepetitive, nonroutine work that entails a significant
amount of cognitive activity (Sorrells-Jones &
Weaver, 1999a). Drucker (1994) describes a
knowledge worker as one who has advanced formal
education and is able to apply theoretical and analytical
knowledge. According to Drucker, the knowledge
worker must be a continuous learner and a specialist in
a field. McCormick (2009) estimates that a knowledge
worker spends at least 50% of his or her work time
searching for and evaluating information.

According to Androwich (2010), it is important to
understand that there is a dual role for accessing and
using information (content) in health care. In the first
instance, when the nurse is caring for an individual
patient, evidence-based information (content) and
patient data need to be available at the point of care to
inform the present patient encounter. In the second
instance, patient data that are entered by the nurse in
the process of documentation need to be entered in
such a manner that they are able to be aggregated to
inform future patient encounters.

The world is transitioning from the Industrial Age to

the Information Age (Snyder-Halpern, Corcoran-
Perry, & Narayan, 2001; Sorrells-Jones & Weaver,
1999a). In the early 1900s, the workforce consisted
predominantly of farmers. After World War I, the
workforce began to become predominantly industrial.
This transition occurred when many farmers and
domestic help moved to the cities to take jobs at
factories. Today, the industrial worker is slowly being
replaced by the technologist (Drucker, 1994); the
technologist is adept at using both mind and hand.
Many industrial workers are finding it increasingly more
difficult to obtain jobs because they do not have the
educational base or mindset required of knowledge
workers (Drucker, 1994). The technologist is no longer
trained on the job, as industrial workers traditionally
were, which can cause significant problems for the
industrial worker who does not have the education
required to transition to a knowledge worker position
(Drucker, 1994; Sorrells-Jones & Weaver, 1999a).

Knowledge workers are innovators, and the work they
produce is the foundation for organizational
sustainability and growth. Knowledge workers are
specialized, have advanced education, and typically
have a high degree of autonomy and control over their
own work environments (Davenport, Thomas, &
Cantrell, 2002; Sorrells-Jones & Weaver, 1999a).
Such individuals are most efficient when they are
working in a multidisciplinary team. These teams are
typically composed of members with complementary

knowledge bases. The team members possess
problem-solving and decision-making skills and
advanced interpersonal skills. All members of the team
are considered equal and are there to contribute their
expertise. Leadership shifts and changes as the team
tackles different parts of the project, with the topic
expert taking the lead. A well-functioning team can
consistently outperform an individual (Sorrells-Jones
& Weaver, 1999b). Many of these teams become
focused and passionate about the project on which
they are working.

A key impediment to team effectiveness is a lack of
understanding among team members and a lack of
respect for one another’s knowledge and experience
(Sorrells-Jones & Weaver, 1999a). Another barrier to
efficiency within the multidisciplinary team is the
individual knowledge worker who does not want to give
up his or her own identity even though he or she may
be swayed by other professional opinions.
Professionals have a more difficult time adjusting to
working in a team than do nonprofessionals.
Professionals fail very few times in their lives, which
often results in their not being able to learn from their
failures (Sorrells-Jones & Weaver, 1999b).
Knowledge workers also tend to be resistant to
change, and as a result they dig in their heels and
refuse to adapt to changes that management has
implemented to improve the work process or workflow
(Davenport et al., 2002).

Companies that employ knowledge workers have been
forced to change their management structures to better
support these employees. Management no longer
commands, but rather seeks to inspire workers to
produce the best product (Drucker, 1992). Companies
that rely on knowledge workers have come to the
realization that the machines are unproductive without
the knowledge of those workers. Loyalty is no longer
purchased with a paycheck but is earned by giving
knowledge workers the ability to use their knowledge
effectively and innovatively (Drucker, 1992). In turn,
the physical environment and workplace arrangements
have been adjusted to maximize the workflow of the
knowledge workers (Davenport et al., 2002). Many of
these changes have occurred in the business world but
have been slow to be adopted in health care.

Right now, health care is in the process of transitioning
from the Industrial Age to the Information Age. This
transition has proved challenging because of the
success of healthcare institutions that have enjoyed
using current management methods. Its history of
success will make it difficult for the healthcare industry
to abandon the old so as to learn the new. A new
philosophy recognizing that employees are mature,
self-reliant, independent-thinking adults who function
as partners in carrying out the work of the organization
is needed. The organization needs to view (knowledge
worker) employees as an asset and supply the

resources, tools, information, and power they need to
self-manage their work. Innovation needs to be
supported, especially when it meets the customers’
needs, desires, and wishes (Weaver & Sorrells-
Jones, 1999).

Nursing entails a significant amount of knowledge and
nonknowledge work. Knowledge work includes such
duties as interpreting trends in laboratories and
symptoms. Nonknowledge work includes such tasks as
calling the laboratory to check on laboratory results or
making beds. Nurses, on a daily basis, rely on their
extensive clinical information and specialized
knowledge to implement and evaluate the processes
and outcomes related to patient care (Snyder-Halpern
et al., 2001).

Snyder-Halpern and colleagues (2001) have identified
four tasks associated with human information
processing: (1) data gathering, (2) information use, (3)
creative application of knowledge to clinical practice,
and (4) generation of new knowledge. These four tasks
are associated with four roles that nursing takes on as
a knowledge worker: data gatherer, information user,
knowledge user, and knowledge builder,
respectively.

Nurses are data gatherers by nature. They collect and
record objective clinical data on a daily basis. These
items include such things as patient history information,

vital signs, and patient assessment data. Nurses as
data gatherers transition to information users when
they begin to interpret the data that they have collected
and recorded. Nurses as information users then
structure the clinical data into information that can be
used to guide patient care decisions (Snyder-Halpern
et al., 2001). An example of this is when the nurse
notices that the patient’s blood pressure is elevated.
Information users transition to knowledge users when
they begin to notice trends in a patient’s clinical data
and determine whether the clinical data fall within or
outside of the normal data range. Nurses transition
from knowledge users to knowledge builders when
they examine clinical data and trends across groups of
patients. These trends are interpreted and compared to
current scientific data to determine whether these data
would improve the nursing knowledge domain. An
example of the transition of a nurse as knowledge user
to a nurse as knowledge builder is an observation of
medication compliance rates over a specified time
period for patients diagnosed with chronic high blood
pressure, with the nurse then comparing these rates to
evidence-based literature to determine if this
information improves the nursing knowledge base
(Snyder-Halpern et al., 2001).

Snyder-Halpern and colleagues (2001) found that as
nurses assumed each of these roles, they required
different types of decision support processes to support
their knowledge needs. The data gatherer requires a

system that captures and stores data accurately and
reliably and allows the data to be readily accessed.
Most current healthcare decision support systems
(DSSs) support the nurse in this role. The information
user role requires a system that can transform clinical
data into a format that allows for easy recognition of
patterns and trends. These systems recognize the
trend and display it for the nurse, who in turn uses this
information to adjust the plan of care for the patient.
The information user role is generally well supported by
current DSSs. The knowledge user role is the least
supported role, and many systems are currently
looking at ways to support nurses in this role. One
advantage of these DSSs is their ability to bring
knowledge to nurses so that they do not have to
retrieve the information themselves, which allows them
to adjust a patient’s plan of care in a more efficient and
timely manner. The knowledge builder role is typically
seen in conjunction with the nurse researcher role and
quality management roles. These roles typically look at
aggregated data that have been captured over time
and from numerous patients, with these data then
being compared to clinical variables and interventions;
this analysis results in the development of new domain
knowledge (Snyder-Halpern et al., 2001).

Most of the available DSS tools for nursing practice,
although promising, are simplistic and in early
development. Typically, DSS includes such tools as (1)
computerized alerts and reminders (e.g., medication

due, patient has an allergy, potassium level abnormal),
(2) clinical guidelines (e.g., best practice for prevention
of skin breakdown), (3) online information retrieval
(e.g., CINAHL, drug information), (4) clinical order sets
and protocols, and (5) online access to organizational
policies and procedures. In the future, these tools may
be expanded to include applications with embedded
case-based reasoning.

In the context of nursing practice supported by CISs,
nurses will eventually have access to evidence and
knowledge derived from large aggregates of clinical
data, including nursing interventions and resultant
outcomes. Experiential evidence provides practice
guidelines and directives to ensure concurrence with
optimal clinical decisions and actions. To illustrate,
consider this example: A nurse assesses a patient who
has experienced a stroke for signs of skin breakdown,
photographs and documents early ulcerations, and
submits the photos and documentation to CIS. The
nurse receives an option to review the best practices
for care of the patient and to submit a request for a
consult to a wound management specialist. The
ongoing clinical findings, treatment, and response are
logged and aggregated with similar cases, thereby
contributing to the knowledge base related to nursing
and care of the integumentary system.

The informational elements of CISs can also be
designed to include specifics about individuals’

multicultural practices and beliefs. Consider the
situation where a client voices concerns about her
prescribed dietary treatment and expresses a
preference for a female care provider. With a query to
the CIS for the client’s history and sociocultural
background, the nurse obtains explanations for these
requests that derive from the patient’s religious and
cultural background and makes a notation to highlight
and carry this information forward in the electronic
record for any future admissions. Future systems may
also be designed to provide access to standards of
ethical practice and online access to experts in the field
of moral reasoning to guide clinical interactions and
decision making.

Through each and every instance of interacting with
the CIS, nurses add to these repositories of knowledge
by chronicling their daily clinical challenges and
queries. The continued expansion and aggregation of
knowledge about clients and populations; their
personal, cultural, physical, and clinical presentations;
and individuals’ experiences and the guidance received
from others enhance the delivery of personalized,
knowledge-based care.

Graves and Corcoran (1989) have suggested that
nursing knowledge is “simultaneously the laws and
relationships that exist between the elements that
describe the phenomena of concern in nursing (factual
knowledge) and the laws or rules that the nurse uses to

combine the facts to make clinical nursing decisions”
(p. 230). In their view, not only does knowledge support
decision making, but it also leads to new discoveries.
Thus one might think about the future creation of
nursing knowledge as being the discovery of new laws
and relationships that can continue to advance nursing
practice.

New technologies have made the capture of
multifaceted data and information possible through the
use of such technologies as digital imaging (e.g.,
photography to support wound management). Now
included as part of the clinical record, such images add
a new dimension to the assessment, monitoring, and
treatment of illness and the maintenance of wellness.
Beyond the use of computer keyboards, input devices
are being integrated with CISs and used to gather data
and information for the following clinical and
administrative purposes:

Biometrics (e.g., facial recognition, security)
Voice and video recordings (e.g., client interviews
and observations, diagnostic procedures,
ultrasounds)
Voice-to-text files (e.g., voice recognition for
documentation)
Medical devices, (e.g., infusion pumps, ventilators,
hemodynamic monitors)
Bar-code and radio-frequency identification (RFID)
technologies (e.g., medication administration)

Telehomecare monitoring (e.g., for use in diabetes
and other chronic disease management)

These are but a few of the emerging capabilities that
allow for numerous data inputs to be transposed,
combined, analyzed, and displayed to provide
information and views of clinical situations currently not
possible in a world dominated by hard-copy
documentation. Through the application of information
and communication technologies to support the
capture and processing (i.e., interpretation,
organization, and structuring) of all relevant clinical
data, relationships can be identified and formalized into
new knowledge. This transformational process is at the
core of generating new nursing knowledge at a rate
never experienced before; in the context of current
research paradigms, the same relationships would
likely take years to uncover.

As CISs advance, nurses will eventually become
generators of new knowledge by virtue of designs that
embed machine learning and case-based reasoning
methods within their core functionality. This
functionality will become possible only with national
and international adoption of standardized nursing
language, as previously described. Imagine the power
of having access to systems that aggregate the same
data elements and information garnered from multiple
clinical situations and provide a probability estimate of
the likely outcome for individuals of a certain age, with

a specific diagnosis and comorbid conditions,
medication profile, symptoms, and interventions. How
much more rapidly would an understanding of the
efficacy of clinical interventions be elucidated?
Historically, some knowledge might have taken years
of research to discover (e.g., that long-standing
practices are sometimes more harmful than beneficial).
A case in point is the long-standing practice of instilling
endotracheal tubes with normal saline before
suctioning (O’Neal, Grap, Thompson, & Dudley,
2001). Based on the evidence gathered through
several studies, the potentially deleterious effects of
this practice have become widely recognized.
Conceivably, a meta-analysis approach to clinical
studies will be expedited by convergence of large
clinical data repositories across care settings, thereby
making available to practitioners the collective
contributions of health professionals and longitudinal
outcomes for individuals, families, and populations.

Nurses need to be engaged in the design of CIS tools
that support access to and the generation of nursing
knowledge. As we have emphasized, the adoption of
clinical data standards is of particular importance to the
future design of CIS tools. We are also beginning to
see the development and use of expert systems that
implement knowledge automatically without human
intervention. For example, an insulin pump that senses
the patient’s blood glucose level and administers
insulin based on those data is a form of expert system.

The expert system differs from decision support tools in
that the decision support tools require the human to act
on the information provided, whereas the expert
system intervenes automatically based on an algorithm
that directs the intervention. Consider that as CISs are
widely implemented, as standards for nursing
documentation and reporting are adopted, and as
healthcare IT solutions continue to evolve, the
synthesis of findings from a variety of methods and
worldviews becomes much more feasible.

The Future
The future landscape is yet to be fully understood, as
technology continues to evolve with a rapidity and
unfolding that is rich with promise and potential peril.
Box 6-3 helps us to imagine what future practice might
entail. It is anticipated that computing power will be
capable of aggregating and transforming additional
multidimensional data and information sources (e.g.,
historical, multisensory, experiential, and genetic
sources) into CIS. With the availability of such rich
repositories, further opportunities will open up to
enhance the training of health professionals, advance
the design and application of CDSs, deliver care that is
informed by the most current evidence, and engage
with individuals and families in ways yet unimagined.

BOX 6-3 CASE STUDY: CASTING TO

THE FUTURE

In the year 2025, nursing practice enabled by
technology has created a professional culture of
reflection, critical inquiry, and interprofessional
collaboration. Nurses use technology at the
point of care in all clinical settings (e.g., primary
care, acute care, community, and long-term
care) to inform their clinical decisions and effect
the best possible outcomes for their clients.
Information is gathered and retrieved via
human–technology biometric interfaces
including voice, visual, sensory, gustatory, and
auditory interfaces, which continuously monitor
physiologic parameters for potentially harmful
imbalances. Longitudinal records are maintained
for all citizens from their initial prenatal
assessment to death; all lifelong records are
aggregated into the knowledge bases of expert
systems. These systems provide the basis of
the artificial intelligence being embedded in
emerging technologies. Smart technologies and
invisible computing are ubiquitous in all sectors
where care is delivered. Clients and families are
empowered to review and contribute actively to
their record of health and wellness. Invasive
diagnostic techniques are obsolete,
nanotechnology therapeutics are the norm, and
robotics supplement or replace much of the
traditional work of all health professions. Nurses

provide expertise to citizens to help them
effectively manage their health and wellness life
plans, and navigate access to appropriate
information and services.

The basic education of all health professions will
evolve over the next decade to incorporate core
informatics competencies. In general, the clinical care
environments will be connected, and information will be
integrated across disciplines to the benefit of care
providers and citizens alike. The future of health care
will be highly dependent on the use of CISs and CDSs
to achieve the global aspiration of safer, quality care for
all citizens.

The ideal is a nursing practice that has wholly
integrated informatics and nursing education and that
is driven by the use of information and knowledge from
a myriad of sources, creating practitioners whose way
of being is grounded in informatics. Nursing research is
dynamic and an enterprise in which all nurses are
engaged by virtue of their use of technologies to gather
and analyze findings that inform specific clinical
situations. In every practice setting, the contributions of
nurses to health and well-being of citizens will be highly
respected and parallel, if not exceed, the preeminence
granted physicians.

Summary

In this chapter, we have traced the development of
informatics as a specialty, defined nursing informatics,
and explored the DIKW paradigm central to
informatics. We also explored the need for and the
development of standardized terminologies to capture
and codify the work of nursing and how informatics
supports the knowledge work of nursing. This chapter
advanced the view that every nurse’s practice will
make contributions to new nursing knowledge in
dynamically interactive CIS environments. The core
concepts associated with informatics will become
embedded in the practice of every nurse, whether
administrator, researcher, educator, or practitioner.
Informatics will be prominent in the knowledge work of
nurses, yet it will be a subtlety because of its eventual
fulsome integration with clinical care processes.
Clinical care will be substantially supported by the
capacity and promise of technology today and
tomorrow.

Most importantly, readers need to contemplate a future
without being limited by the world of practice as it is
known today. Information technology is not a panacea
for all of the challenges found in health care, but it will
provide the nursing profession with an unprecedented
capacity to generate and disseminate new knowledge
at rapid speed. Realizing these possibilities
necessitates that all nurses understand and leverage
the informatician within and contribute to the future.

THOUGHT-PROVOKING QUESTIONS

1. How is the concept of wisdom in NI like or
unlike professional nursing judgment?
Can any aspect of nursing wisdom be
automated?

2. How can a single agreed-upon model of
terminology use (with linkages to a single
terminology) help to integrate knowledge
into routine clinical practice?

3. Can you create examples of how expert
systems (not decision support systems
but true expert systems) can be used to
support nursing practice?

4. How would you incorporate the data-to-
wisdom continuum into a job description
for nurse?

5. What are the possibilities to accelerate
the generation and uptake of new nursing
knowledge?

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doi:10.1093/jamia/ocu011

CHAPTER 7: Nursing
Informatics as a
Specialty

Dee McGonigle, Kathleen Mastrian, Julie A. Kenney,
and Ida Androwich

Objectives
1. Describe the nursing informatics

specialty.
2. Explore the scope and standards of

nursing informatics practice.
3. Assess the evolving roles and

competencies of nursing informatics
practice.

4. Appreciate the future of nursing
informatics in our rich, technology-laden
healthcare environments.

Key Terms
» Advocate/policy developer

» Certification

» Consultant

» Data

» Decision support/outcomes manager

» Educator

» Entrepreneur

» Informatics

» Informatics innovator

» Informatics nurse specialist

» Information

» Knowledge

» Knowledge worker

» Medical informatics

» Nursing informatics competencies

» Product developer

» Project manager

» Researcher

» TIGER initiative

Introduction
In the previous chapter, you reviewed the history and
evolution of nursing informatics, and the ways that all
nurses use informatics for practice. In this chapter, we
will focus on nursing informatics as a specialty.
Nursing informatics (NI) is an established, yet ever-
evolving, specialty. Those choosing NI as a career find
it full of numerous and varied opportunities. Previously,
most nurse informaticists entered the field by showing
an understanding and enthusiasm for working with
computers. Now, however, nurses have many
educational opportunities available to become formally
trained in the field of NI to become an informatics nurse
specialist (INS). We will explore the scope and
standards of NI; NI roles, education, and specialization;
rewards of working in the field; and organizations and
professional journals of the INS.

Nursing Contributions to
Healthcare Informatics
Nursing has been involved in the purchase, design,
and implementation of information systems (ISs) since
the 1970s (Saba & McCormick, 2006). One of the first
health IS vendors studied how nurses managed patient

care and realized that nursing activity was the core of
patient activity and needed to be the foundation of the
health or clinical IS. Nursing informaticists have been
instrumental in developing, critiquing, and promoting
standard nursing terminologies to be used in the health
IS. Nursing is involved heavily in the design of
educational materials for practicing nurses, student
nurses, other healthcare workers, and patients.
Computers have revolutionized the way individuals
access information and have revolutionized
educational and social networking processes.

Scope and Standards
NI is important to nursing and health care because it
focuses on representing nursing data, information,
and knowledge. As identified in the earlier edition of
the Nursing Informatics: Scope and Standards of
Practice, NI meets the following needs for health
informatics (American Nurses Association [ANA],
2008; Brennan, 1994):

Provides a nursing perspective
Showcases nursing values and beliefs
Provides a foundation for nurses in NI
Produces unique knowledge
Distinguishes groups of practitioners
Emphasizes the interest for nursing
Provides needed nursing language and word
context

In 2008, the ANA published a revised scope and
standards of nursing informatics practice. This
publication included the most recent INS standards of
practice and the INS standards of professional
performance, and addressed the who, what, when,
where, how, why, and functional roles of INS practice.
There were three overarching standards of practice
(ANA, 2008, p. 33):

1. Incorporate theories, principles, and concepts
from appropriate sciences into informatics
practice.

2. Integrate ergonomics and human–computer
interaction (HCI) principles into informatics
solution design, development, selection,
implementation, and evaluation.

3. Systematically determine the social, legal, and
ethical impact of an informatics solution within
nursing and health care.

The standards of practice and professional
performance for an INS are listed in Box 7-1.

BOX 7-1 INFORMATICS NURSE

SPECIALIST STANDARDS OF

PRACTICE AND PERFORMANCE

STANDARDS OF

PROFESSIONAL PRACTICE
FOR NURSING INFORMATICS

Standard 1: Assessment

Standard 2: Diagnosis, Problems, and Issues
Identification

Standard 3: Outcomes Identification

Standard 4: Planning

Standard 5: Implementation

Standard 5A: Coordination of Activities

Standard 5B: Health Teaching and Health
Promotion

Standard 5C: Consultation

Standard 6: Evaluation

STANDARDS OF
PROFESSIONAL
PERFORMANCE FOR NURSING
INFORMATICS

Standard 7: Ethics

Standard 8: Education

Standard 9: Evidence-Based Practice and
Research

Standard 10: Quality of Practice

Standard 11: Communication

Standard 12: Leadership

Standard 13: Collaboration

Standard 14: Professional Practice
Evaluation

Standard 15: Resource Utilization

Standard 16: Environmental Health

Data from American Nurses Association (ANA). (2015). Nursing

informatics: Scope and standards of practice (2nd ed.). Silver

Spring, MD: Nursesbooks.org.

In 2015, the second edition of the ANA’s Nursing
Informatics: Scope and Standards of Practice was
released. The ANA described the functional areas of
nursing informatics as follows (p. 19):

Administration, leadership, and management
Systems analysis and design
Compliance and integrity management
Consultation
Coordination, facilitation, and integration
Development of systems, products, and resources

Educational and professional development
Genetics and genomics
Information management/operational architecture
Policy development and advocacy
Quality and performance improvement
Research and evaluation
Safety, security, and environmental health

As INSs assume their roles, it is evident that typical
roles cover more than one functional area and that our
“informatics solutions are more closely integrated with
the delivery of care” (ANA, 2015, p. 36). The ANA also
denoted telehealth as an integrated functional area that
is a dynamic health information technology. As nursing,
information, computer, and cognitive sciences continue
to evolve, so will NI functions. With the rapid
advancements we have already seen in the previous
decade, we know that the INSs of the future will be
assuming roles and working in areas that we have not
imagined yet.

Nursing Informatics Roles
NI has become a viable and essential nursing specialty
with the introduction of computers and the EHR to
health care. Many nurses entered the NI field because
of their natural curiosity and their dedication to being
lifelong learners. Others who entered this field might
have done so by accident: Perhaps they were
comfortable working with computers and their

coworkers used them as a resource for computer-
related questions. The introduction of the EHR has
forced all clinicians to learn to use this new technology
and incorporate it into their already busy days.
According to one estimate, nurses spend as little as
10–15% of their days with their patients and as much
as 28–50% of their day documenting (Healthcare
Information and Management Systems Society
[HIMSS] Nursing Informatics Awareness Task
Force, 2007; Munyisia, Yu, & Hailey, 2014). Assisting
nurses to incorporate this new technology into their
daily workflow is one of many challenges that the INS
may tackle. Even though INSs appear to work behind
the scenes, INSs impact the health and clinical
outcomes of patients.

The INS may take on numerous roles; refer to Figure
7-1. For example, one position that INSs fill quite well
is the role of the project manager, as a result of their
ability to simultaneously manage multiple complex
situations. Because of the breadth of the NI field,
however, many INSs find that they need to further
specialize. The following list includes some typical INS
positions. It is far from comprehensive, because this
field changes rapidly, as does technology (ANA, 2015;
Thede, 2003).

Figure 7-1 NI Roles

Project Manager. In the project manager role, the
INS is responsible for the planning and
implementation of informatics projects. The INS
uses communication, change management,
process analysis, risk assessment, scope definition,
and team building. This role acts as the liaison
among clinicians, management, IS, stakeholders,
vendors, and all other interested parties.
Consultant. The INS who takes on the consultant
role provides expert advice, opinions, and
recommendations based on his or her area of
expertise. Flexibility, good communication skills,
excellent interpersonal skills, and extensive clinical
and informatics knowledge are highly desirable skill
sets needed by the NI consultant.
Educator. The success or failure of an informatics
solution can be directly related to the education and
training that were provided for end users. The INS

who chooses the educator role develops and
implements educational materials and sessions and
provides education about the system to new or
current employees during a system implementation
or an upgrade.
Researcher. The researcher role entails
conducting research (especially data mining) to
create new informatics and clinical knowledge.
Research may range from basic informatics
research to developing clinical decision support
tools for nurses.
Product Developer. An INS in the product
developer role participates in the design,
production, and marketing of new informatics
solutions. An understanding of business and
nursing is essential in this role.
Decision Support/Outcomes Manager. Nurses
assuming the role of decision support/outcomes
manager use tools to maintain data integrity and
reliability. Contributing to the development of a
nursing knowledge base is an integral component
of this role.
Advocate/Policy Developer. INSs are key to
advocating for the patients and healthcare systems
and developing the infrastructure of health policy.
Policy development on a local, national, and
international level is an integral part of the
advocate/policy developer role.
Clinical Analyst/System Specialist. INSs may work
at varying levels and serve as a link between

nursing and information services in healthcare
organizations.
Entrepreneur. Those nurses involved in the
entrepreneur role combine their passion, skills,
and knowledge to develop marketable business
ideas by analyzing nursing information needs and
developing and marketing solutions.

Specialty Education and
Certification
Many nurses who entered into NI did so without any
formal education in this field. In many cases, these
nurses served as the unit resource for computer or
program questions. Often, they acquired their skills
through on-the-job training or by attending classes.
Although this pathway to the NI field is still available
today, more formal ways of acquiring these skills exist.
The informatics nurse has a bachelor of science
degree in nursing and additional knowledge and
expertise in the informatics field (ANA, 2015). The INS
holds an advanced degree or a post-master’s
certificate and is prepared to assume roles requiring
this advanced knowledge. INSs may attend informatics
conferences and obtain contact hours or continuing
education units.

Box 7-2 lists some of the pioneering colleges and
universities that offer advanced degrees or certificates

in NI. This is not a comprehensive list; new programs
are continually being developed. Local colleges and
universities should be researched to see which may
have informatics programs.

BOX 7-2 FORMAL NURSING

INFORMATICS EDUCATIONAL

PROGRAMS

GRADUATE DEGREE
PROGRAMS

Chamberlin College of Nursing:
www.chamberlain.edu/admissions/graduate/Master-
of-Science-in-Nursing/informatics-track

Duke University:
http://nursing.duke.edu/academics/programs/msn/health-
informatics-major

Excelsior College:
www.excelsior.edu/nursing-masters-
informatics-faq

Loyola University Chicago:
www.luc.edu/hsm

New York University:
http://nursing.nyu.edu/academics/masters

Northeastern University:
www.healthinformatics.neu.edu

University of Alabama at Birmingham:
www.uab.edu/nursing/home/msn/nursing-
informatics-major

University of Colorado at Denver:
www.ucdenver.edu/academics/colleges/nursing/programs-
admissions/masters-programs/ms-
program/specialties/healthcareinformatics/Pages/default.aspx

University of Iowa:
http://informatics.grad.uiowa.edu/health-
informatics/curriculum

University of Kansas:
http://nursing.kumc.edu/academics/master-
of-science/nursing-informatics.html

University of Maryland:
www.nursing.umaryland.edu/academics/grad/specialties/ni

University of North Carolina at Chapel Hill:
http://nursing.unc.edu/academics/graduate-
practice-
programs/master_of_science_in_nursing/health-
care-systems-msn/

University of Pittsburgh:
www.nursing.pitt.edu/degree-
programs/master-science-nursing-

msn/msn-program-majors/nursing-
informatics/nursing

University of Utah:
http://nursing.utah.edu/programs/msnursinginformatics.php

University of Washington:
www.son.washington.edu/portals/cipct

Vanderbilt University:
www.nursing.vanderbilt.edu/msn/ni.html

CERTIFICATE PROGRAMS
Chamberlain College of Nursing:
www.chamberlain.edu/admissions/graduate/graduate-
certificate-programs

Indiana University:
nursing.iupui.edu/continuing/informatics.shtml

Loyola University Chicago:
www.luc.edu/media/lucedu/nursing/pdfs/Informatics%20Certificate.pdf

Northeastern University:
www.ccis.northeastern.edu/program/health-
informatics-grad-certificate/

Penn State University:
www.worldcampus.psu.edu/degrees-and-
certificates/nursing-informatics-
certificate/overview

University of Iowa:
informatics.grad.uiowa.edu/health-
informatics/curriculum

Nurses who choose to specialize in NI have two
certification options available to them. The first is
obtained through the American Nurses Credentialing
Center (ANCC). The ANCC’s examination is specific
for the informatics nurse. The applicant must be a
licensed registered nurse with at least 2 years of recent
experience and have a baccalaureate degree in
nursing. The applicant must have completed 30 contact
hours of continuing education in informatics. The
applicant must meet one of the following criteria: (1)
2,000 hours practicing as an informatics nurse, (2)
1,000 hours practicing as an informatics nurse and 12
semester hours of graduate academic credit toward an
NI degree, or (3) completion of an NI degree that
included at least 200 supervised practicum hours. For
further information on this certification examination,
visit
www.nursecredentialing.org/Certification/NurseSpecialties/Informatics
This website includes the aforementioned criteria and
provides further information about test eligibility, fees,
examination content, examination locations, study
materials, and practice tests.

The second certification examination is sponsored by
the Healthcare Information and Management Systems

Society (HIMSS). Candidates who successfully pass
this examination are designated as certified
professionals in healthcare information and
management systems. The HIMSS examination is
open to any candidate who is involved in healthcare
informatics. Candidates must hold positions in the
following fields: administration/management, clinical IS,
e-health, IS, or management engineering. Candidates
may include any of the following: chief executive
officers, chief information officers, chief operating
officers, senior executives, senior managers, IS
technical staff, physicians, nurses, consultants,
attorneys, financial advisors, technology vendors,
academicians, management engineers, and students.
Candidates must meet the following criteria to be
eligible to sit for the examination: a baccalaureate
degree plus 5 years of associated information and
management systems experience, with 3 of those
years being in health care; or a graduate degree plus 3
years of associated information and management
systems experience, with 2 of those years being in
health care. The information discussed in this text and
additional information about the examination can be
found by visiting
http://www.himss.org/ASP/certification_cphims.asp.

Nursing Informatics
Competencies

One challenge that has been identified in the literature
and continues to plague health care is the vast
differences in computer literacy and information
management skills that healthcare workers possess
(Gassert, 2008; McNeil, Elfrink, Beyea, Pierce, &
Bickford, 2006; Topkaya & Kaya, 2014). Gassert
(2008) felt that new graduates were not adequately
literate. Barton (2005) believed that new nurses should
have the following critical skills: use e-mail, operate
Windows applications, search databases, and know
how to work with the institution-specific nursing
software used for charting and medication
administration. These skills should not be limited to just
new nurses, but instead should be required of all
nurses and healthcare workers.

Staggers, Gassert, and Curran (2001) advocated that
nursing students and practicing nurses should be
educated on core NI competencies. Although
information technology and informatics concepts
certainly need to be incorporated into nursing school
curricula, progress in this area has been slow. In the
1980s, a nursing group of the International Medical
Informatics Association convened to develop the first
level of nursing competencies. While developing these
competencies, the nursing group found that nurses fell
in to one of the following three categories: (1) user, (2)
developer, or (3) expert. These categories have since
been expanded.

Staggers and colleagues (2001) decided that the NI
competencies developed in the 1980s were inadequate
and needed to be updated. These authors reviewed 35
NI competency articles and 14 job descriptions, which
resulted in 1,159 items that were sorted into three
broad categories: (1) computer skills, (2) informatics
knowledge, and (3) informatics skills. These items were
then placed in a database, where redundant items
were removed. When this process was completed, 313
items remained.

When these items were then further subdivided,
Staggers and colleagues, along with the American
Medical Informatics Association (AMIA) work group,
realized that these competencies were not universal to
all nurses; thus, before it could be determined if the
competency was an NI competency, nursing skill levels
needed to be defined. The group determined that
practicing nurses could be classified into four
categories: (1) beginning nurse, (2) experienced nurse,
(3) informatics nurse specialist, and (4) informatics
innovator. Each of these skill levels needed to be
defined before Staggers and colleagues (2001) could
determine which level was the most appropriate for that
skill set. Table 7-1 provides the definition criteria for
each skill level. Once the levels were defined, the
group determined that 305 items were NI
competencies and placed them into appropriate
categories.

TABLE 7-1 Definitions of Four Levels of Practicing
Nurses

Beginning Nurse

Has basic computer technology skills and information

management skills

Uses institution’s information systems and the contained

information to manage patients

Experienced Nurse

Proficient in a specialty

Highly skilled in using computer technology skills and information

management skills to support his or her specialty area of practice

Pulls trends out of data and makes judgments based on this

information

Uses current systems, but will collaborate with informatics nurse

specialist regarding concerns or suggestions provided by staff

Informatics Nurse Specialist

RN with advanced education who possesses additional knowledge

and skills specific to computer technology and information

management

Focuses on nursing’s information needs, which include education,

administration, research, and clinical practice

Application and integration of the core informatics sciences:

information, computer, and nursing science

Uses critical thinking, process skills, data management skills,

systems life cycle development, and computer skills

Informatics Innovator

Conducts informatics research and generates informatics theory

Vision of what is possible

Keen sense of timing to make things happen

Creative in developing solutions

Leads the advancement of informatics practice and research

Sophisticated level of skills and understanding in computer

technology and information management

Cognizant of the interdependence of systems, disciplines, and

outcomes and is able to finesse situations to obtain the best

outcome

Reproduced from Staggers, N., Gassert, C., & Curran, C. (2001).
Informatics competencies for nurses at four levels of practice. Journal

of Nursing Education, 40(7), 303–316. With permission of SLACK

Incorporated.

Staggers, Gassert, and Curran (2002) conducted the
seminal work in this area, a Delphi study to validate the
placement of the competencies into the correct skill
level. Of the 305 original competencies identified, 281
achieved an 80% approval rating for both importance
as a competency and placement in the correct practice
level. The authors stressed that this is a
comprehensive list; thus, for a nurse to enter a
particular skill level, he or she need not have mastered
every item listed for that skill level. For a list of
competencies by skill level, see Table 7-2.

Table 7-2 Nursing Informatics Compentencies by Skill
Level

Based on research conducted by Hunter, Mc

Gonigle, and Hebda (2013), the online self-assessment instrument,
TIGER-based Assessment of Nursing Informatics Competencies

(TANIC) was developed. This instrument assesses the Level I:

Beginning Nurse and Level 2: Experienced Nurse competencies.

Level 1: Beginning Nurse

Start the computer and log on securely to access select

applications/software

Access and send email

Collect and enter patient data into the information system

Level 2: Experienced Nurse

Identify the risks and limitations of surfing the Internet to locate

evidence-based practice information

Gather data to draw and synthesize conclusions

Explain how to sustain the integrity of information resources

Based on the research conducted by Mc

Gonigle, Hunter, Hebda, and Hill (2014), the online self-assessment
instrument, Nursing Informatics Competency Assessment – Level

3/Level 4 (NICA L3/L4) was developed. This instrument assesses the

Level 3: Informatics Nurse Specialist and Level 4: Informatics

Innovator competencies.

Level 3: Informatics Nurse Specialist

Fluent in nursing informatics and nursing terminologies

Applies aspects of human technology interface to screen, device,

and software design

Teach nurses how to locate, access, retrieve, and evaluate

information

Level 4: Informatics Innovator

Analyze systems

Transform software programs to support data analysis and

aggregation

Lead research efforts to determine and address application needs

References

Hill, T., Mc

Gonigle, D., Hunter, K., Sipes, C. & Hebda, T. (2014). An instrument
for assessing advanced nursing informatics competencies. Journal of

Nursing Education and Practice, 4(7), 104–112.

Hunter, K., Mc

Gonigle, D. & Hebda, T. (2011, December). Operationalizing TIGER
NI competencies for online assessment of perceived competency.

TIGER Initiative Foundation Newsletter. Retrieved from

http://www.thetigerinitiative.org [must subscribe to access]

Hunter, K., Mc

Gonigle, D., & Hebda, T. (2013). TIGER-based measurement of
nursing informatics competencies: The development and

implementation of an online tool for self-assessment. Journal of

Nursing Education and Practice, 3(12), 70–80. doi:

10.5430/jnep.v3n12p70

Hunter, K., Mc

Gonigle, D., Hebda, T., Sipes, C., Hill, T., & Lamblin, J. (2015).
TIGER-based assessment of nursing informatics competencies

(TANIC). In A. Rocha, S. Correia, S. Costanza, & L. Reis (Eds.). New

contributions in information systems and technologies: Volume 1

(advances in intelligent systems and computing) (pp. 171–177).

Basel, Switzerland: Springer. DOI: 10.1007/978-3-319-16486-1_7

Mc

Gonigle, D., Hunter, K., Hebda, T., & Hill, T. (2014). Self-assessment
of Level 3 and Level 4 NI competencies tool development. Retrieved

from http://www.himss.org/file/1307246/download?
token=cNOya_Lm

Mc

Gonigle, D., Hunter, K., Hebda, T., Sipes, C., Hill, T., & Lamblin, J.

(2015). Nursing informatics competencies assessment Level 3 and
Level 4 (NICA L3/L4). In A. Rocha, S. Correia, S. Costanza, & L. Reis

(Eds.). New contributions in information systems and technologies:

Volume 1 (advances in intelligent systems and computing) (pp. 209–

214). Basel, Switzerland: Springer. DOI: 10.1007/978-3-319-16486-

1_21

In 2004, a group of nurses came together after
attending a national informatics conference to ensure
that nursing was equally recognized in the national
informatics movement. This so-called Technology
Informatics Guiding Education Reform (TIGER) team
determined that using informatics was a core
competency for all healthcare workers. They also
determined that many nurses lack information
technology skills, which limits their ability to access
evidence-based information that could otherwise be
incorporated into their daily practice. This group is
currently working on a plan to include informatics
courses in all levels of nursing education; when that
effort is complete, they will examine how to get the
information out to practicing nurses who are not
currently enrolled in an academic program (HIMSS,
2016). Many of the items identified by the TIGER team
as lacking in both nursing students and practicing
nurses are items that Staggers et al. (2002) determined
to be NI competencies. To learn more about the TIGER
initiative, visit
http://www.himss.org/professionaldevelopment/tiger-
initiative.

Through the work of Hunter et al. (2011; 2013; 2015)
and McGonigle et al. (2014; 2015), the competencies
for nursing informatics practice Levels 1 through 4
have been further refined with two self-assessment
tools developed. Hunter and colleagues focused on the
Level 1 and Level 2 competencies and developed the

self-assessment of competencies TANIC tool, Tiger-
based Assessment of Nursing Informatics
Competencies. McGonigle and colleagues focused on
the competencies related to the advanced levels 3 and
4, developing the self-assessment of competencies
NICA L3/L4 tool, Nursing Informatics Competency
Assessment Level 3/Level 4 (ANA, 2015, p. 43).

It is critical that nurses and INSs can demonstrate
competence. As there were many definitions of the
term competency, the authors of these tools first had to
define the term competency. Hunter et al. (2013)
concluded that

Competency, then, is a concept
applicable to multiple situations. At its
most basic, competency denotes having
the knowledge, skills, and ability to
perform or do a specific task, act, or job.
Depending on the context, competency
can refer to adequate or expert
performance. For this research,
competency was used to mean adequate
knowledge, skills, and ability. Nursing-
informatics competency was defined as
adequate knowledge, skills, and ability to
perform specific informatics tasks. (p. 71)

The teams began instrument development by
synthesizing both seminal and current literature to
construct instrument items; they reviewed, formatted,
and initiated instrument testing with a Delphi study and
then piloted the resulting instrument with experts.
Cronbach’s alpha values were calculated. The TANIC
Cronbach was 0.944 for clinical information
management, 0.948 for computer skills, and 0.980 for
information literacy. The NICA L3/L4 reliability
estimates were as follows: computer skills, 0.909;
informatics knowledge, 0.982; and informatics skills,
0.992. The Cronbach’s reliability estimates for each
tool showed strong internal consistency reliability.

The TANIC self-assessment instrument has four parts,
including questions about demographics and the self-
assessment, consisting of 85 items covering basic
computer literacy, clinical information management,
and information literacy. The NICA L3/L4 self-
assessment instrument also has four parts: questions
about demographics and the 178 item self-
assessment, consisting of computer skills, informatics
knowledge, and informatics skills.

These tools and those that will follow are extremely
important because they help each of us identify our
own level of comfort with technology and our self-
confidence in our ability to perform these skills/tasks.
Nurse educators in all practice settings and school-
based programs must help their nurses or nursing

students recognize deficits in their current knowledge
and skills. The nurse educators can facilitate the
professional development of their nurses or nursing
students through the identification of courses or skill-
based labs that will help them turn their deficits into
strengths.

Rewards of NI Practice
NI is a nursing specialty that does not focus on direct
patient care but instead focuses on enhancing patient
care and safety and improving the workflow and work
processes of nurses and other healthcare workers. The
INS is instrumental in designing the electronic
healthcare records that healthcare workers use on a
daily basis. This nurse is also responsible for designing
tools that allow healthcare workers to access patient
information more efficiently than they have been able
to do so in the past. Watching these changes take
place brings great satisfaction to the INS.

Change is a factor that an INS deals with on a daily
basis. This dynamic nature of the position is probably
its most difficult aspect, because people deal with
change differently. Understanding change theory and
processes and appreciating how change affects people
assist the INS in developing strategies to encourage
healthcare workers to accept changes and become
proficient in informatics solutions that have been

implemented. Seeing the change adopted with a
minimal amount of discord is very rewarding to the INS.

The INS also participates in informatics organizations
that allow INSs to network and share experiences with
one another. Such interactions allow INSs to bring
these new solutions back to their respective
organizations and improve informatics trouble spots.
Attending professional conferences allows the INS to
stay abreast of changes in the industry. Continuing
education may help the INS to improve a process or
workflow within the hospital or to change the way a
system upgrade is rolled out.

NI Organizations and Journals
One of the first informatics organizations founded was
HIMSS. HIMSS, which celebrated its 55th year in 2016,
was launched in 1961 and now has offices throughout
the United States and Europe. HIMSS currently
represents more than 20,000 individuals and 300
corporations. This organization supports both local and
national chapters. It has many associated work groups,
one of which is an NI work group. HIMSS is well known
for its development of industry-wide policies and its
educational and professional development initiatives,
all of which are directed toward the goal of ensuring
safe patient care. Membership in HIMSS offers many
advantages for nurses, such as access to numerous
weekly and monthly publications, and two scholarly

journals, the Journal of Healthcare Information
Management and the Online Journal of Nursing
Informatics. HIMSS offers many educational programs,
including virtual expos, which allow participants to
experience the expo without having to travel. These
educational opportunities allow participants to network
with colleagues and peers, which is a valuable asset in
this field. HIMSS also periodically conducts NI
workforce surveys. It is interesting to review the most
current survey results and compare them to your
setting and role.

The American Medical Informatics Association (AMIA)
was founded in 1990 when three health informatics
associations merged. AMIA currently has more than
3,000 members who reside in 42 countries. This
organization focuses on the development and
application of biomedical and healthcare informatics.
Members include physicians, nurses, dentists,
pharmacists, health information technology
professionals, and biomedical engineers. AMIA offers
many benefits to its members, such as weekly and
monthly publications and a scholarly journal, JAMIA—
The Journal of the American Medical Informatics
Association. Members may join a working group that is
specific to their specialty, including an NI work group.
AMIA offers multiple educational opportunities and
many opportunities for networking with colleagues.

The American Nursing Informatics Association (ANIA)

was established in 1992 to provide an opportunity for
southern California informatics nurses to meet. It has
since grown to a national organization whose members
include healthcare professionals who work with clinical
IS, educational applications, data collection/research
applications, administrative/DSS, and those who have
an interest in the field of NI. In 2009, ANIA merged with
the Capital Area Roundtable on Informatics in Nursing
(CARING). Membership benefits include the following:

Access to a network of more than 3,200 informatics
professionals in 50 states and 30 countries
Active email list
Quarterly newsletter indexed in CINAHL and
Thomson
Job bank with employee-paid postings
Reduced rate at the ANIA Annual Conference
Reduced rate for CIN: Computers, Informatics,
Nursing
ANIA Online Library of on-demand and webinar
education activities
Membership in the Alliance for Nursing Informatics
Web-based meetings
In-person meetings and conferences held nationally
and worldwide

The Alliance for Nursing Informatics (ANI) is a coalition
of NI groups that represents more than 3,000 nurses
and 20 distinct NI groups in the United States. Its
membership represents local, national, and

international NI members and groups. These individual
groups have developed organizational structures and
have established programs and publications. ANI
functions as the link between NI organizations and the
general nursing and healthcare communities and
serves as the united voice of NI.

These groups have been instrumental in establishing
the informatics community. Box 7-3 lists some of these
organizations and their publications, but many other
informatics groups exist.

BOX 7-3 NURSING INFORMATICS

WEBSITES AND CORRESPONDING

JOURNALS

Alliance for Nursing Informatics

Website: www.allianceni.org

American Health Information
Management Association

Website: www.ahima.org

Journal: Journal of AHIMA & Perspectives in
Health Information Management (online)

American Medical Informatics
Association

Website: www.amia.org

Journal: JAMIA—Journal of the American
Medical Informatics Association

NI website:
www.amia.org/programs/working-
groups/nursing-informatics

American Nursing Informatics
Association

(includes Capital Area Roundtable on
Informatics in Nursing [CARING]) Website:
www.ania.org

Resources link:
www.ania.org/Resources.htm

Journal: CIN: Computers, Informatics,
Nursing

Health Information and Management
Systems Society

Website: www.himss.org

Chapter websites:
www.himss.org/ASP/chaptersHome.asp

Journal: The Journal of Healthcare
Information Management

NI website:
www.himss.org/asp/topics_nursingInformatics.asp

International Medical Informatics
Association

Website: www.imia.org

Journal: International Journal of Medical
Informatics

NI website: www.imia.org/ni

Online Journal of Nursing Informatics

Website: www.himss.org/ojni

The Future of Nursing
Informatics
NI is still in its infancy, as is the technology that the INS
uses on a daily basis. NI will continue to influence
development of the EHR; in turn, the EHR will continue
to improve and will one day accurately capture the care
nurses give to their patients. This is a formidable
challenge because much of the care provided by
nurses is intangible in nature. In the future, the EHR
will provide data to the INS that can then be used to
improve nursing workflow and to determine whether
current practices are the most efficient and beneficial to
the patient.

Nursing and health care are on a roller-coaster ride
that will undoubtedly prove very interesting. New

technology is being introduced at a breakneck speed,
and nursing and health care must be ready to ride this
roller coaster. Programs need to be developed to keep
nurses and healthcare workers abreast of the new
technological changes as they occur, and educating
new and current nurses presents a significant
challenge to the INS. Therefore, the INS’s future looks
very promising and rewarding.

According to the ANA (2015), five trends will influence
the future of nursing informatics:

1. Changing practice roles in nursing
2. Increasing informatics competence requirements

for all nurses
3. Rapidly evolving technology
4. Regulatory changes and quality standards that

include healthcare consumers as partners in
healthcare models

5. Care delivery models and innovation (p. 52)

As the future becomes yesterday, people are waking
up to the fact that we need the healthcare team
prepared with informatics competencies. All healthcare
providers should receive education on informatics
because they need basic informatics skills, such as the
ability to use search engines to find information about a
specific topic. Consequently, all healthcare providers
need to be able to attend classes to improve their
computer skills and knowledge. Those entering the

nursing field need a general knowledge of computer
capabilities. Many new trends—such as Web 2.0,
increased attention to evidence-based practice, and a
better understanding of genomics—will impact care
delivery in the 21st century, and NI nurses need to be
prepared to lead these efforts to improve care and help
nurses have a voice in the informatics skills they need,
as well as in the advances and tools they use,
including the EHR (Bakken, Stone, & Larson, 2008;
Lavin, Harper, & Barr, 2015).

Change plays a significant part in health care today,
and those interested in NI must embrace change. They
must also be good at enticing others to embrace
change. Nevertheless, NI candidates must realize that
change is often accompanied by resistance. For their
part, INSs must be ready to leave the bedside,
because nurses entering into this field will no longer be
giving hands-on care. NI is a very challenging but very
rewarding field. In an ideal world, all healthcare
agencies will employ at least one INS, and all nurses
will embrace the knowledge worker title.

Summary
Nursing informatics is a specialty that integrates
nursing science, computer science, and information
science to manage and communicate data,
information, knowledge, and wisdom in nursing
practice. Our definition: the synthesis of nursing

science, information science, computer science, and
cognitive science for the purpose of managing,
disseminating, and enhancing healthcare data,
information, knowledge, and wisdom to improve
collaboration and decision making, provide high-quality
patient care, and advance the profession of nursing.
Informatics practices support nurses as they seek to
care for their patients effectively and safely, by making
the information that they need more readily available.
Nurses have been actively involved in this field since
computers were introduced to health care. With the
advent of the EHR, it became apparent that nursing
needed to develop its own terminology related to the
new technology and its applications; NI has been
instrumental in this process.

Today, the healthcare industry employs the largest
number of knowledge workers in the world. Nurses, as
knowledge workers in technology-laden healthcare
facilities, must continuously improve their informatics
competencies. The INS is instrumental in leading the
advancement of informatics concepts and tools in all
settings and across all specialties. NI is a specialty
governed by standards that have been established by
the ANA. Because NI is a very diverse field, many INSs
eventually specialize in one segment of the field. While
NI is an established specialty, the core NI principles are
utilized by all nurses. Nursing informatics
competencies have been developed to encompass all
levels of practice and ensure that entry-level nurses

are ready to enter the more technologically advanced
field of nursing, as well as establish advanced
competencies for the INS’s specialty practice. These
competencies may be used to determine the
educational needs of current staff members.

The growth of the NI field has resulted in the formation
of numerous NI organizations or subgroups of the
medical informatics organizations. Nurses no longer
have to enter the field by chance but can obtain an
advanced degree in NI at many well-established
universities. In addition, INSs may continue their
learning by attending the numerous conferences
offered.

NI has grown tremendously as a specialty since its
inception and has the expectation of continued growth.
The NI specialty not only engages nurses and patients,
but also engages data to improve patient outcomes,
enhance patient care, and advance the science of
nursing. It will be interesting to see where NI and INSs
take health care in the future.

THOUGHT-PROVOKING QUESTIONS

1. A hospital is seeking to update its EHR. It
has been suggested that an INS be hired.
This position does not involve direct
patient care and the administration is

struggling with how to justify the position.
How can this position be justified?

2. It is important that all nurses be
informatics competent at all levels. In
particular, at which levels should the INS
be able to exhibit competency? Provide
several examples of the knowledge and
skills that an INS might demonstrate.

3. How does nursing move from measuring
the tasks completed to measuring the
final outcome of the patient? How can the
INS help us reach this goal?

References
Alliance for Nursing Informatics. (2013).

Homepage. Retrieved from
http://www.allianceni.org

American Medical Informatics Association.
(2013). Homepage. Retrieved from
http://www.amia.org

American Nurses Association (ANA).
(2008). Nursing informatics: Scope and
standard of practice. Silver Spring,
MD: Nursesbooks.org.

American Nurses Association (ANA).
(2015). Nursing informatics: Scope and
standard of practice (2nd ed.). Silver
Spring, MD: Nursesbooks.org.

Androwich, I. (2010, June). Paper
presented at Delaware Valley Nursing
Informatics Annual Meeting, Malvern,
PA.

Bakken, S., Stone, P., & Larson, E.
(2008). A nursing informatics research
agenda for 2008–2018: Contextual
influences and key components.
Nursing Outlook, 56(5), 206–214.

Barton, A. J. (2005). Cultivating
informatics competencies in a
community of practice. Nursing
Administration Quarterly, 29(4), 323–
328.

Brennan, P. F. (1994). On the relevance of
discipline to informatics. Journal of the
American Medical Informatics
Association, 1(2), 200–201.

Davenport, T. H., Thomas, R., & Cantrell,
S. (2002). The mysterious art and
science of knowledge worker
performance. MIT Sloan Management
Review, 44(1), 23–30.

Drucker, P. F. (1992). The new society of
organizations. Harvard Business
Review, 70(5), 95–104.

Drucker, P. F. (1994). The age of social
transformation. Atlantic Monthly,
274(5), 52–80.

Gassert, C. (2008). Technology and
informatics competencies. Nursing
Clinics of North America, 43(4), 507–
521. doi: 10.1016/j.cnur.2008.06.005

Health Information and Management
Systems Society (HIMSS). (2006).
HIMSS dictionary of healthcare
information technology terms,
acronyms and organizations. Chicago,
IL: Author.

Health Information and Management
Systems Society (HIMSS). (2013).
Homepage. Retrieved from
http://www.himss.org

Health Information and Management
Systems Society (HIMSS). (2016). The
TIGER initiative. Retrieved from
http://www.himss.org/professionaldevelopment/tiger-
initiative

HIMSS Nursing Informatics Awareness
Task Force. (2007). An emerging giant:
Nursing informatics. Nursing
Management, 13(10), 38–42.

Hunter, K., McGonigle, D. & Hebda, T.
(2011, December). Operationalizing
TIGER NI competencies for online
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CHAPTER 8: Legislative
Aspects of Nursing
Informatics: HITECH and
HIPAA

Kathleen M. Gialanella, Kathleen Mastrian, and Dee
McGonigle

Objectives
1. Explore the Health Insurance Portability

and Accountability Act (HIPAA) of 1996.
2. Describe the purposes of the Health

Information Technology for Economic and
Clinical Health (HITECH) Act of 2009.

3. Explore how the HITECH Act is
enhancing the security and privacy
protections of HIPAA.

4. Determine how the HITECH Act and its
impact on HIPAA apply to nursing
practice.

5. Identify informatics technologies likely to
be legislated in the future.

Key Terms
» Access

» Agency for Healthcare Research and
Quality

» American National Standards Institute

» American Recovery and Reinvestment
Act

» Centers for Medicare and Medicaid
Services

» Certified EHR technology

» Civil monetary penalties

» Compliance

» Confidentiality

» Consequences

» Electronic health records

» Enterprise integration

» Entities

» Gramm-Leach-Bliley Act

» Health disparities

» Health information technology

» Health Insurance Portability and
Accountability Act

» Health Level Seven

» Healthcare-associated infections

» International Standards Organization

» Meaningful use

» National Institute of Standards and
Technology

» Office of Civil Rights

» Office of the National Coordinator for
Health Information Technology

» Open Systems Interconnection

» Patient-centered care

» Policies

» Privacy

» Protected health information

» Qualified electronic health record

» Rights

» Sarbanes-Oxley Act

» Security

» Standards

» Standards-developing organizations

» Treatment/payment/operations

Introduction
Two key pieces of legislation have shaped the nursing
informatics landscape: the Health Insurance Portability
and Accountability Act (HIPAA) of 1996 and the Health
Information Technology for Economic and Clinical
Health Act (HITECH) of 2009. This chapter presents an
overview of the HITECH Act, including the Medicare
and Medicaid health information technology (HIT)
provisions of the law. Nurses need to be familiar with
the goals and purposes of this law, know how it
enhances the security and privacy protections of the
Health Insurance Portability and Accountability Act
(HIPAA) of 1996, and appreciate how it otherwise
affects nursing practice in the emerging electronic
health records age. The concepts of “meaningful use”
and “certified EHR technology” also are explored in this
chapter, as well as potential future legislation regulating
medical devices and apps and the movement toward
payment based on quality. Figure 8-1 provides a

snapshot of the legislation affecting the informatics
landscape.

Figure 8-1 Health Informatics Regulations

HIPAA Came First
HIPAA was signed into law by President Bill Clinton in
1996. Hellerstein (1999) summarized the intent of the
act as follows: to curtail healthcare fraud and abuse,
enforce standards for health information, guarantee the
security and privacy of health information, and ensure
health insurance portability for employed persons.
Consequences were put into place for institutions and
individuals who violate the requirements of this act. For
this text, we concentrate on the health information

security and privacy aspects of HIPAA, which are
outlined as follows:

The privacy provisions of the federal law,
the Health Insurance Portability and
Accountability Act of 1996 (HIPAA), apply
to health information created or
maintained by healthcare providers who
engage in certain electronic transactions,
health plans, and healthcare
clearinghouses. The U.S. Department of
Health and Human Services (USDHHS)
issued the regulation, “Standards for
Privacy of Individually Identifiable Health
Information,” applicable to entities
covered by HIPAA. The Office for Civil
Rights (OCR) is the Departmental
component responsible for implementing
and enforcing the privacy regulation.
(U.S. Department of Health and Human
Services, 2015, para. 5–6)

The need and means to guarantee the security and
privacy of health information was the focus of
numerous debates. Comprehensive standards for the
implementation of this portion of the Act eventually
were finalized, but the process to adopt final standards
took years. In August 1998, the USDHHS released a
set of proposed rules addressing health information

management. Proposed rules specific to health
information privacy and security were released in
November 1999. The purpose of the proposed rules
was to balance patients’ rights to privacy and providers’
needs for access to information (Hellerstein, 2000).

Hellerstein (2000) summarized the proposed privacy
rules. The rules do the following:

Define protected health information as “information
relating to one’s physical or mental health, the
provision of one’s health care, or the payment for
that health care, that has been maintained or
transmitted electronically and that can be
reasonably identified with the individual it applies to”
(Hellerstein, 2000, p. 2). Figure 8-2 depicts the
types of information protected under HIPAA.

Figure 8-2 What Is Protected Health Information?

Propose that authorization by patients for release of
information is not necessary when the release of
information is directly related to treatment and
payment for treatment. Specific patient
authorization is not required for research, medical
or police emergencies, legal proceedings, and
collection of data for public health concerns. All
other releases of health information require a
specific form for each release and only information
pertinent to the issue at hand is allowed to be
released. All releases of information must be
formally documented and accessible to the patient
on request.

Establish patient ownership of the healthcare record
and allow for patient-initiated corrections and
amendments.
Mandate administrative requirements for the
protection of healthcare information. All healthcare
organizations are required to have a privacy official
and an office to receive privacy violation
complaints. A specific training program for
employees that includes a certification of
completion and a signed statement by all
employees that they will uphold privacy procedures
must be developed and implemented. All
employees must re-sign the agreement to uphold
privacy every 3 years. Sanctions for violations of
policy must be clearly defined and applied.
Mandate that all outside entities that conduct
business with healthcare organizations (e.g.,
attorneys, consultants, auditors) must meet the
same standards as the organization for information
protection and security.
Allow protected health information to be released
without authorization for research studies. Patients
may not access their information in blinded
research studies because this access may affect
the reliability of the study outcomes.
Propose that protected health information may be
deidentified before release in such a manner that
the identity of the patient is protected. The
healthcare organization may code the

deidentification so that the information can be
reidentified once it has been returned.
Apply only to health information maintained or
transmitted by electronic means.

As concerns mounted and deadlines loomed, the
healthcare arena prepared to comply with the
requirements of the law. The administrative
simplification portion of this law was intended to
decrease the financial and administrative burdens by
standardizing the electronic transmission of certain
administrative and financial transactions. This section
also addressed the security and privacy of healthcare
data and information for the covered entities of
healthcare providers who transmit any health
information in electronic form in connection with a
covered transaction, health plans, and healthcare
clearinghouses (Centers for Medicare & Medicaid
Services, 2014).

The privacy requirements, which went into effect on
April 14, 2003, limited the release of protected health
information without the patient’s knowledge and
consent. Covered entities must comply with the
requirements. Notably, they must dedicate a privacy
officer, adopt and implement privacy procedures,
educate their personnel, and secure their electronic
patient records. Most individuals are familiar with the
need to notify patients of their privacy rights, having
signed forms on interacting with healthcare providers.

According to the USDHHS (2002), the privacy rule
provides certain rights to patients: the right to request
restrictions to access of the health record; the right to
request an alternative method of communication with a
provider; the right to receive a paper copy of the notice
of privacy practices; the right to file a complaint if the
patient believes his or her privacy rights were violated;
the right to inspect and copy one’s health record; the
right to request an amendment to the health record;
and the right to see an account of disclosures of one’s
health record. This places the burden of maintaining
privacy and accuracy on the healthcare system, rather
than the patient.

On October 16, 2003, the electronic transaction and
code set standards became effective. At the time, they
did not require electronic transmission, but rather
mandated that if transactions were conducted
electronically, they must comply with the required
federal standards for electronically filed healthcare
claims. “The Secretary has made the Centers for
Medicare & Medicaid Services (CMS) responsible for
enforcing the electronic transactions and code sets
provisions of the law” (“Guidance on Compliance with
HIPAA Transactions and Code Sets,” 2003, para. 3).

The security requirements went into effect on April 21,
2005, and required the covered entities to put
safeguards that protect the confidentiality, integrity, and

availability of protected health information when stored
and transmitted electronically into place.

The safeguards that were addressed were
administrative, physical, and technical. The
administrative safeguards refer to the documented
formal policies and procedures that are used to
manage and execute the security measures. They
govern the protection of healthcare data and
information and the conduct of the personnel. The
physical safeguards refer to the policies and
procedures that must be in place to limit physical
access to electronic information systems. Technical
safeguards are the policies and procedures used to
control access to healthcare data and information.
Safeguards need to be in place to control access
whether the data and information are at rest, residing
on a machine or storage medium, being processed, or
in transmission, such as being backed up to storage or
disseminated across a network.

Overview of the HITECH Act
The federal Health Information Technology for
Economic and Clinical Health Act of 2009 (HITECH
Act; Leyva & Leyva, 2011), enacted February 17,
2009, is part of the American Recovery and
Reinvestment Act (ARRA). The ARRA, also known as
the “Stimulus” law, was enacted to stimulate various
sectors of the U.S. economy during the most severe

recession this country had experienced since the Great
Depression of the late 1920s and early 1930s. The
health information technology (HIT) industry was
one area where lawmakers saw an opportunity to
stimulate the economy and improve the delivery of
health care at the same time. This explains why the
title of the HITECH Act contains the phrase “for
Economic and Clinical Health.”

The ARRA is a lengthy piece of legislation that is
organized into two major sections: Division A and
Division B. Each division contains several titles. Title
XIII of Division A of the ARRA is the HITECH Act. It
addresses the development, adoption, and
implementation of HIT policies and standards and
provides enhanced privacy and security protections
for patient information—an area of the law that is of
paramount concern in nursing informatics. Title IV of
Division B of the ARRA is considered part of the
HITECH Act. It addressed Medicare and Medicaid HIT
and provided significant financial incentives to
healthcare professionals and hospitals that adopted
and engaged in the “meaningful use” of electronic
health records (EHRs) technology.

At the time the HITECH Act was enacted, it was
estimated that less than 8% of U.S. hospitals used a
basic EHR system in at least one of their clinical units,
and less than 2% of U.S. hospitals had an EHR system
in all of their clinical settings (Ashish, 2009). Not

surprisingly, the cost of an EHR system has been a
major barrier to widespread adoption of this technology
in most healthcare facilities. The HITECH Act sought to
change that situation by providing each person in the
United States with an EHR. In addition, a nationwide
HIT infrastructure would be developed so that access
to a person’s EHR will be readily available to every
healthcare provider who treats the patient, no matter
where the patient may be located at the time treatment
is rendered. According to the Office of the National
Coordinator for Health Information Technology (2015),
three out of four hospitals now have at least a basic
EHR with clinician notes, and for larger acute care
hospitals, nearly 97% have EHR technology certified
by USDHHS.

Definitions
The HITECH Act includes some important definitions
that anyone involved in nursing informatics should
know:

“Certified EHR Technology”: An EHR that meets
specific governmental standards for the type of
record involved, whether it is an ambulatory EHR
used by office-based healthcare practitioners or an
inpatient EHR used by hospitals. The specific
standards that are to be met for any such EHRs are
set forth in federal regulations.

“Enterprise Integration”: The electronic linkage of
healthcare providers, health plans, the government,
and other interested parties to enable the electronic
exchange and use of health information among all
the components in the health care infrastructure.
“Healthcare Provider”: Hospitals, skilled nursing
facilities, nursing homes, long-term care facilities,
home health agencies, hemodialysis centers,
clinics, community mental health centers,
ambulatory surgery centers, group practices,
pharmacies and pharmacists, laboratories,
physicians, and therapists, among others.
“Health Information Technology” (HIT): “Hardware,
software, integrated technologies or related
licenses, intellectual property, upgrades, or
packaged solutions sold as services that are
designed for or support the use by healthcare
entities or patients for the electronic creation,
maintenance, access, or exchange of health
information.”
“Qualified Electronic Health Record”: “An
electronic record of health-related information on an
individual.” A “qualified” EHR contains a patient’s
demographic and clinical health information,
including the medical history and a list of health
problems, and is capable of providing support for
clinical decisions and entry of physician orders. It
must also have the capacity “to capture and query
information relevant to health care quality” and
“exchange electronic health information with, and

integrate such information from other sources”
(Readthestimulus.org, 2009, pp. 32–35).

Purposes
The HITECH Act established the Office of the
National Coordinator for Health Information
Technology (ONC) within the USDHHS. The ONC is
headed by the national coordinator, who is responsible
for overseeing the development of a nationwide HIT
infrastructure that supports the use and exchange of
information to achieve the following goals:

1. Improve healthcare quality by enhancing
coordination of services between and among the
various healthcare providers a patient may have,
fostering more appropriate healthcare decisions
at the time and place of delivery of services, and
preventing medical errors and advancing the
delivery of patient-centered care

2. Reduce the cost of health care by addressing
inefficiencies, such as duplication of services
within the healthcare delivery system, and by
reducing the number of medical errors

3. Improve people’s health by promoting
prevention, early detection, and management of
chronic diseases

4. Protect public health by fostering early detection
and rapid response to infectious diseases,
bioterrorism, and other situations that could have

a widespread impact on the health status of
many individuals

5. Facilitate clinical research
6. Reduce health disparities
7. Better secure patient health information

Improving healthcare quality has been an ongoing
challenge in the United States. According to the
Agency for Healthcare Research and Quality
(AHRQ), quality health care is care that is “safe, timely,
patient centered, efficient, and equitable” (AHRQ,
2009, p. 1). AHRQ, an agency within USDHHS, has
been releasing a national healthcare quality report
(NHQR) every year since 2003. Access the most
recent report at
www.ahrq.gov/research/findings/nhqrdr/index.html.
The NHQR emphasized the need for HIT to support the
goal of improving quality of care.

Providers need reliable information about
their performance to guide improvement
activities. Realistically, HIT infrastructure
is needed to ensure that relevant data are
collected regularly, systematically, and
unobtrusively while protecting patient
privacy and confidentiality…. Systems
need to generate information that can be
understood by end users and that are
interoperable across different institutions’
data platforms… Quality improvement

typically requires examining patterns of
care across panels of patients rather than
one patient at a time . . . Ideally,
performance measures should be
calculated automatically from health
records in a format that can be easily
shared and compared across all
providers involved with a patient’s care.
(AHRQ, 2009, p. 13)

The prevalence of healthcare-associated infections
serves as an excellent example of how use of EHR
technology and a nationwide HIT infrastructure can
play a significant role in addressing healthcare quality
issues. According to the NHQR, “wound infections are
a common occurrence following surgery, but hospitals
can reduce the risk of these health care–associated
infections by making sure patients receive an
appropriate antibiotic within an hour before their
procedures” (AHRQ, 2009, p. 110). The Centers for
Medicare and Medicaid Services (CMS) already has
the capacity to track Medicare patients who receive this
prophylactic treatment and the rate of postsurgical
wound infections for those patients who do and do not
receive the treatment. Imagine being able to track this
issue for all surgical patients and developing evidence-
based care plans to ensure that all patients within the
infrastructure receive the same quality of care. This is

just one of many examples in which the end result of
EHR adoption is better patient outcomes.

EHR technology also will make it easier for all
providers involved in a patient’s care to readily access
that patient’s complete and current healthcare record,
thereby allowing providers to make well-informed,
efficient, and effective decisions about a patient’s care
at the time those decisions need to be made. This is of
tremendous benefit to the patient and promotes a
higher level of patient-centered care. It also allows
effective coordination of care between and among all
providers involved in the patient’s care, including
doctors, nurses, therapists, nutritionists, hospitals,
nursing homes, rehabilitation facilities, home health
agencies, laboratories, and other diagnostic centers,
thereby assuring the continuum of patient care.

Such an integrated system would have clear benefits
for patients and providers alike. For example, imagine
how much easier it would be for a patient with a rare
form of cancer to obtain a second oncologist’s opinion
before beginning a course of treatment. The patient’s
complete record, including the results of numerous
diagnostic tests conducted at multiple sites, such as
blood tests, biopsies, radiographs, and scans, would
be readily available to the second oncologist. Imagine
how much easier it would be for a patient with end-
stage renal disease, who is receiving outpatient
hemodialysis several times a week, to receive

appropriate treatment if he or she is suddenly
hospitalized or would like to take a vacation out of
state. Imagine how much easier it would be for nurses
to complete a medication reconciliation for a newly
admitted patient. The possibilities are endless, and the
savings realized from enhancing quality, avoiding
duplication of services, and streamlining delivery of
patient care are obvious.

Reducing healthcare errors has been another ongoing
challenge in the United States. Healthcare providers
strive to meet the standard of care and avoid harm to
patients. Patients have a right to receive appropriate
care, but that does not always happen. Ten years ago,
the Institute of Medicine’s Committee on the Quality of
Health Care in America undertook a comprehensive
literature review and summarized the results of more
than 40 studies about healthcare errors in its seminal
report, To Err Is Human: Building a Safer Health
System (Institute of Medicine, 2000). That report
concluded that approximately 44,000–98,000 people in
the United States die each year as a result of
healthcare errors. Many thousands more who do not
die are seriously injured from such errors. In addition to
the human pain and suffering associated with
healthcare errors, the monetary costs of these errors
are substantial. Although some progress in reducing
healthcare errors has been made since the release of
To Err Is Human, substantial work remains to be done.
It is anticipated that a nationwide HIT infrastructure will

contribute to a reduction in healthcare errors by
providing mechanisms to assist with the prevention of
errors and to provide timely warnings of the possibility
of a repetitive error that may affect many patients.

Containing and reducing healthcare costs in the United
States, where more than $2 trillion is spent on health
care each year (Keehan, Sisko, & Truffler, 2008), is
another daunting challenge. Using EHR technology
and a nationwide HIT infrastructure to improve quality
and reduce errors within the healthcare delivery system
is one way to address this challenge. Imagine the
billions of dollars that could be saved just by reducing
the estimated 1.7 million cases of healthcare-
associated infections contracted by patients in U.S.
hospitals each year (AHRQ, 2009, p. 108).

Promoting prevention, early detection, and
management of chronic diseases is another purpose of
the HITECH Act. The delivery of health care in the
United States traditionally has been based on a
disease model rather than a wellness model. Having
an EHR for each individual could help with the
necessary transition as providers and their patients
become more aware of the variables that positively or
negatively impact health. The ability to identify
appropriate choices to promote wellness and either
prevent illness and injury or detect and manage chronic
diseases sooner will be enhanced.

Chronic diseases are of major concern to this country,
not only because of the impact they have on
individuals, but also because of the tremendous cost
associated with providing treatment for patients with
these conditions. Adult-onset diabetes, for example,
has reached epidemic proportions. A national HIT
infrastructure will help providers better identify those
patients who are at risk for developing this disease and
provide treatment strategies to avoid it. For those
patients who develop type 2 diabetes, their providers
will be able to diagnose the condition much sooner and
manage it more effectively because of the vast
resources that a national HIT infrastructure can
provide.

Improving public health is another purpose of the
HITECH Act. The recent Zika virus challenge is
illustrative of how a national HIT infrastructure can
protect public health by fostering early detection and
rapid response to infectious diseases, bioterrorism, and
other situations that could have a widespread impact
on the health status of many individuals and groups.

The impact that a national HIT infrastructure will have
on clinical research is self-evident. Once the
infrastructure becomes operational, the amount of data
that will become readily available for clinical research
will increase exponentially compared to what is
available today. The ability of researchers to conduct
studies and provide clinicians with the most current

evidence-based practice will be of tremendous benefit
to patients everywhere.

Reducing health disparities is another purpose of the
HITECH Act. According to the AHRQ (2013), “Health
care disparities are differences or gaps in the care
experienced by one population compared with another
population” (p. 1). Detailed information about
healthcare disparities can be found at the website for
the Office of Minority Health and Health Disparities at
www.cdc.gov/omhd. The AHRQ routinely examines
the issue of disparities in health care and reports its
findings to the public. The National Healthcare
Disparities Report of 2012 confirms that some
Americans continue to receive inferior care because of
such factors as race, ethnicity, and socioeconomic
status (AHRQ, 2013). This report found disparities in
the following areas:

Across all dimensions of healthcare quality:
Effectiveness, patient safety, timeliness, and patient
centeredness
Across all dimensions of access to care: Facilitators
and barriers to care and health care utilization
Across many levels and types of care: Preventive
care, treatment of acute conditions, and
management of chronic diseases
Across many clinical conditions: Cancer, diabetes,
end-stage renal disease, heart disease, HIV

disease, mental health and substance abuse, and
respiratory diseases
Across many care settings: Primary care, home
health care, hospice care, emergency department,
hospitals, and nursing homes
Within many subpopulations: Women, children,
older adults, residents of rural areas, and
individuals with disabilities and other special
healthcare needs (AHRQ, 2013, pp. H1–H4)

All patients, regardless of race, ethnicity, or
socioeconomic status, should receive care that is
effective, safe, and timely. When the national HIT
infrastructure contemplated by the HITECH Act is fully
implemented, such disparities are bound to decrease.
The ability to monitor for disparities and promote the
delivery of appropriate care to all patients will be
enhanced. Clinicians will be prompted to base their
treatments on appropriate factors and avoid biased
care.

Perhaps the most important task facing the national
coordinator during the development and
implementation of a nationwide HIT infrastructure is
ensuring the security of the patient health information
within that system. The ability to secure and protect
confidential patient information has always been of
paramount importance to clinicians, who view this
consideration as an ethical and legal obligation of
practice. Patients value their privacy and they have a

right to expect that their confidential health information
will be properly safeguarded. Nurses have been
complying with the regulatory requirements of HIPAA
for years, and the HITECH Act has enhanced the
security and privacy protections each patient has a
right to expect under HIPAA. The specific changes are
discussed in greater detail later in this chapter.

How a National HIT
Infrastructure Is Being
Developed
Developing a national HIT infrastructure is an
enormous and extremely complex undertaking that
requires extensive financial, technologic, and human
resources. The HITECH Act established the ONC, as
noted earlier, and the USDHHS appointed a national
coordinator, who is responsible for the development of
the infrastructure. The HITECH Act also established
two committees within the ONC: the HIT Policy
Committee and the HIT Standards Committee.

The Policy Committee is responsible for making
recommendations to the coordinator about how to
implement the requirements of the HITECH Act, such
as the technologies to use in the infrastructure. The
Policy Committee has a total of 20 members, one of
whom must be a member from a labor organization
and two of whom must be healthcare providers. At

least one of the healthcare providers must be a
physician. There is no specific requirement that a nurse
be on the Policy Committee. A complete list of the
Policy Committee members is available at
www.healthit.hhs.gov.

The Standards Committee is responsible for
recommending standards by which health information
is to be electronically exchanged. The HITECH Act
does not designate the number of members to be on
the committee; however, its members include
healthcare providers, ancillary healthcare workers,
consumers of health care, and others. Again, there is
no specific requirement that a nurse be on the
Standards Committee, and a complete list of the
Standards Committee members is available at
www.healthit.gov.

The HITECH Act also made provisions to include
meaningful public input in the development of a
national HIT infrastructure. Both the Policy Committee
and the Standards Committee hold public meetings,
and anyone interested in this process can participate. A
schedule of meetings, committee agendas, and the
transcripts of past meeting are posted at
www.healthit.gov.

The national coordinator has several duties. He or she
decides whether to endorse the recommendations of
the Policy and Standards Committees and acts as a

liaison among the committees and various federal
agencies involved in the process of developing a
national HIT infrastructure. He or she consults with
these other agencies, including the National Institute
of Standards and Technology, and along with those
agencies updates the Federal HIT Strategic Plan (U.S.
Department of Commerce, 2011). The initial Federal
HIT Strategic Plan was published in June 2008, before
the enactment of the HITECH Act, and the plan has
been updated frequently to reflect evolving IT
strategies. The most current plan can be accessed at
www.healthit.gov/policy-researchers-
implementers/health-it-strategic-planning.

The HITECH Act also provides significant monetary
incentives for providers who engaged in meaningful
use of HIT. “Meaningful use” was defined as “using
electronic health records (EHRs) in a meaningful
manner, which includes, but is not limited to
electronically capturing health information in a coded
format, using that information to track key clinical
conditions, communicating that information to help
coordinate care, and initiating the reporting of clinical
quality measures and public health information” (CMS,
2010, para. 3).

Monetary incentives are available to clinicians and
facilities that implement EHR systems that meet the
specific standards. Providers that fail to adopt such

systems within a specified time frame may be subject
to significant governmental penalties.

How the HITECH Act Changed
HIPAA

HIPAA Privacy and Security Rules
Nurses have been complying with HIPAA for years.
HIPAA was enacted by the federal government for
several purposes, including better portability of health
insurance as a worker moved from one job to another;
deterrence of fraud, abuse, and waste within the
healthcare delivery system; and simplification of the
administrative functions associated with the delivery of
health care, such as reimbursement claims sent to
Medicare and Medicaid. Simplification of administrative
functions entailed the adoption of electronic
transactions that included sensitive healthcare
information. To protect the privacy and security of
health information, two sets of federal regulations were
implemented. The Privacy Rule became effective in
2003, and the Security Rule became effective in 2005.
Many practitioners that refer to HIPAA are not referring
to the comprehensive federal statute enacted in 1996,
but rather to the Privacy Rule and the Security Rule—
that is, the federal regulations that were adopted years
after HIPAA became law.

Under the Privacy Rule, patients have a right to expect
privacy protections that limit the use and disclosure of
their health information. Under the Security Rule,
providers are obligated to safeguard their patients’
health information from improper use or disclosure,
maintain the integrity of the information, and ensure its
availability. Both rules apply to protected health
information (PHI), defined as any physical or mental
health information created, received, or stored by a
“covered entity” that can be used to identify an
individual patient, regardless of the form of the health
information (i.e., it can be electronic, handwritten, or
verbal) (Legal Information Institute [LII], 2013).
Covered entities include hospitals and other healthcare
providers that transmit any health information
electronically, as well as health insurance companies
and healthcare clearinghouses (LII, 2013).

Clinicians have become very knowledgeable about the
requirements of the Privacy and Security Rules. They
are familiar with their obligations to protect patient
information and the rights afforded to their patients
under these regulations. Patients are entitled to a
notice of privacy practices from their healthcare
provider. Inpatients are entitled to opt out of the
facility’s directory, thereby protecting disclosure of
information that they are even a patient in the facility.
Under certain circumstances, patients must authorize
disclosure of their PHI before it can be released by the
provider. Patients can request and obtain access to

their own healthcare records and may request that
corrections and additions be made to their records.
Providers must consider a patient’s request to amend a
healthcare record, but they are not required to make
such an amendment if the request is unwarranted.
Unauthorized access or use or any loss of healthcare
information must be disclosed to any patient affected
by the breach. Patients may request an accounting of
anyone who accessed their healthcare information, and
the provider is required to provide that information in a
timely manner. Finally, patients have a right to
complain if they perceive that the privacy or security of
their healthcare information has been compromised in
some way. Such complaints can be made directly to
the provider or to the Office of Civil Rights (OCR).

The OCR, which is part of the USDHHS, is responsible
for enforcing HIPAA. It provides significant information
and guidance to clinicians who must comply with the
Privacy and Security Rules. It has been tracking
complaints and investigating violations since 2003.
Guidance and information about the complaint process
and the violations that the OCR has handled are
available on its website at
www.healthit.gov/providers-professionals/model-
notices-privacy-practices. As an example, one such
violation involved a nurse practitioner who had
privileges within a healthcare system. She accessed
her ex-husband’s medical records without his
authorization by using the system-wide EHRs. A

complaint was filed and the OCR investigated the
matter. The OCR resolved the complaint with the
healthcare system. As part of this resolution, the
healthcare system curtailed the nurse practitioner’s
access to its EHRs and it required her to undergo
remedial training. In addition, it reported the nurse
practitioner to her professional board (USDHHS, Office
of Civil Rights, n.d.)

Many businesses are moving to enact a “bring your
own device” (BYOD) policy for employees. This policy,
which helps to streamline the lives of employees by
maintaining personal and business information on one
device, can also result in cost savings for the
organization overall. BYOD is an issue, however, when
dealing with PHI. Healthcare organizations typically do
not encourage use of personal devices for professional
matters, and in many instances they actually have
policies in place forbidding employees from using
personal devices in the workplace. According to HIT
Consultant (2013), approximately 50% of healthcare
organizations report that personal mobile devices can
be used to access the Internet within their facilities but
these devices are not given access to the
organization’s network. Typically, only devices that are
issued by the organization, secured, and routinely
audited are able to access to the network. Nurses must
exercise caution when bringing their personal devices
into the healthcare organization to ensure that they are
not violating any specifics of the BYOD policy.

Compliance with the Privacy and Security Rules is
mandatory for all covered entities, and the HITECH Act
extends compliance with these requirements directly to
other entities that are business associates of a covered
entity. Requirements include designation of privacy and
information security officials to protect health
information and appropriate handling of any
complaints. Sanctions must be imposed if a violation of
HIPAA occurs. The Privacy and Security Rules also
mandate that certain physical and technical safeguards
be implemented for PHI, and they require entities to
conduct periodic training of all staff to ensure
compliance with these safeguards. Most entities
adhere to industry standards and provide their
personnel with yearly training. In addition, entities are
to conduct regular audits to ensure compliance, and
any breaches in the privacy or security of PHI must be
remedied immediately. It is important to avoid a
security incident as such incidents trigger certain
notification requirements and may be associated with
monetary penalties.

The HITECH Act Enhanced HIPAA
Protections
The HITECH Act has had a significant impact on
HIPAA’s Privacy and Security Rules in the following
ways:

USDHHS is to provide annual guidance about how
to secure health information.
Notification requirements in the event of a breach in
the security of health information have been
enhanced.
HIPAA requirements now apply directly to any
business associates of a covered entity.
The rules that pertain to providing an accounting to
patients who want to know who accessed their
health information have changed.
Enforcement of HIPAA has been strengthened.

These measures are being implemented to provide
further assurance that health information will be
protected as the country transitions to a nationwide HIT
infrastructure. Several other organizations are also
involved in the privacy and security aspects of the HIT
infrastructure development (Box 8-1).

BOX 8-1 OTHER ORGANIZATIONS

ASSISTING HIPAA

Dee McGonigle, Kathleen Mastrian, and Nedra
Farcus

Several other organizations have been involved
in HIPAA implementation. The American
National Standards Institute (ANSI) X12N and
Health Level Seven (HL7) standards
organizations worked together to develop an

electronic standard for claims attachments to
recommend to USDHHS (Spencer &
Bushman, 2006, para. 2). ANSI (n.d.) was
founded in 1918 and has served as the
coordinator of the U.S. voluntary standards and
conformity assessment system (para. 1). ANSI
provides a forum where the private and public
sectors can cooperatively work together toward
the development of voluntary national
consensus standards and the related
compliance programs (para. 2). HL7 (n.d.) is
one of several ANSI-accredited standards-
developing organizations (SDOs) operating in
the healthcare arena (para. 1). It states that its
mission is to provide standards for
interoperability that improve care delivery,
optimize workflow, reduce ambiguity, and
enhance knowledge transfer among all
stakeholders, including healthcare providers,
government agencies, the vendor community,
fellow SDOs, and patients (para. 5).

HL7 was initially associated with HIPAA in 1996
through the creation of a claims attachments
special interest group charged with
standardizing the supplemental information
needed to support healthcare insurance and
other e-commerce transactions. The initial
deliverable of this group was six claim
attachments. This special interest group is

currently known as the Attachment Special
Interest Group. As the attachment projects
continue, they are slated to include skilled
nursing facilities, home health care,
preauthorization, and referrals.

The “Level Seven” in HL7’s name refers to the
highest level of the International Standards
Organization’s (ISO’s) communications model
for Open Systems Interconnection (OSI)
application level. The application level
addresses definition of the data to be
exchanged, the timing of the interchange, and
the communication of certain errors to the
application. The seventh level supports such
functions as security checks, participant
identification, availability checks, exchange
mechanism negotiations and, most importantly,
data exchange structuring (HL7, n.d., para. 5).

The OSI was an attempt to standardize
networking by the ISO. HL7 addresses the
distinct requirements of the systems in use in
hospitals and other facilities, is more concerned
with application than the other levels, and
considers user authentication and privacy
(Webopedia, 2008). The lower levels of OSI
address hardware, software, and data
reformatting.

HL7’s mission is supported through two
separate groups, the Extensible Markup
Language (XML) special interest group and the
structured documents technical committee. The
XML special interest group makes
recommendations on use of XML standards for
all of HL7’s platform- and vendor-independent
healthcare specifications (HL7, n.d., para. 21).
XML began as a simplified subset of the
standard generalized markup language; its
major purpose is to facilitate the exchange of
structured data across different information
systems, especially via the Internet. It is
considered an extensible language because it
permits users to define their own elements,
thereby supporting customization to enable
purpose-specific development. The structured
documents technical committee supports the
HL7 mission through development of structured
document standards for health care (para. 21).
HL7 also organizes, maintains, and sustains a
repository for the vocabulary terms used in its
messages to provide a shared, well-defined, and
unambiguous knowledge base of the meaning of
the data transferred.

ISO (2008a) is a network of the national
standards institutes of 157 countries. It includes
one member per country, and a central
secretariat in Geneva, Switzerland, coordinates

the system (para. 1). ISO is a nongovernmental
organization; its members are not delegations of
national governments (unlike the case in the
United Nations system). Nevertheless, ISO
occupies a special position between the public
and private sectors. On the one hand, many of
its member institutes are part of the
governmental structure of their countries or are
mandated by their government. On the other
hand, other members have their roots uniquely
in the private sector, having been set up by
national partnerships of industry associations
(ISO, 2008a, para. 2).

This placement enables ISO to become a
bridging organization where members can reach
agreement on solutions that meet both the
requirements of business and the broader needs
of society, consumers, and users. These
international agreements become standards that
use the prefix ISO followed by the number of the
standard. An example is the health informatics,
health cards, numbering system, and
registration procedure for issuer identifiers, ISO
20302:2006; it is designed to confirm, via a
numbering system and registration procedure,
the identities of both the healthcare application
provider and the health card holder so that
information may be exchanged by using cards
issued for healthcare service (ISO, 2008b, para.

12). ISO provides standards for interoperability
that improve care delivery, optimize workflow,
reduce ambiguity, and enhance knowledge
transfer among all of its stakeholders, including
healthcare providers, government agencies, the
vendor community, fellow SDOs, and patients.
The standards are used on a voluntary basis
because ISO has no power to force their
enactment.

All of the organizations described here have
guidelines, standards, and rules to help
healthcare entities collect, store, manipulate,
dispose of, and exchange secure PHI. Many
SDOs work to help develop standards. HIPAA
guarantees the security and privacy of health
information and curtails healthcare fraud and
abuse while enforcing standards for health
information.

UNITED STATES AND
BEYOND
Health care was not the only focus of U.S.
legislative acts. One often sees “GLBA” and
“SOX” when searching for information on
HIPAA. The Gramm-Leach-Bliley Act (GLBA)
is federal legislation in the United States to
control how financial institutions handle the
private information they collect from individuals.

The Sarbanes-Oxley Act (SOX) is legislation
put in place to protect shareholders and the
public from deceptive accounting practices in
organizations.

Privacy and data regulations are also being
established around the world. See a map of the
world depicting the laws of various countries at
this website:
www.dlapiperdataprotection.com/#handbook/world-
map-section. It is quite evident that privacy and
security have become global concerns.

Avoiding security incidents has become a paramount
concern for healthcare organizations and providers.
Providers must protect their information and prevent
unauthorized persons from accessing, using,
disclosing, changing, or destroying a patient’s health
information, or otherwise interfering with the operations
of a health information system, such as an EHR. To
facilitate a provider’s ability to do this, the HITECH Act
requires USDHHS to provide annual guidance to
secure health information. PHI can be secured or
unsecured. PHI is considered unsecured if the provider
does not follow the guidance provided by USDHHS for
implementing technologies and methodologies that
make PHI “unusable, unreadable, or indecipherable to
unauthorized individuals” (USDHHS, 2009). PHI can be
secured through encryption, shredding and other forms
of complete destruction, or electronic media sanitation.

Figure 8-3 depicts some common causes of PHI
vulnerabilities.

Figure 8-3 Vulnerability of Private Health Information

The distinction between secured and unsecured PHI is
important because providers that experience a breach
in the privacy or security of their PHI must adhere to
certain notification requirements depending on the type
of PHI affected by the breach. The HITECH Act
enhanced the breach notification requirements of
HIPAA. If the PHI is unsecured, the provider must take
certain steps to notify those individuals who have been
affected. Providers can avoid these onerous breach
notification requirements if the PHI is secured in
accordance with the specifications of USDHHS.

A breach is considered discovered as soon as an
employee other than the individual who committed the
breach knows or should have known of the breach,
such as unauthorized access or even an unsuccessful
attempt to access information. For example, if a nurse
knows that a colleague has accessed or attempted to
access the record of a patient for whom the colleague
is not providing care (e.g., the nurse practitioner who
accessed her ex-husband’s EHR, as discussed
previously), the nurse’s employer is deemed to have
discovered the breach as soon as the nurse learned of
it. The discovery of a breach triggers the beginning of
the time frame during which the provider must fulfill the
notification requirements. A provider must fulfill these
requirements within a reasonable period of time; under
no circumstances may a provider take more than 60
days from discovery of the breach. It is easy to
understand why providers require their employees to
report knowledge of such breaches immediately to the
privacy or information security officer. A provider’s
failure to adhere to the breach notification requirements
could result in OCR sanctions, including monetary
penalties.

Whenever a breach involves unsecured PHI, covered
entities are responsible for alerting each affected
individual by mail, or by e-mail if preferred by the
individual. If there is insufficient contact information for
10 or more patients, the provider is required to place
conspicuous postings on the home page of its website

or in major print or broadcast media (without identifying
patients). A toll-free telephone number must be
provided so that affected individuals can call for
information about the breach. For breaches involving
unsecured PHI of more than 500 individuals, a
prominent media outlet must also be notified. Notice
must be given to USDHHS as well, and USDHHS will
post the information on its public website (USDHHS,
2009). It is easy to see why providers would want to
avoid these requirements by making sure their PHI is
secured. Having to post such notices undermines the
trust that exists between healthcare providers and the
patients and communities they serve.

The HITECH Act has improved the privacy and security
of patient health information by applying the
requirements of HIPAA directly to the business
associates of covered entities. In the past, it was up to
the covered entity to enter into contracts with its
business associates to ensure compliance with HIPAA.
Now business associates are responsible for their own
compliance. An example of such a business associate
is a HIT company hired by a hospital to implement or
upgrade an EHR system. The technology company has
access to the hospital’s EHR system and must comply
with the HIPAA Privacy and Security Rules, just as
covered entities must comply with these rules. This
includes being subject to enforcement by the OCR for
any violations.

Existing accounting rules are enhanced under the
HITECH Act, giving patients the right to access their
EHR and receive an accounting of all disclosures.
Before the HITECH Act, HIPAA regulations provided an
exception to the accounting requirements. Providers
and other covered entities were not required to include
in the accounting any disclosures that were made to
facilitate treatment/payment/operations—treatment
of patients, the payment for services, or the operations
of the entity—a provision commonly known as the
“TPO exception.” This exception ended in January
2011 for providers that recently implemented new EHR
systems. For those providers with EHR systems that
were implemented before the HITECH Act, the TPO
exception ended in January 2014. It is easy to
understand why this exception has ended. As all
providers implement comprehensive EHR systems, it
will be very easy to generate an electronic record with
an accounting of anyone who accessed a patient’s
record.

Finally, the HITECH Act strengthens the enforcement
of HIPAA. USDHHS can conduct audits, which will be
even easier to accomplish once a nationwide HIT
infrastructure is in place. In addition, stiffer civil
monetary penalties (CMP) for violations of HIPAA
became effective as soon as the HITECH Act became
law in February 2009. CMPs are divided into three
tiers. A Tier 1 CMP, in which the covered entity had no
reason to know of a violation, is $100 per incident, up

to a cap of $25,000 per year. A Tier 2 CMP, in which
the covered entity had reasonable cause to know of a
violation, is $1,000 per incident, up to a cap of
$100,000 per year. A Tier 3 CMP, in which the covered
entity engaged in willful neglect that resulted in a
breach, is $10,000 per incident, up to a cap of
$250,000 per year. In addition, the HITECH Act gives
authority to impose an additional CMP of $50,000 to
$1.5 million if the covered entity does not properly
correct a violation. Criminal penalties also can be
imposed when warranted. It is imperative that providers
avoid these penalties.

Before enactment of the HITECH Act, the federal
government alone enforced HIPAA. Now, state
attorneys general can play a significant role in the
enforcement and prosecution of HIPAA violations.
Once the HITECH Act became law, state attorneys
general were authorized to pursue civil claims for
HIPAA violations and collect up to $25,000 plus
attorneys’ fees. As of 2012, individuals who are
damaged by such violations became eligible to share in
any monetary awards obtained by these state officials.

Implications for Nursing
Practice

Being Involved and Staying Informed

The development and implementation of a nationwide
EHR system holds great promise for nursing practice
and nursing informatics. The profession of nursing will
benefit from the many enhancements such an
infrastructure has to offer, including the ability to
improve the delivery of nursing care and the quality of
that care, the ability to make more efficient and timely
nursing care decisions for patients, the ability to avoid
errors that may harm patients, and the ability to
promote health and wellness for the patients whom
nurses serve. On a broader scale, nurse researchers
will have the ability to more readily access data that
can be used to continue to foster evidence-based
practice. The possibilities seem endless. For those who
devote their professional careers to nursing informatics
or plan to do so, the opportunities abound. Much work
remains to be done as this country transitions to a
nationwide HIT infrastructure, and moves beyond
meaningful use requirements.

All nurses need to be engaged in this process, whether
they treat patients, are managers within healthcare
organizations, teach, develop computer programs, or
help create institutional or governmental policies.
Nurses, as the end users of developing technologies,
cannot afford to be left behind in these exciting times.
Their voices must be heard, whether it is within the
facility where they work as changes to the EHR system
are contemplated, or whether it is in the public policy
arena. How often are nurses the last to know that a

new EHR system has been adopted by their hospital?
How many times have nurses been trained to use a
system that would have benefited from their input
before it was implemented or even purchased? Nurses
often are not invited to the table when entities make
decisions about informatics, so they should not be
afraid to ask to be included, whether it is to be heard
within the workplace or within the governmental
agencies that are overseeing the changes that are
taking place.

Even nurses who do not get involved in this process
need to stay current with the rapid changes that are
taking place. Information about federal initiatives is
available from the ONC and the OCR. Both offices are
housed within USDHHS and are excellent resources
for additional information about the HITECH Act and
HIPAA. Regulations to implement the HITECH Act and
enhance the HIPAA protections required by it are being
proposed and adopted at a rapid pace. See
www.healthit.gov to access the most current
information.

Protecting Yourself
Nurses who strive to protect the privacy and security of
patient information are protecting themselves from
ethical lapses and violations of law. The American
Nurses Association’s (ANA’s) Code of Ethics for
Nurses with Interpretive Statements mandates that

nurses protect a patient’s rights to privacy and
confidentiality.

Associated with the right to privacy, the nurse has a
duty to maintain confidentiality of all patient
information. Nurses who engage with social media
need to be especially cognizant of the potential for
breaching the confidentiality of patient information. Box
8-2 provides more information related to nurses’ use of
social media. Refer also to the ethical use of social
media discussed in Chapter 5. The patient’s well-being
could be jeopardized and the fundamental trust
between patient and nurse destroyed by unnecessary
access to data or by the inappropriate disclosure of
identifiable patient information. The rights, well-being,
and safety of the individual patient should be the
primary factors in arriving at any professional judgment
concerning the disposition of confidential information
received from or about the patient, whether oral,
written, or electronic. The standard of nursing practice
and the nurse’s responsibility to provide quality care
require that relevant data be shared with only those
members of the healthcare team who have a need to
know that information. Only information pertinent to a
patient’s treatment and welfare should be disclosed,
and only to those directly involved with the patient’s
care. When using electronic communications, special
effort should be made to maintain data security (ANA,
2010, p. 6).

BOX 8-2 USE OF SOCIAL NETWORKS

BY NURSES

Glenn Johnson and Jeff Swain

New opportunities to share information via social
networks have grabbed the headlines. Since
their inception in 2004, the growth in popularity
of social networking tools, such as Facebook
(www.facebook.com) and Twitter
(www.twitter.com), has been phenomenal. What
makes these sites so attractive? Web-based
applications, such as Facebook, allow users to
connect and share information in ways that were
not previously possible. Users develop online
profiles that contain information they select to
share with others. Using simple online utilities,
users can easily connect and share their
profiles, communicating with friends over the
Internet. Virtual groups of users with similar
profiles may be created, connecting users with
others who have similar interests. Twitter, a
micro-blogging platform, allows users to create
interpersonal networks for socializing, support,
and information sharing. The power of such
tools as Twitter lies in their being lightweight,
their limiting of updates to 140 or fewer
characters, and their convenience—users can
update their status from any device that has an

Internet connection or text messaging
capabilities.

The popularity of social and mobile networking
applications is one indication of how new Web-
based technologies are changing
communication preferences. The Web is no
longer a destination place, but instead has
become a vehicle of communication where
individuals use application software (“apps”),
which are installed or downloaded, to connect
with others. Individuals act as their own portal
and can connect from anywhere with their
various communities. This makes it difficult to
separate out various communities and social
networks. Where once it was relatively easy to
separate work relationships from friends and
family, networked communities tend to overlap,
blurring the boundaries between them. The
phenomenon of overlapping networks means
that the unintended audience is almost always
greater than the intended one. A status update
that may be construed as harmless and funny to
one’s friends could be taken an entirely different
way by family or colleagues. This is not to say
networked communities are harmful or bad.
Indeed, the benefits of such communities far
exceed their negatives. However, the immediacy
and the permanence of the updates shared
mean that the user must think about the impact

beyond the intended audience in ways never
before required (Johnson & Swain, 2011).

Nurses and other healthcare workers who use
social media must be aware that the overlapping
of networks may unintentionally create privacy
and confidentiality breaches. Even when
patients are not identified by name, general
sharing of information or venting about a difficult
day may constitute a privacy breach. The
National Council of State Boards of Nursing
(NCSBN, 2011) has collaborated with the ANA
to develop specific guidelines for the use of
social media by nurses. See
www.ncsbn.org/Social_Media.pdf to read a
white paper discussing common misconceptions
about social media, consequences for breaching
confidentiality using social media, guidelines for
appropriate use of social media, and case
scenarios with discussion.

REFERENCES

Johnson, G., & Swain, J. (2011).
Professional development and
collaboration tools. In D.
McGonigle & K. Mastrian (Eds.),
Nursing informatics and the
foundation of knowledge (2nd
ed., pp. 185–195). Burlington,
MA: Jones & Bartlett Learning.

National Council of State Boards of
Nursing. (2011). White paper: A
nurse’s guide to the use of social
media. Retrieved from
https://www.ncsbn.org/Social_Media.pdf

The similarities between these ethical obligations and
the legal requirements of HIPAA and other federal and
state privacy and confidentiality laws are readily
apparent to nurses. By complying with their ethical
code, nurses were complying with the Privacy and
Security Rules before they were required to do so.
Since the adoption of the HIPAA Privacy and Security
Rules, and now with the passage of the HITECH Act, it
is more important than ever for nurses to understand
their obligations in this area and avoid the pitfalls of
violations.

In addition to the sanctions imposed by the OCR,
violations can lead to disciplinary actions by employers
and professional licensing boards, as well as litigation.
Such actions can have a serious negative impact on
the nurse’s reputation and financial well-being. If a
nurse is terminated for invading a patient’s privacy or
breaching the confidentiality of a patient’s information,
some state laws require reporting the information to

prospective employers of the nurse; other laws require
reporting to the State Board of Nursing. State Boards
of Nursing have the authority to publicly discipline a
nurse who has engaged in professional misconduct by
invading a patient’s privacy, which includes
inappropriately accessing a patient’s EHR, and
breaching confidentiality of patient information, such as
allowing or tolerating unauthorized access to a
patient’s EHR. These types of situations can also
cause patients to file complaints with the OCR and
lawsuits against the offenders. Nurses must be ever
mindful of their obligations to report a breach in the
privacy or security of PHI to their employers, even if it
entails reporting a colleague.

Finally, some view the EHR as a convenient method for
employers to monitor the performance of its nurses.
Clearly, an EHR system provides a wealth of
information that can be, and often is required to be,
monitored. Audits are required to make sure that no
breaches in the system’s security occur. Audits are not
necessarily required to determine, for example, which
nurses are failing to complete the hospital’s
documentation requirements in a timely fashion, which
nurses are improperly altering (attempting to correct)
the record, or which nurses are dispensing more pain
medication than the average. Nurses have been
challenged by employers who allege failure to
document, improper or false documentation, and
suspected diversion of narcotics. These types of

situations are unsettling and may be on the rise as
more providers adopt or augment EHR systems. Thus
it behooves every nurse who works with such a system
to obtain proper training and to know the policies and
procedures that pertain to its use.

Social media can and should be used in an appropriate
manner by professionals to educate and promote
health behaviors in the clients they serve,
communicate with clients if they choose this method of
communication, and network with other professionals
by sharing information (deidentified) and knowledge.
As Gagnon and Sabus (2015) suggest, “the reach of
social media for health and wellness presents exciting
opportunities for the health care professional with a
well-executed social media presence. Social media
give health care providers a far-reaching platform on
which to contribute high-quality online content and
amplify positive and accurate health care information
and messages. It also provides a forum for correcting
misinformation and addressing misconceptions” (p.
410). They advocated for healthcare professionals to
practice digital professionalism, and for social media
use to be one of the professional competencies for
health professional education. Bazan (2015) suggested
that social media can be used to consult with other
healthcare providers, such as in a professional
Facebook group using direct private messaging
between the two providers, but cautioned that posting
to the main social site cannot contain any hint of PHI.

He also shared information about a progressive
practice that communicates with patients via private
messaging on Facebook. Remember that everything
you do electronically leaves a digital footprint! Proceed
with caution and be certain that your digital interactions
comply completely with professional ethics, laws, and
organizational policies.

Future Regulations
CMS recently released new legislation, the Medicare
Access and CHIP Reauthorization Act of 2015
(MACRA; USDHHS, 2016). Although this legislation
primarily affects provider payments, all members of the
healthcare team will have a hand in ensuring quality
care. The final implementation guidelines have yet to
be released, but this new legislation is expected to
replace the former CMS meaningful use guidelines. For
more information on this program, refer to the chapter
on Workflow and Meaningful Use.

The U.S. Food and Drug Administration (FDA), a
division of USDHHS, is responsible for regulating
medical devices to ensure public safety. In 2015, the
FDA released a guidance document for manufacturers,
developers, and FDA staff related to mobile medical
applications. At the current time, the most common
types of these applications, or apps, are not regulated
by the FDA because they are not defined as medical
devices. An app is defined as a medical device and

may be subject to regulation by the FDA if “the
intended use of a mobile app is for the diagnosis of a
disease or other conditions, or the cure, mitigation,
treatment, or prevention of disease, or if it is intended
to affect the structure or function of the body of man”
(FDA, 2015, p. 8). The guidance document also
provides a list of examples of apps that are not
currently viewed as medical devices, such as apps that
help users organize personal medical data, track
fitness, or self-manage a disease. If, however, the
mobile app is an accessory to a regulated medical
device, then it is also considered a medical device and
is subject to FDA oversight. We need to be aware that
as these mobile apps become more sophisticated in
the future, they may indeed be subject to more
stringent oversight by the FDA to ensure consumer
safety.

Summary
The HITECH Act and the HIPAA Privacy and Security
Rules are intended to enhance the rights of individuals.
These laws provide patients with greater access and
control over their PHI. They can control its uses,
dissemination, and disclosures. Covered entities must
establish not only a required level of security for PHI,
but also sanctions for employees who violate the
organization’s privacy policies and administrative
processes for responding to patient requests regarding
their information. Therefore, they must be able to track

the PHI, note access from the perspective of which
information was accessed and by whom, and identify
any disclosures. Finally, readers should recognize that
there is global awareness of the need for privacy
protections for personal information or PHI. Over the
next few years, international efforts will accelerate,
enhancing international data exchange.

THOUGHT-PROVOKING QUESTIONS

1. One of the largest problems with
healthcare information security has
always been inappropriate use by
authorized users. How do HIPAA and the
HITECH Act help to curb this problem?

2. How do you envision Health Level Seven,
HIPAA, and the HITECH Act evolving in
the next decade?

3. If you were the privacy officer in your
organization, how would you address the
following?
a. Tracking each point of access of the

patient’s database, including who
entered the data.

b. Encouraging employees to report
privacy and security breaches.

c. The healthcare professionals are using
smartphones, iPads, and other mobile
devices. How do you address privacy

when data can literally walk out of your
setting?

d. You observe one of the healthcare
professionals using his smartphone to
take pictures of a patient. He sees you
and says, in front of the patient, “I am
not capturing her face!” How do you
respond to this situation?

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SECTION III: Nursing
Informatics Administrative
Applications: Precare and
Care Support

Chapter 9 Systems Development Life Cycle:
Nursing Informatics and Organizational
Decision Making

Chapter 10 Administrative Information Systems

Chapter 11 The Human–Technology Interface

Chapter 12 Electronic Security

Chapter 13 Workflow and Beyond Meaningful
Use

Nursing informatics (NI) and information technology
(IT) have invaded nursing, and some nurses are happy
with the capabilities afforded by this specialty. Others,
however, remain convinced that the changes wrought
by IT are nothing more than a nuisance. In the past,
nursing administrators have found the implementation
of technology tools to be an expensive venture with
minimal rewards. This disappointment is likely related
to their lack of knowledge about NI, which caused
nursing administrators to listen to vendors or other

colleagues; in essence, it was decision making based
on limited and biased information. There were at least
two reasons for the experience of limited rewards.
First, nurses were rarely included in the testing and
implementation of products designed for nurses and
nursing tasks. Second, the new products they
purchased had to interface with old, legacy systems
that were not at all compatible or seemed compatible
until the glitches arose. These glitches caused
frustration for clinicians and administrators alike. They
purchased tools that should have made the nurses
happy, but instead all they did was grumble.

The good news is that approaches have changed as a
result of the difficult lessons learned from the early
forays into technology tools. Nursing personnel are
involved both at the agency level and at the vendor
level, in the decision-making process and development
of new systems and products charged with enhancing
the practice of nursing. Older legacy systems are being
replaced with newer systems that have more capacity
to interface with other systems. Nurses and
administrators have become more astute in the realm
of NI, but there is still a long way to go. The Systems
Development Life Cycle: Nursing Informatics and
Organizational Decision Making chapter introduces the
system development life cycle, which is used to make
important and appropriate organizational decisions for
technology adoption.

Administrators need information systems that facilitate
their administrative role, and they particularly need
systems that provide financial, risk management,
quality assurance, human resources, payroll, patient
registration, acuity, communication, and scheduling
functions. The administrator must be open to learning
about all of the tools available. One of the most
important tasks that an administrator can oversee and
engage in is data mining, or the extraction of data and
information from big data, sizeable datasets that have
been collected and warehoused. Data mining helps to
identify patterns in aggregate data, gain insights, and
ultimately discover and generate knowledge applicable
to nursing science. To take advantage of these
benefits, nursing administrators must become astute
informaticists—knowledge workers who harness the
information and knowledge at their fingertips to
facilitate the practice of their clinicians, improve patient
care, and advance the science of nursing.

Clinical information systems (CIS) have traditionally
been designed for use by one unit or department within
an institution. However, because clinicians working in
other areas of the organization need access to this
information, these data and information are generally
used by more than one area. The new initiatives arising
with the integration of the electronic health record place
institutions in the position of striving to manage their
CIS through the electronic health record. Currently,
there are many CISs, including nursing, laboratory,

pharmacy, monitoring, and order entry, plus additional
ancillary systems to meet the individual institutions’
needs. The Administrative Information Systems
chapter provides an overview of administrative
information systems and helps the reader to
understand the powerful data aggregation and data
mining tools afforded by these systems.

The Human–Technology Interface chapter discusses
the need to improve quality and safety outcomes
significantly in the United States. Through the use of IT,
the designs for human–technology interfaces can be
radically improved so that the technology better fits
both human and task requirements. A number of useful
tools are currently available for the analysis, design,
and evaluation phases of development life cycles and
should be used routinely by informatics professionals
to ensure that technology better fits both task and user
requirements. In this chapter, the authors stress that
the focus on interface improvement using these tools
has dramatically improved patient safety in a specific
area of health care: anesthesiology. With increased
attention from informatics professionals and engineers,
the same kinds of improvements are being made in
other areas. This human–technology interface is a
crucial area if the theories, architectures, and tools
provided by the building block sciences are to be
implemented.

Each organization must determine who can access and

use its information systems and provide robust tools for
securing information in a networked environment. The
Electronic Security chapter addresses the important
safeguards for protecting information. As new
technologies designed to improve inter-professional
collaboration and enhance patient care are adopted,
barriers to implementation and resistance by
practitioners to change are frequently encountered.
The Workflow and Beyond Meaningful Use chapter
provides insights into clinical workflow analysis and
provides advice on improving efficiency and
effectiveness while reviewing what we have learned as
we tried to achieve meaningful use of caring
technologies.

Pause to reflect on the Foundation of Knowledge
model (Figure III-1) and its relationship to both
personal and organizational knowledge management.
Consider that organizational decision making must be
driven by appropriate information and knowledge
developed in the organization and applied with wisdom.
Equally important to adopting technology within an
organization is the consideration of the knowledge
base and knowledge capabilities of the individuals
within that organization. Administrators must use the
system development life cycle wisely and carefully
consider organizational workflow as they adopt NI
technology for meaningful use.

Figure III-1 Foundation of Knowledge Model

Designed by Alicia Mastrian

The reader of this section is challenged to ask the
following questions: (1) How can I apply the knowledge
gained from my practice setting to benefit my patients
and enhance my practice?; (2) How can I help my
colleagues and patients understand and use the
current technology that is available?; and (3) How can I
use my wisdom to create the theories, tools, and
knowledge of the future?

CHAPTER 9: Systems
Development Life Cycle:
Nursing Informatics and
Organizational Decision
Making

Dee McGonigle and Kathleen Mastrian

Objectives
1. Describe the systems development life

cycle (SDLC).
2. Explore selected approaches to SDLC.
3. Assess interoperability and its importance

in addressing and meeting the challenges
of implementing the HITECH Act in
health care.

4. Reflect on the past to move forward into
the future to determine how new systems
will be developed, integrated, and made
interoperable in health care.

Key Terms
» Chief information officer

» Computer-aided software engineering

» Dynamic system development method

» End users

» Health management information
system

» Hospital information system

» Information technology

» Integration

» Interoperability

» Iteration

» Milestones

» MoSCoW

» Object-oriented systems development

» Open source software

» Prototype

» Rapid application development

» Rapid prototyping

» Repository

» Systems development life cycle

» TELOS strategy

» Waterfall model

Introduction
The following case scenario demonstrates the need to
have all of the stakeholders involved from the
beginning to the end of the systems development life
cycle (SDLC). Creating the right team to manage the
development is key. Various methodologies have been
developed to guide this process. This chapter reviews
the following approaches to SDLC: waterfall, rapid
prototyping or rapid application development (RAD),
object-oriented system development (OOSD), and
dynamic system development method (DSDM). When
reading about each approach, think about the case
scenario and how important it is to understand the
specific situational needs and the various
methodologies for bringing a system to life. As in this
case, it is generally necessary or beneficial to use a
hybrid approach that blends two or more models for a
robust development process.

As the case demonstrates, the process of developing
systems or SDLC is an ongoing development with a life

cycle. The first step in developing a system is to
understand the problems or business needs. It is
followed by understanding the solution or how to
address those needs; developing a plan; implementing
the plan; evaluating the implementation; and, finally,
maintenance, review, and destruction. If the system
needs major upgrading outside of the scope of the
maintenance phase, if it needs to be replaced because
of technological advances, or if the business needs
change, a new project is launched, the old system is
destroyed, and the life cycle begins anew.

SDLC is a way to deliver efficient and effective
information systems (ISs) that fit with the strategic
business plan of an organization. The business plan
stems from the mission of the organization. In the world
of health care, its development includes a needs
assessment for the entire organization, which should
include outreach linkages (as seen in the case
scenario) and partnerships and merged or shared
functions. The organization’s participating physicians
and other ancillary professionals and their offices are
included in thorough needs assessments. When
developing a strategic plan, the design must take into
account the existence of the organization within the
larger healthcare delivery system and assess the
various factors outside of the organization itself,
including technological, legislative, and environmental
issues that impact the organization. The plan must
identify the needs of the organization as a whole and

propose solutions to meet those needs or a way to
address the issues.

CASE SCENARIO

Envision two large healthcare facilities that
merge resources to better serve their
community. This merger is called the Wellness
Alliance, and its mission is to establish and
manage community health programming that
addresses the health needs of the rural,
underserved populations in the area. The
Wellness Alliance would like to establish pilot
clinical sites in five rural areas to promote
access and provide health care to these
underserved consumers. Each clinical site will
have a full-time program manager and three
part-time employees (a secretary, a nurse, and a
doctor). Each program manager will report to the
wellness program coordinator, a newly created
position within the Wellness Alliance.

Because you are a community health nurse with
extensive experience, you have been appointed
as the wellness program coordinator. Your
directive is to establish these clinical sites within
3 months and report back in 6 months as to the
following: (1) community health programs
offered, (2) level of community involvement in
outreach health programs and clinical site–

based programming, (3) consumer visits made
to the clinical site, and (4) personnel
performance.

You are excited and challenged, but soon reality
sets in: You know that you have five different
sites with five different program managers. You
need some way to gather the vital information
from each of them in a similar manner so that
the data are meaningful and useful to you as
you develop your reports and evaluate the
strengths and weaknesses of the pilot project.
You know that you need a system that will
handle all of the pilot project’s information
needs.

Your first stop is the chief information officer
of the health system, a nurse informaticist. You
know her from the health management
information system mini-seminar that she led.
After explaining your needs, you share with her
the constraint that this system must be in place
in 3 months when the sites are up and running
before you make your report. When she begins
to ask questions, you realize that you do not
know the answers. All you know is that you must
be able to report on which community health
programs were offered, track the level of
community involvement in outreach health
programs and clinical site–based programming,
monitor consumer visits made to the clinical site,

and monitor the performance of site personnel.
You know that you want accessible, real-time
tracking, but as far as programming and clinical
site–related activities are concerned, you do not
have a precise description of either the process
or procedures that will be involved in
implementing the pilot, or the means by which
they will gather and enter data.

The chief information officer requires that you
and each program manager remain involved in
the development process. She assigns an
information technology (IT) analyst to work
with you and your team in the development of a
system that will meet your current needs. After
the first meeting, your head is spinning: The IT
analyst has challenged your team not only to
work out the process for your immediate needs,
but also to envision what your needs will be in
the future. At the next meeting, you tell the
analyst that your team does not feel comfortable
trying to map everything out at this point. He
states that there are several ways to go about
building the system and software by using the
SDLC. Noticing the blank look on everyone’s
faces, he explains that the SDLC is a series of
actions used to develop an IS. The SDLC is
similar to the nursing process, in which the
nurse must assess, diagnose, plan, implement,
evaluate, and revise. If the plan developed in

this way does not meet the patient’s need or if a
new problem arises, the nurse either revises
and updates the plan or starts anew. Likewise,
you will plan, analyze, design, implement,
operate, support, and secure the proposed
community health system.

The SDLC is an iterative process—a conceptual
model that is used in project management
describing the phases involved in building or
developing an IS. It moves from assessing
feasibility or project initiation, to design analysis,
to system specification, to programming, to
testing, to implementation, to maintenance, and
to destruction—literally from beginning to end.
As the IT analyst describes this process, once
again he sees puzzled looks. He quickly states
that even the destruction of the system is
planned—that is, how it will be retired, broken
down, and replaced with a new system. Even
during upgrades, destruction tactics can be
invoked to secure the data and even decide if
servers are to be disposed of or repurposed.
The security people will tell you that this is their
phase, where they make sure that any sensitive
information is properly handled and decide
whether the data are to be securely and safely
archived or destroyed.

After reviewing all of the possible methods and
helping you to conduct your feasibility and

business study, the analyst chooses the DSDM.
This SDLC model was chosen because it works
well when the time span is short and the
requirements are fluctuating and mainly
unknown at the outset. The IT analyst explains
that this model works well on tight schedules
and is a highly iterative and incremental
approach that stresses continuous user input
and involvement. As part of this highly iterative
process, the team will revisit and loop through
the same development activities numerous
times; this repetitive examination provides ever-
increasing levels of detail, thereby improving
accuracy. The analyst explains that you will use
a mockup of the hospital information system
(HIS) and design for what is known; you will
then create your own mini-system that will
interface with the HIS. Because time is short,
the analysis, design, and development phases
will occur simultaneously while you are
formulating and revising your specific
requirements through the iterative process so
that they can be integrated into the system.

The functional model iteration phase will be
completed in 2 weeks based on the information
that you have given to the analyst. At that time,
the prototype will be reviewed by the team. The
IT analyst tells you to expect at least two or
more iterations of the prototype based on your

input. You should end with software that
provides some key capabilities. Design and
testing will occur in the design and build iteration
phase and continue until the system is ready for
implementation, the final phase. This DSDM
should work well because any previous phase
can be revisited and reworked through its
iterative process.

One month into the SDLC process, the IT
analyst tells the team that he will be leaving his
position at Wellness Alliance. He introduces his
replacement. She is new to Wellness Alliance
and is eager to work with the team. The initial IT
analyst will be there 1 more week to help the
new analyst with the transition. When he
explains that you are working through DSDM,
she looks a bit panicky and states that she has
never used this approach. She has used the
waterfall, prototyping, iterative enhancement,
spiral, and object-oriented methodologies—but
never the DSDM. From what she heard, DSDM
is new and often runs amok because of the lack
of understanding as to how to implement it
appropriately. After 1 week on the project, the
new IT analyst believes that this approach was
not the best choice. As the leader of this SDLC,
she is growing concerned about having a
product ready at the point when the clinical sites
open. She might combine another method to

create a hybrid approach with which she would
be more comfortable; she is thinking out loud
and has everyone very nervous.

The IT analyst reviews the equipment that has
arrived for the sites and is excited to learn that
the computers were ordered from Apple. They
will be powerful and versatile enough for your
needs.

Two months after the opening of the clinical
sites, you, as the wellness program coordinator
are still tweaking the system with the help of the
IT analyst. It is hard to believe how quickly the
team was able to get a robust system in place.
As you think back on the process, it seems so
long ago that you reviewed the HIS for
deficiencies and screen shots. You reexamined
your requirements and watched them come to
life through five prototype iterations and
constant security updates. You trained your
personnel on its use, tested its performance,
and made final adjustments before
implementation. Your own stand-alone system
that met your needs was installed and fully
operational on the Friday before you opened the
clinic doors on Monday, 1 day ahead of
schedule. You are continuing to evaluate and
modify the system, but that is how the SDLC
works: It is never finished, but rather constantly
evolving.

SDLC can occur within an organization, be outsourced,
or be a blend of the two approaches. With outsourcing,
the team hires an outside organization to carry out all
or some of the development. Developing systems that
truly meet business needs is not an easy task and is
quite complex. Therefore, it is common to run over
budget and miss milestones. When reading this
chapter, reflect on the case scenario and in general the
challenges teams face when developing systems.

Waterfall Model
The waterfall model is one of the oldest methods and
literally depicts a waterfall effect—that is, the output
from each previous phase flows into or becomes the
initial input for the next phase. This model is a
sequential development process in that there is one
pass through each component activity from conception
or feasibility through implementation in a linear order.
The deliverables for each phase result from the inputs
and any additional information that is gathered. There
is minimal or no iterative development where one takes
advantage of what was learned during the
development of earlier deliverables. Many projects are
broken down into six phases (Figure 9-1), especially
small- to medium-size projects.

Figure 9-1 Waterfall Phases

Feasibility
As the term implies, the feasibility study is used to
determine whether the project should be initiated and
supported. This study should generate a project plan
and estimated budget for the SDLC phases. Often, the
TELOS strategy—technological and systems,
economic, legal, operational, and schedule feasibility—
is followed. Technological and systems feasibility
addresses the issues of technological capabilities,
including the expertise and infrastructure to complete
the project. Economic feasibility is the cost–benefit
analysis, weighing the benefits versus the costs to
determine whether the project is fiscally possible and
worth undertaking. Formal assessments should include
return on investment. Legal feasibility assesses the
legal ramifications of the project, including current
contractual obligations, legislation, regulatory bodies,

and liabilities that could affect the project. Operational
feasibility determines how effective the project will be in
meeting the needs and expectations of the
organization and actually achieving the goals of the
project or addressing and solving the business
problem. Schedule feasibility assesses the viability of
the time frame, making sure it is a reasonable
estimation of the time and resources necessary for the
project to be developed in time to attain the benefits
and meet constraints. TELOS helps to provide a clear
picture of the feasibility of the project.

Analysis
During the analysis phase, the requirements for the
system are teased out from a detailed study of the
business needs of the organization. As part of this
analysis, work flows and business practices are
examined. It may be necessary to consider options for
changing the business process.

Design
The design phase focuses on high- and low-level
design and interface and data design. At the high-level
phase, the team establishes which programs are
needed and ascertains how they will interact. At the
low-level phase, team members explore how the
individual programs will actually work. The interface
design determines what the look and feel will be or

what the interfaces will look like. During data design,
the team critically thinks about and verifies which data
are required or essential.

The analysis and design phases are vital in the
development cycle, and great care is taken during
these phases to ensure that the software’s overall
configuration is defined properly. Mockups or
prototypes of screenshots, reports, and processes may
be generated to clarify the requirements and get the
team or stakeholders on the same page, limiting the
occurrence of glitches that might result in costly
software development revisions later in the project.

Implement
During this phase, the designs are brought to life
through programming code. The right programming
language, such as C++, Pascal, Java, and so forth, is
chosen based on the application requirements.

Test
The testing is generally broken down into five layers:
(1) the individual programming modules, (2)
integration, (3) volume, (4) the system as a whole,
and (5) beta testing. Typically, the programs are
developed in a modular fashion, and these individual
modules are then subjected to detailed testing. The
separate modules are subsequently synthesized, and

the interfaces between the modules are tested. The
system is evaluated with respect to its platform and the
expected amount or volume of data. It is then tested as
a complete system by the team. Finally, to determine if
the system performs appropriately for the user, it is
beta tested. During beta testing, users put the new
system through its paces to make sure that it does
what they need it to do to perform their jobs.

Maintain
Once the system has been finalized from the testing
phase, it must be maintained. This could include user
support through actual software changes necessitated
through use or time.

According to Isaias and Issa (2015), “one common trait
covers all the variations of this model: It is a sequential
model. Each of its stages must be entirely concluded
before the next can begin” (p. 23). The main lack of
iterative development is seen as a major weakness,
according to Purcell (2007). No projects are static, and
typically changes occur during the SDLC. As
requirements change, there is no way to address them
formally using the waterfall method after project
requirements are developed. The waterfall model
should be used for simple projects when the
requirements are well known and stable from the
outset.

Rapid Prototyping or Rapid
Application Development
As technology advances and faster development is
expected, rapid prototyping, also known as rapid
application development (RAD), provides a fast way
to add functionality through prototyping and user
testing. It is easier for users to examine an actual
prototype rather than documentation. A rapid
requirements-gathering phase relies on workshops and
focus groups to build a prototype application using real
data. This prototype is then beta tested with users, and
their feedback is used to perfect or add functionality
and capabilities to the system (Figure 9-2).

Figure 9-2 Rapid Application Development (RAD) or
Rapid Prototyping

According to Alexandrou (2016), “RAD (rapid
application development) proposes that products can
be developed faster and of higher quality” (para. 1).
The RAD approach uses informal communication,

repurposes components, and typically follows a fast-
paced schedule. Object-oriented programming using
such languages as C++ and Java promotes software
repurposing and reuse.

The major advantage is the speed with which the
system can be deployed; a working, usable system can
be built within 3 months. The use of prototyping allows
the developers to skip steps in the SDLC process in
favor of getting a mockup in front of the user. At times,
the system may be deemed acceptable if it meets a
predefined minimum set of requirements rather than all
of the identified requirements. This rapid deployment
also limits the project’s exposure to change elements.
Unfortunately, the fast pace can be its biggest
disadvantage in some cases. Once one is locked into a
tight development schedule, the process may be too
fast for adequate testing to be put in place and
completed. The most dangerous lack of testing is in the
realm of security.

The RAD approach is chosen because it builds
systems quickly through user-driven prototyping and
adherence to quick, strict delivery milestones. This
approach continues to be refined and honed, and other
contemporary manifestations of RAD continue to
emerge in the agile software development realm.

Object-Oriented Systems

Development
The object-oriented systems development model
blends SDLC logic with object-oriented modeling and
programming power (Stair & Reynolds, 2016). Object-
oriented modeling makes an effort to represent real-
world objects by modeling the real-world entities or
things (e.g., clinic, patient, account, nursing or
healthcare professional) into abstract computer
software objects. Once the system is object oriented,
all of the interactions or exchanges take place between
or among the objects. The objects are derived from
classes, and each object is comprised of data and the
actions that can be enacted on that data. Class
hierarchy allows objects to inherit characteristics or
attributes from parent classes, which fosters object
reuse, resulting in less coding. The object-oriented
programming languages, such as C++ and Java,
promote software repurposing and reuse. Therefore,
the class hierarchy must be clearly and appropriately
designed to reap the benefits of this SDLC approach,
which uses object-oriented programming to support the
interactions of objects.

For example, in the case scenario, a system could be
developed for the Wellness Alliance to manage the
community health programming for the clinic system
being set up for outreach. There could be a class of
programs, and well-baby care could be an object in the
class of programs; programs is a relationship between

Wellness Alliance and well-baby care. The program
class has attributes, such as clinic site, location
address, or attendees or patients. The relationship
itself may be considered an object having attributes,
such as pediatric programs. The class hierarchy from
which all of the system objects are created with
resultant object interactions must be clearly defined.

The OOSD model is a highly iterative approach. The
process begins by investigating where object-oriented
solutions can address business problems or needs,
determining user requirements, designing the system,
programming or modifying object modeling (class
hierarchy and objects), implementing, user testing,
modifying, and reimplementing the system, and ends
with the new system being reviewed regularly at
established intervals and modifications being made as
needed throughout its life.

Dynamic System Development
Method
The dynamic system development method is a
highly iterative and incremental approach with a high
level of user input and involvement. The iterative
process requires repetitive examination that enhances
detail and improves accuracy. The DSDM has three
phases: (1) preproject, (2) project life cycle (feasibility
and business tudies, functional model iteration, design

and build iteration, and implementation), and (3)
postproject.

In the preproject phase, buy-in or commitment is
established and funding is secured. This helps to
identify the stakeholders (administration and end
users) and gain support for the project. In the second
phase, the project’s life cycle begins. This phase
includes five steps: (1) feasibility, (2) business studies,
(3) functional model iteration, (4) design and build
iteration, and (5) implementation (Figure 9-3).

Figure 9-3 Dynamic System Development Method
(DSDM)

Copyright 2014 Agile Business Consortium Limited. Reproduced by kind

permission.

In steps 1 and 2, the feasibility and business studies
are completed. The team ascertains if this project
meets the required business needs while identifying
the potential risks during the feasibility study. In step 1,
the deliverables are a feasibility report, project plan,
and a risk log. Once the project is deemed feasible,
step 2, the business study, is begun. The business
study extends the feasibility report by examining the
processes, stakeholders, and their needs. It is
important to align the stakeholders with the project and
secure their buy-in because it is necessary to have
user input and involvement throughout the entire
DSDM process. Therefore, bringing them in at the
beginning of the project is imperative.

Using the MoSCoW approach, the team works with the
stakeholders to develop a prioritized requirements list
and a development plan. MoSCoW stands for “Must
have, Should have, Could have, and Would have.” The
“must have” requirements are needed to meet the
business needs and are critical to the success of the
project. “Should have” requirements are those that
would be great to have if possible, but the success of
the project does not depend on them being addressed.
The “could have” requirements are those that would be
nice to have met, and the “would have” requirements
can be put off until later; these may be undertaken
during future developmental iterations. Timeboxing is
generally used to develop the project plan. In
timeboxing, the project is divided into sections, each

having its own fixed budget and dates or milestones for
deliverables. The MoSCoW approach is then used to
prioritize the requirements within each section; the
requirements are the only variables because the
schedule and budget are set. If a project is running out
of time or money, the team can easily omit the
requirements that have been identified as the lowest
priority to meet their schedule and budget obligations.
This does not mean that the final deliverable, the actual
system, would be flawed or incomplete. Instead,
because the team has already determined the “must
have” or “should have” items, it still meets the business
needs. According to Haughey (2010), the 80/20 rule, or
Pareto principle, can be applied to nearly everything.
The Pareto principle states that 80% of the project
comes from 20% of the system requirements;
therefore, the 20% of requirements must be the crucial
requirements or those with the highest priority. One
also must consider the pancake principle: The first
pancake is not as good as the rest, and one should
know that the first development will not be perfect. This
is why it is extremely important to clearly identify the
“must have” and “should have” requirements.

In the third step of the project life cycle phase, known
as functional model iteration, the deliverables are a
functional model and prototype ready for user testing.
Once the requirements are identified, the next step is
to translate them into a functional model with a
functioning prototype that can be evaluated by users.

This could take several iterations to develop the
desired functionality and incorporate the users’ input.
At this stage, the team should examine the quality of
the product and revise the list requirements and risk
log. The requirements are adjusted, the ones that have
been realized are deleted, and the remaining
requirements are prioritized. The risk log is revised
based on the risk analysis completed during and after
prototype development.

The design and build iteration step focuses on
integrating functional components and identifying the
nonfunctional requirements that need to be in the
tested system. Testing is crucial; the team will develop
a system that the end users can safely use on a daily
basis. The team will garner user feedback and
generate user documentation. These efforts provide
this step’s deliverable, a tested system with
documentation for the next and final phase of the
development process.

In the final step of the project life cycle phase, known
as implementation, deliverables are the system (ready
to use), documentation, and trained users. The
requirements list should be satisfied, along with the
users’ needs. Training users and implementing the
approved system is the first part of this phase, and the
final part consists of a full review. It is important to
review the impact of the system on the business
processes and to determine if it addressed the goals or

requirements established at the beginning of the
project. This final review determines if the project is
completed or if further development is necessary. If
further development is needed, preceding phases are
revisited. If the project is complete and satisfies the
users, then it moves into maintenance and ongoing
development.

The final phase is labeled “postproject.” In this phase,
the team verifies that the system is functioning
properly. Once verified, the maintenance schedule is
begun. Because the DSDM is iterative, this postproject
phase is seen as ongoing development and any of the
deliverables can be refined. This is what makes the
DSDM such an iterative development process.

DSDM is one of an increasing number of agile
methodologies being introduced, such as Scrum and
Extreme Programming. These new approaches
address the organizational, managerial, and
interpersonal communication issues that often bog
down SDLC projects. Empowerment of teams and user
involvement enhance the iterative and programming
strengths provided in these SDLC models.

Computer-Aided Software
Engineering Tools

When reviewing SDLC, the computer-aided software
engineering (CASE) tools that will be used must be
described.

CASE tools promote adherence to the SDLC process
since they automate several required tasks; this
provides standardization and thoroughness to the total
systems development method (Stair & Reynolds,
2016). These tools help to reduce cost and
development time while enriching the quality of the
product. CASE tools contain a repository with
information about the system: models, data definitions,
and references linking models together. They are
valuable in their ability to make sure the models follow
diagramming rules and are consistent and complete.

The various types of tools can be referred to as upper-
CASE tools or lower-CASE tools. The upper-CASE
tools support the analysis and design phases, whereas
the lower-CASE tools support implementation. The
tools can also be general or specific in nature, with the
specific tools being designed for a particular
methodology.

Two examples of CASE tools are Visible Analyst and
Rational Rose. According to Andoh-Baidoo, Kunene,
and Walker (2009), Visible Analyst “supports structured
and object-oriented design (UML),” whereas Rational
Rose “supports solely object-oriented design (UML)”
(p. 372). Both tools can “build and reverse database

schemas for SQL and Oracle” and “support code
generation for pre-.NET versions of Visual Basic” (p.
372). Visible Analyst can also support shell code
generation for pre-.NET versions of C and COBOL,
whereas Rational Rose can support complete code for
C++ and Java. In addition, Andoh-Baidoo et al. found
that Rational Rose “[p]rovides good integration with
Java, and incorporates common packages into class
diagrams and decompositions through classes” (p.
372).

CASE tools have many advantages, including
decreasing development time and producing more
flexible systems. On the down side, they can be difficult
to tailor or customize and use with existing systems.

Open Source Software and
Free/Open Source Software
Another area that must be discussed with SDLC is
open source software (OSS). An examination of job
descriptions or advertisements for candidates shows
that many ISs and IT professionals need a thorough
understanding of SDLC and OSS development tools
(e.g., PHP, MySQL, and HTML). With OSS, any
programmer can implement, modify, apply, reconstruct,
and restructure the rich libraries of source codes
available from proven, well-tested products.

As Karopka, Schmuhl, and Demski (2014) noted,

Free/Libre Open Source Software
(FLOSS) has been successfully adopted
across a wide range of different areas
and has opened new ways of value
creation. Today there are hundreds of
examples of successful FLOSS projects
and products. . . . Especially in times of
financial crisis and austerity the adoption
of FLOSS principles opens interesting
alternatives and options to tremendously
lower total cost of ownership (TCO) and
open the way for a continuous user-
driven improvement process. (para. 6)

To transform health care, it is necessary for clinicians
to use information systems that can share patient data
(Goulde & Brown, 2006; NORC, 2014). This all
sounds terrific and many people wonder why it has not
happened yet, but the challenges are many. How does
one establish the networks necessary to share data
between and among all healthcare facilities easily and
securely? “Healthcare IT is beginning to adopt open
source software to address these challenges” (Goulde
& Brown, p. 4). Early attempts at OSS ventures in the
healthcare realm failed because of a lack of support or
buy-in for sustained effort, technologic lags, authority
and credibility, and other such issues. “Spurred by a

greater sense of urgency to adopt IT, health industry
leaders are showing renewed interest in open source
solutions” (Goulde & Brown, p. 5).

Karopka et al., (2014) concluded that

North America has the longest tradition in
applying FLOSS-HC delivery. It is home
of many mature, stable and widely
disseminated FLOSS applications. Some
of them are even used on a global scale.
The deployment of FLOSS systems in
healthcare delivery is comparatively low
in Europe. (para. 48)

Health care is realizing the benefits of FLOSS.
According to Goulde and Brown (2006), “other benefits
of open source software—low cost, flexibility,
opportunities to innovate—are important but
independence from vendors is the most relevant for
health care” (p. 10).

Interoperability
Interoperability, the ability to share information across
organizations, will remain paramount under the
HITECH Act. The ability to share patient data is
extremely important, both within an organization and
across organizational boundaries (Figure 9-4).

Figure 9-4 Interoperability

According to the Health Information and Management
Systems Society (HIMSS; Murphy, 2015), “an
acceptable 2015 [interoperability standards] Advisory
and more complete 2016 Advisory will not be
achievable without the inclusion of health IT security
standards” (para. 4). Few healthcare systems take
advantage of the full potential of the current state of the
art in computer science and health informatics (HIMSS,
2010). The consequences of this situation include a
drain on financial resources from the economy, the
inability to truly mitigate the occurrence of medical

errors, and a lack of national preparedness to respond
to natural and manmade epidemics and disasters.
HIMSS has created the Integration and Interoperability
Steering Committee to guide the industry on allocating
resources to develop and implement standards and
technology needed to achieve interoperability (para. 2).

As we enter into SDLCs, we must be aware of how this
type of development will affect both our own healthcare
organization and the healthcare delivery system as a
whole. In an ideal world, we would all work together to
create systems that are integrated within our own
organization while having the interoperability to cross
organizational boundaries and unite the healthcare
delivery system to realize the common goal of
improving the quality of care provided to consumers.

Summary
At times during the SDLC, new information affects the
outputs from earlier phases; the development effort
may be reexamined or halted until these modifications
can be reconciled with the current design and scope of
the project. At other times, teams are overwhelmed
with new ideas from the iterative SDLC process that
result in new capabilities or features that exceed the
initial scope of the project. Astute team leaders will
preserve these ideas or initiatives so they can be
considered at a later time. The team should develop a
list of recommendations to improve the current

software when the project is complete. This iterative
and dynamic exchange makes the SDLC robust.

As technology and research continue to advance, new
SDLC models are being pioneered and revised to
enhance development techniques. The interpretation
and implementation of any model selected reflect the
knowledge and skill of the team applying the model.
The success of the project is often directly related to
the quality of the organizational decision making
throughout the project—that is, how well the plan was
followed and documented. United efforts to create
systems that are integrated and interoperable will
define the future of health care.

THOUGHT-PROVOKING QUESTIONS

1. Reflect on the SDLC in relation to the
quality of the organizational decision
making throughout the project. What are
some of the major stumbling blocks faced
by healthcare organizations?

2. Why is it important for all nurses and
healthcare professionals to understand
the basics of how information systems are
selected and implemented?

References

Alexandrou, M. (2016). Rapid application
development (RAD) methodology.
Infolific. Retrieved from
http://www.infolific.com/technology/methodologies/rapid-
application-development

Andoh-Baidoo, F., Kunene, K., & Walker,
R. (2009). An evaluation of CASE tools
as pedagogical aids in software
development courses. 2009 SWDSI
Proceedings. Retrieved from
http://www.swdsi.org/swdsi2009/Papers/9K10.pdf

Goulde, M., & Brown, E. (2006). Open
source software: A primer for health
care leaders. Protocode. Retrieved
from http://www.protecode.com/an-
open-source-world-a-primer-on-
licenses-obligations-and-your-
company

Haughey, D. (2010). Pareto analysis step
by step. Project Smart. Retrieved from
http://www.projectsmart.co.uk/pareto-
analysis-step-by-step.html

Health Information and Management
Systems Society (HIMSS). (2010).
Interoperability & standards. Retrieved
from
http://www.himss.org/library/interoperability-
standards?navItemNumber=13323

Isaias, P. & Issa, T. (2015). High level
models and methodologies for
information systems. New York, NY:
Springer.

Karopka, T., Schmuhl, H., & Demski, H.
(2014). Free/Libre open source
software in health care: A review.
Healthcare Informatics Research,
20(1), 11–22. PMCID: PMC3950260

Murphy, K. (2007). HIMSS has ideas for
2015 interoperability standards
advisory. HealthIT Interoperability.
Retrieved from
http://healthitinteroperability.com/news/himss-
has-ideas-for-2015-interoperability-
standards-advisory

NORC. (2014). Data sharing to enable
clinical transformation at the
community level: IT takes a village.
Retrieved from
http://www.healthit.gov/sites/default/files/beacondatasharingbrief062014.pdf

Purcell, J. (2007). Comparison of software
development lifecycle methodologies.
SANS Institute. Retrieved from
https://software-
security.sans.org/resources/paper/cissp/comparison-
software-development-lifecycle-
methodologies

Stair, R., & Reynolds, G. (2016).
Principles of information systems (12th
ed.). Boston, MA: Cengage Learning.

CHAPTER 10:
Administrative
Information Systems

Marianela Zytkowski, Susan Paschke, Kathleen
Mastrian, and Dee McGonigle

Objectives
1. Explore agency-based health information

systems.
2. Evaluate how administrators use core

business systems in their practice.
3. Assess the function and information

output from selected information systems
used in healthcare organizations.

Key Terms
» Acuity systems

» Admission, discharge, and transfer
systems

» American National Standards Institute
(ANSI)

» Attribute

» Care plan

» Case management information systems

» Clinical documentation systems

» Clinical information systems

» Collaboration

» Columns

» Communication systems

» Computerized physician (provider)
order entry systems

» Core business systems

» Data dictionary

» Data file

» Data mart

» Data mining

» Data warehouse

» Database

» Database management system

» Decision support

» Drill-down

» Electronic health record

» Entity

» Entity–relationship diagram

» Fields

» Financial systems

» Information systems

» Information technology

» International Organization for
Standardization (ISO)

» Interoperability

» Key field

» Knowledge exchange

» Laboratory information systems

» Managed care information systems

» Order entry systems

» Patient care information system

» Patient care support system

» Patient centered

» Pharmacy information systems

» Picture and archiving communication
system

» Primary key

» Query

» Radiology information system

» Records

» Relational database management
system (RDMS)

» Repository

» Rows

» Scheduling systems

» Stakeholders

» Standardized plan of care

» Structured Query Language (SQL)

» Table

» Tiering

» Triage

» Tuples

Introduction
To compete in the ever-changing healthcare arena,
organizations require quick and immediate access to a
variety of types of information, data, and bodies of
knowledge for daily clinical, operational, financial, and
human resource activities. Information is continuously
shared between units and departments within
healthcare organizations and is also required or
requested from other healthcare organizations,
regulatory and government agencies, educational and
philanthropic institutions, and consumers.
Organizations need interoperable systems that are
accessible for data storage and retrieval.

The healthcare context is distinct from other
organizations that use information systems.

Fichman, Kohli, and Krishnan (2011) identify six
important elements of health care that influence the
development and implementation of information
systems:

The stakes are life and death.
Healthcare information is highly personal.
Health care is highly influenced by regulation and
competition.
Health care is professionally driven and
hierarchical.
Health care is multidisciplinary.

Healthcare information system implementation is
complex, with important implications for learning
and adaptation (pp. 420–423).

Healthcare organizations integrate a variety of clinical
and administrative types of information systems
(ISs). These systems collect, process, and distribute
patient-centered data to aid in managing and providing
care. Together, they create a comprehensive record of
the patient’s medical history and support organizational
processes. Each of these systems is unique in the way
it functions and provides information to clinicians and
administrators. An understanding of how each of these
types of systems works within healthcare organizations
is fundamental in the study of informatics. This chapter
will focus on the administrative organizational systems.

Types of Healthcare
Organization Information
Systems

Case Management Information
Systems
Case management information systems identify
resources, patterns, and variances in care to prevent
costly complications related to chronic conditions and
to enhance the overall outcomes for patients with

chronic illness. These systems span past episodes of
treatment and search for trends among the records.
Once a trend is identified, case management systems
provide decision support promoting preventive care.
Care plans are a common tool found in case
management systems. A care plan is a set of care
guidelines that outline the course of treatment and the
recommended interventions that should be
implemented to achieve optimal results. By using a
standardized plan of care, these systems present
clinicians with treatment protocols to maximize patient
outcomes and support best practices. Information
technology in health care is positioned to support the
development of interdisciplinary care plans. In the
health informatics pathway, Standard 5 deals with
documentation: “Health informatics professionals will
understand the content and diverse uses of health
information. They will accurately document and
communicate appropriate information using legal and
regulatory processes” (National Consortium for
Health Science Education, 2012, para. 11).

Case management information systems are especially
beneficial for patient populations with a high cost of
care and complex health needs, such as the elderly or
patients with chronic disease conditions. Avoiding
complications requires identifying the right resources
for care and implementing preventive treatments
across all medical visits. Ultimately, this preventive
care decreases the costs of care for patients with

chronic illnesses and supports a better quality of life.
Such systems increase the value of individual care
while controlling the costs and risks associated with
long-term health care.

Case management systems are increasingly being
integrated with electronic health records (EHRs).
Information collected by these systems is processed in
a way that helps to reduce risks, ensure quality, and
decrease costs. A presentation of results of the 2012
Health Information Technology Survey, conducted by
the Case Management Society of America (CMSA,
2014), revealed several key trends in information
technology, including the increased use of social media
and wireless communications, the use of IT to support
care transitions and prevent readmissions, expanded
use of patient engagement technologies (text
messaging, email, portals, smartphone apps), and
work toward the integration of case management
software into the EHR.

Communication Systems
Communication systems promote interaction among
healthcare providers and between providers and
patients. Such systems have historically been kept
separate from other types of health information
systems and from one another. Healthcare
professionals overwhelmingly recognize the value of
these systems, however, so they are now more

commonly integrated into the design of other types of
systems as a newly developing standard within the
industry. Examples of communication systems include
call light systems, wireless telephones, pagers, email,
and instant messaging, which have traditionally been
forms of communication targeted at clinicians. Other
communication systems target patients and their
families. Some patients are now able to access their
electronic chart from home via an Internet connection.
They can update their own medical record to inform
their physician of changes to their health or personal
practices that impact their physical condition. Inpatients
in hospital settings also receive communication directly
to their room. Patients and their families may, for
example, review individualized messages with
scheduled tests and procedures for the day and
confirm menu choices for their meals. These types of
systems may also communicate educational
messages, such as smoking cessation advice.

As health care begins to introduce more of this
technology into practice, the value of having
communication tools integrated with other types of
systems is being widely recognized. Integrating
communication systems with clinical applications
provides a real-time approach that facilitates
interactions among the entire healthcare team,
patients, and their families to enhance care. These
systems enhance the flow of communication within an
organization and promote an exchange of information

to care better for patients. The next generation of
communication systems will be integrated with other
types of healthcare systems and guaranteed to work
together smoothly. The Research Brief discusses the
economic impact of communication inefficiencies in
U.S. hospitals. As hospitals and physician practices
strive to become more patient centered,
communication technologies will be an integral part of
this goal. Many of us have experienced the anxiety of
waiting for news about a loved one during a surgical
procedure. Newer communication techniques, such as
surgical tracking boards that communicate about the
process, help to ease these anxieties. Gordon and
colleagues (2015) report high patient and family
satisfaction with a HIPAA-compliant surgical instant
messaging system to communicate real-time surgical
progress with patient-designated recipients. They
stated that

[w] hile this study focused on the
discipline of surgery, we can easily
imagine the benefits of this type of
communications application outside of
the surgical model that we have studied.
The results of any laboratory, pathology,
or radiography studies can be
instantaneously shared with concerned
family members all over the globe. In the
critical care setting, doctors can
communicate with a patient’s extended

support group more efficiently and in a
less stress-inducing environment than the
typical crowded consultation room
outside of the intensive care unit. News of
the arrival of a newborn baby boy or girl
can be sent to eager aunts, uncles, and
grandparents back home. The
opportunities for enhancing
communication pertaining to medical
issues are seemingly limitless. (p. 6)

What are some other ways that new communication
technologies could be used to increase patient and
family satisfaction with health care in your practice?

Core Business Systems
Core business systems enhance administrative tasks
within healthcare organizations. Unlike clinical
information systems (CISs), whose aim is to provide
direct patient care, these systems support the
management of health care within an organization.
Core business systems provide the framework for
reimbursement, support of best practices, quality
control, and resource allocation. There are four
common core business systems: (1) admission,
discharge, and transfer (ADT) systems; (2) financial
systems; (3) acuity systems; and (4) scheduling
systems.

Admission, discharge, and transfer systems
provide the backbone structure for the other types of
clinical and business systems (Hassett & Thede,
2003). These systems were among the first to be
automated in health care. Admitting, billing, and bed
management departments most commonly use ADT
systems. These systems hold key information on which
all other systems rely. For example, ADT systems
maintain the patient’s name; medical record number;
visit or account number; and demographic information,
such as age, gender, home address, and contact
information. Such systems are considered the central
source for collecting this type of patient information and
communicating it to other types of healthcare
information systems.

RESEARCH BRIEF

Researchers attempted to quantify the costs of
poor communication, termed “communication
inefficiencies,” in hospitals. This qualitative study
was conducted in seven acute care hospitals of
varying sizes via structured interviews with key
informants at each facility. The interview
questions focused on four broad categories: (1)
communication bottlenecks, (2) negative
outcomes as a result of those bottlenecks, (3)
subjective perceptions of the potential
effectiveness of communication improvements
on the negative outcomes, and (4) ideas for

specific communication improvements. The
researchers independently coded the interview
data and then compared results to extract
themes.

All of the interviewees indicated that
communication was an issue. Inefficiencies
revolved around time spent tracking people
down to communicate with them, with various
estimates provided: 3 hours per nursing shift
wasted tracking people down, 20% of productive
time wasted on communication bottlenecks, and
a reported average of five to six telephone calls
to locate a physician. Several respondents
pointed to costly medical errors that were the
direct result of communication issues.
Communication lapses also resulted in
inefficient use of clinician resources and
increased length of stay for patients.

The researchers developed a conceptual model
of communication quality with four primary
dimensions: (1) efficiency of resource use, (2)
effectiveness of resource use, (3) quality of work
life, and (4) service quality. They concluded that
the total cost of communication inefficiencies in
U.S. hospitals is more than $12 billion annually
and estimated that a 500-bed hospital could lose
as much as $4 million annually because of such
problems. They urge the adoption of information

technologies to redesign workflow processes
and promote better communication.

The full article appears in Agarwal, R., Sands, D., Schneider, J.,

& Smaltz, D. (2010). Quantifying the economic impact of

communication inefficiencies in U.S. hospitals. Journal of

Healthcare Management, 55(4), 265–281.

Financial systems manage the expenses and
revenue for providing health care. The finance,
auditing, and accounting departments within an
organization most commonly use financial systems.
These systems determine the direction for
maintenance and growth for a given facility. They often
interface to share information with materials
management, staffing, and billing systems to balance
the financial impact of these resources within an
organization. Financial systems report fiscal outcomes,
which can then be tracked and related to the
organizational goals of an institution. These systems
are key components in the decision-making process as
healthcare institutions prepare their fiscal budgets.
They often play a pivotal role in determining the
strategic direction for an organization.

Acuity systems monitor the range of patient types
within a healthcare organization using specific
indicators. They track these indicators based on the
current patient population within a facility. By
monitoring the patient acuity, these systems provide

feedback about how intensive the care requirement is
for an individual patient or group of patients. Identifying
and classifying a patient’s acuity can promote better
organizational management of the expenses and
resources necessary to provide care. Acuity systems
help predict the ability and capacity of an organization
to care for its current population. They also forecast
future trends to allow an organization to successfully
strategize on how to meet upcoming market demands.

Scheduling systems coordinate staff, services,
equipment, and allocation of patient beds. They are
frequently integrated with the other types of core
business systems. By closely monitoring staff and
physical resources, these systems provide data to the
financial systems. For example, resource-scheduling
systems may provide information about operating room
use or availability of intensive care unit beds and
regular nursing unit beds. These systems also provide
great assistance to financial systems when they are
used to track medical equipment within a facility.
Procedures and care are planned when the tools and
resources are available. Scheduling systems help to
track resources within a facility while managing the
frequency and distribution of those resources.

Order Entry Systems
Order entry systems are one of the most important
systems in use today. They automate the way that

orders have traditionally been initiated for patients—
that is, clinicians place orders using these systems
instead of creating traditional handwritten transcriptions
onto paper. Order entry systems provide major
safeguards by ensuring that physician orders are
legible and complete, thereby providing a level of
patient safety that was historically missing with paper-
based orders. Computerized physician (provider)
order entry systems provide decision support and
automated alert functionality that was unavailable with
paper-based orders.

The seminal report by the Institute of Medicine
estimated that medical errors cost the United States
approximately $37.6 billion each year; nearly $17
billion of those costs are associated with preventable
errors (Kohn, Corrigan, Donaldson, & Institute of
Medicine, 2000). Consequently, the federal Agency for
Healthcare Research and Quality Patient Safety
Network (2015) continued to recommend eliminating
reliance on handwriting for ordering medications.
Because of the global concern for patient safety as a
result of incorrect and misinterpreted orders,
healthcare organizations are incorporating order entry
systems into their operations as a standard tool for
practice. Such systems allow for clear and legible
orders, thereby both promoting patient safety and
streamlining care. Although much of the health
information technology literature suggests that
physicians are resistant to adopting health information

technology, a recent study by Elder, Wiltshire, Rooks,
BeLue, and Gary (2010) found that physicians who use
information technology were more satisfied overall
with their careers. The Informatics Tools to Promote
Patient Safety and Quality Outcomes chapter provides
more information about the use of computerized
physician order entry systems in clinical care.

Patient Care Support Systems
Most specialty disciplines within health care have an
associated patient care information system. These
patient-centered systems focus on collecting data and
disseminating information related to direct care.
Several of these systems have become mainstream
types of systems used in health care. The four systems
most commonly encountered in health care include (1)
clinical documentation systems, (2) pharmacy
information systems, (3) laboratory information
systems, and (4) radiology information systems.

Clinical documentation systems, also known as
“clinical information systems,” are the most commonly
used type of patient care support system within
healthcare organizations. CISs are designed to collect
patient data in real time. They enhance care by putting
data at the clinician’s fingertips and enabling decision
making where it needs to occur—that is, at the
bedside. For that reason, these systems often are
easily accessible at the point of care for caregivers

interacting with the patient. CISs are patient centered,
meaning they contain the observations, interventions,
and outcomes noted by the care team. Team members
enter information, such as the plan of care,
hemodynamic data, laboratory results, clinical notes,
allergies, and medications. All members of the
treatment team use clinical documentation systems; for
example, pharmacists, allied health workers, nurses,
physicians, support staff, and many others access the
clinical record for the patient using these systems.
Frequently these types of systems are also referred to
as the electronic patient record or electronic health
record. The Electronic Health Record and Clinical
Informatics chapter provides a comprehensive
overview of CISs and the electronic health record.

Pharmacy information systems also have become
mainstream patient care support systems. They
typically allow pharmacists to order, manage, and
dispense medications for a facility. They also
commonly incorporate information regarding allergies
and height and weight to ensure effective medication
management. Pharmacy information systems
streamline the order entry, dispensing, verification, and
authorization process for medication administration.
They often interface with clinical documentation and
order entry systems so that clinicians can order and
document the administration of medications and
prescriptions to patients while having the benefits of
decision support alerting and interaction checking.

Laboratory information systems were perhaps some
of the first clinical information systems ever used in
health care. Because of their long history of use within
medicine, laboratory systems have been models for the
design and implementation of other types of patient
care support systems. Laboratory information systems
report on blood, body fluid, and tissue samples, along
with biological specimens collected at the bedside and
received in a central laboratory. They provide clinicians
with reference ranges for tests indicating high, low, or
normal values to make care decisions. Often, the
laboratory system provides result information in the
EHR and directs clinicians toward the next course of
action within a treatment regimen.

The final type of patient care support system commonly
found within health care is the radiology information
system (RIS) found in radiology departments. These
systems schedule, result, and store information related
to diagnostic radiology procedures. One feature found
in most radiology systems is a picture archiving and
communication system (PACS). The PACS may be a
stand-alone system, kept separate from the main
radiology system, or it can be integrated with the RIS
and CIS. These systems collect, store, and distribute
medical images, such as computed tomography scans,
magnetic resonance images, and X-rays. PACS
replace traditional hard-copy films with digital media
that are easy to store, retrieve, and present to

clinicians. The benefit of RIS and PACS is their ability
to assist in diagnosing and storing vital patient care
support data. Imaging studies can be available in
minutes as opposed to 2–6 hours for images in a film-
based system. The digital workstations provide
enhanced imaging capabilities and on-screen
measurement tools to improve diagnostic accuracy.
Finally, the archive system stores images in a database
that is readily accessible, so that images can be easily
retrieved and compared to subsequent testing or
shared instantly with consultants.

The mobility of patients both geographically and within
a single healthcare delivery system challenges
information systems because data must be captured
wherever and whenever the patient receives care. In
the past, managed care information systems were
implemented to address these issues. Consequently,
data can be obtained at any and all of the areas where
a patient interacts with the healthcare system. Patient-
tracking mechanisms continue to be honed, but the
financial impact of health care also has changed these
systems to some extent. The information systems
currently in use enable nurses and physicians to make
clinical decisions while being mindful of their financial
ramifications. In the future, vast improvements in
information systems and systems that support health
information exchange are likely to continue to emerge.

One such trend is the incentive to develop accountable

care organizations encouraged by the Patient
Protection and Affordable Care Act of 2010. According
to the Centers for Medicare and Medicaid Services
(2015), “Accountable Care Organizations (ACOs) are
groups of doctors, hospitals, and other health care
providers, who come together voluntarily to give
coordinated high quality care to their Medicare
patients. The goal of coordinated care is to ensure that
patients, especially the chronically ill, get the right care
at the right time, while avoiding unnecessary
duplication of services and preventing medical errors”
(para. 1–2). Members of an ACO share data and
information to better coordinate care and they also
share in any health care cost savings generated when
the coordination of care reduces unnecessary and
duplicated costs.

Interoperability
A key component to coordinated care is the
interoperability of healthcare information systems. In
2015, the Office of the National Coordinator for Health
IT (ONC) released an interoperability roadmap to
promote ease of access and use of electronic
healthcare data. Interoperability is defined as “the
ability of a system to exchange electronic health
information with and use electronic health information
from other systems without special effort on the part of
the user” (Healthcare Information and Management
Systems Society [HIMSS], 2015, para. 2). The final

goal of the national roadmap emphasis on
interoperability is driven by the need to “achieve
nationwide interoperability to enable a learning health
system, with the person at the center of a system that
can continuously improve care, public health, and
science through real-time data access” (ONC, 2015, p.
vii). As we develop more sophisticated electronic
systems, we are realizing the huge potential benefits of
exchanging secure and precise healthcare data.
However, in the current landscape, several things need
to happen to realize this goal. Chief among them is a
worldwide commitment to interoperability. HIMSS
(2013) identified three types of health information
technology interoperability—foundational, structural,
and semantic—each with increasing complexity.
Foundational interoperability is basic data reception
from one system to another without interpretation.
Structural interoperability is more complex and
depends on consistency of clinical terminology and
meaning of the data. Semantic interoperability depends
on data that is consistent and codified allowing for
information system interpretation and analysis of the
data. Semantic interoperability is considered the
highest and most complex form of interoperability.
Semantic interoperability is necessary for seamless
health information exchange.

Suppose you have a joint replacement patient who is
being discharged from the acute care facility to a
rehabilitation center. You create a discharge summary

for the patient in a PDF format and send it via a secure
electronic exchange to the new facility. The staff at the
rehabilitation center is able to read and understand the
report and a staff assistant can scan a copy of the
discharge summary into the electronic record for the
rehabilitation facility. This is an example of functional
interoperability. If each facility uses Health Level Seven
standards for data exchange and collects certain
minimum data, then it might be possible for certain
data fields from one facility to populate automatically
into an appropriate data field in the new facility. This is
an example of structural interoperability. To achieve
true semantic interoperability, systems must use the
same standardized terminologies or disparate
terminologies must be mapped, and the two systems
must be able to “talk” to each other to exchange data
seamlessly and to populate the data into to the
appropriate fields in the new system. True semantic
interoperability enables machine-to-machine data
exchange.

Consistently representing electronic
health information across different
stakeholders and systems is the bedrock
of successful interoperability. In a
learning health system, while user
interfaces can and should be different
depending on the user, the format in
which electronic health information is
shared between health IT systems must

be consistent and machine readable, so
that the meaning and integrity of
information is retained as a variety of
users interact with it. (ONC, 2015, p. 28)

For more detailed information on interoperability,
download and read the ONC’s Interoperability
Roadmap:
https://www.healthit.gov/sites/default/files/hie-
interoperability/nationwide-interoperability-
roadmap-final-version-1.0.pdf

Aggregating Patient and
Organizational Data
Many healthcare organizations now aggregate data in
a data warehouse (DW) for the purpose of mining the
data to discover new relationships and to build
organizational knowledge. Rojas (2015) stated that

Hospitals and medical centers have more
to gain from big data analytics than
perhaps any other industry. But as data
sets continue to grow, healthcare facilities
are discovering that success in data
analytics has more to do with storage
methods than with analysis software or
techniques. Traditional data silos are
hindering the progress of big data in the

healthcare industry, and as terabytes turn
into petabytes, the most successful
hospitals are the ones that are coming up
with new solutions for storage and access
challenges. (para. 1)

When disparate information systems within an
organization are unable to interface with any other
information systems (either within or outside of the
organization), the result is poor communication, billing
errors, and issues with continuity of care. By
developing a single comprehensive database,
healthcare systems are able to facilitate
interprofessional communications, yet maintain
compliance with privacy regulations. Figure 10-1
depicts moving from siloed to integrated data.

Figure 10-1 Moving from Data Silos to Integrated Data

Data from Smart Data Collective. (2015). 2 critical obstacles facing

retailers for data driven marketing. Retrieved from

http://www.smartdatacollective.com/lbedgood/349875/two-critical-

obstacles-facing-retailers-data-driven-marketing

Based on the size of the organization, data triage and
tiering might be necessary. These decision-making
processes related to data storage are based on
predictions related to how quickly data might need to
be accessed.

Consider the case of Intermountain, a chain of 22
hospitals in Salt Lake City. With 4.7 petabytes of data
under its management, cloud storage becomes cost
prohibitive. The network estimates the size of the
hospital chain’s data will grow by 25–30% each year
until it reaches 15 petabytes in 5 years. With such
massive data needs, Intermountain found ways to cut
costs and streamline efficiency. One way was through
data tiering, which is the creation of data storage tiers
that can be accessed at the appropriate speeds.
Tiering is currently done manually through triaging, but
several different organizations are exploring
autotiering, which automatically stores data according
to availability needs (Rojas, 2015, para. 9–10).

The most basic element of a database system is the
data. Data refers to raw facts that can consist of
unorganized text, graphics, sound, or video.
Information is data that have been processed—it has
meaning; information is organized in a way that people
find meaningful and useful. Even useful information
can be lost if one is mired in unorganized information.
Computers can come to the rescue by helping to
create order out of chaos. Computer science and

information science are designed to help cut down the
amount of information to a more manageable size and
organize it so that users can cope with it more
efficiently through the use of databases and database
programs technology. Learning about basic databases
and database management programs is paramount so
that users can apply data and information management
principles in health care.

A database is a structured or organized collection of
data that is typically the main component of an
information system. Databases and database
management software allow the user to input, sort,
arrange, structure, organize, and store data and turn
those data into useful information. An individual can set
up a personal database to organize recipes, music,
names and addresses, notes, bills, and other data. In
health care, databases and information systems make
key information available to healthcare providers and
ancillary personnel to promote the provision of quality
patient care. Box 10-1 provides a detailed description
of a database.

BOX 10-1 OVERVIEW OF DATABASE

CONSTRUCTION

Databases consist of fields (columns) and
records (rows). Within each record, one of the
fields is identified as the primary key or key

field. This primary key contains a code, name,
number, or other information that acts as a
unique identifier for that record. In the
healthcare system, for example, a patient is
assigned a patient number or ID that is unique
for that patient. As you compile related records,
you create data files or tables. A data file is a
collection of related records. Therefore,
databases consist of one or more related data
files or tables.

An entity represents a table, and each field
within the table becomes an attribute of that
entity. The database developer must critically
think about the attributes for each specific entity.
For example, the entity “disease” might have the
attributes of “chronic disease,” “acute disease,”
or “communicable disease.” The name of the
entity, “disease,” implies that the entity is about
diseases. The fields or attributes are “chronic,”
“acute,” or “communicable.”

The entity–relationship diagram specifies the
relationship among the entities in the database.
Sometimes the implied relationships are readily
apparent based on the entities’ definitions;
however, all relationships should be specified as
to how they relate to one another. Typically,
three relationships are possible: (1) one to one,
(2) one to many, and (3) many to many. A one-
to-one relationship exists between the entities of

the table about a patient and the table about the
patient’s birth. A one-to-many relationship could
exist when one entity is repeatedly used by
another entity. Such a one-to-many relationship
could then be a table query for age that could be
used numerous times for one patient entity. The
many-to-many relationship reflects entities that
are all used repeatedly by other entities. This is
easily explained by the entities of patient and
nurse. The patient could have several nurses
caring for him or her, and the nurse could have
many patients assigned to him or her (see
Figure 10-2).

Figure 10-2 Example of an Entity Relationship
Diagram (ERD)

The relational model is a database model that
describes data in which all data elements are
placed in relation in two-dimensional tables; the
relations or tables are analogous to files. A
relational database management system
(RDMS) is a system that manages data using
this kind of relational model. A relational
database could link a patient’s table to a
treatment table (e.g., by a common field, such
as the patient ID number). To keep track of the
tables that constitute a database, the database
management system uses software called a
data dictionary. The data dictionary contains a
listing of the tables and their details, including
field names, validation settings, and data types.
The data type refers to the type of information,
such as a name, a date, or a time.

The database management system is an
important program because before it was
available, many health systems and businesses
had dozens of database files with incompatible
formats. Because patient data come from a
variety of sources, these separated, isolated
data files required duplicate entry of the same
information, thereby increasing the risk of data
entry error. The design of the relational
databases eliminates data duplication. Some
examples of popular database management
system software include Microsoft’s Access or

Visual FoxPro, Corel’s Paradox, Oracle’s Oracle
Database 10g, and IBM’s DB2.

On a large scale, a data warehouse is an extremely
large database or repository that stores all of an
organization’s or institution’s data and makes these
data available for data mining. The DW can combine
an institution’s many different databases to provide
management personnel with flexible access to the
data. On the smaller scale, a data mart represents a
large database where the data used by one of the units
or a division of a healthcare system are stored and
maintained. For example, a university hospital system
might store clinical information from its many affiliate
hospitals in a DW, and each separate hospital might
have a data mart housing its data.

There are many ways to access and retrieve
information in databases. Searching information in
databases can be done through the use of a query, as
is used in Microsoft’s Access database. A query asks
questions of the database to retrieve specific data and
information. Box 10-2 provides a detailed description
of the Structured Query Language (SQL).

BOX 10-2 SQL

SQL was originally called SEQUEL, or
Structured English Query Language. SQL, still

pronounced “sequel,” now stands for Structured
Query Language; it is a database querying
language, rather than a programming language.
It is a standard language for accessing and
manipulating databases. SQL is “used with
relational databases; it allows users to define
the structure and organization of stored data,
verify and maintain data integrity, control access
to the data, and define relationships among the
stored data items” (University of California at
San Diego, 2010, para. 8). In this way, it
simplifies the process of retrieving information
from a database in a functional or usable form
while facilitating the reorganization of data within
the databases.

The relational database management system is
the foundation or basis for SQL. An RDMS
stores data in “database objects called tables”
(W3Schools.com, 2010, para. 6). A table is a
collection of related data that consists of
columns and rows; as noted earlier, columns are
also referred to as fields, and rows are also
referred to as records or tuples. Databases can
have many tables, and each table is identified
by a name (see the Database Example: School
of Nursing Faculty).

SQL statements handle most of the actions
users need to perform on a database. SQL is an
International Organization for

Standardization (ISO) standard and American
National Standards Institute (ANSI) standard,
but many different versions of the SQL language
exist (Indiana University, 2010). To remain
compliant with the ISO and ANSI standards,
SQL must handle or support the major
commands of SELECT, UPDATE, DELETE,
INSERT, and WHERE in a similar manner
(W3Schools.com, 2010). The SELECT
command allows you to extract data from a
database. UPDATE updates the data, DELETE
deletes the data, and INSERT inserts new data.
WHERE is used to specify selection criteria,
thereby restricting the results of the SQL query.
Thus SQL allows you to create databases and
manipulate them by storing, retrieving, updating,
and deleting data.

Database Example: School of Nursing Faculty

Table Named “Faculty”

Last First Department Office
Phone

Office

P_ID Name Name Affiliation Number Location User
ID

1 Eggleers Renee Informatics 444-

111-

1104

104A Eggleersr100

2 Feistyz Judi Gerontology 444-

111-

2202

202b Feistyzj562

3 Martinez Bethann Neurology 444-

111-

3336

336C Martinezb789

4 Smythe Ralph Informatica 444-

111-

1110

110A Smyther355

The database example provided here reflects
the faculty listing for a school of nursing. The
table that contains the data is identified by the
name “Faculty.” The faculty members are each
categorized by the following fields (columns):
Last Name, First Name, Department Affiliation,
Office Phone Number, Office Location, and
UserID. Each individual faculty member’s
information is a record (tuple or row).

Using the SQL command SELECT, all of the
records in the “Faculty” table can be selected:

SELECT*FROM Faculty

This command would SELECT all (*) of the
records FROM the table known as FACULTY.
The asterisk (*) is used to select all of the
columns.

Data mining software sorts thorough data to discover
patterns and ascertain or establish relationships. This
software discovers or uncovers previously unidentified
relationships among the data in a database by
conducting an exploratory analysis looking for hidden
patterns in data. Using such software, the user
searches for previously undiscovered or undiagnosed
patterns by analyzing the data stored in a DW. Drill-
down is a term that means the user can view DW
information by drilling down to lower levels of the
database to focus on information that is pertinent to his
or her needs at the moment.

As users move through databases within the
healthcare system, they can access anything from
enterprise-wide DWs to data marts. For example, an
infection-control nurse might notice a pattern of
methicillin-resistant Staphylococcus aureus infections
in the local data mart (a single hospital within a larger
system). The nurse might want to find out if the
outbreak is local (data mart) or more widespread in the
system (DW). The nurse might also query the database
to determine if certain patient attributes (e.g., age or
medical diagnosis) are associated with the incidence of
infection.

These kinds of data mining capabilities are also quite
useful for healthcare practitioners who wish to conduct
clinical research studies. For example, one might query
a database to tease out attributes (patient

characteristics) associated with asthma-related
hospitalizations. For a more detailed description and
review of data mining, refer to the Data Mining as a
Research Tool chapter.

According to Mishra, Sharma, and Pandey (2013),
there is a new set of challenges and opportunities for
managing data, data mining, and establishing
algorithms in the cloud. Data mining in the cloud is
emerging and evolving. This frontier is becoming a
potent way to take advantage of the power of cloud
computing and combine it with SQL. The world as we
know it is changing: “Clouds” are leading us to develop
revolutionary data mining technologies. There are five
typical clinical applications for databases: (1) hospitals,
(2) clinical research, (3) clinical trials, (4) ambulatory
care, and (5) public health. Some healthcare systems
are connecting their hospitals together by choosing a
single CIS to capture data on a system-wide basis. In
such healthcare organizations, multiple application
programs share a pool of related data. Think about
how potent such databases might potentially be in
managing organizations and providing insights into
new relationships that may ultimately transform the
way work is done.

Department Collaboration and
Exchange of Knowledge and
Information

The implementation of systems within health care is
the responsibility of many people and departments. All
systems require a partnership of collaboration and
knowledge sharing to implement and maintain
successful standards of care. Collaboration is the
sharing of ideas and experiences for the purposes of
mutual understanding and learning. Knowledge
exchange is the product of collaboration when sharing
an understanding of information promotes learning
from past experiences to make better future decisions.

Depending on the type of project, collaboration may
occur at many different levels within an organization. At
an administrative level, collaboration among key
stakeholders is critical to the success of any project.
Stakeholders have the most responsibility for
completing the project. They have the greatest
influence in the overall design of the system, and
ultimately they are the people who are most impacted
by a system implementation. Together with the
organizational executive team, stakeholders
collaborate on the overall budget and time frame for a
system implementation.

Collaboration may also occur among the various
departments impacted by the system. These groups
frequently include representatives from information
technology, clinical specialty areas, support services,
and software vendors. Once a team is assembled, it
defines the objectives and goals of the system. The

team members work strategically to align their goals
with the goals of the organization where the system is
to be used. The focus for these groups is on planning,
resource management, transitioning, and ongoing
support of the system. Their collaboration determines
the way in which the project is managed, the
deliverables for the project, the individuals held
accountable for the project, the time frame for the
project, opportunities for process improvement using
the system, and the means by which resources are
allocated to support the system.

From collaboration comes the exchange of information
and ideas through knowledge sharing. Specialists
exchange knowledge within their respective areas of
expertise to ensure that the system works for an entire
organization. From one another, they learn
requirements that make the system successful. This
exchange of ideas is what makes healthcare
information systems so valuable. A multidisciplinary
approach ensures that systems work in the complex
environment of healthcare organizations that have
diverse and complex patient populations.

Summary
The integration of technology within healthcare
organizations offers limitless possibilities. As new types
of systems emerge, clinicians will become smarter and
more adept at incorporating these tools into their daily

practice. Success will be achieved when health care
incorporates technology systems in a way that they are
not viewed as separate tools to support healthcare
practices, but rather as necessary instruments to
provide health care. Patients, too, will become savvier
at using healthcare information systems as a means of
communication and managing their personal and
preventive care. In the future, these two mindsets will
become expectations for health care and not simply a
high-tech benefit, as they are often viewed today.

Ultimately, it is not the type of systems adopted that is
important, but rather the method in which they are put
into practice. In an ideal world, robust and transparent
information technologies will support clinical and
administrative functions and promote safe, quality, and
cost-effective care.

THOUGHT-PROVOKING QUESTIONS

1. Which type of technology exists today
that could be converted into new types of
information systems to be used in health
care?

2. How could collaboration and knowledge
sharing at a single organization be used
to help individuals preparing for
information technology at a different
facility?

3. Explore the administrative information
systems and their applications in your
healthcare organization.
a. What are the main systems used?
b. How is data shared among systems?
c. What examples of functional,

structural, and semantic
interoperability can you identify?

References
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Case Management Society of America
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Centers for Medicare and Medicaid
Services (CMS). (2015). Accountable
care organizations. Retrieved from

https://www.cms.gov/Medicare/Medicare-
Fee-for-Service-
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Elder, K., Wiltshire, J., Rooks, R., BeLue,
R., & Gary, L. (2010, Summer). Health
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Gordon, C. R., Rezzadeh, K. S., Li, A.,
Vardanian, A., Zelken, J., Shores, J. T.,
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Hassett, M., & Thede, L. (2003).
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Healthcare Information and Management
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Healthcare Information and Management
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roadmap?ItemNumber=44779

Indiana University. (2010). University
information technology services
knowledge base: What is SQL?
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pathway standards and accountability
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Health Information Technology (ONC).
(2015). Connecting health and care for
the nation: A shared nationwide
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CHAPTER 11: The
Human–Technology
Interface

Dee McGonigle, Kathleen Mastrian, and Judith A.
Effken

Objectives
1. Describe the human–technology

interface.
2. Explore human–technology interface

problems.
3. Reflect on the future of the human–

technology interface.

Key Terms
» Cognitive task analysis

» Cognitive walkthrough

» Cognitive work analysis

» Earcons

» Ergonomics

» Field study

» Gulf of evaluation

» Gulf of execution

» Heuristic evaluation

» Human–computer interaction

» Human factors

» Human–technology interaction

» Human–technology interface

» Mapping

» Situational awareness

» Task analysis

» Usability

» Workarounds

Introduction
One of this chapter’s authors stayed in a new hotel on
the outskirts of London. When she entered her room,

she encountered three wall-mounted light switches in a
row, but with no indication of which lights they
operated. In fact, the mapping of switches to lights was
so peculiar that she was more often than not surprised
by the light that came on when she pressed a particular
switch. One might conclude that the author had a
serious problem, but she prefers to attribute her
difficulty to poor design.

When these kinds of technology design issues surface
in health care, they are more than just an annoyance.
Poorly designed technology can lead to errors, lower
productivity, or even the removal of the system
(Alexander & Staggers, 2009). Unfortunately, as more
and more kinds of increasingly complex health
information technology applications are integrated, the
problem becomes even worse (Johnson, 2006).
However, nurses are very creative and, if at all
possible, will design workarounds that allow them to
circumvent troublesome technology. However,
workarounds are only a Band-Aid; they are not a long-
term solution.

In his classic book The Psychology of Everyday
Things, Norman (1988) argued that life would be a lot
simpler if people who built the things that others
encounter (such as light switches) paid more attention
to how they would be used. At least one everyday thing
meets Norman’s criteria for good design: the scythe.
Even people who have never encountered one will pick

up a scythe in the manner needed to use it because
the design makes only one way feasible. The scythe’s
design fits perfectly with its intended use and a human
user. Would it not be great if all technology were so
well fit to human use? In fact, this is not such a far-
fetched idea. Scientists and engineers are making
excellent strides in understanding human–technology
interface problems and proposing solutions to them.

As you read through this chapter, reflect on the
everyday items you use. What makes them easy or
difficult to use? Is it evident that the developer thought
about how they would be used to facilitate their design
and function? Next, turn your attention to the
technologies you use. Is it evident that the developer
thought about how the technology would be used to
facilitate its design and function? Think about your
smartphone. How easy is it to hold your smartphone?
Is it intuitive and easy to access and use? What
improvements would you make? Does the electronic
health record (EHR) system you use support your
workflow and patient needs? Do you use workarounds
to avoid items that you feel should not be there or are
not needed at the time of entry? Do you think that the
developer understood you, as the user, or did not
realize how their technology tool would be used? By
the end of this chapter, you should be able to critically
examine the human–technology interfaces currently
available in health care and describe models,
strategies, and exemplars for improving interfaces

during the analysis, design, and evaluation phases of
the development life cycle.

The Human–Technology
Interface
What is the human–technology interface? Broadly
speaking, anytime a human uses technology, some
type of hardware or software enables and supports the
interaction. It is this hardware and software that defines
the interface. The array of light switches described
previously was actually an interface (although not a
great one) between the lighting technology in the room
and the human user.

In today’s healthcare settings, one encounters a wide
variety of human–technology interfaces. Those who
work in hospitals may use bar-coded identification
cards to log their arrival time into a human resources
management system. Using the same cards, they
might log into their patients’ EHR, access their patient’s
drugs from a drug administration system, and even
administer the drugs using bar-coding technology.
Other examples of human–technology interfaces one
might encounter include a defibrillator, a patient-
controlled analgesia (PCA) pump, any number of
physiologic monitoring systems, electronic
thermometers, and telephones and pagers. According
to Rice and Tahir (2014),

[R]ecent studies have found that rapid
implementation of new medical
technology—electronic health records,
patient monitoring devices, surgical
robots and other tools—can lead to
adverse patient events when it is not
thoughtfully integrated into workflow. The
right processes require understanding the
devices and the users. Testing in
controlled environments often does not
adequately consider the “human factor,”
or how people interact with technology in
high-pressure, real-life situations. (p. 12)

The human interfaces for each of these technologies
are different and can even differ among different
brands or versions of the same device. For example, to
enter data into an EHR, one might use a keyboard, a
light pen, a touch screen, or voice. Healthcare
technologies may present information via computer
screen, printer, or smartphone. Patient data might be
displayed in the form of text, images (e.g., the results
of a brain scan), or even sound (an echocardiogram);
in addition, the information may be arrayed or
presented differently, based on roles and preferences.
Some human–technology interfaces mimic face-to-face
human encounters. For example, faculty members are
increasingly using videoconferencing technology to
communicate with their students. Similarly, telehealth

allows nurses to use telecommunication and
videoconferencing software to communicate more
effectively and more frequently with patients at home
by using the technology to monitor patients’ vital signs,
supervise their wound care, or demonstrate a
procedure. According to Gephart and Effken (2013),
“The National eHealth Collaborative Technical Expert
Panel recommends fully integrating patient-generated
data (e.g., home monitoring of daily weights, blood
glucose, or blood pressure readings) into the clinical
workflow of healthcare providers” (para. 3). Telehealth
technology has fostered other virtual interfaces, such
as system-wide intensive care units in which
intensivists and specially trained nurses monitor
critically ill patients in intensive care units, some of
whom may be in rural locations. Sometimes telehealth
interfaces allow patients to interact with a virtual
clinician (actually a computer program) that asks
questions, provides social support, and tailors
education to identify patient needs based on the
answers to screening questions. These human–
technology interfaces have been remarkably
successful; sometimes patients even prefer them to
live clinicians.

Human–technology interfaces may present information
using text, numbers, images, icons, or sound. Auditory,
visual, or even tactile alarms may alert users to
important information. Users may interact with (or

control) the technology via keyboards, digital pens,
voice activation, or even touch.

A small, but growing, number of clinical and
educational interfaces rely heavily on tactile input. For
example, many students learn to access an
intravenous site using virtual technology. Other, more
sophisticated virtual reality applications help physicians
learn to do endoscopies or practice complex surgical
procedures in a safe environment. Still others allow
drug researchers to design new medications by
combining virtual molecules (here, the tactile response
is quite different for molecules that can be joined from
those that cannot). In each of these training
environments, accurately depicting tactile sensations is
critical. For example, feeling the kind and amount of
pressure required to penetrate the desired tissues, but
not others, is essential to a realistic and effective
learning experience.

© Thomas Andreas/Shutterstock

The growing use of large databases for research has
led to the design of novel human–technology interfaces
that help researchers visualize and understand
patterns in the data that generate new knowledge or
lead to new questions. Many of these interfaces now
incorporate multidimensional visualizations, in addition
to scatter plots, histograms, or cluster representations
(Vincent, Hastings-Tolsma, & Effken, 2010). Some
designers, such as Quinn (the founder of the Design
Rhythmics Sonification Research Laboratory at the
University of New Hampshire) and Meeker (2000), use
variations in sound to help researchers hear the
patterns in large datasets. In Quinn and Meeker’s
(2000) “climate symphony,” different musical
instruments, tones, pitches, and phrases are mapped

onto variables, such as the amounts and relative
concentrations of minerals, to help researchers detect
patterns in ice core data covering more than 110,000
years. Climate patterns take centuries to emerge and
can be difficult to detect. The music allows the entire
110,000 years to be condensed into just a few minutes,
making detection of patterns and changes much easier.

The human–technology interface is ubiquitous in health
care and takes many forms. A look at the quality of
these interfaces follows. Be warned: It is not always a
pretty picture.

© Innocenti/Cultura/Getty

© Carlos Amarillo/Shutterstock

The Human–Technology
Interface Problem
In The Human Factor, Vicente (2004) cited the many
safety problems in health care identified by the Institute
of Medicine’s (1999) report and noted how the
technology (defined broadly) used often does not fit
well with human characteristics. As a case in point,
Vicente described his own studies of nurses’ PCA
pump errors. Nurses made the errors, in large part,
because of the complexity of the user interface, which
required as many as 27 steps to program the device.
Vicente and his colleagues developed a PCA in which
programming required no more than 12 steps. Nurses
who used it in laboratory experiments made fewer

errors, programmed drug delivery faster, and reported
lower cognitive workloads compared to the commercial
device. Further evidence that human–technology
interfaces do not work as well as they might is evident
in the following events.

Doyle (2005) reported that when a bar-coding
medication system interfered with their workflow,
nurses devised workarounds, such as removing the
armband from the patient and attaching it to the bed,
because the bar-code reader failed to interpret bar
codes when the bracelet curved tightly around a small
arm. Koppel et al. (2005) reported that a widely used
computer-based provider order entry (CPOE) system
meant to decrease medication errors actually facilitated
22 types of errors because the information needed to
order medications was fragmented across as many as
20 screens, available medication dosages differed from
those the physicians expected, and allergy alerts were
triggered only after an order was written.

Han et al. (2005) reported increased mortality among
children admitted to Children’s Hospital in Pittsburgh
after CPOE implementation. Three reasons were cited
for this unexpected outcome. First, CPOE changed the
workflow in the emergency room. Before CPOE, orders
were written for critical time-sensitive treatment based
on radio communication with the incoming transport
team before the child arrived. After CPOE
implementation, orders could not be written until the

patient arrived and was registered in the system (a
policy that was later changed). Second, entering an
order required as many as 10 clicks and took as long
as 2 minutes; moreover, computer screens sometimes
froze or response time was slow. Third, when the team
changed its workflow to accommodate CPOE, face-to-
face contact among team members diminished.
Despite the problems with study methods identified by
some of the informatics community, there certainly
were serious human–technology interface problems.

In 2005, a Washington Post article reported that
Cedars-Sinai Medical Center in Los Angeles had shut
down a $34 million system after 3 months because of
the medical staff’s rebellion. Reasons for the rebellion
included the additional time it took to complete the
structured information forms, failure of the system to
recognize misspellings (as nurses had previously
done), and intrusive and interruptive automated alerts
(Connolly, 2005). Even though physicians actually
responded appropriately to the alerts, modifying or
canceling 35% of the orders that triggered them,
designers had not found the right balance of helpful-to-
interruptive alerts. The system simply did not fit the
clinicians’ workflow.

Such unintended consequences (Ash, Berg, & Coiera,
2004) or unpredictable outcomes (Aarts, Doorewaard,
& Berg, 2004) of healthcare information systems may
be attributed, in part, to a flawed implementation

process, but there were clearly also human–
technology interaction issues. That is, the technology
was not well matched to the users and the context of
care. In the pediatric case, a system developed for
medical–surgical units was implemented in a critical
care unit.

Human–technology interface problems are the major
cause of as many as 87% of all patient monitoring
incidents (Walsh & Beatty, 2002). It is not always that
the technology itself is faulty. In fact, the technology
may perform flawlessly, but the interface design may
lead the human user to make errors (Vicente, 2004).

Rice and Tahir (2014) reported on two errors that
remind us we still have a long way to go to ensure
patient safety: In 2011, a pop-up box on a digital blood
glucose reader was misread and the patient was given
too much insulin, sending her into a diabetic coma; in
2013, a patient did not receive his psychiatric medicine
for almost 3 weeks because the pharmacy’s computer
system was set to automatically discontinue orders for
certain drugs, and there was no alert built in to notify
the team providing care to this patient that the drug
was suspended. The real issue is that the healthcare
personnel–technology interfaces continue to cause
these adverse events and near-misses. It is important
to remember that it is not only a technology or human
interface issue. Many of these problems occur when
new technology is introduced or existing technology is

modified. In addition, we must examine how the
technology tools are tested, how the human users are
prepared for their use, and how the tools are integrated
into the care delivery process (Rice & Tahir, 2014).

Improving the Human–
Technology Interface
Much can be learned from the related fields of
cognitive engineering, human factors, and
ergonomics (Figures 11-1 and 11-2) about how to
make interfaces more compatible with their human
users and the context of care. Each of these areas of
study is multidisciplinary and integrates knowledge
from multiple disciplines (e.g., computer science,
engineering, cognitive engineering, psychology, and
sociology).

Figure 11-1 Human Factors and Ergonomics

Figure 11-2 Human Factors and Ergonomics,
Continued

These areas are also concerned with health issues
arising from computer and other technology use. Longo
and Reese (2014) reminded us that

Nearly 20 years ago, the American
Optometric Association termed computer
vision syndrome (CVS) as the complex of
eye and vision problems related to near
work experienced while using a
computer. CVS symptoms reflect the

current broad diagnosis of asthenopia
(ICD-9, 368.13) [2017 ICD-10-CM
H53.149] also referred to as eyestrain.
Symptoms include: fatigue, blurred distal
or proximal vision, headache, dry or
irritated eyes, neck and/or backaches,
blurred near vision and diplopia (double
vision). (p. 8)

Longo and Reese described how to prevent computer
vision syndrome. One of the best ways to help your
eyes is to remember to look 20 feet away from your
screen every 20 minutes for a minimum of 20 seconds.
With the increased smartphone use, we are seeing
neck issues caused by the tilt of the head (with the chin
on the chest) while looking down at the smartphone or
other handheld device. You should hold your phone up
so that you are keeping your neck and eyes aligned
properly with the device’s screen for more comfortable
viewing and interactions. We must all be aware of our
posture and how our work areas are set up when using
our computers, smartphones, tablets, and any other
devices that consume a great deal of our time during
our work or personal hours.

Effken (2016) proposed the ecological approach to
interface design to help us realize a more meaningful
EHR. This approach borrowed from a small field of
psychology, ecological psychology, which “emerged

after the 3-Mile Island nuclear fiasco to allow complex
processes (like nuclear power plants) to be more easily
and safely controlled by operators. Ecological displays
subsequently have enhanced the control of airplanes,
bottling plants—and even nuclear power plants. In the
1990s, the approach began to be extended to the
complexities of healthcare” (Effken, para. 2). Ecological
displays help the user identify deviations from normal
physical or physiological processes. According to
Effken,

Given the current pressure to achieve
meaningful use of the EHR and the
availability of new, more flexible
technology, this seems like an ideal time
for informaticists (and nurse
informaticists, in particular) to consider
seriously how the ecological approach
might be applied to make the meaning of
the EHR’s data more transparent to
clinician and patient users, as well as to
make clear the value proposition of
various treatments. (para. 8)

It is evident that users and clinicians need the
technology and interfaces necessary to quickly
comprehend the multiple discrete data that are
contained in distinct parts of the EHR. “Because these
are exactly the kind of complex problems that they

were developed to solve, the analysis and design
approaches derived from ecological psychology are
worth examining further as we attempt to derive a more
meaningful EHR” (Effken, 2016, para. 8).

Over the years, three axioms have evolved for
developing effective human–computer interactions
(Staggers, 2003): (1) Users must be an early and
continuous focus during interface design; (2) the
design process should be iterative, allowing for
evaluation and correction of identified problems; and
(3) formal evaluation should take place using rigorous
experimental or qualitative methods. These axioms still
apply today and, even after all of these years, are often
not followed.

Axiom 1: Users Must Be an Early and
Continuous Focus During Interface
Design
Rubin (1994) used the term user-centered design to
describe the process of designing products (e.g.,
human–technology interfaces) so that users can carry
out the tasks needed to achieve their goals with
“minimal effort and maximal efficiency” (p. 10). Thus, in
user-centered design, the end user is emphasized.
This is still a focus of human–technology interface
design today.

Vicente (2004) argued that technology should fit
human requirements at five levels of analysis (physical,
psychological, team, organizational, and political).
Physical characteristics of the technology (e.g., size,
shape, or location) should conform to the user’s size,
grasp, and available space. Information should be
presented in ways that are consistent with known
human psychological capabilities (e.g., the number of
items that can be remembered is seven plus or minus
two). In addition, systems should conform to the
communication, workflow, and authority structures of
work teams; to organizational factors, such as culture
and staffing levels; and even to political factors, such
as budget constraints, laws, or regulations.

A number of analysis tools and techniques have been
developed to help designers better understand the task
and user environment for which they are designing.
Discussed next are task analysis, cognitive task
analysis, and cognitive work analysis (CWA).

Task analysis examines how a task must be
accomplished. Generally, analysts describe the task in
terms of inputs needed for the task, outputs (what is
achieved by the task), and any constraints on actors’
choices on carrying out the task. Analysts then lay out
the sequence of temporally ordered actions that must
be carried out to complete the task in flowcharts
(Vicente, 1999). A worker’s tasks must be analyzed.
Task analysis is very useful in defining what users must

do and which functions might be distributed between
the user and technology (U.S. Department of Health
and Human Services, 2013). Cognitive task
analysis usually starts by identifying, through
interviews or questionnaires, the particular task and its
typicality and frequency. Analysts then may review the
written materials that describe the job or are used for
training and determine, through structured interviews or
by observing experts perform the task, which
knowledge is involved and how that knowledge might
be represented. Cognitive task analysis can be used to
develop training programs. Zupanc and colleagues
(2015) reported on the use of cognitive task analysis
techniques to develop a framework from which a
colonoscopy training program could be designed. “Task
analysis methods (observation, a think-aloud protocol
and cued-recall) and subsequent expert review were
employed to identify the competency components
exhibited by practicing endoscopists with the aim of
providing a basis for future instructional design”
(Zupanc et al., p. 10). The resulting colonoscopy
competency framework consisted of “twenty-seven
competency components grouped into six categories:
clinical knowledge; colonoscope handling; situation
awareness; heuristics and strategies; clinical
reasoning; and intra and inter-personal” (Zupanc et al.,
p. 10).

Cognitive work analysis was developed specifically
for the analysis of complex, high-technology work

domains, such as nuclear power plants, intensive care
units, and emergency departments, where workers
need considerable flexibility in responding to external
demands (Burns & Hajdukiewicz, 2004; Vicente,
1999). A complete CWA includes five types of analysis:
(1) work domain, (2) control tasks, (3) strategies, (4)
social–organizational, and (5) worker competencies.
The work domain analysis describes the functions of
the system and identifies the information that users
need to accomplish their task goals. The control task
analysis investigates the control structures through
which the user interacts with or controls the system. It
also identifies which variables and relations among
variables discovered in the work domain analysis are
relevant for particular situations so that context-
sensitive interfaces can present the right information
(e.g., prompts or alerts) at the right time. The strategies
analysis looks at how work is actually done by users to
facilitate the design of appropriate human–computer
dialogues. The social–organizational analysis identifies
the responsibilities of various users (e.g., doctors,
nurses, clerks, or therapists) so that the system can
support collaboration, communication, and a viable
organizational structure. Finally, the worker
competencies analysis identifies design constraints
related to the users themselves (Effken, 2002).

Specialized tools are available for the first three types
of CWA (Vicente, 1999). Analysts typically borrow tools
(e.g., ethnography) from the social sciences for the two

remaining types. Hajdukiewicz, Vicente, Doyle,
Milgram, and Burns (2001) used CWA to model an
operating room environment. Effken (2002) and Effken
et al. (2001) used CWA to analyze the information
needs for an oxygenation management display for an
ICU. Other examples of the application of CWA in
health care are described by Burns and Hajdukiewicz
(2004) in their chapter on medical systems (pp. 201–
238). Ashoon et al. (2014) used team CWA to reveal
the interactions of the healthcare team in the context of
work models in a birthing unit. They felt that team CWA
enhances CWA in complex environments, such as
health care, that require effective teamwork because it
reveals additional constraints relevant to the workings
of the team. The information gleaned about the
teamwork could be used for systems design
applications.

Axiom 2: The Design Process Should
Be Iterative, Allowing for Evaluation
and Correction of Identified Problems
Today, both principles and techniques for developing
human–technology interfaces that people can use with
minimal stress and maximal efficiency are available. An
excellent place to start is with Norman’s (1988, pp.
188–189) principles:

1. Use both knowledge in the world and knowledge
in the head. In other words, pay attention not
only to the environment or to the user, but to
both, and to how they relate. By using both, the
problem actually may be simplified.

2. Simplify the structure of tasks. For example,
reduce the number of steps or even computer
screens needed to accomplish the goal.

3. Make things visible: Bridge the gulf of
execution and the gulf of evaluation. Users
need to be able to see how to use the
technology to accomplish a goal (e.g., which
buttons does one press and in which order to
program this PCA?); if they do, then designers
have bridged the gulf of execution. They also
need to be able to see the effects of their actions
on the technology (e.g., if a nurse practitioner
prescribes a drug to treat a certain condition, the
actual patient response may not be perfectly
clear). This bridges the gulf of evaluation.

4. Get the mappings right. Here, the term mapping
is used to describe how environmental facts
(e.g., the order of light switches or variables in a
physiologic monitoring display) are accurately
depicted by the information presentation.

5. Exploit the power of constraints, both natural
and artificial. Because of where the eyes are
located in the head, humans have to turn their
heads to see what is happening behind them;
however, that is not true of all animals. As the

location of one’s eyes constrains what one can
see, so also do physical elements, social factors,
and even organizational policy constrain the way
tasks are accomplished. By taking these
constraints into account when designing
technology, it can be made easier for humans
use.

6. Design for error. Mistakes happen. Technology
should eliminate predictable errors and be
sufficiently flexible to allow humans to identify
and recover from unpredictable errors.

7. When all else fails, standardize. To get a feel for
this principle, think how difficult it is to change
from a Macintosh to a Windows environment or
from the iPhone operating system to Android.

Kirlik and Maruyama (2004) described a real-world
human–technology interface that follows Norman’s
principles. In their classic analogy, the authors
observed how a busy expert short-order cook
strategically managed to grill many hamburgers at the
same time, but each to the customer’s desired level of
doneness. The cook put those burgers that were to be
well-done on the back and far right portion of the grill,
those to be medium well-done in the center of the grill,
and those to be rare at the front of the grill, but farther
to the left. The cook moved all burgers to the left as
grilling proceeded and turned them over during their
travel across the grill. Everything the cook needed to
know was available in this simple interface. As a

human–technology interface, the grill layout was
elegant. The interface used knowledge housed both in
the environment and in the expert cook’s head; also,
things were clearly visible, both in the position of the
burgers and in the way they were moved. The process
was clearly and effectively standardized, with built-in
constraints. What might it take to create such an
intuitive human–technology interface in health care?

Several useful books have been written about effective
interface design (e.g., Burns & Hajdukiewicz, 2004;
Cooper, 1995; Mandel, 1997; McKay, 2013; Wigdor &
Wixon, 2011). In addition, a growing body of research
is exploring new ways to present clinical data that
might facilitate clinicians’ problem identification and
accurate treatment (Agency for Healthcare Research
and Quality, 2010). Just as in other industries, health
care is learning that big data can provide big insights if
it can be visualized, accessed, and meaningful (Intel IT
Center, 2013). Often, designers use graphical objects
to show how variables relate. The first to do so were
likely Cole and Stewart (1993), who used changes in
the lengths of the sides and area of a four-sided object
to show the relationship of respiratory rate to tidal
volume. Other researchers have demonstrated that
histograms and polygon displays are better than
numeric displays for detecting changes in patients’
physiologic variables (Gurushanthaiah, Weinger, &
Englund, 1995). When Horn, Popow, and Unterasinger
(2001) presented physiologic data via a single circular

object with 12 sectors (where each sector represented
a different variable), nurses reported that it was easy to
recognize abnormal conditions, but difficult to
comprehend the patient’s overall status. This kind of
graphical object approach has been most widely used
in anesthesiology, where a number of researchers
have shown improved clinician situational awareness
or problem detection time by mapping physiologic
variables onto display objects that have meaningful
shapes, such as using a bellows-like object to
represent ventilation (Agutter et al., 2003; Blike,
Surgenor, Whallen, & Jensen, 2000; Michels,
Gravenstein, & Westenskow, 1997; Zhang et al.,
2002).

Effken (2006) compared a prototype display that
represented physiologic data in a structured pictorial
format with two bar graph displays. The first bar graph
display and the prototype both presented data in the
order that experts were observed to use them. The
second bar graph display presented the data in the
way that nurses collected them. In an experiment in
which resident physicians and novice nurses used
simulated drugs to treat observed oxygenation
management problems using each display, residents’
performance was improved with the displays ordered
as experts used them, but nurses’ performance was
not improved. Instead, nurses performed better when
the variables were ordered as they were used to
collecting them, demonstrating the importance of

understanding user roles and the tasks they need to
accomplish.

Data also need to be represented in ways other than
visually. Gaver (1993) proposed that because ordinary
sounds map onto familiar events, they could be used
as icons to facilitate easier technology navigation and
use and to provide continuous background information
about how a system is functioning. In health care,
auditory displays have been used to provide clinicians
with information about patients’ vital signs (e.g., in
pulse oximetry), such as by altering volume or tone
when a significant change occurs (Sanderson, 2006).

Admittedly, auditory displays are probably more useful
for quieter areas of the hospital, such as the operating
room. Perhaps that is why researchers have most
frequently applied the approach in anesthesiology. For
example, Loeb and Fitch (2002) reported that
anesthesiologists detected critical events more quickly
when auditory information about heart rate, blood
pressure, and respiratory parameters was added to a
visual display. Auditory tones also have been combined
as earcons to represent relationships among data
elements, such as the relationship of systolic to
diastolic blood pressure (Watson & Gill, 2004).

Axiom 3: Formal Evaluation Should
Take Place Using Rigorous

Experimental or Qualitative Methods
Perhaps one of the highest accolades that any
interface can achieve is to say that it is transparent. An
interface becomes transparent when it is so easy to
use that users no longer think about it, but only about
the task at hand. For example, a transparent clinical
interface would enable clinicians to focus on patient
decisions rather than on how to access or combine
patient data from multiple sources. In Figure 11-3,
instead of the nurse interacting with the computer, the
nurse and the patient interact through the technology
interface. The more transparent the interface, the
easier the interaction should be.

Figure 11-3 Nurse–Patient Interaction Framework in
Which the Technology Supports the Interaction

Modified from Staggers, N., & Parks, P. L. (1993). Description and initial

applications of the Staggers & Parks nurse–computer interaction

framework. Computers in Nursing, 11, 282–290. Reprinted by permission

of AMIA.

Usability is a term that denotes the ease with which
people can use an interface to achieve a particular
goal. Usability of a new human–technology interface
needs to be evaluated early and often throughout its
development. Typical usability indicators include ease
of use, ease of learning, satisfaction with using,
efficiency of use, error tolerance, and fit of the system
to the task (Staggers, 2003). Some of the more
commonly used approaches to usability evaluation are
discussed next.

Surveys of Potential or Actual Users

Chernecky, Macklin, and Waller (2006) assessed
cancer patients’ preferences for website design.
Participants were asked their preferences for a number
of design characteristics, such as display color, menu
buttons, text, photo size, icon metaphor, and layout, by
selecting on a computer screen their preferences for
each item from two or three options.

Focus Groups

Typically used at the very start of the design process,
focus groups can help the designer better understand

users’ responses to potential interface designs and to
content that might be included in the interface.

Cognitive Walkthrough

In a cognitive walkthrough, evaluators assess a
paper mockup, working prototype, or completed
interface by observing the steps users are likely to take
to use the interface to accomplish typical tasks. This
analysis helps designers determine how
understandable and easy to learn the interface is likely
to be for these users and the typical tasks (Wharton,
Rieman, Lewis, & Polson, 1994).

Heuristic Evaluation

A heuristic evaluation has become the most popular
of what are called “discount usability evaluation”
methods. The objective of a heuristic evaluation is to
detect problems early in the design process, when they
can be most easily and economically corrected. The
methods are termed “discount” because they typically
are easy to do, involve fewer than 10 experts (often
experts in relevant fields such as human–computer
technology or cognitive engineering), and are much
less expensive than other methods. They are called
“heuristic” because evaluators assess the degree to
which the design complies with recognized usability
rules of thumb or principles (the heuristics), such as
those proposed by Nielsen (1994) and available on his

website
(www.useit.com/papers/heuristic/heuristic_list.html).

For example, McDaniel and colleagues (2002)
conducted a usability test of an interactive computer-
based program to encourage smoking cessation by
low-income women. As part of the initial evaluation,
healthcare professionals familiar with the intended
users reviewed the design and layout of the program.
The usability test revealed several problems with the
decision rules used to tailor content to users that were
corrected before implementation.

Formal Usability Test

Formal usability tests typically use either experimental
or observational studies of actual users using the
interface to accomplish real-world tasks. A number of
researchers use these methods. For example,
Staggers, Kobus, and Brown (2007) conducted a
usability study of a prototype electronic medication
administration record. Participants were asked to add,
modify, or discontinue medications using the system.
The time they needed to complete the task, their
accuracy in the task, and their satisfaction with the
prototype were assessed (the last criterion through a
questionnaire). Although satisfaction was high, the
evaluation also revealed design flaws that could be
corrected before implementation.

Field Study

In a field study, end users evaluate a prototype in the
actual work setting just before its general release. For
example, Thompson, Lozano, and Christakis (2007)
evaluated the use of touch-screen computer kiosks
containing child health–promoting information in
several low-income, urban community settings through
an online questionnaire that could be completed after
the kiosk was used. Most users found the kiosk easy to
use and the information it provided easy to understand.
Researchers also gained a better understanding of the
characteristics of the likely users (e.g., 26% had never
used the Internet and 48% had less than a high school
education) and the information most often accessed
(television and media use, and smoke exposure).

Dykes and her colleagues (2006) used a field test to
investigate the feasibility of using digital pen and paper
technology to record vital signs as a way to bridge an
organization from a paper to an electronic health
record. In general, satisfaction with the tool increased
with use, and the devices conformed well to nurses’
workflow. However, 8% of the vital sign entries were
recorded inaccurately because of inaccurate
handwriting recognition, entries outside the recording
box, or inaccurate data entry (the data entered were
not valid values). The number of modifications needed
in the tool and the time that would be required to make

those changes ruled out using the digital pen and
paper as a bridging technology.

Ideally, every healthcare setting would have a usability
laboratory of its own to test new software and
technology in its own setting before actual
implementation. However, this can be expensive,
especially for small organizations. Kushniruk and
Borycki (2006) developed a low-cost rapid usability
engineering method for creating a portable usability
laboratory consisting of video cameras and other
technology that one can take out of the laboratory into
hospitals and other locations to test the technology on
site using as close to a real world environment as
possible. This is a much more cost-effective and
efficient solution and makes it possible to test all
technologies before their implementation.

A Framework for Evaluation
Ammenwerth, Iller, and Mahler (2006) proposed a fit
between individuals, tasks, and technology (FITT)
model that suggests that each of these factors be
considered in designing and evaluating human–
technology interfaces. It is not enough to consider only
the user and technology characteristics; the tasks that
the technology supports must be considered as well.
The FITT model builds on DeLone and McLean’s
(1992) information success model, Davis’s (1993)
technology acceptance model, and Goodhue and

Thompson’s (1995) task technology fit model. A
notable strength of the FITT model is that it
encourages the evaluator to examine the fit between
the various pairs of components: user and technology,
task and technology, and user and task.

Johnson and Turley (2006) compared how doctors and
nurses describe patient information and found that
doctors emphasized diagnosis, treatment, and
management, whereas the nurses emphasized
functional issues. Although both physicians and nurses
share some patient information, how they thought
about patients differed. For that reason, an EHR needs
to present information (even the same information) to
the two groups in different ways.

Hyun, Johnson, Stetson, and Bakken (2009) used a
combination of two models (technology acceptance
model and task–technology fit model) to design and
evaluate an electronic documentation system for
nurses. To facilitate the design, they employed multiple
methods, including brainstorming of experts, to identify
design requirements. To evaluate how well the
prototype design fit both task and user, nurses were
asked to carry out specific tasks using the prototype in
a laboratory setting, and then complete a questionnaire
on ease of use, usefulness, and fit of the technology
with their documentation tasks. Because the
researchers engaged nurses at each step of the design

process, the result was a more useful and usable
system.

Future of the Human–
Technology Interface
Increased attention to improving the human–
technology interface through human factors
approaches has already led to significant
improvements in one area of health care:
anesthesiology. Anesthesia machines that once had
hoses that would fit into any delivery port now have
hoses that can only be plugged into the proper port.
Anesthesiologists have also been actively working with
engineers to improve the computer interface through
which they monitor their patients’ status and are among
the leaders in investigating the use of audio techniques
as an alternative way to help anesthesiologists
maintain their situational awareness. As a result of
these efforts, anesthesia-related deaths dropped from
2 in 20,000 to 1 in 200,000 in less than 10 years
(Vicente, 2004). It is hoped that continued emphasis
on human factors (Vicente, 2004) and user-centered
design (Rubin, 1994) by informatics professionals and
human–computer interactions experts will have equally
successful effects on other parts of the healthcare
system. The increased amount of informatics research
in this area is encouraging, but there is a long way to
go.

A systematic review of clinical technology design
evaluation studies (Alexander & Staggers, 2009)
found 50 nursing studies. Of those, nearly half (24)
evaluated effectiveness, fewer (16) evaluated
satisfaction, and still fewer (10) evaluated efficiency.
The evaluations were not systematic—that is, there
was no attempt to evaluate the same system in
different environments or with different users. Most
evaluations were done in a laboratory, rather than in
the setting where the system would be used. The
authors argued for a broader range of studies that use
an expanded set of outcome measures. For example,
instead of looking at user satisfaction, evaluators
should dig deeper into the design factors that led to the
satisfaction or dissatisfaction. In addition, performance
measures, such as diagnostic accuracy, errors, and
correct treatment, should be used.

Rackspace, Brauer, and Barth (2013) reported on a
social study of the human cloud formed in part by data
collected from wearable technologies; they focused on
assessing attitudes and “exploring how cloud
computing is enabling this new generation of smart
devices” (p. 2). Today, smartphones, glasses, clothing,
watches, cameras, and monitors for health or patient
tracking, to name but a few devices, are available to
this purpose.

The additional technologies that are entering our lives
on a daily basis can enhance or challenge our ability to

complete both our activities of daily living and our
professional tasks. As our home monitoring and patient
technologies increase, the user’s (patient’s or nurse’s)
ability to use the technology is paramount. No matter
who is using the technology, the human–technology
interface addresses the user’s ability and the
technology’s functionality to complete the task
demands (see Figure 11-4).

Figure 11-4 Human Technology Interface and Task
Completion

As our technologies continue to evolve, we are creating
more design issues. The proliferation of smart devices

and wearable technology brings new concerns related
to human–technology interfaces. According to Madden
(2013), wearable technologies are adding another
wrinkle into the design process—namely, human
behavior. How will someone use this technology? How
will individuals behave with it on their person? How will
they wear it? How and when will they enable and use
it? Will others be able to detect the technologies (that
is, will someone be able to wear Google Glass and
take pictures or videos of other people’s actions), and
will users be able to seamlessly move among all of the
capabilities of his or her wearable technologies? The
human–technology interface must address these
issues. There is a long way to go.

Summary
There are at least three messages the reader should
take away from the discussion in this chapter. First, if
there is to be significant improvement in quality and
safety outcomes in the United States through the use
of information technology, the designs for human–
technology interfaces must be radically improved so
that the technology better fits human and task
requirements. However, that improvement will be
possible only if clinicians identify and report problems,
rather than simply creating workarounds. That means
that each clinician has a responsibility to participate in
the design process and to report designs that do not
work.

Second, a number of useful tools are currently
available for the analysis, design, and evaluation
phases of development life cycles. They should be
used routinely by informatics professionals to ensure
that technology better fits both task and user
requirements.

Third, focusing on interface improvement using these
tools has had a huge impact on patient safety in the
area of anesthesiology and medication administration.
With increased attention from informatics professionals
and engineers, the same kind of improvement should
be possible in other areas regardless of the
technologies actually employed there. In the ideal
world, one can envision that every human–technology
interface will be designed to enhance users’ workflow,
will be as easy to use as banking ATMs, and will be
fully tested before its implementation in a setting that
mirrors the setting where it will be used.

THOUGHT-PROVOKING QUESTIONS

1. You are a member of a team that has
been asked to evaluate a prototype
smartphone-based application for
calculating drug dosages. Based on what
you know about usability testing, which
kind of test (or tests) might you do and
why?

2. Is there a human–technology interface
that you have encountered that you think
needs improvement? If you were to
design a replacement, which analysis
techniques would you choose? Why?

3. Which type of functionality and
interoperability would you want from your
smartphone, watch, clothing, glasses,
camera, and monitor? Provide a detailed
response.

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CHAPTER 12: Electronic
Security

Lisa Reeves Bertin, Kathleen Mastrian, and Dee
McGonigle

Objectives
1. Assess processes for securing electronic

information in a computer network.
2. Identify various methods of user

authentication and relate authentication
to security of a network.

3. Explain methods to anticipate and
prevent typical threats to network
security.

Key Terms
» Antivirus software

» Authentication

» Baiting

» Biometrics

» Brute force attack

» Confidentiality

» Electronic protected health information
(EPHI)

» Firewall

» Flash drives

» Hackers

» Integrity

» Intrusion detection devices

» Intrusion detection system

» Jump drives

» Malicious code

» Malicious insiders

» Malware

» Mask

» Negligent insider

» Network

» Network accessibility

» Network availability

» Network security

» Password

» Phishing

» Proxy server

» Radio frequency identification (RFID)

» Ransomware

» Scareware

» Secure information

» Security breaches

» Shoulder surfing

» Social engineering

» Spear phishing

» Spyware

» Thumb drives

» Trojan horses

» Viruses

» Worms

» Zero day attack

Introduction
In addition to complying with federal HIPAA and
HITECH guidelines regarding the privacy of patient
information, healthcare systems need to be vigilant in
the way that they secure information and manage
network security. Mowry and Oakes (n.d.) discuss the
vulnerability of electronic health records to data
breaches. They suggest that as many as 77 persons
could view a patient’s record during a hospital stay. It is
critical for information technology (IT) policies and
procedures to ensure appropriate access by clinicians
and to protect private information from inappropriate
access. However, authentication procedures can be
cumbersome and time consuming, thus reducing
clinician performance efficiency.

Physicians spend on average 7 minutes per patient
encounter, with nearly 2 minutes of that time being
devoted to managing logins and application navigation.
Likewise, an average major healthcare provider must
deal with more than 150 applications—most requiring
different user names and passwords—making it difficult
for caregivers to navigate and receive contextual
information. Healthcare organizations must strike the
right balance, in terms of simplifying access to core
clinical datasets while maximizing the time providers

can interact with patients without jeopardizing data
integrity and security (Mowry & Oakes, n.d., para. 7).

This chapter explores use of information and
processes for securing information in a health system
computer network.

Securing Network Information
Typically, a healthcare organization has computers
linked together to facilitate communication and
operations within and outside the facility. This is
commonly referred to as a network. The linking of
computers together and to the outside world creates
the possibility of a breach of network security and
exposes the information to unauthorized use. With the
advent of smart devices, managing all of these risks
has become a nightmare for some institutions’ security
processes. In the past, stationary devices or computers
resided within healthcare facilities. Today, smart
devices travel in and out of healthcare organizations
with patients, family members, and other visitors, as
well as employees—both staff and healthcare
providers alike. According to Sullivan (2012), “Even as
they promise better health and easier care delivery,
wireless medical devices (MDs) carry significant
security risks. And the situation is only getting trickier
as more and more MDs come with commercial
operating systems that are both Internet-connected
and susceptible to attack” (para. 1).

The three main areas of secure network information
are (1) confidentiality, (2) availability, and (3)
integrity. An organization must follow a well-defined
policy to ensure that private health information remains
appropriately confidential. The confidentiality policy
should clearly define which data are confidential and
how those data should be handled. Employees also
need to understand the procedures for releasing
confidential information outside the organization or to
others within the organization and know which
procedures to follow if confidential information is
accidentally or intentionally released without
authorization. In addition, the organization’s
confidentiality policy should contain consideration for
elements as basic as the placement of monitors so that
information cannot be read by passersby. Shoulder
surfing, or watching over someone’s back as that
person is working, is still a major way that
confidentiality is compromised.

Availability refers to network information being
accessible when needed. This area of the policy tends
to be much more technical in nature. An accessibility
policy covers issues associated with protecting the key
hardware elements of the computer network and the
procedures to follow in case of a major electric outage
or Internet outage. Food and drinks spilled onto
keyboards of computer units, dropping or jarring
hardware, and electrical surges or static charges are all
examples of ways that the hardware elements of a

computer network may be damaged. In the case of an
electrical outage or a weather-related disaster, the
network administrator must have clear plans for data
backup, storage, and retrieval. There must also be
clear procedures and alternative methods of ensuring
that care delivery remains largely uninterrupted.

Another way organizations protect the availability of
their networks is to institute an acceptable use policy.
Elements covered in such policy could include which
types of activities are acceptable on the corporate
network. For example, are employees permitted to
download music at work? Restricting downloads is a
very common way for organizations to prevent viruses
and other malicious code from entering their networks.
The policy should also clearly define which activities
are not acceptable and identify the consequences for
violations.

The last area of information security is integrity.
Employees need to have confidence that the
information they are reading is true. To accomplish this,
organizations need clear policies to clarify how data
are actually inputted, determine who has the
authorization to change such data, and track how and
when data are changed. All three of these areas use
authorization and authentication to enforce the
corporate policies. Access to networks can easily be
grouped into areas of authorization (e.g., users can be
grouped by job title). For example, anyone with the job

title of “floor supervisor” might be authorized to change
the hours worked by an employee, whereas an
employee with the title of “patient care assistant”
cannot make such changes.

Authentication of Users
Authentication of employees is also used by
organizations in their security policies. The most
common ways to authenticate rely on something the
user knows, something the user has, or something the
user is (Figure 12-1).

A © Photos.com

B

C © Gary James Calder/Shutterstock

Figure 12-1 Ways to Authenticate Users

A. An ID badge, B. Examples of weak and strong passwords, C. A finger

on a biometric scanner.

Something a user knows is a password. Most
organizations today enforce a strong password policy,
because free software available on the Internet can
break a password from the dictionary very quickly.
Strong password policies include using combinations of
letters, numbers, and special characters, such as plus
signs and ampersands. Some organizations are
suggesting the use of passphrases to increase the
strength of a password. See Box 12-1 for an overview
of best practices to create strong passwords. Policies
typically include the enforcement of changing
passwords every 30 or 60 days. Passwords should
never be written down in an obvious place, such as a
sticky note attached to the monitor or under the
keyboard.

BOX 12-1 BEST PRACTICES FOR

CREATING AND MANAGING

PASSWORDS

DO
Review the specific system guidelines for
users—most will have information on
password parameters and allowable
characters.
Use a combination of letters, numbers,
special characters (!, $, %, &, *) and upper-

and lowercase.
Longer passwords are harder to crack.
Consider at least 8 characters if the system
allows.
Choose a password that is based on a
phrase: Use portions or abbreviations of the
words in the phrase, or use substitutions
(e.g., $ for S, 4 for “for”) to create the
password. Example phrase: “Lucy in the Sky
with Diamonds” was released in 1967;
example password: LUit$wdia67.
Think carefully about the password and
create something that is easy for you to
remember.
Change your password frequently, and do so
immediately if you believe your system or
email has been hacked.
Consider using a password manager
program to help you create strong
passwords and store them securely.

Do NOT:
Share your password with anyone.
Post your passwords in plain sight.
Use dictionary words or any personal
characteristics (your name, phone number,
or birthday).
Use a string of numbers.
Use the same password for multiple sites.

Data from Pennsylvania State Information
Technology Services. (2015). Password best
practices. Retrieved from
http://its.psu.edu/legacy/be-safe/password-
best-practices.html

The second area of authentication is something the
user has, such as an identification (ID) card. ID cards
can be magnetic, similar to a credit card, or have a
radio frequency identification (RFID) chip embedded
into the card.

The last area of authentication is biometrics. Devices
that recognize thumb prints, retina patterns, or facial
patterns are available. Depending on the level of
security needed, organizations commonly use a
combination of these types of authentication.

Threats to Security
The largest benefit of a computer network is the ability
to share information. However, organizations need to
protect that information and ensure that only authorized
individuals have access to the network and the data
appropriate to their role. Threats to data security in
healthcare organizations are becoming increasingly
prevalent. A nationwide survey by the Computing
Technology Industry Association (CompTIA) found that
human error was responsible for more than half of
security breaches. Human error was categorized as

failure to follow policies and procedures, general
carelessness, lack of experience with websites and
applications, and being unaware of new threats
(Greenberg, 2015). According to Degaspari (2010),
“Given the volume of electronic patient data involved,
it’s perhaps not surprising that breaches are occurring.
According to the Department of Health and Human
Services’ Office of Civil Rights (OCR), 146 data
breaches affecting 500 or more individuals occurred
between December 22, 2009, and July 28, 2010. The
types of breaches encompass theft, loss, hacking, and
improper disposal; and include both electronic data and
paper records” (para. 4). The Fifth Annual Benchmark
Study on Privacy & Security of Healthcare Data
(Ponemon Institute, 2015) reported that “[m]ore than
90 percent of healthcare organizations represented in
this study had a data breach, and 40 percent had more
than five data breaches over the past two years” (para.
3). Interestingly, the most common type of data breach
was related to a criminal attack on the healthcare
organization (up 125% in the last 5 years). Key terms
related to criminal attacks are brute force attack
(software used to guess network passwords) and zero
day attack (searching for and exploiting software
vulnerabilities). Of the intentional data breaches (as
opposed to unintentional), “45 percent of healthcare
organizations say the root cause of the data breach
was a criminal attack and 12 percent say it was due to
a malicious insider” (Ponemon Institute, para. 4). That
leaves nearly 43% of data breaches in the

unintentional category. The Healthcare Information and
Management Systems Society (HIMSS) 2015 survey
reported the negligent insider as the most common
source of a security breach. Examples of
unintentional/negligent breaches include lost or stolen
devices, or walking away from a workstation without
logging off. If you use a device in your work and it is
lost or stolen, or you violate policy by walking away
from a workstation without logging off, this may be
considered negligence and you may be subject to
discipline or even lose your job. An interesting example
of an unintentional data breach was reported on the
OCR website: A company leased photocopier
equipment and returned it without erasing the
healthcare data stored on the copier hard drive,
resulting in a settlement of over $1.2 million (U.S.
Department of Health and Human Services, n.d.).
Healthcare organizations need to be proactive in
anticipating the potential for and preventing security
breaches.

The first line of defense is strictly physical. A locked
office door, an operating system that locks down after 5
minutes of inactivity, and regular security training
programs are extremely effective in this regard. Proper
workspace security discipline is a critical aspect of
maintaining security. Employees need to be properly
trained to be aware of computer monitor visibility,
shoulder surfing, and policy regarding the removal of
computer hardware. A major issue facing organizations

is removable storage devices (Figure 12-2). CD/DVD
burners, jump drives, flash drives, and thumb drives
(which use USB port access) are all potential security
risks. These devices can be slipped into a pocket and,
therefore, are easily removed from the organization.
One way to address this physical security risk is to limit
the authorization to write files to a device.
Organizations are also turning off the CD/DVD burners
and USB ports on company desktops.

Figure 12-2 A Removable Storage Device

© Alex Kotlov/Shutterstock

The most common security threats a corporate network
faces are hackers, malicious code (spyware,
adware, ransomware, viruses, worms, Trojan
horses), and malicious insiders. Acceptable use
policies help to address these problems. For example,

employees may be restricted from downloading files
from the Internet. Downloaded files, including email
attachments, are the most common way viruses and
other malicious codes enter a computer network.
Network security policies typically prohibit employees
from using personal CDs/DVDs and USB drives,
thereby preventing the transfer of malicious code from
a personal computer to the network.

Let’s look more closely at some of these common
network security threats. We typically think of hackers
as outsiders who attempt to break into a network by
exploiting software and network vulnerabilities, and
indeed these black hat (malicious) hackers (crackers)
do exist. However, more organizations are looking to
employ ethical hackers (white hat hackers), those who
are skilled at looking for and closing network security
vulnerabilities (Caldwell, 2011).

Spyware and adware are normally controlled in a
corporate network by limiting the functions of the
browsers used to surf the Internet. For example, the
browser privacy options can control how cookies are
used. A cookie is a very small file written to the hard
drive of a computer whose user is surfing the Internet.
This file contains information about the user. For
example, many shopping sites write cookies to the
user’s hard drive containing the user’s name and
preferences. When that user returns to the site, the site
will greet her by name and list products in which she is

possibly interested. Weather websites send cookies to
users’ hard drives with their ZIP code so that when
each user returns to that site, the local weather
forecast is immediately displayed. On the negative
side, cookies can follow the user’s travels on the
Internet. Marketing companies use spying cookies to
track popular websites that could provide a return on
advertising expenditures. Spying cookies related to
marketing typically do not track keystrokes in an
attempt to steal user IDs and passwords; instead, they
simply track which websites are popular, and these
data are used to develop advertising and marketing
strategies. Nurse informaticists exploring new
healthcare technologies on the Internet may find that
ads for these technologies begin to pop up the next few
times they are on the Internet. Spyware that does steal
user IDs and passwords contains malicious code that
is normally hidden in a seemingly innocent file
download. This threat to security explains why
healthcare organizations typically do not allow
employees to download files. The rule of thumb to
protect the network and one’s own computer system is
to only download files from a reputable site that
provides complete contact information. Be aware that
malicious code is sometimes hidden in an email link or
in a file sent by a trusted contact whose email has
been hacked. If you are not expecting a file from an
email contact, or if you receive an email with only a link
in it—resist the urge to download or click!

A relatively new threat to healthcare organizations is
ransomware—malicious code that blocks the
organization from using their computer systems until a
ransom is paid to the hacker. Consider this recent case
of ransomware intrusion:

In February 2016 a hospital in Los
Angeles made headlines for giving in to
the ransom demand of hackers who used
encryption to cripple its internal computer
network, including electronic patient
records, for three weeks, causing it to
lose patients and money. After the
hackers initially demanded $3.4 million,
the hospital paid them $17,000. In
explaining his decision, Allen Stefanek,
president of Hollywood Presbyterian
Medical Center, said, “The quickest and
most efficient way to restore our systems
and administrative functions was to pay
the ransom.” The money was transferred
through Bitcoin, a cryptocurrency that
permits anonymity. (Goldsborough,
2016, para. 2–3)

In addition to strict policies related to network security,
organizations may also use such devices as firewalls
(covered in the next section) and intrusion detection
devices to protect from hackers. Protect yourself at

home by ensuring that you have an updated version of
antivirus software, be wary of unusual emails, and
develop strong passwords and change them frequently.
If your email is hacked, report it to the proper
authorities as soon as possible, warn your contacts
that you have been hacked, change your password,
and check to see that your antivirus software is up to
date.

Another huge threat to corporate security is social
engineering, or the manipulation of a relationship
based on one’s position (or pretend position) in an
organization. For example, someone attempting to
access a network might pretend to be an employee
from the corporate IT office, who simply asks for an
employee’s user ID and password. The outsider can
then gain access to the corporate network. Once this
access has been obtained, all corporate information is
at risk. A second example of social engineering is a
hacker impersonating a federal government agent.
After talking an employee into revealing network
information, the hacker has an open door to enter the
corporate network. A related type of social engineering
is phishing. Phishing is an attempt to steal information
by manipulating the recipient of an email or phone call
to provide passwords or other private information. Box
12-2 contains an example of a phishing email and tips
for identifying phishing scams.

BOX 12-2 IDENTIFYING PHISHING

SCAMS

Example of a Phishing Scam Email

Check suspicious emails for grammar and
spelling errors, generic greetings (User, Dear,
Dearest, etc.), requests for immediate action, or
requests for personal information (passwords,
bank account numbers). Some phishing emails
may appear to come from your bank or other
trusted organization. Think carefully about why a
seemingly legitimate organization might be
asking for information they should already have,
or ask yourself why they might need to know
what they are asking for. Be aware of your
organization’s procedures for reporting phishing
scams, and do so immediately.

Data from Pennsylvania State University Office
of Information Security. (2016). Stop phishing
scams. Retrieved from
http://phishing.psu.edu/what-is-phishing

Additional types of social engineering schemes include
spear phishing, which is a more specifically targeted
scheme where the attacker takes advantage of contact
information provided in an organization’s directory and
tailors the scam email to a specific person; baiting,
where a malware-infected USB flash drive is left in a
public area, thus tricking the finder into loading it to
identify its owner; and scareware, where the scam
email reports that the user has been hacked and tricks
them into giving the hacker remote access to the
computer to “fix” it (TechTarget, n.d.).

Another example of an important security threat to a
corporate network is the malicious insider. This person
can be a disgruntled or recently fired employee whose
rights of access to the corporate network have not yet
been removed. In the case of a recently fired
employee, his or her network access should be
suspended immediately upon notice of termination. To
avoid the potentially hazardous issues created by
malicious insiders, healthcare organizations need
some type of policy and specific procedures to monitor
employee activity to ensure that employees carry out
only those duties that are part of their normal job.
Separation of privileges is a common security tool; no
one employee should be able to complete a task that
could cause a critical event without the knowledge of
another employee. For example, the employee who
processes the checks and prints them should not be
the same person who signs those checks. Similarly, the

employee who alters pay rates and hours worked
should be required to submit a weekly report to a
supervisor before the changes take effect. Software
that can track and monitor employee activity is also
available. This software can log which files an
employee accesses, whether changes were made to
files, and whether the files were copied. Depending on
the number of employees, organizations may also
employ a full-time electronic auditor who does nothing
but monitor activity logs. More than half of healthcare
organizations have hired full-time employees to provide
network security (HIMSS, 2015). Additional strategies
for securing networks suggested in this most recent
HIMSS survey were mock cyberdefense exercises,
sharing information between and among healthcare
organizations, monitoring vendor intelligence feeds,
and subscribing to security alerts and tips from
US_CERT (United States Computer Emergency
Readiness Team).

Security Tools
A wide range of tools are available to an organization
to protect the organizational network and information.
These tools can be either a software solution, such as
antivirus software, or a hardware tool, such as a
proxy server. Such tools are effective only if they are
used along with employee awareness training. The
2015 HIMSS Cybersecurity Survey results indicate that
an average of 11 different software tools were used by

respondents to provide network security, with antivirus
technology, firewalls, and data encryption as the most
common tools.

For example, email scanning is a commonly used
software tool. All incoming email messages are
scanned to ensure they do not contain a virus or some
other malicious code. This software can find only
viruses that are currently known, so it is important that
the virus software be set to search for and download
updates automatically. Organizations can further
protect themselves by training employees to never
open an email attachment unless they are expecting
the attachment and know the sender. Even IT
managers have fallen victim to email viruses that sent
infected emails to everyone in their address book.
Employees should be taught to protect their
organization from new viruses that may not yet be
included in their scanning software by never opening
an email attachment unless the sender is known and
the attachment is expected. Email scanning software
and antivirus software should never be turned off, and
updates should be installed at least weekly—or, ideally,
daily. Software is also available to scan instant
messages and to delete automatically any spam email.

Many antivirus and adware software packages are
available for fees ranging from free to more than $25
per month (for personal use) to several thousands of
dollars per month (to secure an organization’s

network). The main factors to consider when
purchasing antivirus software are its effectiveness (i.e.,
the number of viruses it has missed), the ease of
installation and use, the effectiveness of the updates,
and the help and user support available. Numerous
websites compare and contrast the most recent
antivirus software packages. Be aware, however, that
some of these sites also sell antivirus software, so they
may present biased information.

Firewalls are another tool used by organizations to
protect their corporate networks when they are
attached to the Internet. A firewall can be either
hardware, software, or a combination of both that
examines all incoming messages or traffic to the
network. The firewall can be set up to allow only
messages from known senders into the corporate
network. It can also be set up to look at outgoing
information from the corporate network. If the message
contains some type of corporate secret, the firewall
may prevent the message from leaving. In essence,
firewalls serve as electronic security guards at the gate
of the corporate network.

Proxy servers also protect the organizational network.
Proxy servers prevent users from directly accessing
the Internet. Instead, users must first request passage
from the proxy server. The server looks at the request
and makes sure the request is from a legitimate user
and that the destination of the request is permissible.

For example, organizations can block requests to view
a website with the word “sex” in the title or the actual
uniform resource locator of a known pornography site.
The proxy server can also lend the requesting user a
mask to use while he or she is surfing the Web. In this
way, the corporation protects the identity of its
employees. The proxy server keeps track of which
employees are using which masks and directs the
traffic appropriately.

With hacking becoming more common, healthcare
organizations must have some type of protection to
avoid this invasion. An intrusion detection system
(both hardware and software) allows an organization to
monitor who is using the network and which files that
user has accessed. Detection systems can be set up to
monitor a single computer or an entire network.
Corporations must diligently monitor for unauthorized
access of their networks. Anytime someone uses a
secured network, a digital footprint of all of the user’s
travels is left, and this path can be easily tracked by
electronic auditing software.

Offsite Use of Portable Devices
Offsite uses of portable devices, such as laptops,
tablets, home computing systems, smartphones, smart
devices, and portable data storage devices, can help to
streamline the delivery of health care. For example,
home health nurses may need to access electronic

protected health information (EPHI) via a wireless
laptop connection during a home visit, or a physician
might use a smartphone to get specific patient
information related to a prescription refill in response to
a patient request. These mobile devices are invaluable
to healthcare efficiency and responsiveness to patient
need in such cases. At the very least, however,
agencies should require data encryption when EPHI is
being transmitted over unsecured networks or
transported on a mobile device as a way of protecting
sensitive information. Hotspots provided by companies,
such as coffee shops or restaurants, and by airports
are not secured networks. Virtual private networks
(VPNs) must be used to ensure that all data
transmitted on unsecured networks are encrypted. The
user must log into the VPN to reach the organization’s
network.

Only data essential for the job should be maintained on
the mobile device; other nonclinical information, such
as Social Security numbers, should never be carried
outside the secure network. Some institutions make
use of thin clients, which are basic interface portals that
do not keep secure information stored on them.
Essentially, users must log in to the network to get the
data they need. Use of thin clients may be problematic
in patient care situations where the user cannot access
the network easily. For example, some rural areas of
the United States do not have wireless or cellular data
coverage. In these instances, private health information

may need to be stored in a clinician’s laptop or tablet.
This is comparable to home health nurses carrying
paper charts in their cars to make home visits, and it
entails the same responsibilities accompanying such
use of private information outside the institution’s walls.

What happens if one of these devices is lost or stolen?
The agency is ultimately responsible for the integrity of
the data contained on these devices and is required by
HIPAA regulations (U.S. Department of Health and
Human Services, 2006) to have policies in place
covering such items as appropriate remote use,
removal of devices from their usual physical location,
and protection of these devices from loss or theft.
Simple rules, such as covering laptops left in a car and
locking car doors during transport of mobile devices
containing EPHI, can help to deter theft. If a device is
lost or stolen, the agency must have clear procedures
in place to help ensure that sensitive data are not
released or used inappropriately. Software packages
that provide for physical tracking of the static and
mobile computer inventory including laptops,
smartphones, and tablets are being used more widely
and can assist in the recovery of lost or stolen devices.
In addition, some software that allows for remote data
deletion (data wipe) in the event of theft or loss of a
mobile device can be invaluable to the agency in
preventing the release of EPHI.

If a member of an agency is caught accessing EPHI

inappropriately or steals a mobile device, the sanctions
should be swift and public. Sanctions may range from a
warning or suspension with retraining to termination or
prosecution, depending on the severity of the security
breach. The sanctions must send a clear message to
all that protecting EPHI is serious business.

The U.S. Department of Health and Human Services
(n.d.) suggests the following strategies for managing
remote access:

Restricting remote access to computers owned or
configured by your organization
Disallowing administrator privileges on remote
access computers
Placing restrictions in the VPN and remote access
policies
Configuring the VPN to operate in a “sandbox” or
virtual environment that isolates the session from
other software running on the remote machine
Educating users about safe computing practices in
remote locations (para. 8)

To protect our patients and their data, nurses must
consider the impact of wireless mobile devices (see
Box 12-3). Data can be stolen by an employee very
easily through the use of email or file transfers.

Malware, or malicious code that infiltrates a network,
can collect easily accessible data. One of the evolving

issues is lost or stolen devices that can provide a
gateway into a healthcare organization’s network and
records. When the device is owned by the employee,
other issues arise as to how the device is used and
secured.

The increase in cloud computing has also challenged
our personal and professional security and privacy.
Cloud computing refers to storing and accessing data
and computer programs on the Internet, rather than the
local hard drive of a computer. Common examples of
cloud computing for personal use include Google
Drive, Apple iCloud, and Amazon. Cloud computing
allows for easy syncing of separate devices to promote
sharing and collaboration (Griffith, 2016). According to
Jansen and Grance (2011), cloud computing “promises
to have far reaching effects on the systems and
networks of federal agencies and other organizations.
Many of the features that make cloud computing
attractive, however, can also be at odds with traditional
security models and controls” (p. vi). Healthcare
organizations are moving to the cloud because cloud
computing tends to be cheaper and faster, offers more
flexibility for work location, provides nearly immediate
disaster recovery, supports collaboration, provides
security, and offers frequent software updates
(Salesforce UK, 2015). However, there are important
security concerns related to cloud computing in health
care. Guccione (2015) offers these important

considerations for maintaining security in a cloud
environment:

BOX 12-3 POKEMON TARGETS

HOSPITAL

Informatics nurse specialists must be aware of
the uses of portable devices. In 2016, one
hospital in the Pittsburgh area was a site of a
popular game, and the administration was upset
because it creates a privacy issue for people
using their hospital as a search site. This
hospital actually contacted the game developer
to be removed from their game.

Hospitals must always be concerned about
privacy and safety issues within their control, but
also be on the alert for those outside their
control, such as the Pokemon Go game.
Pittsburgh’s Action News 4, Marcie Cipriani,
reported that Pokemon Go used West Penn
Hospital, part of Allegheny Health Network in
Pittsburgh, as a real-world location in the game.
The game utilizes enhanced reality, which
allows players to combine images from the real
world with those of the game. The Allegheny
Health Network officials stated that the exciting,
interactive game created concerns when it
brought players inside their hospital. They say
hunting Pokemon at the hospital created a

patient privacy issue and a safety concern.
Administrators warned those who are playing to
stay out of their hospitals and contacted the
game’s developer, who agreed to remove their
hospitals from the app. They have asked their
employees to be on the lookout for anyone
playing the app while they are walking around
the hospital and to contact security if they see
Pokemon Go players.

Data from Cipriani, M. (2016, July 30). Pokemon
Go targets Allegheny Health System hospitals in
Pittsburgh. Pittsburgh’s Action News 4.
Retrieved from
http://www.wtae.com/news/pokemon-go-
players-not-welcome-at-allegheny-health-
network-hospitals/40946828

First, a cloud service should be have
client-side encryption of data, which both
protects files on the local hard drive as
well as in the cloud. Second, a secure
cloud service should offer multi-factor
authentication to add an extra layer of
access control for all users. Finally, a
secure cloud provider should either
provide data loss prevention tools to
protect the stored data or allow an
organization to extend its DLP protocols
to the cloud. In both cases, the

organization is alerted immediately the
moment a user attempts to send sensitive
files to an outside source. (para. 5)

It is clear that healthcare organizations need to be
extra vigilant about their data security when using
cloud computing. However, as we emphasized several
times in this chapter, employee training on security
measures may be the most important defense,
because “the latest techniques for cyber theft are much
less about breaching networks from the outside, such
as through the cloud service, than they are exploiting
holes inside an organization, particularly from careless
employees” (Guccione, 2015, para. 9).

Summary
Technology changes so quickly that even the most
diligent user will likely encounter a situation that could
constitute a threat to his or her network. Organizations
must provide their users with the proper training to help
them avoid known threats and—more importantly—be
able to discern a possible new threat. Consider that 10
years ago wireless networks were the exception to the
rule, where today access to wireless networks is
almost taken for granted. How will computer networks
be accessed 10 years from now? The most important
concept to remember from this chapter is that the only
completely safe network is one that is turned off.

Network accessibility and network availability are
necessary evils that pose security risks. The
information must be available to be accessed, yet
remain secured from hackers, unauthorized users, and
any other potential security breaches. As the cloud
expands, so do the concerns over security and privacy.
In an ideal world, everyone would understand the
potential threats to network security and would
diligently monitor and implement tools to prevent
unauthorized access of their networks, data, and
information.

THOUGHT-PROVOKING QUESTIONS

1. Sue is a chronic obstructive pulmonary
disorder clinic nurse enrolled in a
master’s education program. She is
interested in writing a paper on the factors
that are associated with poor compliance
with medical regimens and associated
repeat hospitalization of chronic
obstructive pulmonary disorder patients.
She downloads patient information from
the clinic database to a thumb drive that
she later accesses on her home
computer. Sue understands rules about
privacy of information and believes that
because she is a nurse and needs this
information for a graduate school
assignment, she is entitled to the

information. Is Sue correct in her
thinking? Describe why she is or is not
correct.

2. The nursing education department of a
large hospital system has been
centralized; as a consequence, the nurse
educators are no longer assigned to one
hospital but must now travel among all of
the hospitals. They use their smartphones
to interact and share data and
information. What are the first steps you
would take to secure these transactions?
Describe why each step is necessary.

3. Research cloud computing in relation to
health care. What are the major security
and privacy challenges? Please choose
three and describe them in detail.

References
Caldwell, T. (2011). Ethical hackers:

Putting on the white hat. Network
Security, 2011(7), 10–13.
doi:10.1016/S1353-4858(11)70075-7

Degaspari, J. (2010). Staying ahead of the
curve on data security. Healthcare
Informatics, 27(10), 32–36.

Goldsborough, R. (2016). Protecting
yourself from ransomware. Teacher
Librarian, 43(4), 70–71.

Griffith, E. (2016). What is cloud
computing? PCMag. Retrieved from
http://www.pcmag.com/article2/0,2817,2372163,00.asp

Greenberg, A. (2015). Human error cited
as leading contributor to breaches,
study shows. SC Magazine. Retrieved
from
http://www.scmagazine.com/study-
find-carelessness-among-top-
human-errors-affecting-
security/article/406876

Guccione, D. (2015). Is the cloud safe for
healthcare? Healthcare Informatics.
Retrieved from
http://www.healthcare-
informatics.com/article/cloud-safe-
healthcare

Health Information and Management
Systems Society (HIMSS). (2015)
2015 HIMSS Cybersecurity Survey.
Retrieved from
http://www.himss.org/2015-
cybersecurity-survey/executive-
summary

Jansen, W., & Grance, T. (2011). National
Institute of Standards and Technology
(NIST): Guidelines on security and
privacy in public cloud computing.
Retrieved from
https://cloudsecurityalliance.org/wp-
content/uploads/2011/07/NIST-Draft-
SP-800-144_cloud-computing.pdf

Mowry, M., & Oakes, R. (n.d.). Not too
tight, not too loose. Healthcare
Informatics, Healthcare IT Leadership,
Vision & Strategy. Retrieved from
http://www.healthcare-
informatics.com/article/not-too-
tight-not-too-loose

Ponemon Institute. (2015, May). Fifth
annual benchmark study on privacy &

security of healthcare data. Retrieved
from
http://media.scmagazine.com/documents/121/healthcare_privacy_security_be_30019.pdf

Salesforce UK. (2015). Why move to the
cloud? Ten benefits of cloud
computing. Retrieved from
https://www.salesforce.com/uk/blog/2015/11/why-
move-to-the-cloud-10-benefits-of-
cloud-computing.html

Sullivan, T. (2012). Government health IT:
DHS lists top 5 mobile medical device
security risks. Retrieved from
http://www.govhealthit.com/news/dhs-
lists-top-5-mobile-device-security-
risks

TechTarget (n.d.). Social engineering.
Retrieved from
http://searchsecurity.techtarget.com/definition/social-
engineering

U.S. Department of Health and Human
Services. (2006). HIPAA security
guidance. Retrieved from
https://www.hhs.gov/sites/default/files/ocr/privacy/hipaa/administrative/securityrule/remoteuse.pdf

U.S. Department of Health and Human
Services. (n.d.). Implement privacy and
security protection measures.
Retrieved from
http://www.hrsa.gov/healthit/toolbox/healthitimplementation/implementationtopics/ensureprivacysecurity/ensureprivacysecurity_9.html

CHAPTER 13: Workflow
and Beyond Meaningful
Use

Dee McGonigle, Kathleen Mastrian, and Denise
Hammel-Jones

Objectives
1. Provide an overview of the purpose of

conducting workflow analysis and design.
2. Deliver specific instructions on workflow

analysis and redesign techniques.
3. Cite measures of efficiency and

effectiveness that can be applied to
redesign efforts.

4. Explore meaningful use and beyond with
the Medicare Access and Summary CHIP
Reauthorization Act.

Key Terms
» Alternative Payment Models (APMs)

» American Recovery and Reinvestment
Act (ARRA)

» Bar-code medication administration
(BCMA)

» Clinical transformation

» Computerized provider order entry
(CPOE)

» Electronic health records (EHRs)

» Events

» Health information exchange (HIE)

» Health information technology (HIT)

» Information systems

» Interactions

» Lean

» Meaningful use (MU)

» Medical home models

» Medicare Access and CHIP
Reauthorization Act of 2015 (MACRA)

» Merit-Based Incentive Payment System
(MIPS)

» Metrics

» Process analysis

» Process map

» Process owners

» Qualified Clinical Data Registries
(QCDRs)

» Quality

» Quality payment program (QPP)

» Six Sigma

» Tasks

» Work process

» Workflow

» Workflow analysis

Introduction
The healthcare environment has grown more complex
and continues to evolve every day. Unfortunately, the
complexities that help clinicians to deliver better care

and improve patient outcomes also take a toll on the
clinicians themselves. This toll is exemplified through
hours spent learning new technology, loss in
productivity as the user adjusts and adapts to new
technology, and unintended workflow consequences
from the use of technology.

Despite the perceived negative downstream effects to
end users and patients as a result of technology, this
very same technology can improve efficiency and yield
a leaner healthcare environment. The intent of this
chapter is to outline the driving forces that create the
need to redesign workflow as well as to elucidate what
the nurse needs to know about how to conduct
workflow redesign, measure the impact of workflow
changes, and assess the impact of meaningful use.

Workflow Analysis Purpose
According to the American Association for Justice
(2016),

Research has confirmed that 440,000
people die every year because of
preventable medical errors. That is
equivalent to almost the entire population
of Atlanta, Georgia dying from a medical
error each year. Preventable medical
errors are the third leading cause of
death in the United States and cost our

country tens of billions of dollars a year.
(para. 1)

Not only is there an impact on patients and their
families from these errors, but there is also a significant
financial impact on healthcare organizations. Clearly,
we must minimize these errors, and one of the most
important tools for this purpose is the use of electronic
health records and information systems to provide
point-of-care decision support and automation. The key
point is that most of these errors are preventable and
we must find ways to prevent them.

Technology can provide a mechanism to improve care
delivery and create a safer patient environment,
provided it is implemented appropriately and considers
the surrounding workflow. In an important article by
Campbell, Guappone, Sittig, Dykstra, and Ash (2009),
the authors suggested that technology implemented
without consideration of workflow can provide greater
patient safety concerns than no technology at all.
Computerized provider order entry (CPOE) causes
us to focus more specifically on workflow
considerations. These workflow implications are
referred to as the unintended consequences of CPOE
implementation; they are just some of the effects of
poorly implemented technology. The Healthcare
Information Management Systems Society (HIMSS,
2010) ME-PI Toolkit addressed workflow redesign and

considered why it is so critical to successful technology
implementations. Thompson, Kell, Shetty, and
Banerjee (2016) stated “By partnering clinicians with
informaticists we strove to leverage the power of the
electronic medical record (EMR) to reduce heart failure
readmissions and improve patient transitions back to
the community” (p. 380). They concluded that
“Partnering with clinical informatics enabled the
multidisciplinary team to leverage the power of the
EMR in supporting and tracking new clinical workflows
that impact patient outcomes” (p. 380). This
multidisciplinary team believed that their success could
reshape how healthcare providers facilitate patient
discharge and the transition home. Leveraging the
multidisciplinary team and EMR could provide a model
for patient-centered and cost-effective care that could
extend beyond their patients with heart failure.

Technology is recognized to have a potentially positive
effect on patient outcomes. Nevertheless, even with
the promise of improving how care is delivered,
adoption of technology has been slow. The cost of
technology solutions such as CPOE, barcode
medication administration (BCMA), and electronic
health records (EHRs) remain staggeringly high. The
cost of technology, coupled with the lengthy timelines
required to develop and implement such technology,
has put this endeavor out of reach for many healthcare
organizations. In addition, upgrades or enhancements
to the technology are often necessary either mid-

implementation or shortly after a launch, leaving little
time to focus efforts on the optimization of the
technology within the current workflow. Furthermore,
the existence of technology does not in itself guarantee
that it will be used in a manner that promotes better
outcomes for patients.

Given the sluggish adoption of technology, in 2009 the
U.S. government took an unprecedented step when it
formally recognized the importance of health
information technology (HIT) for patient care
outcomes. As a result of the provisions of American
Recovery and Reinvestment Act (ARRA), healthcare
organizations can qualify for financial incentives based
on the level of meaningful use achieved. Meaningful
use (MU) refers to the rules and regulations
established by the ARRA. The three stages of MU
were part of an EHR incentive program. During stage
1, the focus was on data capturing and sharing. Stage
2 focused on advanced clinical processes, and stage 3
sought to improve outcomes. Stage 1 was initiated
during 2011–2012, stage 2 began in 2014, and stage 3
was to be launched in 2016/2017 and was intended to
last through 2019 and beyond (Centers for Medicare &
Medicaid Services [CMS], 2016a). However, with the
new goal of paying for value and better care, the
Medicare Access and CHIP Reauthorization Act of
2015 (MACRA) reformed Medicare payments by
making changes that created a quality payment
program (QPP) to replace the hodgepodge system of

Medicare reporting programs (CMS, 2016b; see
Figure 13-1). The MACRA QPP has two paths—Merit-
Based Incentive Payment System (MIPS) or
Alternative Payment Models (APMs)—that will be in
effect through 2021 and beyond (CMS, 2016b). The
MACRA requirements for the measure development
plan consist of the following:

Figure 13-1 MACRA

Multipayer applicability
Coordination and sharing across measure
developers
Clinical practice guidelines
Evidence base for non-endorsed measures
Gap analysis
Quality domains and priorities
Applicability of measures across healthcare settings
Clinical practice improvement activities
Considerations for electronic specifications and
Qualified Clinical Data Registries (QCDRs)
(CMS, 2016c, p. 16).

According to Hagland (2016), MACRA, MIPS, and
APMs will:

Allow physicians and other clinicians to choose to
select the measures that reflect how technology
best suits their day-to-day practice
Simplify the process for achievement and provide
multiple paths for success
Align with the Office for the National Coordinator for
Health Information Technology’s 2015 edition
Health IT Certification Criteria
Emphasize interoperability, information exchange,
and security measures and give patients access to
their information through APIs (application program
interfaces)
Reduce the number of measures to an all-time low
of 11 measures, down from 18 measures, and no
longer require reporting on the clinical decision
support and CPOE measures
Exempt certain physicians from reporting when
EHR technology is less applicable to their practice
and allow physicians to report as a group (para. 4).

For an organization that seeks to meet these
measures, the data to support these measures must be
gathered and reported on electronically—necessitating
the use of technology in all patient care areas. The
successful implementation of the measurement
development plan “depends on a successful
partnership with patients, frontline clinicians, and

professional organizations and collaboration with other
diverse stakeholders to develop measures that are
meaningful to patients and clinicians and can be used
across payers and health care settings” (CMS, 2016c,
p. 64). Many of the quality reporting measures rely on
nursing and medical documentation. Most healthcare
personnel already use EHRs, but MACRA measures
will push healthcare organizations to reexamine the
use of clinical technologies within their organization
and approach implementations in a new way.

Not only is there a potential for patient safety and
quality issues to arise from technology implementations
that do not address workflow, but a financial impact to
the organization is possible as well. All organizations,
regardless of their industry, must operate efficiently to
maintain profits and continue to provide services to
their customers. For hospitals, which normally have
significantly smaller profit margins than other
organizations, the need to maintain efficient and
effective care is essential for survival. Given that
hospital profit margins are diminishing, never has there
been a more crucial time to examine the costs of errors
and poorly designed workflows and the financial
burden they present to an organization than now.
Moreover, what are the costs to an organization that
fails to address the integration of technology? This is
an area where few supporting data exist to substantiate
the claim that technology without workflow
considerations can, in fact, impact the bottom line.

Today, many healthcare organizations are experiencing
the effects of poorly implemented clinical technology
solutions. These effects may be manifested in the form
of redundant documentation, non-value-added steps,
and additional time spent at the computer rather than in
direct care delivery. For example, Gugerty et al. (2007)
studied the challenges and opportunities in nursing
documentation and determined that it was possible to
decrease the time a nurse spends documenting per
shift by 25%. Technology ought not to be implemented
for the sake of automation unless it promises to deliver
gains in patient outcomes and proper workflow. In fact,
the cost to organizations for duplicate/redundant
documentation by nursing can range from $6,500 to
$13,000 per nurse, per year (Clancy, Delaney,
Morrison, & Gunn, 2006). Stokowski (2013) found
other issues, such as systems that are slow, freeze,
lose data, and “don’t dump data from monitors and
screening devices into the EHR in real time” slowing
the documentation process and increasing the amount
of time the nurse must spend on the computer and not
in direct patient care (p. 9).

Examining the workflow surrounding the use of
technology enables better use of the technology and
more efficient work. It also promotes safer patient care
delivery. The need to focus on workflow and
technology is attracting increasing recognition,
although there remains a dearth of literature that

addresses the importance of this area. As more
organizations work to achieve a level of technology
adoption that will enable them to meet MACRA
measures and receive financial payments, we will likely
see more attention paid to the area of workflow design
and, therefore, a greater body of research and
evidence (AHRQ, n.d.; Qualis Health, 2011; Yuan,
Finley, Long, Mills, & Johnson, 2013).

Workflow and Technology
Workflow is a term used to describe the action or
execution of a series of tasks in a prescribed
sequence. Another definition of workflow is a
progression of steps (tasks, events, interactions) that
constitute a work process, involve two or more
persons, and create or add value to the organization’s
activities. In a sequential workflow, each step depends
on the occurrence of the previous step; in a parallel
workflow, two or more steps can occur concurrently.
The term workflow is sometimes used interchangeably
with process or process flows, particularly in the
context of implementations. Observation and
documentation of workflow to better understand what is
happening in the current environment and how it can
be altered is referred to as process or workflow
analysis. A typical output of workflow analysis is a
visual depiction of the process, called a process map.
The process map ranges from simplistic to fairly
complex and provides an excellent tool to identify

specific steps. It also can provide a vehicle for
communication and a tool upon which to build
educational materials as well as policies and
procedures.

One school of thought suggests that technology should
be designed to meet the needs of clinical workflow
(Yuan et al., 2013). This model implies that system
analysts have a high degree of control over screen
layout and data capture. It also implies that technology
is malleable enough to allow for the flexibility to adapt
to a variety of workflow scenarios. Lessons learned
from more than three decades of clinical technology
implementations suggest that clinical technologies still
have a long way to go on the road to maturity to allow
this to be possible. The second and probably most
prevalent thought process is that workflow should be
adapted to the use of technology. Today, this is by far
the most commonly used model given the progress of
clinical technology. Bucur et al. (2016) developed
clinical models to support clinical decision making that
were inserted into the workflow models. This system
integrates a workflow suite and functionality for the
storage, management, and execution of clinical
workflows and for the storage of traces of execution.
The knowledge models are integrated and run from the
workflow to support decisions at the right point in the
clinical process (Bucur et al., p. 152). The ability to
track and assess decision making throughout a clinical

course of care for a patient will enhance our knowledge
and improve patient care.

A concept that has gained popularity in recent years
relative to workflow redesign is clinical transformation.
Clinical transformation is the complete alteration of
the clinical environment and, therefore, this term
should be used cautiously to describe redesign efforts.
Earl, Sampler, and Sghort (1995) define transformation
as “a radical change approach that produces a more
responsive organization that is more capable of
performing in unstable and changing environments that
organizations continue to be faced with” (p. 31). Many
workflow redesign efforts are focused on relatively
small changes and not the widespread change that
accompanies transformational activities. Moreover,
clinical transformation would imply that the manner in
which work is carried out and the outcomes achieved
are completely different from the prior state—which is
not always true when the change simply involves
implementing technology. Technology can be used to
launch or in conjunction with a clinical transformation
initiative, although the implementation of technology
alone is not perceived as transformational.

Before undertaking transformative initiatives, the
following guidelines should be understood:

Leadership must take the lead and create a case
for transformation.

Establish a vision for the end point.
Allow those persons with specific expertise to
provide the details.
Think about the most optimal experience for both
the patient and the clinician.
Do not replicate the current state.
Focus on those initiatives that offer the greatest
value to the organization.
Recognize that small gains have no real impact on
transformation.

Optimization
Most of what has been and will be discussed in this
chapter is related to workflow analysis in conjunction
with technology implementations. Nevertheless, not all
workflow analysis and redesign occurs prior to the
implementation of technology. Some analysis and
redesign efforts may occur weeks, months, or even
years following the implementation. When workflow
analysis occurs postimplementation, it is often referred
to as optimization. Optimization is the process of
moving conditions past their current state and into
more efficient and effective method of performing
tasks. Merriam-Webster Online Dictionary (2016)
considered optimization to be the act, process, or
methodology of making something (as a design,
system, or decision) as fully perfect, functional, or
effective as possible. Some organizations will routinely
engage in optimization efforts following an

implementation, whereas other organizations may
undertake this activity in response to clinician concerns
or marked change in operational performance.

Furthermore, workflow analysis can be conducted
either as a stand-alone effort or as part of an
operational improvement event. When the process is
addressed alone, the effort is termed process
improvement. Nursing informatics professionals should
always be included in these activities to represent the
needs of clinicians and to serve as a liaison for
technological solutions to process problems.
Additionally, informaticists will likely become
increasingly operationally focused and will need to
transform their role accordingly to address workflow in
an overall capacity as well as respective to technology.
As mentioned earlier, hospitals tend to operate with
smaller profit margins than other industries and these
profits will likely continue to diminish, forcing
organizations to work smarter, not harder—and to use
technology to accomplish this goal.

If optimization efforts are undertaken, the need to
revisit workflow design should not be considered a flaw
in the implementation approach. Even a well-designed
future-state workflow during a technology
implementation must be reexamined
postimplementation to ensure that what was projected
about the future state remains valid and to incorporate

any additional workflow elements into the process
redesign.

Exploring the topic of workflow analysis with regard to
clinical technology implementation will yield
considerably fewer literature results than searching for
other topical areas of implementation. More research is
needed in the area of the financial implications of
workflow inefficiencies and their impact on patient care.
Time studies require an investment of resources and
may be subject to patient privacy issues as well as the
challenges of capturing time measurements on
processes that are not exactly replicable. Another
confounding factor affecting the quality and quantity of
workflow research is the lack of standardized
terminology for this area. A comprehensive literature
search was conducted and published through the
Agency for Healthcare Quality and Research (AHRQ)
in 2008 as an evidence-based handbook for nurses;
this literature search yielded findings indicating that a
lack of standardized terminology in the area of
workflow and publications on this topic have made it a
difficult topic to support through research findings.

What all organizations ultimately strive for is efficient
and effective delivery of patient care. The terms
efficient and effective are widely known in quality areas
or Six Sigma and Lean departments, but are not
necessarily known or used in informatics. Effective
delivery of care or workflow suggests that the process

or end product is in the most desirable state. An
efficient delivery of care or workflow would mean that
little waste—that is, unnecessary motion,
transportation, over-processing, or defects—was
incurred. Health systems such as Virginia Mason
University Medical Center, among others, have
experienced significant quality and cost gains from the
widespread implementation of Lean development
throughout their organization.

Workflow Analysis and
Informatics Practice
The American Nurses Association (ANA), in Nursing
Informatics: Scope and Standards of Practice (2015),
defined functional areas of practice for the informatics
nurse specialist (INS). The functional area of analysis
identified the specific functional qualities related to
workflow analysis. Particularly, the ANA indicated that
the INS should develop techniques necessary to
assess and improve human–computer interaction.
Workflow analysis, however, is not relevant solely to
analysis, but rather is part of every functional area the
INS engages in. The functional areas covered by
consultants, researchers, and other areas need to
understand workflow and appreciate how lack of
efficient workflow affects patient care.

A critical aspect of the informatics role is workflow
design. Nursing informatics is uniquely positioned to
engage in the analysis and redesign of processes and
tasks surrounding the use of technology. The ANA
(2015) cites workflow redesign as one of the
fundamental skills sets that make up the discipline of
this specialty. Moreover, workflow analysis should be
part of every technology implementation, and the role
of the informaticist within this team is to direct others in
the execution of this task or to perform the task directly.

Case Study

In my experience consulting, I have seen
several examples of organizations that engage
in the printing of paper reports that replicate
information that has been entered and is
available with the electronic health record.
These reports are often reviewed, signed, and
acted on, instead of using the electronic
information. Despite the knowledge that the
information contained in these reports was
outdated the moment the report was printed and
that the very nature of using the report for
workflow is an inefficient practice, this method of
clinical workflow remains prevalent in many
hospitals across the United States.

There is an underlying fear that drives the
decisions to mold a paper-based workflow

around clinical technology. There is also a lack
of the appropriate amount of integration that
would otherwise allow this information to be
available in an electronic form.

Unfortunately, many nurses find themselves in an
informatics capacity without sufficient preparation for a
process analysis role. One area of practice that is
particularly susceptible to inadequate preparation is the
ability to facilitate process analysis. Workflow analysis
requires careful attention to detail and the ability to
moderate group discussions, organize concepts, and
generate solutions. These skills can be acquired
through a formal academic informatics program or
through courses that teach the discipline of Six Sigma
or Lean, by example. Regardless of where these skills
are acquired, it is important to understand that they are
now and will continue to remain a vital aspect of the
informatics role.

Some organizations have felt strongly enough about
the need for workflow analysis that departments have
been created to address this very need. Whether the
department carries the name of clinical excellence,
organizational effectiveness, or Six Sigma/Lean, it is
critical to recognize the value this group can offer
technology implementations and clinicians.

As we examine how workflow analysis is conducted,
note that while the nursing informaticist is an essential
member of the team to participate in or enable
workflow analysis, a team dedicated to this effort is
necessary for its success.

Building the Design Team
The workflow redesign team is an interdisciplinary
team consisting of “process owners.” Process owners
are those persons who directly engage in the workflow
to be analyzed and redesigned. These individuals can
speak about the intricacy of process, including process
variations from the norm. When constructing the team,
it is important to include individuals who are able to
contribute information about the exact current-state
workflow and offer suggestions for future-state
improvement. Members of the workflow redesign team
should also have the authority to make decisions about
how the process should be redesigned. This authority
is sometimes issued by managers, or it could come
from participation of the managers directly. Such a
careful blend of decision makers and “process owners”
can be difficult to assemble but is critical for forming
the team and enabling them for success. Often,
individuals at the manager level will want to participate
exclusively in the redesign process. While having
management participate provides the advantage of
having decision makers and management-level buy-in,
these individuals may also make erroneous

assumptions about how the process should be versus
how the process is truly occurring. Conversely,
including only process owners who do not possess the
authority to make decisions can slow down the work of
the team while decisions are made outside the group
sessions.

Team focus needs to be addressed at the outset of the
team’s assembly. Early on, the team should decide
which workflow will be examined to avoid confusion or
spending time unnecessarily on workflow that does not
ultimately matter to the outcome. In the early stages of
workflow redesign, the team should define the
beginning and end of a process and a few high-level
steps of the process. Avoid focusing on process steps
in great detail in the beginning, as the conversation can
get sidetracked or team members may get bogged
down by focusing on details and not move along at a
good pace. Six Sigma expert George Eckes uses the
phrase “Stay as high as you can as long as you can”—
a good catch phrase to remember to keep the team
focused and at a high level. The pace at which any
implementation team progresses ultimately affects the
overall timeline of a project; therefore, focus and speed
are skills that the informatics expert should develop
and use throughout every initiative, but particularly
when addressing workflow redesign.

The workflow redesign team will develop a detailed
process map after agreement is reached on the

current-state process’s beginning and end points, and
a high-level map depicting the major process steps is
finalized. Because workflow crosses many different
care providers, it may be useful to construct the
process map using a swim-lane technique (Figure 13-
2). A swim-lane technique uses categories such as
functional workgroups and roles to visually depict
groups of work and to indicate who performs the work.
The resulting map shows how workflow and data
transition to clinicians and can demonstrate areas of
potential process and information breakdowns.

Figure 13-2 Example of the Swim Lane Technique

Courtesy of Greencastle Associates Consulting and Atlantic Health.

Reprinted by permission.

It may take several sessions of analysis to complete a
process map, as details are uncovered and

workarounds discussed. There is a tendency for
individuals who participate in process redesign
sessions to describe workflow as they believe it to be
occurring, rather than not how it really is. The
informatics expert and/or the process team facilitator
should determine what is really happening, however,
and capture that information accurately. Regardless of
whether a swim-lane or simplistic process map design
is used, the goal is to capture enough details to
accurately portray the process as it is happening today.

Other techniques (aside from process mapping) may
be used to help the team understand the workflow as it
exists in the current state. The future-state workflow
planning will be only as good as the reliability of the
current state; thus it is crucial to undertake whatever
other actions are needed to better understand what is
happening in the current state. Observation, interviews,
and process or waste walks are also helpful in
understanding the current state.

Value Added Versus Non–Value Added
Beyond analysis of tasks, current-state mapping
provides the opportunity for the process redesign team
to distinguish between value-added and non-value-
added activities. A value-added activity or step is one
that ultimately brings the process closer to completion
or changes the product or service for the better. An
example of a value-added step would be placing a

name tag on a specimen sample. The name tag is
necessary for the laboratory personnel to identify the
specimen and, therefore, its placement is an essential
or value-added step in the process. Some steps in a
process do not necessarily add value but are
necessary for regulatory or compliance reasons. These
steps are still considered necessary and need to be
included in the future process. A non-value-added step,
in contrast, does not alter the outcome of a process or
product. Activities such as handling, moving, and
holding are not considered value-added steps and
should be evaluated during workflow analysis.
Manipulating papers, moving through computer
screens, and walking or transporting items are all
considered non-value-added activities.

The five whys represent one technique to drive the
team toward identifying value-added versus non-value-
added steps. The process redesign facilitator will query
the group about why a specific task is done or done in
a particular way through a series of questions asking
“why?” The goal is to uncover tasks that came about
due to workarounds or for other unsubstantiated
reasons. Tasks that are considered non–value added
and are not necessary for the purpose of compliance or
regulatory reasons should be eliminated from the
future-state process. The team’s purpose in
redesigning workflow is to eliminate steps in a process
that do not add value to the end state or that create
waste by their very nature.

Waste
A key underpinning of the Lean philosophy is the
removal of waste activities from workflow. Waste is
classified as unnecessary activities or an excess of
products to perform tasks. The seven categories listed
here are the most widely recognized forms of waste:

Overproduction: pace is faster than necessary to
support the process
Waiting
Transport
Inappropriate processing: over-processing
Unnecessary inventory: excess stock
Unnecessary motion: bending, lifting, moving, and
so on
Defects: reproduction

Variation
The nature of the work situation for the nurse is one of
frequent interruptions causing the workflow to be
disrupted and increasing the chance of error (Yuan et
al., 2013). Variation in workflow is considered the
enemy of all good processes and, therefore, should be
eliminated when possible. Variation occurs when
workers perform the same function in different ways. It
usually arises because of flaws in the way a process
was originally designed, lack of knowledge about the

process, or inability to execute a process as originally
designed due to disruption or disturbances in the
workflow. Examining the process as it exists today will
help with identifying variation. A brief statement about
variation that cannot be eliminated: Processes that
involve highly customized products or services are
generally not conducive to standardization and the
elimination of variation inherent to the process.

Some argue that delivery of care is subject to variation
owing to its very nature and the individual needs of
patients. There is little doubt that each patient’s care
should be tailored to meet his or her specific needs.
Nevertheless, delivery of care involves some common
processes that can be standardized and improved
upon without jeopardizing care.

Transitioning to the Future State
Following redesign efforts, regardless of whether they
occurred during or after an implementation or as a
stand-alone process improvement event, steps must
be taken to ensure that change takes hold and the new
workflow continues after the support team has
disbanded. Management support and involvement
during the transition phase is essential, as
management will be necessary to enforce new
workflow procedures and further define/refine roles and
responsibilities. Documentation of the future-state
workflow should have occurred during the redesign

effort but is not completely finished until after the
redesign is complete and the workflow has become
operational. Policies and procedures are addressed
and rewritten to encompass the changes to workflows
and role assignments. Help desk, system analyst,
nursing education, and other support personnel need
to be educated about the workflow specifics as part of
the postimprovement effort. It is considered good
practice to involve the operational staff in the future
process discussions and planning so as to incorporate
specifics of these areas and ensure the buy-in of the
staff.

When workflow changes begin to fail and workarounds
develop, they signal that something is flawed about the
way in which the new process was constructed and
needs to be evaluated further. The workflow redesign
team is then brought together to review and, if
necessary, redesign the process.

The future state is constructed with the best possible
knowledge of how the process will ideally work. To
move from the current state to the future state, gap
analysis is necessary. Gap analysis zeros in on the
major areas most affected by the change—namely,
technology. What often happens in redesign efforts is
an exact or near-exact replication of the current state
using automation. The gap analysis discussion should
generate ideas from the group about how best to utilize
the technology to transform practice. A prudent step is

to consider having legal and risk representatives at the
table when initiating future-state discussions to identify
the parameters within which the group should work;
nevertheless, the group should not assume the existing
parameters are its only boundaries.

Future-state process maps become the basis of
educational materials for end users, communication
tools for the project team, and the foundation of new
policies and procedures. Simplified process maps
provide an excellent schematic for communicating
change to others.

Informatics as a Change Agent
Technology implementations represent a significant
change for clinicians, as does the workflow redesign
that accompanies adoption of technology. Often the
degree of change and its impact are underappreciated
and unaccounted for by leadership and staff alike. A
typical response to change is anger, frustration, and a
refusal to accept the proposed change. All of these
responses should be expected and need to be
accounted for; thus a plan to address the emotional
side of change is developed early on. Every workflow
redesign effort should begin with a change
management plan (Figure 13-3). Engagement of the
end user is a critical aspect of change management
and, therefore, technology adoption. Without end-user
involvement, change is resisted and efforts are subject

to failure. Users may be engaged and brought into the
prospective change through question-and-answer
forums, technology demonstrations, and frequent
communications regarding change, and as department-
specific representatives in working meetings.

Figure 13-3 Change Management

© Digital Storm/Shutterstock

Many change theories have been developed. No
matter which change theory is adopted by the
informatics specialist, however, communication,
planning, and support are key factors in any change
management strategy. Informaticists should become
knowledgeable about at least one change theory and
use this knowledge as the basis for change
management planning as part of every effort. John

Kotter (1996), one of the most widely recognized
change theorists, suggested the following conditions
must be addressed to deal with change in an
organization:

Education and communication
Participation and involvement
Facilitation and support
Negotiation and agreement
Manipulation and co-optation
Explicit and implicit coercion

In the HIMSS (2015) Nursing Informatics Impact
survey, nursing informaticists were identified as the
most significant resource in a project team that
influences adoption and change management. Nurses
bring to such teams their ability to interact with various
clinicians, their knowledge of clinical practice, and their
ability to empathize with the clinicians as they
experience the impact of workflow change. These
innate skills differentiate the nursing informaticist from
other members of the implementation team and are
highly desirable in the informatics community.

Nevertheless, no matter which change management
techniques are employed by the informatics specialist
and the project team, adoption of technology and
workflow may be slow to evolve. Change is often a
slow process that requires continual positive
reinforcement and involvement of supporting

resources. Failure to achieve strong adoption results
early on is not necessarily a failure of the methods
utilized, but rather may be due to other factors not
entirely within the control of the informaticist.

Perhaps a complete alteration in behavior is not
possible, but modifications to behaviors needed to
support a desired outcome can be realized. This
situation is analogous to the individual who stops
smoking; the desire for the cigarette remains, but the
behavior has been modified to no longer sustain
smoking. To manage change in an organization, nurses
must modify behavior to produce the intended
outcome.

Change takes hold when strong leadership support
exists. This support manifests itself as a visible
presence to staff, clear and concise communications,
an unwavering position, and an open door policy to
field concerns about change. Too often, leadership
gives verbal endorsement of change and then fails to
follow through with these actions or withdraws support
when the going gets tough. Inevitability, if leadership
wavers, so too will staff.

Measuring the Results
Metrics provide understanding about the performance
of a process or function. Typically within clinical
technology projects, we identify and collect specific

metrics about the performance of the technology or
metrics that capture the level of participation or
adoption. Equally important is the need for process
performance metrics. Process metrics are collected at
the initial stage of project or problem identification.
Current-state metrics are then benchmarked against
internal indicators. When there are no internal
indicators to benchmark against, a suitable course of
action is to benchmark against an external source such
as a similar business practice within a different
industry. Consider examining the hotel room change-
over strategy or the customer service approach of Walt
Disney Company or Ritz Carlton hotels, for example, to
determine suitable metrics for a particular project or
focus area.

The right workflow complement will provide the
organization with the data it needs to understand
operational and clinical performance. This area is
highlighted through the need for healthcare
organizations to capture MACRA measures. Good
metrics should tell the story of accomplishment. The
presence of technology alone does not guarantee an
organization’s ability to capture and report on these
measures without also addressing the surrounding
workflow. Metrics should focus on the variables of time,
quality, and costs. Table 13-1 provides examples of
relevant metrics.

Table 13-1 Examples of Metrics

Turnaround times Cycle times Throughput

Change-over time Set-up time System availability

Patient satisfaction Employee satisfaction

MACRA highlights the need for healthcare
organizations to collect information that represents the
impact of technology on patient outcomes.
Furthermore, data are necessary to demonstrate how a
process is performing in its current state. In spite of the
MACRA mandates, the need to collect data to
demonstrate improvement in workflow— though it
remains strong—is all too often absent in
implementation or redesign efforts. A team cannot
demonstrate improvements to an existing process
without collecting information about how the process is
performing today. Current-state measures also help the
process team validate that the correct area for
improvement was identified. Once a process
improvement effort is over and the new solution has
been implemented, postimprovement measures should
be gathered to demonstrate progress.

In some organizations, the informatics professional
reports to the director of operations, the chief
information officer, or the chief operations officer. In this
relationship, the need to demonstrate operational
measures is even stronger. Operational measures such

as turnaround times, throughput, and equipment or
technology availability are some of the measures
captured.

Future Directions
Workflow analysis is not an optional part of clinical
implementations, but rather a necessity for safe patient
care supported by technology. The ultimate goal of
workflow analysis is not to “pave the cow path,” but
rather to create a future-state solution that maximizes
the use of technology and eliminates non-value-added
activities. Although many tools to accomplish workflow
redesign are available, the best method is the one that
complements the organization and supports the work
of clinicians. Redesigning how people do work will
evidentially create change; thus the nursing
informaticist will need to apply change management
principles for the new way of doing things to take hold.

Workflow analysis has been described in this chapter
within the context of the most widely accepted tools
that are fundamentally linked to the concepts of Six
Sigma/Lean. Other methods of workflow analysis exist
and may become commonly used to assess clinical
workflow. An example of an alternative workflow
analysis tool is the use of radio frequency badges to
detect movement within a defined clinical area.
Clinician and patient movements may be tracked using
these devices, and corresponding actions may be

documented, painting a picture of the workflow for a
specific area (Vankipuram, 2010).

Another example of a workflow analysis tool involves
the use of modeling software. An application such as
ProModel provides images of the clinical work area
where clinician workflows can be plotted out and
reconfigured to best suit the needs of a specific area.
Simulation applications enable decision makers to
visualize realistic scenarios and draw conclusions
about how to leverage resources, implement
technology, and improve performance. Other vendors
that offer simulation applications include Maya and
Autodesk.

Healthcare organizations need to consider how other
industries have analyzed and addressed workflow to
streamline business practices and improve quality
outputs to glean best practices that might be
incorporated into the healthcare industry’s own clinical
and business approaches. First, however, each
healthcare organization must step outside itself and
recognize that not all aspects of patient care are
unique; consequently, many aspects of care can be
subjected to standardization. Many models of workflow
redesign from manufacturing and the service sector
can be extrapolated to health care. The healthcare
industry is facing difficult economic times and can
benefit from performance improvement strategies used
in other industries.

Although workflow analysis principles have been
described within the context of acute and ambulatory
care in this chapter, the need to perform process
analysis on a macro level will expand as more
organizations move forward with health information
exchanges and medical home models. A health
information exchange (HIE) requires the nursing
informaticist to visualize how patients move through the
entire continuum of care and not just a specific patient
care area.

Technology initiatives will become increasingly complex
in the future. In turn, nursing informaticists will need
greater preparation in the area of process analysis and
improvement techniques to meet the growing
challenges that technology brings and the operational
performance demands of fiscally impaired healthcare
organizations.

Summary
Meaningful use (MU) reflected the rules and
regulations arising from ARRA. MACRA has changed
the game and how payment will be determined. EHR
adoptions “represent a small step rather than a giant
leap forward” (Murphy, 2013, para. 1). Workflows
integrating technology provide the healthcare
professional with the data necessary to make informed

decisions. This quality data must be collected and
captured to meet MACRA measures. Nurses must be
involved in “meaningful data collection and reporting.
Documentation by nurses can tell what’s going on with
the patient beyond physical exams, test results, and
procedures” (Daley, 2013, para. 5).

Workflow redesign is a critical aspect of technology
implementation. When done well, it yields technology
that is more likely to achieve the intended patient
outcomes and safety benefits. Nursing informatics
professionals are taking on a greater role with respect
to workflow design, and this aspect of practice will grow
in light of MACRA-driven measures. Other initiatives
that impact hospital performance will also drive
informatics professionals to influence how technology
is used in the context of workflow to improve the
bottom line for their organizations. In an ideal world,
nurse informaticists who are experts at workflow
analysis will be core members of every technology
implementation team.

THOUGHT-PROVOKING QUESTIONS

1. What do you perceive as the current
obstacles to redesigning workflow within
your clinical setting?

2. Thinking about your last implementation,
were you able to challenge the policies
and practices that constitute today’s

workflow or were you able to create a
workflow solution that eliminated non–
value-added steps?

3. Is the workflow surrounding technology
usage providing the healthcare
organization with the data it needs to
make decisions and eventually meet
MACRA criteria?

4. How does the current educational
preparation need to change to address
the skills necessary to perform workflow
analysis and redesign clinical processes?

5. Describe the role of the nurse
informaticist as the payment programs
change related to MACRA.

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SECTION IV: Nursing
Informatics Practice
Applications: Care Delivery

Chapter 14 The Electronic Health Record and
Clinical Informatics

Chapter 15 Informatics Tools to Promote Patient
Safety and Quality Outcomes

Chapter 16 Patient Engagement and Connected
Health

Chapter 17 Using Informatics to Promote
Community/Population Health

Chapter 18 Telenursing and Remote Access
Telehealth

Nursing information systems must support nurses as
they fulfill their roles in delivering quality patient care.
Such systems must be responsive to nurses’ needs,
allowing them to manage their data and information as
needed and providing access to necessary references,
literature sources, and other networked departments.
Nurses have always practiced in a field where they
have needed to use their ingenuity, resourcefulness,
creativity, initiative, and skills. To improve patient care

and advance the science of nursing, clinicians as
knowledge workers must apply these same abilities
and skills to become astute users of available
information systems.

In this section, the reader learns about clinical practice
tools, electronic health records, and clinical information
systems; informatics tools to enhance patient safety,
provide consumer information, and meet education
needs; population and community health tools; and
telehealth and telenursing.

Information systems, electronic documentation, and
electronic health records are changing the way nurses
and physicians practice. Nursing informatics systems
are also changing how patients enter and receive data
and information. Some institutions, for example, are
permitting patients to access their own records
electronically via the Internet or a dedicated patient
portal. Confidentiality and privacy issues loom with
these new electronic systems. HIPAA regulations
(covered in the Perspectives on Nursing Informatics
section) and professional ethics principles (covered in
the Building Blocks of Nursing Informatics section)
must remain at the forefront when clinicians interact
electronically with intimate patient data and
information.

The material within this book is placed within the
context of the Foundation of Knowledge model (Figure

IV-1) to meet the needs of healthcare delivery systems,
organizations, patients, and nurses. Readers should
continue to assess their personal knowledge
progression. The Foundation of Knowledge model
challenges us to reflect on how our knowledge
foundation is ever-changing and to appreciate that
acquiring new information is a key resource for
knowledge building. This section addresses the
information systems with which clinicians interact in
their healthcare environments as affected by
legislation, professional codes of ethics, consumerism,
and reconceptualization of practice paradigms, such as
in telenursing. All of the various nursing roles—
practice, administration, education, research, and
informatics—involve the science of nursing.

Figure IV-1 Foundation of Knowledge Model

Designed by Alicia Mastrian

CHAPTER 14: The
Electronic Health Record
and Clinical Informatics

Emily B. Barey, Kathleen Mastrian, and Dee McGonigle

Objectives
1. Describe the common components of an

electronic health record.
2. Assess the benefits of implementing an

electronic health record.
3. Explore the ownership of an electronic

health record.
4. Evaluate the flexibility of the electronic

health record in meeting the needs of
clinicians and patients.

Key Terms

» Administrative processes

» American Recovery and Reinvestment
Act of 2009 (ARRA)

» Connectivity

» Decision support

» Electronic communication

» Electronic health records

» Health information

» Health Information Technology for
Economic and Clinical Health Act of 2009
(HITECH)

» Interoperability

» Meaningful use

» Order entry management

» Patient support

» Population health management

» Reporting

» Results management

Introduction

The significance of electronic health records (EHRs)
to nursing cannot be underestimated. Although EHRs
on the surface suggest a simple automation of clinical
documentation, in fact their implications are broad,
ranging from the ways in which care is delivered, to the
types of interactions nurses have with patients in
conjunction with the use of technology, to the research
surrounding EHRs that will inform nursing practice for
tomorrow. Although EHR standards are evolving and
barriers to adoption remain, the collective work has a
positive momentum that will benefit clinicians and
patients alike.

A basic knowledge of EHRs and nursing informatics is
now considered by many to be an entry-level nursing
competency. Various nursing workgroups have
delineated nursing informatics competencies from entry
level to nursing informatics specialists, and other
groups have identified competencies specific to the
EHR. The American Health Information Management
Association (AHIMA) collaborated with the Health
Professions Network and the Employment and Training
Administration to create a graphic depiction of
competencies necessary for EHR interaction. The
Electronic Health Records Competency Model is
divided into six levels: Personal Effectiveness
Competencies, Academic Competencies, Workplace
Competencies, Industry-Wide Technical Competencies,
Industry-Sector Technical Competencies, and a
Management Competencies level shared with

Occupation Specific Requirements. The EHR
Competency Model can be viewed at:
www.careeronestop.org/CompetencyModel/competency-
models/electronic-health-records.aspx. Hovering
over each block in the model provides a definition of
each of the competencies covered by the model. For
example, the industry-sector technical competencies
section includes health information literacy and skills,
health informatics skills using the EHR, privacy and
confidentiality of health information, and health
information data technical security. This drive to adopt
EHRs was underscored with the passage of the Health
Information Technology for Economic and Clinical
Health Act of 2009 (HITECH). It is essential that EHR
competency be developed if nurses are to participate
fully in the changing world of healthcare information
technology.

This chapter has four goals. First, it describes the
common components of an EHR. Second, it reviews
the benefits of implementing an EHR. Third, it provides
an overview of successful ownership of an EHR,
including nursing’s role in promoting the safe adoption
of EHRs in day-to-day practice. Fourth, it discusses the
flexibility of an EHR in meeting the needs of both
clinicians and patients and emphasizes the need for
fully interoperable EHRs and clinical information
systems (CISs).

Setting the Stage
The U.S. healthcare system faces the enormous
challenge of improving the quality of care while
simultaneously controlling costs. EHRs were proposed
as one solution to achieve this goal (Institute of
Medicine [IOM], 2001). In January 2004, President
George W. Bush raised the profile of EHRs in his State
of the Union address by outlining a plan to ensure that
most Americans have an EHR by 2014. He stated that
“by computerizing health records we can avoid
dangerous medical mistakes, reduce costs, and
improve care” (Bush, 2004). This proclamation
generated an increased demand for understanding
EHRs and promoting their adoption, but relatively few
healthcare organizations were motivated at that time to
pursue adoption of EHRs. The Healthcare Information
and Management Systems Society (HIMSS) has been
tracking EHR adoption since 2005 through its “Stage 7”
award, and in 2013 reported that most U.S. healthcare
organizations (77%) were in Stage 3, reflecting only
implementation of the basic EHR components of
laboratory, radiology, and pharmacy ancillaries; a
clinical data repository, including a controlled medical
vocabulary; and simple nursing documentation and
clinical decision support (HIMSS, 2013). Higher stages
of the electronic medical record adoption model include
more sophisticated use of clinical decision support
systems (CDSSs) and medication administration tools,
with HIMSS Stage 7—the highest level—consisting of

EHRs that have data sharing and warehousing
capabilities and that are completely interfaced with
emergency and outpatient facilities (HIMSS Analytics,
2013). Real progress is being made on the adoption of
more robust EHRs. HIMSS Analytics (2015) reports
that 1,313 hospitals in the United States have achieved
Stage 6 with full physician documentation, a robust
CDSS, and electronic access to medical images.
Healthcare IT News (2015) reported that, to date, over
200 hospitals have achieved Stage 7 and are totally
paperless, and that more organizations reach this goal
every day.

In President Barack Obama’s first term in office,
Congress passed the American Recovery and
Reinvestment Act of 2009 (ARRA). This legislation
included the HITECH Act, which specifically sought to
incentivize health organizations and providers to
become meaningful users of EHRs. These incentives
came in the form of increased reimbursement rates
from the Centers for Medicare and Medicaid Services
(CMS); ultimately, the HITECH Act resulted in payment
of a penalty by any healthcare organization that had
not adopted an EHR by January 2015. The final rule
was published by the Department of Health and
Human Services (USDHHS) in July 2010 for the first
phase of implementation. Stage 1 meaningful use
criteria focused on data capture and sharing
(USDHHS, 2010a). Stage 2 criteria, implemented in
2014, advanced several clinical processes and

promoted health information exchange (HIE) and more
patient control over personal data. Stage 3, which has
a target implementation date of 2016, focuses on
improved outcomes for individuals and populations,
and introduction of patient self-management tools
(HealthIT.gov, 2013).

Components of Electronic
Health Records

Overview
Before enactment of the ARRA, several variants of
EHRs existed, each with its own terminology and each
developed with a different audience in mind. The
sources of these records included, for example, the
federal government (Certification Commission for
Healthcare Information Technology, 2007), the IOM
(2003), the HIMSS (2007), and the National Institutes
of Health (2006; Robert Wood Johnson Foundation
[RWJF], 2006). Under ARRA, there is now an explicit
requirement for providers and hospitals to use a
certified EHR that meets a set of standard functional
definitions to be eligible for the increased
reimbursement incentive. Initially, USDHHS granted
two organizations the authority to accredit EHRs: the
Drummond Group and the Certification Commission for
Healthcare Information Technology. In 2015, there
were five recognized bodies for testing and certifying

EHRs (HealthIT.gov, 2015a). These bodies are
authorized to test and certify EHR vendors against the
standards and test procedures developed by the
National Institute of Standards and Technology (NIST)
and endorsed by the Office of the National Coordinator
for Health Information Technology for EHRs.

The initial NIST test procedure included 45 certification
criteria, ranging from the basic ability to record patient
demographics, document vital signs, and maintain an
up-to-date problem list, to more complex functions,
such as electronic exchange of clinical information and
patient summary records (Jansen & Grance, 2011;
NIST, 2010). Box 14-1 lists the 45 certification criteria
outlined by NIST in 2010. These criteria have been
updated several times since 2010, with the 2015
version developed after going out for public comment
(HealthIT.gov, 2015b). Each iteration of certification
criteria and testing procedures seeks to make the EHR
more robust, interoperable, and functional to meet the
needs of patients and users.

BOX 14-1 EHR CERTIFICATION

CRITERIA

Criteria # Certification Criteria

§170.302 (a) Drug–drug, drug–allergy interaction checks

§170.302 (b) Drug formulary checks

§170.302 (c) Maintain up-to-date problem list

§170.302 (d) Maintain active medication list

§170.302 (e) Maintain active medication allergy list

§170.302 (f)

(1)

Vital signs

§170.302 (f)

(2)

Calculate body mass index

§170.302 (f)

(3)

Plot and display growth charts

§170.302 (g) Smoking status

§170.302 (h) Incorporate laboratory test results

§170.302 (i) Generate patient lists

§170.302 (j) Medication reconciliation

§170.302 (k) Submission to immunization registries

§170.302 (l) Public health surveillance

§170.302 (m) Patient-specific education resources

§170.302 (n) Automated measure calculation

§170.302 (o) Access control

§170.302 (p) Emergency access

§170.302 (q) Automatic log-off

§170.302 (r) Audit log

§170.302 (s) Integrity

§170.302 (t) Authentication

§170.302 (u) General encryption

§170.302 (v) Encryption when exchanging electronic health

information

§170.302 (w) Accounting of disclosures (optional)

§170.304 (a) Computerized provider order entry

§170.304 (b) Electronic prescribing

§170.304 (c) Record demographics

§170.304 (d) Patient reminders

§170.304 (e) Clinical decision support

§170.304 (f) Electronic copy of health information

§170.304 (g) Timely access

§170.304 (h) Clinical summaries

§170.304 (i) Exchange clinical information and patient summary

record

§170.304 (j) Calculate and submit clinical quality measures

§170.306 (a) Computerized provider order entry

§170.306 (b) Record demographics

§170.306 (c) Clinical decision support

§170.306 (d)

(1)

Electronic copy of health information

§170.306 (d)

(2)

Electronic copy of health information

Note: For discharge summary

§170.306 (e) Electronic copy of discharge instructions

§170.306 (f) Exchange clinical information and patient summary

record

§170.306 (g) Reportable lab results

§170.306 (h) Advance directives

§170.306 (i) Calculate and submit clinical quality measures

Reproduced from National Institute of Standards and Technology

(NIST). (2010). Meaningful use test method: Approved test procedures
version 1.0. Retrieved from

http://healthcare.nist.gov/use_testing/finalized_requirements.html

Despite the points articulated in the ARRA, the IOM
definition of an EHR also remains a valid reference
point. This definition is useful because it has distilled all
the possible features of an EHR into eight essential
components with an emphasis on functions that
promote patient safety—a universal denominator that
everyone in health care can accept. The eight

components are (1) health information and data, (2)
results management, (3) order entry management, (4)
decision support, (5) electronic communication and
connectivity, (6) patient support, (7) administrative
processes, and (8) reporting and population health
management (IOM, 2003). These initial core
components, as well as more recent modifications
described by the Health Resources and Services
Administration (HRSA, n.d.) and the components of a
comprehensive EHR identified by HealthIT.gov
(Charles, Gabriel, & Searcy, 2015), are described in
more detail here. With the exception of EHR
infrastructure functions, such as security and privacy
management, controlled medical vocabularies, and
interoperability standards, the 45 initial NIST standards
easily map into the IOM categories (Jansen & Grance,
2011).

Health Information and Data
Health information and data comprise the patient data
required to make sound clinical decisions, including
demographics, medical and nursing diagnoses,
medication lists, allergies, and test results (IOM, 2003).
This component of the EHR also includes care
management data regarding details of patient visits
and interactions with patients, medication
reconciliation, consents, and directives (HRSA, n.d.). A
comprehensive EHR will also contain nursing

assessments and problem lists (Charles, Gabriel, &
Searcy, 2015).

Results Management
Results management is the ability to manage results
of all types electronically, including laboratory and
radiology procedure reports, both current and historical
(IOM, 2003).

Order Entry Management
Order entry management is the ability of a clinician to
enter medication and other care orders, including
laboratory, microbiology, pathology, radiology, nursing,
and supply orders; ancillary services; and
consultations, directly into a computer (IOM, 2003). A
comprehensive EHR will also contain nursing orders
(Charles, Gabriel, & Searcy, 2015).

Decision Support
Decision support entails the use of computer
reminders and alerts to improve the diagnosis and care
of a patient, including screening for correct drug
selection and dosing, screening for medication
interactions with other medications, preventive health
reminders in such areas as vaccinations, health risk
screening and detection, and clinical guidelines for
patient disease treatment (IOM, 2003).

Electronic Communication and
Connectivity
Electronic communication and connectivity include
the online communication among healthcare team
members, their care partners, and patients, including
email, Web messaging, and an integrated health
record within and across settings, institutions, and
telemedicine (IOM, 2003). This component has been
expanded to include interfaces and interoperability
required to exchange health information with other
providers, laboratories, pharmacies (e-prescribing),
patients, and government disease registries (HRSA,
n.d., para. 2)

Patient Support
Patient support encompasses patient education and
self-monitoring tools, including interactive computer-
based patient education, home telemonitoring, and
telehealth systems (IOM, 2003).

Administrative Processes
Administrative processes are activities carried out by
the electronic scheduling, billing, and claims
management systems, including electronic scheduling
for inpatient and outpatient visits and procedures,
electronic insurance eligibility validation, claim
authorization and prior approval, identification of

possible research study participants, and drug recall
support (IOM, 2003).

Reporting and Population Health
Management
Reporting and population health management are
the data collection tools to support public and private
reporting requirements, including data represented in a
standardized terminology and machine-readable format
(IOM, 2003).

NIST has not provided an exhaustive list of all possible
features and functions of an EHR. Consequently,
different vendor EHR systems combine different
components in their offerings, and often a single set of
EHR components may not meet the needs of all
clinicians and patient populations. For example, a
pediatric setting may demand functions for
immunization management, growth tracking, and more
robust order entry features to include weight-based
dosing (Spooner & Council on Clinical Information
Technology, 2007). These types of features may not
be provided by all EHR systems, and it is important to
consider EHR certification to be a minimum standard.
See Figure 14-1 for a graphic depiction of EHR
functions and communication capabilities.

Figure 14-1 EHR Functions and Communication
Capabilities

Reproduced from American Hospital Association. (2010). The road to

meaningful use: What it takes to implement EHR systems in hospitals.

Retrieved from http://www.aha.org/research/reports/tw/10apr-tw-

HITmeanuse.pdf

Another group that focuses on EHR standards and
functionality is Health Level Seven International (HL7).
Founded in 1987, “Health Level Seven International
(HL7) is a not-for-profit, ANSI-accredited standards

developing organization dedicated to providing a
comprehensive framework and related standards for
the exchange, integration, sharing, and retrieval of
electronic health information that supports clinical
practice and the management, delivery and evaluation
of health services” (Health level Seven International,
n.d., para. 1). This group concentrates on developing
the behind-the-scenes programming standards (Level
Seven is the application level of the Open Systems
Interconnection model) for interfaces to ensure
interoperability and connectivity among systems.

Advantages of Electronic
Health Records
Measuring the benefits of EHRs can be challenging.
Possible methods to estimate EHR benefits include
using vendor-supplied data that have been retrieved
from their customers’ systems, synthesizing and
applying studies of overall EHR value, creating logical
engineering models of EHR value, summarizing
focused studies of elements of EHR value, and
conducting and applying information from site visits
(HealthIT.gov, 2012; Thompson, Osheroff, Classen,
& Sittig, 2007).

Early on, the four most common benefits cited for
EHRs were (1) increased delivery of guidelines-based
care, (2) enhanced capacity to perform surveillance

and monitoring for disease conditions, (3) reduction in
medication errors, and (4) decreased use of care
(Chaudhry et al., 2006; HealthIT.gov, 2012). These
findings were echoed by two similar literature reviews.
The first review (Dorr et al., 2007) focused on the use
of informatics systems for managing patients with
chronic illness. It found that the processes of care most
positively impacted were guidelines adherence, visit
frequency (i.e., a decrease in emergency department
visits), provider documentation, patient treatment
adherence, and screening and testing.

The second review (Shekelle, Morton, & Keeler,
2006) was a cost–benefit analysis of health information
technology completed by the Agency for Healthcare
Research and Quality (AHRQ) that studied the value of
an EHR in the ambulatory care and pediatric settings,
including its overall economic value. The AHRQ study
highlighted the common findings already described, but
also noted that most of the data available for review
came from six leading healthcare organizations in the
United States, underscoring the challenge of
generalizing these results to the broader healthcare
industry. As noted previously by the HIMSS Stage 7
Awards, the challenge to generalize results persists in
the hospital arena, with fewer than 1% of U.S. hospitals
or eight leading organizations providing most of the
experience with comprehensive EHRs (HIMSS,
2010a). Finally, the literature reviews cited here
indicated that there are a limited number of hypothesis-

testing studies of EHRs and even fewer that have
reported cost data.

The descriptive studies do have value, however, and
should not be hastily dismissed. Although not as
rigorous in their design, they do describe the
advantages of EHRs well and often include useful
implementation recommendations learned from
practical experience. As identified in these types of
reviews, EHR advantages include simple benefits,
such as no longer having to interpret poor handwriting
and handwritten orders, reduced turnaround time for
laboratory results in an emergency department, and
decreased time to administration of the first dose of
antibiotics in an inpatient nursing unit (HealthIT.gov,
2012; Husk & Waxman, 2004; Smith et al., 2004). In
the ambulatory care setting, improved management of
cardiac-related risk factors in patients with diabetes
and effective patient notification of medication recalls
have been demonstrated to be benefits of the EHR
(Jain et al., 2005; Reed & Bernard, 2005). Two other
unique advantages that have great potential are the
ability to use the EHR and decision support functions to
identify patients who qualify for research studies or
who qualify for prescription drug benefits offered by
pharmaceutical companies at safety-net clinics and
hospitals (Embi et al., 2005; Poprock, 2005).

The HIMSS Davies Award may be the best resource
for combined quantitative and qualitative results of

successful EHR implementation. The Davies Award
recognizes healthcare organizations that have
achieved both excellence in implementation and value
from health information technology (HIMSS, 2010a).
One winner demonstrated a significant avoidance of
medication errors because of bar-code scanning alerts,
a $3 million decrease in medical records expenses as
a result of going paperless, and a 5% reduction of
duplicate laboratory orders by using computerized
provider order entry alerting (HIMSS, 2010b). Another
winner noted a 13% decrease in adverse drug
reactions through the use of computerized physician
order entry; it also achieved a decrease in methicillin-
resistant Staphylococcus aureus (MRSA) nosocomial
infections from 9.8 per 10,000 discharges to 6.4 per
10,000 discharges in less than a year using an EHR
flagging function, which made clinicians immediately
aware that contact precautions were required for
MRSA-positive patients (HIMSS, 2009). At both
organizations, there was qualitative and quantitative
evidence of high rates of end user adoption and
satisfaction with use of the EHR.

A 2011 study of the effects of EHR adoption on nurse
perceptions of quality of care, communication, and
patient safety documented that nurses report better
care outcomes and fewer concerns with care
coordination and patient safety in hospitals with a basic
EHR (Kutney-Lee & Kelly, 2011). In this study, nurses
perceived that in hospitals with a functioning EHR,

there was better communication among staff,
especially during patient transfers, and fewer
medication errors. Bayliss et al. (2015) demonstrated
that an integrated care system utilizing an EHR
resulted in fewer hospital readmissions and emergency
room visits for over 12,000 seniors with multiple health
challenges.

Without an EHR system, any of these benefits would
be very difficult and costly to accomplish. Thus, despite
limited standards and published studies, there is
enough evidence to embrace widespread
implementation of the EHR (Halamka, 2006;
HealthIT.gov, 2012), and certainly enough evidence to
warrant further study of the use and benefits of EHRs.
Box 14-2 describes some of the specific CIS functions
of an EHR.

BOX 14-2 THE EHR AS A CLINICAL

INFORMATION SYSTEM

Denise Tyler

A CIS is a technology-based system applied at
the point of care and designed to support care
by providing instant access to information for
clinicians. Early CISs implemented prior to the
advent of EHRs were limited in scope and
provided such information as interpretation of
laboratory results or a medication formulary and

drug interaction information. With the
implementation of EHRs, the goal of many
organizations is to expand the scope of the early
CISs to become comprehensive systems that
provide clinical decision support, an electronic
patient record, and in some instances
professional development and training tools.
Benefits of such a comprehensive system
include easy access to patient data at the point
of care; structured and legible information that
can be searched easily and lends itself to data
mining and analysis; and improved patient
safety, especially the prevention of adverse drug
reactions and the identification of health risk
factors, such as falls.

TRACKING CLINICAL
OUTCOMES
The ability to measure outcomes can be
enhanced or impeded by the way an information
system is designed and used. Although many
practitioners can paint a very good picture of the
patient by using a narrative (free text),
employing this mode of expression in a clinical
system without the use of a coded entry makes
it difficult to analyze the care given or the
patient’s response. Free-text reporting also
leads to inconsistencies of reporting from

clinician to clinician and patient information that
is fragmented or disorganized. This can limit the
usefulness of patient data to other clinicians and
interfere with the ability to create reports from
the data for quality assurance and measurement
purposes. Moreover, not all clinicians are
equally skilled at the free-text form of
communication, yielding inconsistent quality of
documentation. Integrating standardized nursing
terminologies into computerized nursing
documentation systems enhances the ability to
use the data for reporting and further research.

According to the IOM (2012), “Payers,
healthcare delivery organizations and medical
product companies should contribute data to
research and analytic consortia to support
expanded use of care data to generate new
insights” (para. 2). McLaughlin and Halilovic
(2006) described the use of clinical analytics to
promote medical care outcomes research. The
use of a CIS in conjunction with standardized
codes for patient clinical issues helps to support
the rigorous analysis of clinical data. Outcomes
data produced as part of these analyses may
include length of stay, mortality, readmissions,
and complications. Future goals include the
ability to compare data and outcomes across
various institutions as a means of developing
clinical guidelines or best practices guidelines.

With the implementation of a comprehensive
CIS, similar analyses of nursing outcomes could
also be performed and shared. Likewise, such a
system could aid nurse administrators in cross-
unit comparisons and staffing decisions,
especially when coupled with acuity systems
data. In addition, clinical analytics can support
required data reporting functions, especially
those required by accreditation bodies.

SUPPORTING EVIDENCE-
BASED PRACTICE
Evidence-based practice (EBP) can be thought
of as the integration of clinical expertise and
best practices based on systematic research to
enhance decision making and improve patient
care. References supporting EBP, such as
clinical guidelines, are available for review at the
click of a mouse or the press of a few
keystrokes. The CIS’s prompting capabilities
can also reinforce the practice of looking for
evidence to support nursing interventions rather
than relying on how things have been done
historically. This approach enhances processing
and understanding of the information and allows
the nurse to apply the information to other
areas, increasing the knowledge obtained about

why certain conditions or responses result in
prompts for additional questions or actions.

To incorporate EBP into the practice of clinical
nursing, the information needs to be embedded
in the computerized documentation system so
that it is part of the workflow. The most typical
way of embedding this timely information is
through clinical practice guidelines. The
resulting interventions and clinical outcomes
need to be measurable and reportable for
further research. The supporting documentation
for the EBP needs to be easily retrievable and
meaningful. Links, reminders, and prompts can
all be used as vehicles for transmission of this
information. The format needs to allow for rapid
scanning, with the ability to expand the amount
of information when more detail is required or
desired. Balancing a consistency in formatting
with creativity can be difficult but is worth the
effort to stimulate an atmosphere for learning.

EBP is supported by translational research, an
exciting movement that has enormous potential
for the sharing and use of EBP. The use of
translational research to support EBP may help
to close the gap between what is known
(research) and what is done (practice).

THE CIS AS A STAFF

DEVELOPMENT TOOL
Joy Hilty, a registered nurse from Kaweah Delta,
came up with a creative way to provide staff
development or education without taking staff
away from the bedside to a classroom setting.
She created pop-up boxes on the opening
charting screens for all staff who chart on the
computer. These pop-ups vary in color and
content and include a short piece of clinical
information, along with a question. Staff can
earn vacations from these pop-ups for as long
as 14 days by emailing the correct answer to the
question. This medium has provided
information, stimulation, and a definite benefit:
the vacation from the pop-up boxes. The pop-up
box education format has also encouraged staff
to share their answers, thereby creating
interaction, knowledge dissemination, and
reinforcement of the education provided.

Embedding EBP into nursing documentation can
also increase the compliance with Joint
Commission core measures, such as providing
information on influenza and pneumococcal
vaccinations to at-risk patients. In the author’s
experience at Kaweah Delta, educating staff via
classes, flyers, and storyboards was not
successful in improving compliance with the
documentation of immunization status or

offering education on these vaccinations to at-
risk patients. Embedding the prompts,
information, and related questions in the nursing
documentation with a link to the protocol and
educational material, however, improved the
compliance to 96% for pneumococcal
vaccinations and to 95% for influenza
vaccinations (Hettinger, 2007).

As more information is stored electronically,
nurse informaticists must translate the
technology so that the input and retrieval of
information are developed in a manner that is
easy for clinicians to learn and use. A highly
usable product should decrease errors and
improve information entry and retrieval. Nurse
informaticists must be able to work with staff and
expert users to design systems that meet the
needs of the staff who will actually use the
systems. The work is not done after the system
is installed; the system must continue to be
developed and improved, because as staff use
the system, they will be able to suggest changes
to improve it. This ongoing revision should result
in a system that is mature and meets the needs
of the users.

In an ideal world, all clinical documentation will
be shared through a national database, in a
standard language, to enable evaluation of
nursing care, increase the body of evidence,

and improve patient outcomes. With minimal
effort, the information will be translated into new
research that can be analyzed and linked to new
evidence that will be intuitively applied to the
CIS. Alerts will be meaningful and will be patient
and provider specific. The steps required of the
clinician to find current, reliable information will
be almost transparent, and the information will
be presented in a personalized manner based
on user preferences stored in the CIS.

REFERENCES

Hettinger, M. (2007, March). Core
measure reporting: Performance
improvement. Visalia, CA: Kaweah
Delta Health Care District.

Institute of Medicine (IOM). (2012).
Best care at lower cost. Retrieved
from
https://www.nap.edu/catalog/13444/best-
care-at-lower-cost-the-path-to-
continuously-learning

McLaughlin, T., & Halilovic, M. (2006).
Clinical analytics, rigorous coding
bring objectivity to quality
assertions. Medical Staff Update

Online, 30(6). Retrieved from
http://med.stanford.edu/shs/update/archives/JUNE2006/analytics.htm

A more recent description of the benefits of an EHR by
HealthIT.gov (2014) emphasizes that EHRs hold the
promise of transforming healthcare; specifically, EHRs
will lead to:

Better health care by improving all aspects of
patient care, including safety, effectiveness, patient-
centeredness, communication, education,
timeliness, efficiency, and equity
Better health by encouraging healthier lifestyles in
the entire population, including increased physical
activity, better nutrition, avoidance of behavioral
risks, and wider use of preventative care
Improved efficiencies and lower healthcare
costs by promoting preventative medicine and
improved coordination of healthcare services, as
well as by reducing waste and redundant tests
Better clinical decision making by integrating
patient information from multiple sources (para. 4)

Standardized Terminology and
the EHR

As we inch closer to interoperable EHRs that provide
for seamless health information exchange among
providers and healthcare institutions, the need for
standardizing terminologies becomes ever clearer.
Consider also the trend toward value-based care
reimbursements, in which healthcare data are mined
“to demonstrate nursing’s contributions to improving
the cost, quality, and efficiency of care, key elements of
the value equation” (Adams, Ponte, & Somerville,
2016, p. 127). EHR data must be formatted in a
machine-readable manner in order to support
interoperable exchange of information and data mining.
An important distinction that needs to be made here is
the difference between interface terminologies
(NANDA, NIC, or NOC) and reference terminologies
(SMOMED-CT, LOINC).

While interface terminologies play an
important role in promoting direct entry of
categorical data by health care providers,
both terminology developers and the
standards community historically have
focused on other types of terminologies,
including reference and administrative
(rather than on interface) terminologies.
Such terminologies are generally
designed to provide exact and complete
representations of a given domain’s
knowledge, including its entities and
ideas and their interrelationships. For

example, reference terminologies can
support the storage, retrieval, and
classification of clinical data; their
contents correspond to the internal
system representation storage formats to
which interface terminologies are typically
mapped. (Rosenbloom, Miller,
Johnson, Elkin, & Brown, 2006, p. 278)

The various interface terminologies and their subsets
are coded in the EHR and typically presented to the
user in dropdown menus. Users may also be able to
use a search function in the EHR to identify the most
appropriate term that represents the patient’s
condition(s). Bronnert, Masarie, Naeymi-Rad, Rose,
and Aldin (2012) described the value of an interface
terminology for clinician workflow:

Clinicians interact with interface
terminology when documenting
diagnoses and procedures in the patient’s
electronic record. The physician performs
searches using the search functionality in
designated locations in the EHR, which
returns terms to the provider to select the
appropriate problem or procedure. The
physician [nurse] selects the appropriate
term to capture the clinical intent. The
term(s) populate predetermined fields in

the electronic record. The selected term
contains mappings to one or more
industry standard terminologies, such as
ICD or SNOMED CT. The “behind-the-
scenes” mappings allow the physician to
focus on patient care while at the same
time capturing the necessary
administrative and reference codes.
(para. 17)

The National Library of Medicine has been designated
as the central coordinating body for clinical
terminologies by the USDHHS. (See Box 14-3 for a list
and description of administrative and reference
terminologies used in an EHR.) Recall the ongoing
work of nursing groups looking to standardize nursing
terminologies to capture and codify the work of nursing.
(See Chapter 6 for a list of approved nursing
terminologies.) In 2015, the American Nurses
Association reaffirmed its support for the use of
standardized terminologies:

The purpose of this position statement is
to reaffirm the American Nurses
Association’s (ANA) support for the use
of recognized terminologies supporting
nursing practice as valuable
representations of nursing practice and to
promote the integration of those

terminologies into information technology
solutions. Standardized terminologies
have become a significant vehicle for
facilitating interoperability between
different concepts, nomenclatures, and
information systems. (para. 1)

BOX 14-3 STANDARD EHR

ADMINISTRATIVE AND REFERENCE

TERMINOLOGIES

Administrative (Billing) Terminologies

* ICD-10 (International Classification of
Diseases, Version 10): Medical diagnosis
code set

* CPT (Current Procedural Terminology):
Used to code procedures for billing

CLINICAL TERMINOLOGIES
SNOMED CT (Systematized Nomenclature
of Medicine—Clinical Terms):
Comprehensive clinical terminology
(mapping to this terminology is ongoing,
including nursing-orders mapping)
LOINC (Logical Observation Identifier
Names and Codes): Universal codes for
laboratory and clinical observations

RxNorm: Terminology system for drug
names, providing links to drug vocabularies
and interaction software
Unified Medical Language System (UMLS)
and the Metathesaurus: Support terminology
integration efforts and online searches (not a
terminology system)

See the U.S. National Library of Medicine
website for more comprehensive information:
www.nlm.nih.gov/hit_interoperability.html

Because no single model of standardized terminology
for health care or nursing can represent all of the
contributions to the health of a patient, work is ongoing
to map terminologies to one another. For example,
Kim, Hardiker, and Coenen (2014) studied the degree
of similarity between the International Classification for
Nursing Practice (ICNP) and the Systematized
Nomenclature of Medicine–Clinical Terms (SNOMED–
CT); while they identified some areas of overlap, they
cautioned that there is still more work to be done to
truly represent nursing concepts in the EHR. Adams et
al. (2016) issued a call to action to Chief Nursing
Officers (CNOs): “CNOs must begin partnering with
and influencing EHR developers and vendors to ensure
the EHRs implemented in their organizations capture
nursing content using a standardized taxonomy that is
evidence based and mapped to SNOMED-CT and

LOINC” (p. 127). Ongoing efforts to map nursing
problem lists to SNOMED-CT are evident in the work of
Matney and colleagues (2011) and on the National
Library of Medicine website
(www.nlm.nih.gov/hit_interoperability.html). It is
probably safe to say that the number of different types
of EHRs and the variability of EHRs are likely to
contract and converge as the demand for robust
systems supporting interoperability expands. Nurse
informatics specialists and CNOs participating in the
selection and implementation of EHRs must ask a
critical question: To what extent are nursing care
contributions visible, retrievable, and accurately
represented in this EHR?

Ownership of Electronic Health
Records
The implementation of an EHR has the potential to
affect every member of a healthcare organization. The
process of becoming a successful owner of an EHR
has multiple steps and requires integrating the EHR
into the organization’s day-to-day operations and long-
term vision, as well as into the clinician’s day-to-day
practice. All members of the healthcare organization—
from the executive level to the clinician at the point of
care—must feel a sense of ownership to make the
implementation successful for themselves, their
colleagues, and their patients. Successful ownership of

an EHR may be defined in part by the level of clinician
adoption of the tool, and this section reviews key steps
and strategies for the selection, implementation and
evaluation, and optimization of an EHR in pursuit of
that goal.

Historically, many systems were developed locally by
the information technology department of a healthcare
organization. It was not unusual for software
developers to be employed by the organization to
create needed systems and interfaces between them.
As commercial offerings were introduced and matured,
it became less and less common to see homegrown or
locally developed systems.

As this history suggests, the first step of ownership is
typically a vendor selection process for a commercially
available EHR. During this step, it is important to
survey the organization’s level of interest, identify
possible barriers to participation, document desired
functions of an EHR, and assess the willingness to
fund the implementation (Holbrook, Keshavjee,
Troyan, Pray, & Ford, 2003). Although clinicians, as
the primary end users, should drive the project, the
assessment should also include the needs and
readiness of the executive leadership, information
technology, and project management teams. It is
essential that leadership understands that this type of
project is as much about redesigning clinical work as it
is about technically automating it and that they agree to

assume accountability for its success (Goddard,
2000). In addition, this pre-acquisition phase should
concentrate on understanding the current state of the
health information technology industry to identify
appropriate questions and the next steps in the
selection process (American Organization of Nurse
Executives, 2009). These first steps begin to identify
any organizational risks related to successful
implementation and pave the way for initiating a
change management process to educate the
organization about the future state of delivering health
care with an EHR system.

The second step of the selection process is to select a
system based on the organization’s current and
predicted needs. It is common during this phase to see
a demonstration of several vendors’ EHR products.
Based on the completed needs assessment, the
organization should establish key evaluation criteria to
compare the different vendors and products. These
criteria should include both subjective and objective
items that cover such topics as common clinical
workflows, decision support, reporting, usability,
technical build, and maintenance of the system.
Providing the vendor with these guidelines will ensure
that the process meets the organization’s needs;
however, it is also essential to let the vendor
demonstrate a proposed future state from its own
perspective. This activity is critical to ensuring that the
vendor’s vision and the organization’s vision are well

aligned (Konschak & Shiple, n.d.). It also helps spark
dialogue about the possible future state of clinical work
at the organization and the change required in
obtaining it. Such demonstrations not only enable the
organization to compare and contrast the features and
functions of different systems, but also are a good way
to engage the organization’s members in being a part
of this strategic decision.

Implementation planning should occur concurrently
with the selection process, particularly the assessment
of the scope of the work, initial sequencing of the EHR
components to be implemented, and resources
required. However, this step begins in earnest once a
vendor and a product have been selected. In addition
to further refining the implementation plan, this is the
time to identify key metrics by which to measure the
EHR’s success. An organization may realize numerous
benefits from implementing an EHR. It should choose
metrics that match its overall strategy and goals in the
coming years and may include expected improvements
in financial, quality, and clinical outcomes. Commonly
used metrics focus on reductions in the number of
duplicate laboratory tests through duplicate orders
alerting, reductions in the number of adverse drug
events through the use of bar-code medication
administration, meaningful use objectives and
measures, and the EHR advantages mentioned earlier
in this chapter. To ensure that the desired benefits are
realized, it is important to avoid choosing so many that

they become meaningless or unobtainable, to carefully
and practically define those that are chosen, to
measure before and after the implementation, and to
assign accountability to a member of the organization
to ensure the work is completed.

End-user adoption of the EHR is also essential to
realizing its benefits. Clinicians must be engaged to
use the EHR successfully in their practice and daily
workflows so that data may be captured to drive the
decision support that underlies so many of the
advantages and metrics described. To promote
adoption, a change management plan must be
developed in conjunction with the EHR implementation
plan. The most effective change management plans
offer end users several exposures to the system and
relevant workflows in advance of its use and continue
through the go-live and post-live time periods.
Successful pre-live strategies include end-user
involvement as subject-matter experts to validate the
EHR workflow design and content build, hosting end-
user usability testing sessions, shadowing end users in
their current daily work in parallel with the new system,
and formal training activities. The goal of these pre-live
activities is not only to ensure that the EHR
implementation will meet end user needs, but also to
assess the impact of the new EHR on current workflow
and process. The larger the impact, the more change
management is required above and beyond system
training. For example, simulation laboratory

experiences may be offered to more thoroughly dress
rehearse a significant workflow change, executive
leadership may need to convey their support and
expectations of clinicians about a new way of working,
and generally more anticipatory guidance is required to
communicate to those impacted by the changes.

Training may be delivered in a variety of media. Often
a combination of approaches works best, including
classroom time, electronic learning, independent
exercises, and peer-to-peer, at-the-elbow support.
Training must be workflow based and reflect real
clinical processes. It must also be planned and
budgeted for through the post-live period to ensure that
competency with the system is assessed at the go-live
point and that any necessary retraining or
reinforcements are made in the 30 to 60 days post-live.
This not only promotes reliability and safe use of the
system as it was designed but also can have a positive
impact on end users’ morale: Users will feel that they
are being supported beyond the initial go-live period
and have an opportunity to move from basic skills to
advanced proficiency with the system.

Finally, the implementation plan should account for the
long-term optimization of the EHR. This step is
commonly overlooked and often results in benefits
falling short of expectations because the resources are
not available to realize them permanently. It also often
means the difference between end users of EHRs

merely surviving the change versus becoming savvy
about how to adopt the EHR as another powerful
clinical tool, much as clinicians have embraced such
technologies as the stethoscope (HealthIT.gov, 2012).
Optimization activities of the EHR should be
considered a routine part of the organization’s
operations, should be resourced accordingly, and
should emphasize the continued involvement of
clinician users to identify ways that the EHR can
enable the organization to achieve its overall mission.
Many organizations start an implementation of EHRs
with the goal of transforming their care delivery and
operations. An endeavor that differs from simply
automating a previously manual or fragmented
process, transformation often includes steps to improve
the process so as to realize better patient care
outcomes or added efficiency. Although some
transformation is experienced with the initial use of the
system, most of this work is done postimplementation
and relies on widespread clinician adoption of the EHR.
As such, it makes optimization a critical component to
successful ownership of an EHR.

Flexibility and Expandability
Health care is as unique as the patients themselves. It
is delivered in a variety of settings, for a variety of
reasons, over the course of a patient’s lifetime. In
addition, patients rarely receive all their care from one
healthcare organization; indeed, choice is a

cornerstone of the American healthcare system. An
EHR must be flexible and expandable to meet the
needs of patients and caregivers in all these settings,
despite the challenges.

At a very basic level, there is as yet no EHR system
available that can provide all functions for all
specialties to such a degree that all clinicians would
successfully adopt it. Consider oncology as an
example. Most systems do not yet provide the
advanced ordering features required for the complex
treatment planning undertaken in this field. An
oncologist could use a general system, but he or she
would not find as many benefits without additional
features for chemotherapy ordering, lifetime cumulative
dose tracking, or the ability to adjust a treatment day
schedule and recalculate a schedule for the remaining
days of the plan. Some EHRs do a good job of
supporting the work of nursing staff and physicians, but
are not as supportive of the work of clinicians such as
dieticians, physical and occupational therapists, and
other healthcare personnel. These systems will
continue to evolve and support interprofessional
collaboration as more healthcare professionals are
exposed to the power of these systems to support their
work and become better able to articulate their specific
needs.

Further, most healthcare organizations do not yet have
the capacity to implement and maintain systems in all

care areas. As one physician stated, “Implementing an
EMR is a complex and difficult multidisciplinary effort
that will stretch an organization’s skills and capacity for
change” (Chin, 2004, p. 47).

These two conditions are improving every day at both
vendor and healthcare organizations alike.
Improvements in both areas were recently fueled by
ARRA incentives (see Box 14-4).

BOX 14-4 CLOUDY EHRS

A paradigm shift from healthcare facility–owned,
machine-based computing to offsite, vendor-
owned cloud computing, Web browser–based
log-in accessible data, software, and hardware
could link systems together and reduce costs.
Hospitals with shrinking budgets and extreme IT
needs are exploring the successes in this area
achieved in other industries, such as Amazon’s
S3. As providers strive to implement potent
EHRs, they are looking for cloud-based models
that offer the necessary functionality without
having to assume the burden associated with all
of the hardware, software, application, and
storage issues. However, in the face of the
HITECH Act and its associated penalties, how
can we overcome the challenges to realize the
benefits of this approach? Cloud computing has
both advantages and disadvantages, and while

they explore this new paradigm, healthcare
providers must relinquish control as they
continue to strive to maintain security. The
vendors that are responsible for developing and
maintaining this new environment are also
facing challenges originating from both
legislatures and healthcare providers. As the
vendors and healthcare providers work together
to improve the implementation and adoption of
the cloud-based EHR, the sky is the limit!

ARRA has also set the expectation that despite the
large number of settings in which a patient may receive
care, a minimum set of data from those records must
flow or “interoperate” among each setting and the
unique EHR systems used in those settings. Today,
interoperability exists through what is called a
Continuity of Care Document (CCD). This dataset
includes patient demographics, medication, allergy,
and problem lists, among other things, and the
formatting and exchange of the CCD is required to be
supported by EHR vendors and healthcare
organizations seeking ARRA meaningful use
incentives. The document formatted according to HL7
standards is both machine readable and human
readable.

Despite this positive step forward, financial and patient
privacy hurdles remain to be overcome to achieve an

expansive EHR. Most health care is delivered by small
community practices and hospitals, many of which do
not have the financial or technical resources to
implement robust, interoperable EHRs. USDHHS
recently loosened regulations so that physicians may
now be able to receive healthcare information
technology software, hardware, and implementation
services from hospitals to alleviate the financial burden
placed on individual providers and to foster more
widespread adoption of the EHR.

Finally, patient privacy is a pivotal issue in determining
how far and how easy it will be to share data across
healthcare organizations. In addition to the Health
Insurance Portability and Accountability Act privacy
rules, many states have regulations in place related to
patient confidentiality. An experience of the state of
Minnesota foreshadows what all states may encounter.
In 2007, Governor Tim Pawlenty announced the
creation of the Minnesota Health Information Exchange
(State of Minnesota, Office of the Governor, 2007).
Although the intentions of the exchange were to
promote patient safety and increase healthcare
efficiency across the state, it raised significant
concerns about security and privacy. New questions
arose about the definition of when and how patient
consent is required to exchange data electronically,
and older paper-based processes needed to be
updated to support real-time electronic exchange
(Minnesota Department of Health, 2007). For health

exchanges such as these to reach their full potential,
members of the public must be able to trust that their
privacy will be protected, or else the healthcare
industry risks that patients may not share a full medical
history, or worse yet, may not seek care, effectively
making the exchanges useless.

Accountable Care
Organizations and the EHR
EHRs with data-sharing capabilities are central to the
support of Accountable Care Organizations (ACOs), a
payment incentive program established by the CMS
(2015). As discussed elsewhere, this program of
shared medical and financial responsibility is designed
to provide quality, coordinated care while limiting costs.
Some of the core information technology requirements
for an ACO are EHRs, HIEs, care management
systems, and analytics and reporting systems
(Mastagni, Welter, & Holmes, 2015). A robust EHR
can support many of these functions:

EHR solutions that are interoperable
across organizations can significantly
reduce the cost and complication of IT
infrastructure by creating full EHR
visibility between providers. This shared
visibility reduces or eliminates the need to
participate in HIEs or invest in solutions

to integrate data across different EHR
platforms. Many EHRs also can serve as
a program’s care management system,
eliminating the need for a separate
system to document care management
efforts and help care teams engage with
patients. (Mastagni et al., 2015, para. 5)

See Figure 14-2.

Figure 14-2 How EHRs Support Accountable Care

Data from ECG Consultants. (2015). The use of technology in healthcare

reform: IT considerations for accountable care. Retrieved from

http://www.ecgmc.com/thought-leadership/articles/the-use-of-

technology-in-healthcare-reform-it-considerations-for-accountable-

care

The Future
Despite the challenges, the future of EHRs is an
exciting one for patients and clinicians alike. Benefits
may be realized by implementing stand-alone EHRs as
described here, but the most significant transformation
will come as interoperability is realized between
systems. As the former national information technology
coordinator in the USDHHS David Brailer predicted
about the potential of interoperability:

For the first time, clinicians everywhere
can have a longitudinal medical record
with full information about each patient.
Consumers will have better information
about their health status since personal
health records and similar access
strategies can be feasible in an
interoperable world. Consumers can
move more easily between and among
clinicians without fear of their information
being lost. Payers can benefit from the
economic efficiencies, fewer errors, and

reduced duplication that arises from
interoperability. Healthcare information
exchange and interoperability (HIEI) also
underlies meaningful public health
reporting, bioterrorism surveillance,
qsuality monitoring, and advances in
clinical trials. In short, there is little that
most people want from health care for
which HIEI isn’t a prerequisite. ( Brailer ,
2005, p. W 5-20)

The future also holds tremendous potential for EHR
features and functions that will include not only more
sophisticated decision support and clinical reporting
capacity, but also improved support for all healthcare
professionals, improved biomedical device integration,
ease of use and intuitiveness, and access through
more hardware platforms.

Implementation of robust and interoperable EHRs is
becoming more commonplace. More organizations
adopting EHRs will facilitate broader dissemination of
implementation best practices, with the hope of further
shortening the time required to take advantage of
advanced EHR features.

In the future, we can expect to see more EHRs housed
in the cloud, usable patient portals as we move toward
more patient-centered health care, better mobile

applications for the EHR, the expansion of
telemedicine applications for rural patients and those
with chronic illnesses, and precision medicine
advances supported by data analytics (Reisenwitz,
2016).

Summary
It is an important time for health care and technology.
EHRs have come to the forefront and will remain
central to shaping the future of health care. In an ideal
world, all nurses, from entry-level personnel to
executives, will have a basic competency in nursing
informatics that will enable them to participate fully in
shaping the future use of technology in the practice at
a national level and wherever care is delivered. Such
initiatives as Technology Informatics Guiding Education
Reform (TIGER) and the important nursing terminology
work are imperative for better integration and,
ultimately, more visibility of nursing contributions to
health care.

THOUGHT-PROVOKING QUESTIONS

1. What are the implications for nursing
education as the EHR becomes the
standard for caring for patients?

2. What are the ethical considerations
related to interoperability and a shared
EHR?

3. You are asked about a diagnosis with
which you are unfamiliar. Where would
you start looking for information? How
would you determine the validity of the
information?

4. Think about the documentation and
knowledge management functions of your
specialty. If you had the opportunity to
create a wish list, what would you include
in an EHR to support your work?

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CHAPTER 15: Informatics
Tools to Promote Patient
Safety and Quality
Outcomes

Dee McGonigle and Kathleen Mastrian

Objectives
1. Explore the characteristics of a safety

culture.
2. Examine strategies for developing a

safety culture.
3. Recognize how human factors contribute

to errors.
4. Appreciate the impact of informatics

technology on patient safety.

Key Terms

» Adverse events

» Agency for Healthcare Research and
Quality (AHRQ)

» Alarm fatigue

» Applications (apps)

» Bar-code medication administration
(BCMA)

» Clinical decision support (CDS)

» Computerized physician order entry
(CPOE)

» Electronic medication administration
system (eMAR)

» Failure modes and effects analysis
(FMEA)

» Government Accountability Office
(GAO)

» High-hazard drugs

» Human factors engineering

» Just culture

» Never events

» Radio frequency identifier (RFID)

» Root-cause analysis

» Safety culture

» Smart pump

» Smart rooms

» Systems engineering

» Wearable technology

» Workarounds

Introduction
Nursing professionals have an ethical duty to ensure
patient safety. According to Lavin et al. (2015), “Direct
care nurses, at their core, are risk managers. They
attach meaning to what is and anticipate ‘what might
be’” (para. 8). As the media and patients circulate
stories about the lack of safety in healthcare
institutions, it is no wonder that healthcare consumers
are skeptical and providers are wary. A study out of
Johns Hopkins University (Johns Hopkins Medicine,
2016) suggested that medical errors are the third-
leading cause of death in the United States. Versel
(2016) reminded us, however, that “it’s not the first time
someone has called medical error the No. 3 cause of
death in the U.S. John T. James, founder of a group
called Patient Safety America, did that in a 2013 report
in the Journal of Patient Safety.” (para. 2). Increasing
demands on professionals in complex and fast-paced

healthcare environments may lead them to cut corners
or develop workarounds that deviate from accepted
and expected practice protocols. These deviations are
not carried out deliberately to put patients at risk, but
rather are often practiced in the interest of saving time
or because the organizational culture is such that risky
behaviors are commonplace. Occasionally, these
inappropriate actions or omissions of appropriate
actions result in harm or significant risk of harm to
patients. Consider the following case scenario:

A 19-year-old obese woman who had
recently undergone C-section delivery of
a baby presented in the emergency
department (ED) with dyspnea. Believing
the patient had developed a pulmonary
embolism, the physician prescribed an IV
heparin bolus dose of 5,000 units
followed by a heparin infusion at 1,000
units/hour. After administering the bolus
dose, a nurse started the heparin infusion
but misprogrammed the pump to run at
1,000 mL/hour, not 1,000 units/hour (20
mL/hour). By the time the error was
discovered, the patient had received
more than 17,000 units (5,000 unit
loading dose and about 12,000 units from
the infusion) in less than an hour since
arrival in the ED. A smart pump with
dosing limits for heparin had been used.

Thus, the programming error should have
been recognized before the infusion was
started. However, the nurse had elected
to bypass the dose-checking technology
and had used the pump in its standard
mode. It was quite fortunate that the
patient did not experience adverse
bleeding as her aPTT values were as
prolonged as 240 seconds when initially
measured and 148 seconds two hours
later. (Institute for Safe Medication
Practices, 2007, para. 2)

The smart pump used in this scenario was equipped
with dose calculation software that compares the
programmed infusion rate to a drug database to check
for dosing within safe limits. This technology is
particularly important when high-alert or high-hazard
drugs are being administered. In this case, however,
the available dose-checking technology had been
turned off and the pump was operated in standard
mode. A subsequent analysis of the error event
revealed that many nurses in the institution were
bypassing the safety technology afforded by the smart
pump to save time. Even though it has been more than
a decade since this error occurred, we continue to see
alerts and safety checks being worked around, ignored,
or turned off. This chapter focuses on some of the
recommended organizational strategies used to

promote a culture of safety and some of the specific
informatics technologies designed to reduce errors and
promote patient safety.

What Is a Culture of Safety?
The 2000 Institute of Medicine report To Err Is Human
is widely credited for launching the current focus on
patient safety in health care. This report was followed
in 2001 by the Institute of Medicine’s Crossing the
Quality Chasm report, which brought to national
attention healthcare quality and safety. This national
attention resulted in a $50 million grant by Congress to
the Agency for Healthcare Research and Quality
(AHRQ) to launch initiatives focused on safety
research for patients. Other initiatives prompted by
these seminal reports were the Joint Commission’s
National Patient Safety Goals (2002); the National
Quality Forum’s adverse events and “never events”
list (2002); the creation of the Office of National
Coordinator for Health Information Technology (HIT) to
computerize health care (2004); the formation of the
World Health Organization’s Alliance for Patient Safety
(2004); the Institute for Healthcare Improvement’s (IHI)
100,000 Lives campaign (2005) and 5 Million Lives
campaign (2008); Congressional authorization of
patient safety organizations created by the Patient
Safety and Quality Improvement Act to promote
blameless error reporting and shared learning (2005);
the “no pay for errors” initiative launched by Medicare

(2008); and the $19 billion Congressional appropriation
to support electronic health records (EHRs) and patient
safety (Wachter, 2010). In 2013, the Patient Safety
Movement Foundation launched the Open Data
Pledge, and later announced three new patient safety
challenges in 2016 (Patient Safety Movement, 2016).
The most pressing challenges they identified—venous
thromboembolism, mental health, and pediatric
adverse drug events—reflect those where patient
death could be prevented with the proper protocols in
place during the provision of patient care (Patient
Safety Movement).

The AHRQ (2012) safety culture primer laid the
foundation for and suggested that organizations should
strive to achieve high reliability by being committed to
improving healthcare quality and preventing medical
errors and to demonstrate an overall commitment to
patient safety. That is, everyone and every level in an
organization must embrace the safety culture. Key
features of a safety culture identified by the AHRQ are
as follows:

Acknowledgment of the high-risk nature of an
organization’s activities and the determination to
achieve consistently safe operations
A blame-free environment where individuals are
able to report errors or near misses without fear of
reprimand or punishment
Encouragement of collaboration across ranks and

disciplines to seek solutions to patient safety
problems
Organizational commitment of resources to address
safety concerns (AHRQ, 2012, para. 1)

An important part of the safety culture is cultivating a
blame-free environment. Errors and near misses must
always be reported so that they can be thoroughly
analyzed. All organizations can learn from mistakes
and change their organizational processes or culture to
ensure patient safety. The Patient Safety and Quality
Improvement Act of 2005 mandated the creation of a
national database of medical errors and funded several
organizations to analyze these data with the goal of
developing shared learning to prevent medical errors.
Organizations themselves can engage in root-cause
analysis or failure modes and effects analysis
(FMEA) to examine medical errors closely and to
determine the system processes that need to be
changed to prevent similar future errors (Harrison &
Daly, 2009). A tool for implementing root-cause
analysis developed by the U.S. Department of
Veteran’s Affairs National Center for Patient Safety
(2015) had three goals: to determine “what happened,
why did it happen and how to prevent it from
happening again” (para. 4). Everyone is encouraged to
submit actual medical errors and/or patient safety
issues to the Patient Safety Network (PSNet, 2016a).
Similarly, the IHI has a website dedicated to FMEA.
“Failure Modes and Effects Analysis (FMEA) is a

systematic, proactive method for evaluating a process
to identify where and how it might fail, and to assess
the relative impact of different failures in order to
identify the parts of the process that are most in need
of change” (IHI, 2016b, para. 1). If one embraces a
blame-free environment to encourage error reporting,
then where does individual accountability fit in?
According to the AHRQ, one way to balance these
competing cultural values (blameless versus
accountability) is to establish a “just culture” where
system or process issues that lead to unsafe behaviors
and errors are addressed by changing practices or
workflow processes, and a clear message is
communicated that reckless behaviors are not
tolerated. The “just culture” approach accounts for
three types of behaviors leading to patient safety
compromises: (1) human error (unintentional
mistakes); (2) risky behaviors (workarounds); and (3)
reckless behavior (total disregard for established
policies and procedures).

Strategies for Developing a
Safety Culture
Strategies for achieving a safety culture have been
addressed frequently in the literature. The focus here is
limited to those strategies described by two key
organizations, the AHRQ and the IHI. The AHRQ
(2016), based on data from the Hospital Survey on

Patient Safety Culture, suggested that teamwork
training, executive walk-arounds, and unit-based safety
teams have improved safety culture perceptions but
have not led to a significant reduction in error rates.
The AHRQ recommended seven steps of action
planning: “1. Understand your survey results. 2.
Communicate and discuss survey results. 3. Develop
focused action plans. 4. Communicate action plans and
deliverables. 5. Implement action plans. 6. Track
progress and evaluate impact. 7. Share what works” (p.
61). Informatics can assist with the analysis, trending,
synthesis, and dissemination of the action plan results.

The IHI (2016a) stressed that organizational leaders
must drive the culture change by making a visible
commitment to safety and by enabling staff to share
safety information openly. Some of the strategies
suggested by the IHI include appointing a safety
champion for every unit, creating an adverse event
response team, and reenacting or simulating adverse
events to better understand the organizational or
procedural processes that failed. Barnet (2016)
reported that 49 companies had signed the open data
pledge with Patient Safety Movement. Radick (2016)
believed that senior leaders must be involved in order
to sustain patient safety improvements. Leadership
oversight and support is critical to ongoing sharing and,
most importantly, collaborative solution development to
provide safe care and achieve quality outcomes for all
patients.

A systems engineering approach to patient safety, in
which technology manufacturers partner with
organizations to identify risks to patient safety and
promote safe technology integration, has been
advocated by Ebben, Gieras, and Gosbee (2008).
They noted that human factors engineering is “[t]he
discipline of applying what is known about human
capabilities and limitations to the design of products,
processes, systems, and work environments,” and its
application to system design improves “ease of use,
system performance and reliability, and user
satisfaction, while reducing operational errors, operator
stress, training requirements, user fatigue, and product
liability” (p. 327). For example, Ebben et al. described
the feel of an oxygen control knob that rotated
smoothly between settings, suggesting to the user that
oxygen flows at all points on the knob, when in fact
oxygen flowed only at specifically designated liter flow
settings. Human factors engineering testing would
most likely reveal this design flaw, and the setting knob
could be improved to include discrete audio or tactile
feedback (click into place) to the user to indicate a
point on the dial where oxygen flows. Ebben et al. also
emphasized that testing human use factors provides
more objective safety data than the subjective
responses gained from user preference testing.
“Understanding how the equipment shapes human
performance is as important as evaluating reliability or
other technical criteria” (p. 329). Organizations that are

purchasing medical technology devices should avail
themselves of shared safety data on equipment
maintained by several key organizations, including the
Joint Commission, the Food and Drug Administration,
and the Medical Product Safety Network. Many
healthcare practitioners feel that we have not made
great strides in either sharing our data or accessing the
available data to enhance patient safety interests.
According to WISH Patient Safety Forum (2015), the
patient safety premises that harms are inevitable, data
silos are natural, and heroism is the norm “have
inadvertently provided excuses for not addressing
patient safety comprehensively” (p. 9). This forum also
stated that

[t]he belief that data silos are acceptable
in healthcare settings is an irresponsible
view regarding the role of data; it lacks an
understanding of the current operational
setting. Healthcare is a complex,
multidisciplinary environment that
requires collaboration and sharing of data
across an integrated stakeholder
community. (WISH Patient Safety Forum,
p. 9)

As HIT evolves, refinements in HIT continue to improve
patient safety. Banger and Graber (2015) stated that
the

ONC is involved in a number of initiatives
in support of this goal, including plans for
a new national Health IT Safety Center to
coordinate these efforts. Combined with
the active engagement from the private
sector, there is every reason to be
optimistic that health IT will continue to
improve the quality and safety of health
care beyond the accomplishments
realized to date. (p. 10)

According to the PSNet (2015), “busy health care
workers rely on equipment to carry out life-saving
interventions, with the underlying assumption that
technology will improve outcomes” (para. 2). PSNet
provided the following descriptions of equipment
issues:

An obstetric nurse connects a bag of pain
medication intended for an epidural
catheter to the mother’s intravenous (IV)
line, resulting in a fatal cardiac arrest.
Newborns in a neonatal intensive care
unit are given full-dose heparin instead of
low-dose flushes, leading to three deaths
from intracranial bleeding. An elderly man
experiences cardiac arrest while
hospitalized, but when the code blue
team arrives, they are unable to

administer a potentially life-saving shock
because the defibrillator pads and the
defibrillator itself cannot be physically
connected. (para. 1)

See also Figure 15-1.

Figure 15-1 User–Technology–Patient Safety Scheme

Once the technology is integrated into the organization,
biomedical engineers can become valuable partners in
promoting patient safety through appropriate use of
these technologies. For example, in one organization,
the biomedical engineers helped to revamp processes
associated with the new technology alarm systems
after they discovered several key issues: slow

response times to legitimate alarms and multiple false
alarms (promoting alarm fatigue) created by alarm
parameters that were too sensitive. Strategies for
addressing these issues included improving the nurse
call system by adding Voice over Internet Protocol
telephones that wirelessly receive alarms directly from
technology equipment carried by all nurses, thus
reducing response times to alarms; feeding alarm data
into a reporting database for further analysis; and
encouraging nurses to round with physicians to provide
input into alarm parameters that were too sensitive and
were generating multiple false alarms (Joint
Commission, 2013; Williams, 2009). Research Brief 1
describes three investigations spanning from 2009 to
2016: a study of intelligent agent (IA) technology to
improve the specificity of physiologic alarms, an
integrative review of alarms, and default alarm setting
changes coupled with in-service education. The Case
Scenario, Well-Intentioned Providers, demonstrates
how well-intentioned healthcare providers can cause
harm. An audit conducted at one of their customer sites
by Philips Healthcare (2013) revealed that a

Telemetry Charge Nurse was found to be
receiving and responding to an average
of 3.7 alarms per minute over the
duration of the audit. Even allowing for
minimal time to respond to each alarm, it
is clear that this situation was
problematic. A majority of that nurse’s

time was spent responding to alarms, and
inevitably some were missed. (para. 1)

The Joint Commission (2016) released the 2016
Hospital National Patient Safety Goals, and one
category, Use Alarms Safely, stated that hospitals must
“make improvements to ensure that alarms on medical
equipment are heard and responded to on time” (para.
4).

RESEARCH BRIEF 1

The investigators in one study used simple
reactive IA technology to develop and test
decision algorithms for improving the sensitivity
and specificity of physiologic alarms. The IA
technology was tested in a 14-bed
cardiothoracic unit over 28 days and was
implemented in parallel to the usual physiologic
patient monitor that provided measures such as
systolic blood pressure, mean arterial pressure,
central venous pressure, and cardiac index.
Alarm data generated by both systems were
compared and classified as to whether the alarm
represented a true medical event requiring
clinician intervention or a false-positive alarm. A
total of 293,049 alarms were generated by the
usual physiologic monitoring system, and 1,012
alarms were generated by the IA system after
raw physiologic data were filtered using rule-

based IA technology. The IA filtering system
shows promise for improving the specificity of
physiologic alarms and decreasing the number
of false-positive alarms generated by artifacts,
thus reducing the incidence of alert fatigue in
clinicians.

The full article appears in Blum, J., Kruger, G.,
Sanders, K., Gutierrez, J., & Rosenberg, A.
(2009). Specificity improvement for network
distributed physiologic alarms based on a simple
deterministic reactive intelligent agent in the
critical care environment. Journal of Clinical
Monitoring and Computing, 23(1), 21–30.

Another study conducted an integrative review
of monitor alarm fatigue. The study’s evidence-
based practice recommendations for technology
included incorporating short delays to increase
response rates, creating a set of standardized
alarms to enhance the staff’s ability to quickly
determine what the alarm is for, and animated
troubleshooting on monitoring equipment. The
author concluded that lack of response to
alarms has caused harm and death and stated
that, because a focus on patient outcomes is
needed, outcomes research must be performed.

The full article appears in Cvach, M. (2012).
Monitor alarm fatigue: An integrative review.

Biomedical Instrumentation & Technology, 46(4),
268–277. doi.org/10.2345/0899-8205-46.4.268

A pilot project was conducted to investigate if
“(1) a change in default alarm settings of the
cardiac monitors and (2) in-service nursing
education on cardiac monitor use in an ICU”
would decrease alarm rates and improve the
attitudes and practices of nurses in relation to
clinical alarms (para. 2). This quality
improvement project examined 39 nurses in a
20-bed transplant/cardiac ICU. Nurses received
an in-service on monitor use, an audit log of
alarms was collected, and the nurses’ attitudes
and clinical practices were assessed using a
pre- and postintervention survey. The authors
concluded that “changing default alarm settings
and standard in-service education on cardiac
monitor use are insufficient to improve alarm
systems safety” (para. 5).

The full article appears in Sowan, A. K., Gomez, T. M, Tarriela,

A. F., Reed, C. C., & Paper, B. M. (2016). Changes in default

alarm settings and standard in-service are insufficient to improve

alarm fatigue in an intensive care unit: A pilot project. JMIR

Human Factors, 3(1), e1.

CASE SCENARIO: WELL-INTENTIONED

PROVIDERS

Even well-intentioned healthcare providers can
cause harm. Consider what should have been
done differently in the case example below.

Laura, a 25-year-old woman,
arrived at the ER complaining of
chest pain. She has two young
children at home: a 6-year-old boy
and a 4-year-old girl. She stated
that she has been experiencing
severe fatigue and fluttering in her
chest for weeks but felt that she
needed rest and it was probably
nothing. Today, she had the
fluttering with chest pain, and even
her teeth and jaw hurt. This scared
her, so she decided to go to the
hospital. However, she had to wait
2 hours for her mother to arrive to
watch the children. Her husband is
on a business trip and will not be
returning for 4 days. The initial
ECG revealed normal sinus
rhythm and all lab values were
normal. The ER physician decided
to keep her for observation and
sent her to the telemetry unit.

Laura was moved to telemetry
and, as she stated, “wired for
sound.” The nurse described the

equipment and told her that in
addition to all of the monitoring
equipment, they would check her
vital signs every hour as well. The
nurse no sooner returned to the
nurse’s station when Laura’s
cardiac monitor alerted her that
Laura was experiencing severe
bradycardia (heart rate of less than
40 beats per minute). When the
nurse arrived at Laura’s bedside,
she found Laura sound asleep.
She woke her gently and told her
that her monitor was alarming and
that she was going to check her.
Laura stated that she felt tired and
was enjoying the peaceful sleep.
Laura’s vital signs were fine and
her heart rate was 72 beats per
minute. The nurse reset the
monitor, by which point Laura had
already fallen back to sleep. The
monitor alarmed the same way
three more times within the next
hour. Each time the nurse woke
Laura and everything was fine.
The nurse decided to contact the
resident. While she was waiting for
the resident, it alarmed twice
again, but she just reset it and let

Laura sleep. The resident came
and examined Laura. The resident
felt everything was OK and that
this young mother needed her rest.
The resident suggested that the
nurse stop the hourly vitals, call
and have the equipment examined
by the biomedical department, and
in the meantime to turn the alarm
off. The nurse agreed, turned off
the alarm, placed a call to the
biomedical technician on duty, and
left a message.

The nurse had another patient who
also had frequent alarms, but his
corresponded to actual medical
events. As a result, the nurse was
spending a great deal of time with
this elderly gentleman and his
wife. Each time she walked by
Laura’s bed, the nurse noted that
Laura was sleeping. She realized
that it had been 2 hours since she
turned off the alarm and called the
biomedical technician, so she
decided to check on Laura;
however, her other patient’s alarm
went off and, since Laura was
sleeping, the nurse went to the

other pateint’s bedside. At 4 hours
after the alarm had been turned
off, the biomedical technician
arrived and apologized because
there was a call-off in their
department and they were running
shorthanded. The nurse explained
what had happened and the
biomedical technician went to
check Laura’s monitoring
equipment. The biomedical
technician called for the nurse as
the patient was unresponsive. The
nurse could not wake Laura, and
the monitor was showing asystole.
A code was initiated and Laura
was pronounced dead 5 hours
after she arrived on the telemetry
unit.

This situation was assessed by the
patient safety officer and the
patient safety committee.

Because the monitor was
integrated and all functions ran
through the same controller, the
nurse did not realize she was
turning off all of the monitors
(pulse oximetry, blood pressure,
etc.). This was found to be an

issue with the equipment itself
because the alarm settings are too
close together and not clearly
labeled; however, the nurse should
never have turned the alarms off.
With the hourly checks cancelled
and all of the monitoring
equipment silenced, Laura was not
being monitored at all. Well-
intentioned providers were
allowing this young mother to
sleep, but with fatal
consequences.

It is evident from Research Brief 1 and the Case
Scenario that we have yet to find a solution to the
problem of alarm fatigue and related issues that
negatively impact patient safety.

Clearly, there is more work to be done to create safety
cultures in complex healthcare organizations and to
reduce the incidence of errors. Many organizations are
looking to informatics technology to help manage these
complex safety issues by using smart technologies that
provide knowledge access to users, provide automated
safety checks, and improve communication processes.
Harrison (2016) stated that “as nurse leaders in a
clinical setting where smart tools are leveraged to

increase the quality and safety of patient care, we have
certain responsibilities to ensure safe implementation,
training, and monitoring” (p. 21). To best utilize the
available technology, nurse leaders and administrators
must be able to use data. More and more graduate
programs for nursing administrators are realizing the
need for these emerging nursing leaders to be skilled
in nursing informatics. These leaders must be able to
use data, information, and knowledge efficiently and
effectively to assess and manage their clinical settings
and ultimately apply these informatics skills to improve
patient outcomes and the quality of patient care
(Figure 15-2).

We need to know how to access data and information.

Next, we judiciously select and retrieve the data and information

necessary to provide safe, high quality nursing care.

We must be able to search through the available data and information.

Figure 15-2 Data and Quality Connection: There are
many ways to obtain data and information.

On a much higher level, the Government
Accountability Office (GAO) selected and assessed
six hospitals, from which it identified three challenges
in implementing patient safety practices. The number
one challenge was “obtaining data to identify adverse
reactions in their own hospitals” (GAO, 2016, para. 2).
Nursing informatics skills and knowledge can address
this challenge.

The GAO interviewed patient safety experts and the
related literature to identify three key gaps where better
information could help guide hospital officials in their
continued efforts to implement patient safety practices.
These gaps involve a lack of “(1) information about the
effect of contextual factors on implementation of patient
safety practices, (2) sufficiently detailed information on
the experience of hospitals that have previously used
specific patient safety implementation strategies, and
(3) valid and accurate measurement of how frequently
certain adverse events occur” (p. 22). Once again,
implementing solid nursing informatics practices, skills,
and knowledge can close these gaps.

Informatics Technologies for
Patient Safety
Healthcare technologies are frequently designed to
improve patient safety, streamline work processes, and

improve the quality and outcomes of healthcare
delivery. However, technology is not always the answer
to patient safety; as the Joint Commission (2008)
cautioned, “the overall safety and effectiveness of
technology in health care ultimately depends on its
human users, and . . . any form of technology can have
a negative impact on the quality and safety of care if it
is designed or implemented improperly or is
misinterpreted” (para. 2). As we continue to look to HIT
to advance patient safety initiatives, we must realize
that integrating HIT presents other challenges and can
add to the patient safety issues. For example, Singh
and Sittig (2016) stated that HIT has the “potential to
improve patient safety but its implementation and use
has led to unintended consequences and new safety
concerns. A key challenge to improving safety in health
IT–enabled healthcare systems is to develop valid,
feasible strategies to measure safety concerns at the
intersection of health IT and patient safety” (p. 226).

Although technology may certainly help to prevent or
reduce errors, one must always remember that
technology is not a substitution for safety vigilance by
the healthcare team in a safety culture. Harrison (2016)
stated that “[p]atient safety should always be at the
center of the design and adoption of any technology
introduced into patient care settings. Technology that’s
designed to improve patient safety is only as good as
the person using the device. It doesn’t replace critical

thinking, solid nursing practice, and careful patient
monitoring” (p. 21).

The Wired for Health Care Quality Act of 2005 began a
series of funding streams to promote HIT, promote
sharing of best practices in HIT, and help organizations
implement HIT (Harrison & Daly, 2009). Many early
adopters opted to focus technology and safety
initiatives on medication ordering and administration
processes. Medication errors are the most frequent
and the most visible errors because the medication
administration cycle has many poorly designed work
processes with several opportunities for human error.
Thus computerized physician order entry (CPOE),
automated dispensing machines, smart pump
technologies for IV drug administration, and bar-code
medication administration (BCMA) frequently
preceded the adoption of the EHR in many institutions
because of the costs associated with implementing
these technologies. In an ideal world, the EHR would
be adopted concurrently as part of an interoperable
HIT system. In the early EHR systems, clinicians were
prompted by electronic alerts reminding them of
important interventions that should be part of the
standard of care, but these alerts tended to be
generalized and not patient specific—for example, “Did
you check the allergy profile?” or “Has the patient
received a pneumonia immunization?” These early
alert and care reminders are now evolving into more
sophisticated clinical decision support (CDS)

systems to promote accurate medical diagnoses and
suggest appropriate medical and nursing interventions
based on patient data. Ganio and colleagues (2016)
stated that

current EHR software is typically very
customizable and may be adapted to
multiple purposes. There are often
several ways to accomplish a goal using
vendor tools already available. Systems
analysts should explore the options and
weigh the pros and cons of each while
consulting with end users to determine
which tools meet their needs and are
compatible with their workflows. (p. 629)

With the addition of triggers to detect adverse events,
diagnostic errors, adverse drug events, hospital-
acquired infections, and delays in diagnoses have
been identified. “Trigger algorithms are frequently
applied to EMRs for automated surveillance, and
increasingly to prospectively identify patients at risk”
(Rosen & Mull, 2016, p. 3).

The National Patient Safety Foundation (2016) listed
the top patient safety issues as wrong-site surgery,
hospital-acquired infections, falls, hospital
readmissions, diagnostic errors, and medication errors.
Many of these issues can be prevented or detected in

their early stages using informatics technologies,
although we still continue to struggle with these same
safety issues. Other technologies designed to promote
patient safety include wireless technologies for patient
monitoring, clinician alerts, point-of-care applications,
apps, and radiofrequency identification applications.
Each of these is reviewed here, and the chapter
concludes with a section discussing future technologies
for patient safety.

Technologies to Support the Medication
Administration Cycle
The steps in the medication administration cycle
(assessment of need, ordering, dispensing, distribution,
administration, and evaluation) have been relatively
stable for many years. Each of the steps depends on
vigilant humans to ensure patient safety, resulting in
the five rights of medication administration: (1) the right
patient, (2) the right time and frequency of
administration, (3) the right dose, (4) the right route,
and (5) the right drug. Human error can be related to
many aspects of this cycle. Distractions, unclear
thinking, lack of knowledge, short staffing, and fatigue
are a few of the factors that cause humans to deviate
from accepted safety practices and commit medication
errors. Integration of technology into the medication
administration cycle promises to reduce the potential
for human errors in the cycle by performing electronic

checks and providing alerts to draw attention to
potential errors. Research Brief 2 describes high-risk
and preventable drug-related complications.

RESEARCH BRIEF 2

A cluster-randomized, step-wedge trial was
conducted involving 33 primary practices that
were randomly assigned start dates during a 48-
week intervention involving education,
informatics, and financial incentives to conduct
chart reviews; 33,334 patients in the
preintervention period and 33,060 at-risk in the
intervention period were included. The main
outcome was patient-level exposure to high-risk
prescribing of nonsteroidal anti-inflammatory
drugs (NSAIDs) or selected antiplatelet agents
(e.g., NSAID prescription in a patient with
chronic kidney disease or co-prescription of an
NSAID and an oral anticoagulant without
gastroprotection). Secondary outcomes included
the incidence of related hospital admissions.
The analyses were conducted based on the
intention-to-treat principle, with the use of
mixed-effect models to account for clustering in
the data.

Targeted high-risk prescribing was significantly
reduced, from a rate of 3.7% (1,102 of 29,537
patients at risk) immediately before the

intervention to 2.2% (674 of 30,187) at the end
of the intervention (adjusted odds ratio, 0.63;
95% confidence interval [CI], 0.57 to 0.68;
P<0.001). The rate of hospital admissions for
gastrointestinal ulcer or bleeding was
significantly reduced from the preintervention
period to the intervention period (from 55.7 to
37.0 admissions per 10,000 person-years; rate
ratio, 0.66; 95% CI, 0.51 to 0.86; P=0.002), as
was the rate of admissions for heart failure (from
707.7 to 513.5 admissions per 10,000 person-
years; rate ratio, 0.73; 95% CI, 0.56 to 0.95;
P=0.02), but admissions for acute kidney injury
were not (101.9 and 86.0 admissions per 10,000
person-years, respectively; rate ratio, 0.84; 95%
CI, 0.68 to 1.09; P=0.19).

The researchers concluded that their complex
intervention combining education, informatics,
and financial incentives reduced the rate of high-
risk prescribing of antiplatelet medications and
NSAIDs and may have improved clinical
outcomes.

The full article appears in Dreischulte, T.,
Donnan, P., Grant, A., Hapca, A., McCowan, C.,
& Guthrie, B. (2016). Safer prescribing—A trial
of education, informatics, and financial
incentives. New England Journal of Medicine,
374(11), 1053–1064.
doi:10.1056/NEJMsa1508955

CPOE is an electronic prescribing system designed to
support physicians and nurse practitioners in writing
complete and appropriate medication and care orders
for patients. When CPOE is part of an EHR with a CDS
system, the medication order is electronically checked
against specific data in the patient record to prevent
errors, such as ordering a drug that might interact with
a drug the patient is already taking, ordering a dose
that is too large for the patient’s weight, or ordering a
drug that is contraindicated by the patient’s allergy
profile or renal function. Because it is impossible for,
and unreasonable to expect, a clinician to remember
each of the more than 600 drugs that require a dose
adjustment in the case of renal dysfunction, for
example, safe dosing parameters are provided by the
CPOE (Bates & Gawande, 2003). In a stand-alone
CPOE system without a CDS system, the medication
orders are simply checked by the computer against the
drug database to ensure that the dose and route
specified in the order are appropriate for the
medication chosen. Specific benefits of CPOE include
the following:

Prompts that warn against the possibility of drug
interaction, allergy, or overdose
Accurate, current information that helps physicians
keep up with new drugs as they are introduced into
the market
Drug-specific information that eliminates confusion

among drug names that look and sound alike
Reduced healthcare costs caused by improved
efficiencies
Improved communication among doctors, nurses,
specialists, pharmacists, other clinicians, and
patients
Improved clinical decision support at the point of
care (Steele & DeBrow, n.d.)

CPOE solves the safety issues associated with poor
handwriting and unclear or incomplete medication
orders. Orders can be entered in seconds and from
remote sites, eliminating the use of verbal orders that
are especially subject to interpretation errors. Orders
are then transmitted electronically to the pharmacy,
reducing the potential for the transcription errors
commonly encountered in the paper-based system,
such as lost or misplaced orders, delayed dosing, or
unreadable faxes. Thus CPOE changes workflows for
all clinical staff and physicians as well as health team
communication patterns (Doshi, 2015). As with any
technology integration, introduction of CPOE is
associated with a resistance to change and a learning
curve to gain proficiency, and users must learn to trust
the system. Manor (2010) urges careful planning and
training during implementation with plenty of staff
support. Manor also reports on the need for a paper-
based backup system in the case of network or
electrical outages or system maintenance.

The verification and dispensing functions of the
pharmacy can also be assisted by technology. The
pharmacist begins by verifying the allergy status of the
patient and the medication reconciliation information to
ensure that the new medication is compatible with
other medication in the care regimen. This verification
function is computer based, and the medication order
is electronically checked via the knowledge database.
If the order is verified as safe and appropriate, the
pharmacist proceeds to the dispensing process. Bar-
code medication labeling at a unit dose level was
mandated by the Food and Drug Administration in
2004, with targeted compliance to be achieved by
2006. A bar code is a series of alternating bars and
spaces that represents a unique code that can be read
by a special bar-code reader. Bar-code technology
spans both the medication dispensing and
administration steps in the medication administration
cycle. In the pharmacy, the bar code helps to ensure
that the right drug and the right dose are dispensed by
the pharmacy. Medications that are labeled with bar
codes can also be dispensed by robots capable of
reading the codes or by automated dispensing
machines. In this way, bar-code technology helps with
the processes of procurement, inventory, storage,
preparation, and dispensing (University of Rochester
Medical Center, Department of Pharmacy, 2016).

The processes of drug storage, dispensing, controlling,
and tracking are easily carried out via automated

dispensing machines (also known as automated
dispensing cabinets, unit-based cabinets, automated
dispensing devices, and automated distribution
cabinets). These devices have benefits for both the
user and the organization, specifically in the areas of
access security (especially with narcotics
administration tracking), safety, supply chain, and
charge functions (Institute for Safe Medication
Practices, 2016).

Applications (apps) or mobile apps are being used by
and prescribed for patients. The apps used for patient
education can engage and inform our patients; an
educated patient is believed to be “more likely to
understand risks and if there is an adverse event, may
less likely file a lawsuit” (Diamond, 2016, para. 2).
While there are benefits to their use, we must be
judicious in our use of apps. If apps are prescribed for
patients, then it is our responsibility to educate the
patient and/or family on proper use. It is important that
patients and their families understand the benefits and
risks of using the app, as well as how to receive help
when needed. If data are being exchanged, our
patients must comprehend what data will be collected
and where, when, and with whom it will be shared.

There are apps for healthcare personnel as well.
iScrub is an app used to monitor hand hygiene, which
could help prevent healthcare-associated infections
(University of Iowa, 2015). The Patient Safety Manual

was designed as a resource to treat patients quickly,
safely, and effectively (Apkpure, 2016). Apps will
continue to be used by providers and patients, so we
must all assume the responsibility of making sure the
apps are both appropriate to use and used
appropriately.

Radio frequency identifier (RFID) technology is
rapidly gaining a foothold in healthcare technology and
may soon be used in the medication administration
cycle. Although more expensive than bar coding for
packaging, the RFID tags are reprogrammable and
issues associated with bar-code printing imperfections
and bar-code scanner resolution can be mitigated
(Vecchione, 2016). As discussed later in this chapter,
RFID technologies may also be an important
component of a medication compliance system for
patients.

BCMA systems help to ensure adherence to the five
rights of medication administration. Whether BCMA is
part of the larger EHR or a free-standing electronic
medication administration system (eMAR), bar-code
technology provides a system of checks and balances
to ensure medication safety. The nurse begins by
scanning his or her name badge, thereby logging in as
the person responsible for medication administration.
Next, the bar code on the patient’s identification
bracelet is scanned, prompting the electronic system to
pull up the medication orders. Next, the bar code on

each of the medications to be administered is scanned.
This technology check ensures that the five rights of
medication administration are met. If there is a
discrepancy between the order and the medication that
was scanned or a contraindication for administration,
an alert is generated by the system. For example, in an
EHR system with CDS, the nurse may be prompted to
check the most recent laboratory results for electrolytes
before administering a potassium supplement. In a
free-standing eMAR without CDS or EHR links, if the
medication orders have recently been changed, the
nurse is alerted to the change. When an alert is
generated, the nurse must chart the action taken in
response to that alert. For example, an early dose
might need to be given if the patient is leaving the unit
for a diagnostic test.

Despite the promising advances in patient safety
afforded by this technology, it is not fail safe (Cochran,
Jones, Brockman, Skinner, & Hicks, 2007).
Medications that are labeled individually by the in-
house pharmacist increase the potential for human
error if the medication is given an incorrect bar code,
such as one signifying a wrong dose or even the wrong
medication. In addition, the bar-code printers
themselves may generate unreadable labels, leading to
staff workarounds in the interest of saving time.
Cochran et al. make the following recommendations to
reduce BCMA errors:

Purchase unit-of-use medications with
manufacturer bar codes whenever possible.
Double-check all hospital-generated bar-code
labels, including those for compounded injectable
medications, before the product leaves the
pharmacy.
Carefully review all BCMA override reports. Address
system workarounds through process change and
staff education.
Minimize false-positive warnings to reduce the
likelihood that staff will ignore warnings for real
errors.
Ensure that an urgent need exists for all “stat”
orders, as pharmacy review and advantages of bar-
code administration are usually circumvented in
such cases.
Establish institutional policies and procedures that
can be easily implemented when products fail to
scan. Processes in pharmacy will likely be different
than processes at the point of care (p. 300).

Smart pump technologies are designed for safe
administration of high-hazard drugs and to reduce
adverse drug events during IV medication
administration. Smart pumps have software that is
programmed to reflect the facility’s infusion parameters
and a drug library that compares normal dosing rates
with those programmed into the pump. Discrepancies
generate an alarm alerting the clinician to a safety
issue. A soft alarm can typically be overridden by a

clinician at the bedside, but a hard alarm requires the
clinician to reprogram the pump so that the dosing falls
within the facility’s IV administration guidelines for the
drug to be infused. All alarms generated by the smart
pump are tracked along with the clinician’s responses
to them (Cummings & McGowan, 2015; Dulak, 2005;
University of Alabama at Birmingham, 2013). Smart
pumps can be seamlessly integrated into BCMA
systems, and data can be fed directly into the EHR.
The IHI (2012) recommends the following steps to
ensure safe implementation of smart pump technology:

Prior to deploying these pumps, standardize
concentrations within the hospital. Asking the nurse
to choose among several concentrations increases
the risk of selection error.
Prior to deploying these pumps, standardize dosing
units for a given drug (for example, agree to always
dose nitroglycerin in terms of mcg/min or
mcg/kg/min, but not both). Asking the nurse to
choose among several dosing units increases the
risk of selection error.
Prior to deploying these pumps, standardize drug
nomenclature (for example, agree to always use the
term KCl, but not potassium chloride, K, pot
chloride, or others). Asking the nurse to remember
and choose among several possible drug names
increases the risk of selection error.
Perform a failure modes and effects analysis on the
deployment of these devices.

Ensure that the concentrations, dose units, and
nomenclature used in the pump are consistent with
that used on the medication administration record
(MAR), the pharmacy computer system, and the
EHR.
Meet with all relevant clinicians to come to
agreement on the proper upper and lower hard and
soft dose limits.
Monitor overrides of alerts to assess whether the
alerts have been properly configured or whether
additional quality intervention is required.
Be sure the “smart” feature is utilized in all parts of
the hospital. If the pump is set up volumetrically in
the operating room but the “smart” feature is used
in the ICU, an error may occur if the pump is not
properly reprogrammed.
Be sure there are upper and lower dose limits for
bolus doses, when applicable.
Engage the services of a human factors engineer to
identify new opportunities for failure when the
pumps are deployed.
Identify a procedure for the staff to follow in the
event a drug that is not in the library must be given
or when its concentration is not standard.
Deploy the pump in all areas of the hospital. If a
different pump is used on one floor and the patient
is later transferred, this will create new opportunities
for failure. Also, there may be incorrect
assumptions about the technology available to a
given floor or patient.

Consider using “smart” technology for syringe
pumps as well as large-volume infusion devices
(para. 7).

Cummings and McGowan (2015) cautioned that we
must never solely rely on the pump to identify and alert
us to problems. Nurses must always engage in best
practices and follow all patient safety practices. There
is no substitute for nursing assessment of patients as a
key safety tool.

A CDS can enhance the medication administration
cycle by promoting safety and improving patient
outcomes. The CDS is guided by targeted information
delivery, ensuring that the five rights of CDSs are
implemented: the right information provided to the right
person in the right format through the right channel at
the right time in workflow. For example, during
medication selection, a CDS helps a clinician select an
appropriate medication based on client data, such as
clinical condition, weight, renal function, concurrent
medications, and cost. This system ensures that the
order is complete by performing checks for drug
interactions, duplications, or allergy contraindications
and ensures the right dose and right route are
specified. During the verification and dispensing phase
of the medication administration cycle, the CDS
provides double checks for interactions, allergies, and
appropriate dose orders. Consideration is also given to
potential infusion pump programming issues,

incompatibilities during infusion, and proper notation
and dispensing when portions of a dose must be
wasted. During the administration phase, the CDS
assists with patient identification and current
assessment parameters (i.e., blood pressure, glucose
level) that may contraindicate the use of the medication
at that point in time. In addition, checks for interactions
with foods or other medications and timing and
monitoring guidelines are provided to the clinician
administering the medication. The CDS has patient
education guidelines and printable handouts to assist
clinicians in educating patients about their medications.
The monitoring functions of the CDS provide a
structured data reporting system to track side effects
and adverse events across the population (Healthcare
Information and Management Systems Society
[HIMSS], 2009a).

Several promising technologies may become available
in the future to assist patients with medication
compliance after discharge. For example, eMedonline
collects patient medication compliance data by
scanning package bar codes or RFID medication tags
and using personal digital assistant or smartphone
technology to send compliance data to the server.
Clinicians review the medication compliance data and
provide education and feedback to patients to increase
their compliance with proper medication administration
(eMedonline, n.d.). The SIMpill Medication Adherence
System uses Web-based technology to monitor patient

compliance and provide reminders about taking
medications or refilling prescriptions by sending text
messages to the patient or caregivers (SIMpill, 2008).
Caps of pill bottles may contain RFID tags that monitor
and collect data on when the bottle is opened, or that
contain flashing time reminders when a dose is due
(Blankenhorn, 2010). Smart inhalers track asthma
medication compliance using a microprocessor that
records and stores medication compliance. They may
also include visual and audio reminders to use the
inhaler (Adherium, 2010).

In addition, several potential technologies are still being
tested. For example, InPen is a smart insulin pen that
couples with a smartphone to calculate insulin dosages
and track injections (Medgadget, 2016a), PillDrill helps
people adhere to a medication schedule and also
includes a “mood cube” to track how patients are
feeling (Medgadget, 2016b), and Proteus smart pills
have sensors attached to medications to track when
the pill is actually ingested (Medgadget, 2015). These
are just a sampling of the newer technologies for
medication adherence; more are expected to emerge
in the future.

Additional Technologies for Patient
Safety

CDS systems have safety uses beyond the medication
administration cycle. The robust data collection and
data management functions help to ensure quality
approaches to patient health challenges based on
research evidence and clinical guidelines. A CDS may
also ensure cost-effectiveness by alerting clinicians to
duplicate testing orders, or by suggesting the most
cost-effective diagnostic test based on specific patient
data (HIMSS, 2009b). Consider this description of the
features of a CDS based on screen captures
performed by a CDS system:

The patient is a 75-year-old male with
coronary artery disease (CAD), diabetes
mellitus (DM), and elevated creatine
kinase (CK). Assessment prompts and
reminders on the screen for this patient
include: no recent LDL test; BP is above
goal; patient is due for Pneumovax and
influenza vaccines; patient is a current
smoker, not thinking of quitting, last
counseled with date; patient is
overweight; patient is due for eye and ear
checks. The patient management
prompts include:

Lipid management: “No Recent LDL Management”
is printed red with a series of check boxes
presenting choices to the clinician:

* Order lipid panel now

* Order lipid panel with direct LDL now

* Print instructions for fasting lipid panel (link)

* Print orders for outside lab request for lipid
panel testing (link)

BP management: BP is above goal average over
last 2 visits; goal is 130/80

* Choices on checkboxes: Start another
antihypertensive (“help me choose”) link

* Series of links listing current medications with
opportunities to adjust each

Order Chem 7 now or order Chem 7 in (drop-down
menu for timing of order)
Suggestions for referrals include:

* Refer to nutritionist

* Refer to cardiac rehabilitation (“help me
choose” link)

* Refer to BP specialist (“help me choose” link)

* Prompts for patient education handouts
include Print “control high blood pressure” link

* Print DASH diet instructions link

* Print exercise prescription (White, Shiffman,
Middleton, & Cabán, 2008, Slides 63–65)

The prompts and instructions provided to the clinician
by the system in this example are detailed and easy to
navigate. As the example suggests, implementation of
a CDS has the potential to optimize care by ensuring
that all of the details of a patient’s health issues are
presented to the clinician for management, thereby
promoting individualized approaches to the total health
of the patient based on best available evidence and
clinical guidelines (HealthIT.gov, n.d.). According to the
Centers for Medicare and Medicaid Studies (2014),

[the] CDS is not simply an alert,
notification, or explicit care suggestion.
CDS encompasses a variety of tools
including, but not limited to: computerized
alerts and reminders for providers and
patients; clinical guidelines; condition-
specific order sets; focused patient data
reports and summaries; documentation
templates; diagnostic support; and
contextually relevant reference
information. These functionalities may be
deployed on a variety of platforms. (para.
2)

RFID technologies have both supply chain and patient
care applications to patient safety. An RFID system
contains a tag affixed to an object or to a person that
functions as a radiofrequency transponder and

provides a unique identification code, a reader that
receives and decodes the information contained on the
tag, and an antenna that transmits the information
between the tag and the reader. When RFID tags are
embedded in patient identification bracelets, they can
help with patient tracking during procedures and testing
or function as part of the EHR communicating pertinent
information to clinicians at the bedside. RFIDs may be
part of the medication administration process, replacing
bar-code technologies. They can be used to track
medical supplies and equipment, thereby reducing staff
time in locating such items. They may also be
embedded into surgical supplies to automate supply-
counting procedures, thereby reducing the likelihood
that sponges or tools will be erroneously left in a
patient. RFIDs may also reduce the likelihood of the
never events of wrong-patient, wrong-site surgical
procedures (PSNet, 2016b; Revere et al, 2010).
RFIDs used in the medication supply chain protect
patients by reducing the potential that a counterfeit
medication might be inadvertently introduced into the
supply, and by providing for efficient medication recalls.
Potential terrorist manipulation of the medication
supply is also thwarted by RFID supply chain tracking
technology. Blood and blood products can be efficiently
tracked by RFIDs because specialized tags can detect
temperature fluctuations and, therefore, ensure that the
blood or blood product was stored at the optimal
temperature for safe administration; however, RFID

technology will probably not replace bar codes in blood
banking due to the cost (Wray & Sanislo, 2016).

Smart rooms are also being used in healthcare
facilities. As a caregiver enters the room, the RFID tag
on his or her name badge announces to the patient on
a monitor (typically mounted on the wall in the patient’s
line of sight) exactly who has entered the room and
triggers “need to know” data based on caregiver status
to be displayed on the monitor in the room. For
example, when a dietary aide enters the room, only
dietary information is displayed; when a physician or
nurse enters, all of the pertinent medical data from the
EHR is available. Clinicians can review patient data in
real time and chart care at the bedside using touch-
screen technology, thereby increasing productivity
(Cerner, 2016; Cronin, 2010). Some smart room
technologies include workflow algorithms to alert
clinicians as they enter the room about procedures that
need to be implemented for the patient and can track
individual clinician efficiency and effectiveness by
aggregating data over time (Foley, 2016; Sharbaugh &
Boroch, 2010).

New technologies to improve patient monitoring include
wearable technology (devices) and wireless area
networks, variously called “body area networks” or
“patient area networks.” The technologies provide the
ability to wear a small, unobtrusive monitor that collects
and transmits physiologic data via a cell phone to a

server for clinician review. Although most of these
technologies are designed for monitoring patients with
chronic diseases, they also have safety implications
because they help to identify early warning physiologic
signs of impeding serious health events (California
Healthcare Foundation, 2007; Kosir, 2015). A
wireless chip on a disposable Band-Aid with a 5- to 7-
day battery promises to be able to monitor the patient’s
heart rate and electrocardiogram, blood glucose, blood
pH, and blood pressure, allowing for the collection of
important clinical data outside the hospital (Miller,
2008). Wearable stress-sensing monitors detect
electrical changes in the skin that may signal increased
stress in autistic children who are unable to
communicate an impending crisis; caregivers are
alerted to the potential crisis via wireless transmission
and can intervene to reduce the stress and prevent the
crisis (Murph, 2010). Several new technologies
promise to aid in early detection of falls in the elderly,
including a wearable pendant that triggers a personal
emergency response system (Aging in Place
Technology Watch, 2012) and smart slippers with
pressure sensors in the soles that transmit movement
data wirelessly to a remote monitoring site
(Mobihealthnews, 2009).

Robotics technologies are also being increasingly
tested for safety and efficiency uses. Robotics has
been used in minimally invasive surgery for some time;
as with most technologies, there are risks and rewards

(PSNet, 2016c). Surgical devices include haptic
(tactile) feedback to the surgeon, thereby increasing
the sense of reality during the procedure and reducing
the potential for unsafe manipulation (June, 2010). A
robot designed to assist with patient lifting provides
increased safety for both patients and clinicians
(Melanson, 2010). Finally, laser-guided robots are
performing such routine functions as emptying and
disposing of trash, cleaning rooms, delivering supplies
and meals, and dispensing drugs (Savoy, 2010).
Robots are also being used in home care as well as for
telehealth (Dahl & Boulos, 2013).

Personalized health care or personalized medicine,
which tailors treatment to the specific genetic
characteristics of an individual patient and challenges
the patient to be more accountable for his or her own
health, is rapidly advancing as vendors develop
targeted therapies. Its impact is aligned with quality.
According to the Armstrong Institute (2012),
“personalized medicine and quality improvement are
united in a common goal: optimal patient outcomes”
(para. 3). Researchers must pursue specific clinical
trials and make certain that the data, information, and
knowledge generated are captured and disseminated.

The International Medical Informatics Association
(IMIA; 2015) has a working group for health informatics
for patient safety. This working group is focusing on six

areas where health information systems can impact
patient safety:

1. Identifying and documenting how health
information systems and their associated
devices can best be designed, implemented and
applied to improve patient safety (e.g.,
developing usable, integrated workflow solutions
that are safe)

2. Identifying and documenting software safety
issues involving health information systems
(e.g., physician order entry, electronic
documentation, decision support tools) and their
associated devices

3. Discussing, developing and promoting
methodologies that improve patient safety using
health information systems and their associated
devices

4. Discussing, developing, and promoting
methodologies that prevent the occurrence of
safety issues involving health information
systems and their associated devices

5. Educating health informatics professionals,
health professionals, healthcare administrators,
and policy makers about how health information
systems and medical devices can improve
patient safety and the solutions that can be
employed to prevent the occurrence of
technology-induced errors involving software
and medical devices

6. Collecting, analyzing, and disseminating
research results about health information
systems and medical devices that improve
safety as well as those that have been found to
inadvertently decrease safety (para. 1)

Many organizations are showing the value of
healthcare or clinical informatics methods in improving
quality health care and patient safety. We are
beginning to see some strides in improving patient
safety as these technologies are implemented across
healthcare settings, but we still have a long way to go.

Role of the Nurse Informaticist
The human side of patient safety is paramount. As
technologies that can help to reduce errors and
increase safety are integrated into caregiving activities,
healthcare professionals must also improve their ability
to use and manage these technologies. Therefore, not
only must the technology be scrutinized and tested
routinely, but the users must also be maintained and
nurtured so that they are able to use the tools to the
patient’s benefit, avoiding harm and keeping the patient
safe. Even the best CDS systems can contribute to
mistakes by providing meaningless or harmful
information. Nurse informaticists and the IT team in the
facility must ensure that all systems are properly
configured and maintained. They should routinely
monitor and check these systems while making sure

that their human potential—that is, the users—is
capable of using the systems accurately to avoid
errors. A technology and its user can never be left to
their own devices.

As we continue to apply informatics to patient safety,
data warehousing and mining, reporting, data trending,
and predictive modeling will enhance our ability to
improve patient safety and provide quality health care.
In order to gather the data and information necessary
to analyze safety issues, monitoring systems, software,
and hardware will continue to evolve. Risk monitoring
and incident reporting software (reporting software
specifically generating reports regarding incidents
only), patient response monitoring systems, trending
and predictive models, and reporting software will
provide enhanced data and information to be analyzed.

Human inputting activities must focus on patient safety
to raise the appropriate issues and sound out solutions.
Nurse informaticists must be involved in all stages of
the system development life cycle, while maintaining a
focus on safety. Safety concerns and remedies need to
be analyzed, synthesized, and integrated throughout
the system development life cycle to have a robust tool
that provides meaningful information and enhances
patient care while preventing errors and promoting
patient safety. According to Effken and Carty (2002),
“Creating a safe patient environment is a very complex
issue that will require the combined knowledge and

skill of clinical informaticists, informatics faculty,
researchers, and system designers” (para. 16).
Research Brief 3 describes the results of a 2009
HIMSS survey on the impact of nurse informaticists on
patient safety. Research Brief 4 discusses HIMSS’s
2015 follow-up survey.

RESEARCH BRIEF 3

In 2009, HIMSS conducted an Informatics Nurse
Impact Survey sponsored by McKesson. This
Web-based survey yielded 432 acceptable
responses over a 2-month period from
December 2008 to February 2009.

One of the areas assessed was “value and
impact of informatics nurse,” on a scale of 1 to
7, with 7 being the highest rating:

Respondents believe that
informatics nurses involved in
system analysis, design, selection,
implementation and optimization of
IT have the greatest impact on
patient safety (6.21), workflow
(6.17) and user/clinician
acceptance (6.15). The area with
the least impact was integration
with other systems (6.03). These
findings suggest the informatics
nurse is a driver of quality of care

and enhanced patient safety within
their organization. (p. 2)

This demonstrates the belief that nurse
informaticists can greatly improve patient safety.
The nurse executives who responded rated the
positive impact of nurse informaticists on patient
safety at 6.36 out of 7.

In their conclusion, the researchers stated that:

The role of informatics nurses is
not limited to IT; this research also
suggests that informatics nurses
play an instrumental role with
regard to patient safety, change
management and usability of
systems as evidenced by their
impact on quality outcomes,
workflow, and user acceptance.
These additional areas highlight
the value of informatics nurses—
their expertise truly translates to
the adoption of more effective,
higher quality clinical applications
in healthcare organizations. (p. 11)

The full article appears in HIMSS. (2009).
Informatics nurse impact survey. Retrieved from
http://www.himss.org/files/HIMSSorg/content/files/HIMSS2009NursingInformaticsImpactSurveyFullResults.pdf

RESEARCH BRIEF 4

This study follows up on research HIMSS
conducted in 2009 to evaluate the impact that
informatics nurses have on the HIT
environment.

Under the heading of Patient Safety,

more than three-quarters of
respondents (76 percent) indicated
that having an informatics nurse
involved in the analysis, design,
implementation, optimization and
selection process for clinical
systems results in a high degree of
impact with regard to patient
safety. . . . Additionally,
respondents working for an
organization that employs a CMIO
[Chief Medical Information Officer]
were more likely (79 percent) to
report that informatics nurses had
a high degree of impact on patient
safety derived from clinical
systems than were their
counterparts at organizations that
do not employ a CMIO on staff (73
percent). (p. 15)

Under the heading of Quality Outcomes,
“[n]early two-thirds of respondents (64 percent)
indicated that having an informatics nurse
involved in the analysis, design, implementation,
optimization and selection process for clinical
systems has a high degree of impact on quality
outcomes” (p. 15).

Under the heading of Reduction of Never
Events,

[n]early two-thirds of respondents
(61 percent) indicated that having
an informatics nurse involved in
the analysis, design,
implementation, optimization and
selection process for clinical
systems had a substantial positive
impact on the reduction of never
events. Additionally, respondents
working for an organization that
employ a CNIO [Chief Nursing
Informatics Officer] were more
likely to indicate that informatics
nurses have an impact in this area
(72 percent) when compared to
respondents that work for an
organization that does not have a
CNIO (58 percent). (p. 16)

This showed that the majority of the 576 study
participants believed that nurse informaticists
positively impact patent safety. It also reinforced
the fact that the nurse informaticist’s role is not
limited to IT, and suggested that informatics
nurses play an instrumental role with regard to
patient safety, change management, and
usability of systems, as evidenced by their
impact on quality outcomes, workflow, and user
acceptance.

The full article appears in HIMSS. (2015). 2015
impact of the informatics nurse survey.
Retrieved from
http://www.himss.org/sites/himssorg/files/FileDownloads/2015%20Impact%20of%20the%20Informatics%20Nurse%20Survey%20Full%20Report.pdf

Summary
Patient safety is an important and ubiquitous issue in
health care. This chapter explored the characteristics
of a safety culture and technologies designed to
promote patient safety. The need to evaluate errors
carefully to determine why and how they occurred and
how workflow processes might be changed to prevent
future errors of the same type was emphasized.
Technology is changing rapidly, and the culture of
sharing related to technology implementation, error
reporting, and troubleshooting should prompt
continuous process improvements. The key for
organizations is to invest in their users and choose

wisely so that the technologies they are adopting will
not negatively impact safety and will be interoperable
and easily upgradable as technologies and safety
practices evolve.

Organizations must make a commitment to a safety
culture in which everyone at every level is committed to
patient safety at every moment. In an ideal world,
everyone would first stop and think “Is this safe?”
before every action, workarounds would not occur, and
everyone would embrace rather than resist the
technologies and workflow processes designed to
promote patient safety. Table 15-1 provides a list of
websites to watch for updates on patient safety
technologies. The nurse informaticists, healthcare
providers, patients, ancillary team members,
administrators, setting/environment, infrastructure, and
technologies must all work together to create a safety
culture. Every organization must provide safe, quality
health care and prevent harm or adverse events for
every patient under its care by ensuring that patient
safety is critical to the organization’s mission.

Table 15-1 Patient Safety Websites

TITLE URL

AHRQ

Patient

Safety

www.psnet.ahrq.gov/primer

Home.aspx

Network

National

Patient

Safety

Foundation

www.npsf.org

National

Center for

Patient

Safety

www.patientsafety.va.gov

Institute for

Healthcare

Improvement

www.ihi.org/explore/patientsafety/Pages/default.aspx

Center for

Patient

Safety

www.centerforpatientsafety.org

QSEN

Institute

(Quality and

Safety

Education for

Nurses)

www.qsen.org

THOUGHT-PROVOKING QUESTIONS

1. What are the current patient safety
characteristics of your organizational
culture? Identify at least three aspects of
your culture that need to be changed with

regard to patient safety, and suggest
strategies for change.

2. Describe a current technology that you
use in patient care that would benefit from
human factors engineering concepts.
What are some ways this technology
should be improved?

3. Identify a workaround that you have used
and analyze why you chose this risk-
taking behavior over behavior that
conforms to a safety culture.

4. The GAO (2016) interviewed patient
safety experts and the related literature to
identify three key gaps in patient safety
practice implementation:

a lack of (1) information about the
effect of contextual factors on
implementation of patient safety
practices, (2) sufficiently detailed
information on the experience of
hospitals that have previously
used specific patient safety
implementation strategies, and (3)
valid and accurate measurement
of how frequently certain adverse
events occur. (p. 22)

Select one of these gaps and describe in detail
how nursing informatics could help close this
gap.

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case-for-rfid-in-blood-banking

CHAPTER 16: Patient
Engagement and
Connected Health

Kathleen Mastrian and Dee McGonigle

Objectives
1. Define health literacy and e-health.
2. Explore various technology-based

approaches to consumer health
education.

3. Identify barriers to use of technology and
issues associated with health-related
consumer information.

4. Imagine future approaches to technology-
supported consumer health information.

Key Terms

» Blogs

» Connected health

» Digital divide

» Domain name

» E-brochure

» E-health

» eHealth Initiative

» Empowerment

» Gray gap

» Health literacy

» HONcode

» Interactive technologies

» Know–do gap

» Patient engagement

» Static medium

» Trust-e

» Voice recognition

» Web quests

» Weblog

Introduction
Imagine that you have decided to take up running as
your preferred form of exercise in a quest to get in
shape. You start slowly by running a half mile and
walking a half mile. You gradually build up your
endurance and find yourself running nearly every day
for longer distances and longer periods of time. But
then you notice a nagging pain first in your right hip;
over a few weeks, it gradually spreads to the center of
your right buttocks and then down your right leg. You
try rest and heat, but nothing seems to help. You visit
your doctor, and she indicates that you have developed
piriformis syndrome and prescribes a series of
stretching exercises, ice to the involved area, and rest.
You are intrigued by the diagnosis. Upon your return
home, you log on to the Internet and begin a search for
information about piriformis syndrome. When you type
the words into your favorite search engine, you get
371,000 results in response to your query.

Your use of the Internet to seek health information
mirrors the behavior of many consumers, who are
increasingly relying on the Internet for health-related
information. The challenge for consumers and
healthcare professionals alike is the proliferation of
information on the Internet and the need to learn how
to recognize when information is accurate and
meaningful to the situation at hand.

This chapter explores consumer information and
education needs and considers how patient
engagement and connected health technologies,
including new trends in wearable technology, may help
to meet those needs, yet at the same time create ever
increasing demands for health-related information. It
begins with a discussion of health literacy, e-health,
and health education and information needs, and
explores various approaches by healthcare providers
to using technology to promote health literacy. Also
examined is the use of games, Web quests, and
simulations as means of increasing health literacy
among the school-age population. Issues associated
with the credibility of Web-based information and
barriers to access and uses for patient engagement are
discussed. Finally future trends related to technology-
supported consumer information and connectivity are
explored.

Consumer Demand for
Information
This is the Knowledge Age; many people want to be in
the know. People demand news and information, and
they want immediate results and unlimited access. This
is increasingly true with health information. More and
more people, in a trend known as consumer
empowerment, patient engagement, and connected
health, are interested in partnering with healthcare

providers to take control of their health. These patients
are not satisfied being dependent on a healthcare
provider to supply them with the information they need
to manage their health. Instead, they are increasingly
embracing electronic technologies such as patient
portals offering current and past health statuses, lab
results, and secure messaging with providers; social
media interactions; health-related games; wearable
technologies for tracking health; and health
management apps.

The most recent Pew Internet and American Life
Project Health Online survey report (Fox and Duggan,
2013) indicates that 8 in 10 Americans who are online
have searched for health information (these numbers
are comparable to the numbers in previous surveys
conducted in 2006 and 2011). The most frequent
health topic searches (69%) are related to a specific
disease or medical problem that the searcher or a
member of the family is experiencing. Other frequent
topics of health-related searches are weight, diet, and
exercise (60%) and health indicators such as blood
parameters or sleep patterns (33%). The 2011 survey
(n = 3,001) reports that consumers also searched for
information on food (29%) and drug safety (24%; Fox,
2011). Just over half of “online diagnosers” (those who
search online for information about medical conditions)
reported that they shared their Internet findings with
their healthcare providers, and 41% reported that their
findings were confirmed by a clinician (Fox & Duggan,

2013). It is clear that patients are increasingly looking
to be partners with their healthcare providers in
managing their health challenges and maintaining a
level of wellness. All healthcare professionals need to
be prepared to listen to the ideas of patients about their
personal health and, at the same time, provide
direction toward credible health information supplied by
electronic provider portals on the Internet. Here is
some good news: In an attempt to improve the
credibility of the results of online searches about
health, in 2015 Google partnered with Mayo Clinic to
fact-check the information in a database for 400 of the
most-commonly searched for health issues
(Lapowsky, 2015). Mayo Clinic (2015) reported that
Google

[has become] part of our daily lives.
There’s no need to sift through mountains
of data and endless links to find the few
nuggets we need. So naturally, when
people have health concerns, one of their
first stops is Google. But anyone who has
searched the Internet to self-diagnose
knows the dizzying, and sometimes
scary, array of results. To help give their
users the best health information
possible, Google now provides relevant
medical facts upfront. (p. 4)

Google intends to “surface these pre-vetted facts at the
top of its search results, in hopes of getting people to
the right information faster” (Lapowsky, para 2).

It is important to note that surveys of online health
behaviors are limited to those individuals who are
online and do not reflect the health information needs
or demands of those persons who are not online.
Digital divide is the term used to describe the gap
between those who have and those who do not have
access to online information. Nurses and healthcare
providers need to be aware of the various components
of the digital divide to ensure that patients and clients
are receiving the health information they need in a
format that they are interested in and can comprehend.
Notably, persons with chronic diseases are less likely
to have Internet connectivity. Fox and Purcell (2010)
explain the disparity in that having a chronic disease is
associated with age, level of education, ethnicity, and
income—all factors also associated with the digital
divide. Persons living with a chronic disease who have
Internet access are likely to use the Internet for
blogging and online discussion forums, activities
popularly referred to as peer-to-peer support. A recent
issue brief by the Council of Economic Advisers (2015)
reiterates digital divide factors as age, education,
income, and geographic location. By providing
infrastructure investment monies, President Obama’s
ConnectED program is designed to increase
broadband access for schools. A similar initiative is

designed to promote competition among Internet
providers, thereby lowering costs and making high-
speed Internet connections more affordable and
accessible across the country.

Missen and Cook (2007) discussed the potential
impact that technology-based health information
dissemination can have on the know–do gap in
developing countries. The know–do gap reflects the
fact that solutions to global health problems exist but
are not implemented in a timely fashion because of the
lack of access to important health information. The
Internet connections in developing countries are widely
scattered and may not be efficient or sufficient for
viewing healthcare information. Missen and Cook
described the use of a freestanding hard drive loaded
with hundreds of CDs of health-related information in a
webpage format that responds to a search command.
This is a great example of providing technologies that
work with the constraints of the situation. Another
example of addressing the digital divide is the growing
number of health-related websites that support Spanish
and other language formats.

Health Literacy and Health
Initiatives
The goal of health literacy for all is one that is widely
embraced in many sectors of health care; it was a

major goal of Healthy People 2010, and is being
continued in the health communication and health
information technology objective of Healthy People
2020 (Office of Disease Prevention and Health
Promotion & U.S. Department of Health and Human
Services, 2016). Clinicians who have been practicing
for some time recognize that informed patients have
better outcomes and pay more attention to their overall
health and changes in their health than those who are
poorly informed. Some of the earliest formally
developed patient education programs, which included
postoperative teaching, diabetes education, cardiac
rehabilitation, and diet education, were implemented in
response to research that suggested the positive
impact of patient education on health outcomes and
satisfaction with care. Almader-Douglas (2013)
updated the National Network Libraries of Medicine
webpage on health literacy
(http://nnlm.gov/outreach/consumer/hlthlit.html).
She concluded from the research on the economic
impact of health literacy that those persons with low
health literacy have less ability to manage a chronic
illness properly and tend to use more healthcare
services than those who are more literate. In addition,
she used results of health research to demonstrate the
impact of low health literacy and the incidence of
disease.

The site states that “Health Literacy is defined in the
Institute of Medicine report Health Literacy: A

Prescription to End Confusion as ‘The degree to which
individuals have the capacity to obtain, process, and
understand basic health information and services
needed to make appropriate health decisions’”
(Almader-Douglas, 2013, para. 2). For example,
healthcare providers depend on a patient’s ability to
understand and follow directions associated with
dietary restrictions or exercising at home. It is also
assumed, sometimes erroneously, that people will
correctly interpret symptoms of a serious illness and
act appropriately. The ability to locate and evaluate
health information for credibility and quality, to analyze
the various risks and benefits of treatments, and to
calculate dosages and interpret test results are among
the tasks Almader-Douglas identified as essential for
health literacy. Other important and less easily learned
health literacy skills are the ability to negotiate complex
healthcare environments and understand the
economics of payment for services. Parker, Ratzan,
and Lurie (2003) estimated that at least one third of all
Americans have health literacy problems and lament
that in a time-is-money economic climate, healthcare
practitioners are not always reimbursed for patient
education activities. This is still true today. The National
Institutes of Health (NIH; 2015) reported that numerous
studies concerning health literacy demonstrate that a
variety of challenges remain on both the patient and
healthcare-provider sides of the equation.

It is increasingly clear that better outcomes result when

patients are well informed and engaged in their care.
As depicted in Figure 16-1, there are a number of
effective strategies to promote better health, including
strategies for building sound relationships, strategies to
ensure that patients are well informed about their
health challenges, and strategies to build partnerships
with patients.

Figure 16-1 The Health Literacy Umbrella

Developed by the Health Literacy in Communities Prototype Faculty:

Connie Davis, Kelly McQuillen, Irv Rootman, Leona Gadsby, Lori Walker,

Marina Niks, Cheryl Rivard, Shirley Sze, and Angela Hovis with Joanne

Protheroe, and the Ministry of Health, July 2009. IMPACT BC, with

funding from the BC Ministry of Health.

The eHealth Initiative was developed to address the
growing need for managing health information and to
promote technology as a means of improving health
information exchange, health literacy, and healthcare
delivery. The eHealth Initiative website
(www.ehidc.org) provides more information. Although
its scope goes beyond health literacy, a major goal
continues to be empowering consumers to understand
their health needs better and to take action appropriate
to those needs. The eHealth Initiative recently released
a 2020 roadmap outlining a vision toward patient-
centric care. Poor interoperability among healthcare
systems and failure to embrace national data
standards for health care continue to be identified as
barriers to the eHealth Initiative. Further, concerns
about privacy and security of information and the
failure to invest appropriately in technology have
slowed the development of this important initiative. The
Centers for Disease Control and Prevention (CDC,
2016) maintains an interactive map of the United
States that provides access to health literacy and e-
health initiatives by state
(www.cdc.gov/healthliteracy).

Healthcare Organization
Approaches to Engagement
Healthcare organizations (HCOs) use a wide variety of
approaches and tools to engage patients and promote

patient education and health literacy. Although the old
standby for disseminating information is the paper-
based flyer, some HCOs are recognizing that today’s
consumers are more attracted to a dynamic rather than
static medium. In addition, the cost of designing and
printing pamphlets and flyers becomes prohibitive
when one considers the rapidity of change of
information; the brochure may be outdated almost as
soon as it is printed. One approach to deal with these
issues is to have patient education information stored
electronically so that changes can be made as needed
or information can be better tailored to the specific
patient situation and then printed out and reviewed with
the patient.

Another old standby approach that is still widely used is
the group education class. These classes initially were
developed to help people manage chronic health
problems (e.g., diabetes) and were typically scheduled
while people were hospitalized. Now, many HCOs also
sponsor health promotion education classes as a way
of marketing their facilities and showcasing some of
their expert practitioners.

The movement from static to dynamic presentations
began in many HCOs with the use of videotapes, and
then DVDs, which were shown in groups or broadcast
on demand over dedicated channels via television in
patients’ rooms. HCOs are now also taking advantage
of the fact that patients and families are captive

audiences in waiting rooms by promoting education via
pamphlet distribution, health promotion programs
broadcast on television, and health information kiosks
in those locations. The kiosks are typically computer
stations and often contain a variety of self-assessment
tools (especially those related to risks for diabetes,
heart disease, or cancer) and searchable pages of
information about specific health conditions. The self-
assessment tools represent yet another step forward in
technological support for education: In addition to being
dynamic, the kiosk is interactive. On the assessment
page, the user is asked to respond to a series of
questions and then the health risk is calculated by the
computer program. One caution, however, is that just
because the information is made available, it does not
mean that people will participate or that they will
understand what they have experienced. Issues related
to the level of health literacy, the digital divide, and the
gray gap (differences in electronic connectivity by age)
still exist in these situations.

Many HCOs have invested time and money in
developing interactive websites and believe that Web
presence is a critical marketing strategy. Sternberg
(2002) suggested that many websites began as an e-
brochure and progressed through various stages to
reach a true e-care status. Most offer physician search
capabilities, e-newsletters, and call-center tie-ins. As
with all patient education materials, there must be a
sincere commitment to keeping information current and

easily accessible. Web designers must pay particular
attention to the aesthetics of the site, the ease of use,
and the literacy level of those in the intended audience.

A usability study conducted by Lauterbach (2010)
provided some insights into how to measure website
usability. Lauterbach compared the usability of the
symptom checker functions of two popular websites by
asking volunteers to navigate each using four different
case scenarios. Users navigated the site to find the
symptom checker and then entered the symptoms and
evaluated site feedback. Users rated the ease of
understanding for each site and completed a short
comprehension quiz. Data were collected on
descriptions of user site preferences, user satisfaction
with the sites, results of the comprehension quiz, and
efficiency, which was measured by tracking the number
of webpage changes the user performed while
navigating the site.

The rapid growth of electronic communication through
increased use of computers and access to the Internet,
particularly for medical purposes, empowers the
clinician as well as the consumer of healthcare
information. The integration of information and
communication technologies (ICTs) and the growing
trend of consumer empowerment have reshaped the
delivery of health care. As a result of meaningful use
initiatives, many HCOs have developed secure patient
portals that allow patients to access their health

records, including tracking laboratory results and
reviewing the records. Most HCOs, however, do not
allow patients to edit these records. In addition,
patients are occasionally interested in interacting with
others who have the same or similar conditions, and
some HCOs are providing the information necessary to
help them connect. This so-called peer-to-peer support
is especially popular with patients who have cancer
diagnoses, diabetes, and other chronic and debilitating
conditions (Lober & Flowers, 2011).

RESEARCH BRIEF

An exploratory study of social media use among
hospitals sought to examine the prevalence of
social media use among hospitals, whether
hospital structure influenced the choice of social
media strategy, and how frequently Facebook
was used as an engagement strategy or an
information dissemination strategy. The authors
examined the websites of 471 randomly
selected hospitals to identify the methods that
hospitals used to attract customers, such as
advertising, personal stories, content related to
patient satisfaction, and patient education.
Hospital websites were also reviewed for
specific links to social media such as YouTube,
Twitter, Facebook, LinkedIn, or blogs. The
authors examined Facebook usage
characteristics in depth.

The authors reported that Facebook is the most
commonly used social media site and that all
social media use was related to websites that
also concentrated on emphasizing quality
metrics and education. They report that 70% of
the hospitals used some type of social media
network and that social media was more likely to
be used by larger, urban, nonprofit
organizations. In addition, Facebook was more
likely to be used as a dissemination strategy
rather than a strategy for engagement; only 27%
of the sample focused on engagement on
Facebook by posing questions, responding to
comments, or offering prizes. The authors
conclude that social media, and Facebook in
particular, is underutilized and that hospitals are
missing an important opportunity for low-cost
patient engagement.

The full article can be accessed at Richter, J. P.,
Muhlestein, D. B., & Wilks, C. A. (2014). Social
media: How hospitals use it, and opportunities
for future use. Journal of Healthcare
Management, 59(6), 447–460.

Some HCOs are using social media for health
education to promote actual engagement of audiences
rather than as means of one-way messaging. Neiger,
Thackeray, Burton, Giraud-Carrier, and Fagen
(2013) suggested “that the use of social media in

health promotion must lead to engagement between
the health promotion organization and its audience
members, that engagement must provide mutual
benefit, and that an engagement hierarchy culminates
in program involvement with audience members in the
form of partnership or participation (as recipients of
program services)” (p. 158). The CDC (2014) has an
excellent social media tool kit that can be used by
health educators to guide the planning and
implementation of social media strategies for health
promotion. This tool kit can be accessed at the
following website:
www.cdc.gov/socialmedia/Tools/guidelines/pdf/SocialMediaToolkit_BM.pdf
In addition, the Research Brief provides insights into
the potential effectiveness of social media use by
HCOs.

Promoting Health Literacy in
School-Aged Children
Promoting health literacy in school-aged children
presents special challenges to health educators. There
is wide agreement that childhood obesity is a serious
and growing issue, which is related not only to poor
choice of foods, but also to the sedentary lifestyles
promoted by video games and television. In addition,
the time once devoted to health and physical education
programs in schools has given way to more time spent
on core subjects, such as math and science.

The Children’s Nutrition Research Center responded
early to these challenges by supporting the
development of nutrition education programs as
interactive computer games, video games, and
cartoons referred to as “edutainment” (Flores, 2006).
These e-health programs are developed specifically to
appeal to the generational (highly connected and
computer literate) and cultural needs of this group.
Flores describes the Family Web project, which uses
comic strips to impart nutrition information, and Squires
Quest, where the students earn points by choosing
fruits and vegetables to fight the snakes and moles that
are trying to destroy the healthy foods in the Kingdom
of SALot. These are great examples of health
education programs that are designed to appeal to this
connected generation of learners and their intuitive
ability to use interactive technologies.

Donovan (2005) described an interdisciplinary Web
quest designed to appeal to older school-aged
children. The quest is interdisciplinary in that it requires
reading comprehension, critical thinking, presentation,
and writing; thus, core skills and health literacy skills
are learned in a single assignment. Students are
directed to the Web to search for information on the
pros and cons of low-carbohydrate diets and obesity
prevention. Students learn along the way as they
search for information, collect and interpret it, and then
develop a presentation and final paper.

The Cancer Game (Oda & Kristula, n.d.) was
developed by a young man taking a college class on
Macromedia software who had previously undergone a
bone marrow transplant. Subsequently, he and a
professor collaborated and expanded the project to its
present form. The game is designed as an arcade-style
video game for cancer patients to relieve stress by
visualizing the fighting of cancer cells. Although cancer
victims of any age can access and play the game, it
has a special appeal to children and adolescents. Find
the game here: www.cancergame.org. Similarly,
Ben’s Game (www.wish.org/wishes/wish-stories/i-
wish-to-be/ben-video-game-creator) is a video game
designed to help relieve the stress of cancer treatment
for children (Anderson & Klemm, 2008).

You can access these newer games on the Internet by
typing “health games” into a search engine. Be sure to
review the information presented in the game for
accuracy before you recommend it to parents and
children. The National Library of Medicine maintains a
site dedicated to health learning games for both
children and adults
(www.nlm.nih.gov/medlineplus/games.html). You
can feel confident in recommending games from this
trusted website as they have been vetted for accuracy
and credibility.

Supporting Use of the Internet

for Health Education
Nurses and other healthcare providers need to
embrace the Internet as a source of health information
for patient education and health literacy. Patients are
increasingly turning there for instant information about
their health maladies. Health-related blogs (short for
weblog, an online journal) and electronic patient and
parent support groups are also proliferating at an
astounding rate. Clinicians need to be prepared to arm
patients with the skills required to identify credible
websites. They also need to participate in the
development of well-designed, easy-to-use health
education tools. Finally, they need to convince payers
of the necessity of health education and the powerful
impact education has on promoting and maintaining
health. Box 16-1 provides more information about
patient education.

BOX 16-1 CONSIDERATIONS FOR

PATIENT EDUCATION

Julie A. Kenney and Ida Androwich

Nurses need to take many things into account
when teaching patients. They need to assess
patients’ willingness to learn, their reading
ability, the means by which they learn best, and
their existing knowledge about the subject.

These important considerations for patient
education are depicted in Figure 16-2.

Figure 16-2 Choosing an Education Strategy

Photo: © ERproductions Ltd/Blend Images/Getty

Nurses also need to take cultural, language, and
generational differences into account when
teaching their patients. If the nurse chooses to
use an electronic method to educate the patient,
digital natives (patients who have grown up with
technology) need to be taught differently than
digital immigrants (those who are late adopters
of technology; “Educational Strategies,” 2006).
Digital natives are typically born after 1982 and
may also be referred to as “Generation Y.” This
generation prefers to learn using technology and
learns quite well if information is presented in a
format to which they are accustomed, such as

an interactive video game to introduce them to a
topic. This group is also comfortable using
information that they can access via their
handheld devices, such as smartphones and
tablets, as well as wearable devices such as
smartwatches. Those born before 1982 have
learning styles that range from preferring to
learn in a classroom setting to reading a book
about the topic to learning using a hands-on,
interactive approach (“Educational Strategies,”
2006).

A systematic review of the literature related to
teaching methods (Friedman, Cosby, Boyko,
Hatton-Bauer, & Turnbull, 2011) suggested that
various modalities ranging from computer
technologies to demonstrations and reviews of
written materials can all be effective as long as
they are structured and specifically designed for
and congruent with the patient’s culture. More
recently, Sawyer (2016) tested a tablet-based
education program for patients with heart failure.
They sought to demonstrate the value of the
tablet-based education approach to staff and, at
the same time, find ways to minimize the
disruptiveness of the technology-based
education on clinical workflow, ensure patent
safety by establishing specific procedures for
device cleaning, and suggest strategies for
maintaining the security of the devices. They

conclude that technology-based learning tools
may be effective in helping patients manage
their disease postdischarge. They also
emphasize the need to consider clinician
workflow and device security to ensure a
successful implementation.

REFERENCES

Educational strategies in generational
designs. (2006). Progress in
Transplantation, 16(1), 8–9.

Friedman, A. Cosby, R., Boyko, S.,
Hatton-Bauer, J., & Turnbull, G.
(2011). Effective teaching strategies
and methods of delivery for patient
education: A systematic review and
practice guideline
recommendations. Journal of
Cancer Education, 12–21. doi:
10.1007/s13187-010-0183-x.

Sawyer, T. (2016). Implementing
electronic tablet-based education of
acute care patients. Critical Care
Nurse, 36(1), 60–70.
doi:10.4037/ccn2016541

Patient Education Websites
American Academy of Family Physicians:
www.aafp.org/patient-care.html

American Cancer Society: www.cancer.org

American Heart Association: www.heart.org

Centers for Disease Control and Prevention:
www.cdc.gov

Krames (products to purchase):
www.staywell.com/patient-education-2

UpToDate (paid subscription):
www.uptodate.com

The Health on the Net (HON) Foundation (2005)
survey described the certifications and accreditation
symbols that identify trusted health sites. The
HONcode and Trust-e were identified as the two most
common symbols that power users look for. (Website
developers can apply for HONcode certification of
Web-based materials. Initial certification is for 1 year,
after which the site is reevaluated annually by experts.
The HON Foundation also monitors site complaints
and factors reported issues into the recertification
process [Health on the Net Foundation, 2014].) The
survey also indicated that Internet users look at the

domain name and frequently gravitate toward
university sites (.edu), government sites (.gov), and
HCO sites (.org). Half of the survey respondents were
in favor of the use of a domain name called “health” to
identify quality health information websites. In contrast,
Anderson and Rainie (2006) indicate that nearly 75%
of online searchers do not check the date or the source
of information they are accessing on the Web and 3%
of online health seekers report knowing someone who
was harmed by following health information found on
the Web.

The U.S. National Library of Medicine and the NIH
jointly sponsor MedlinePlus, a website that has a
tutorial for learning how to evaluate health information
and an electronic guide to Web surfing that is available
in both English and Spanish. This site is found at
www.medlineplus.gov. A similar guide explains the
major things one should evaluate when accessing
health-related resources on the Web (National Center
for Complementary and Alternative Medicine, 2014)
and can be accessed at
http://nccam.nih.gov/health/webresources. Suggest
that patients visit these sites to become more adept at
identifying whether a website is credible before they
adopt the recommendations provided.

Some healthcare professionals have partnered with
their organizations to develop patient education
materials. These materials must be carefully reviewed

for accuracy and usability. The Agency for Healthcare
Research and Quality (2013) published an
assessment tool for both print and audiovisual patient
education materials. Their tool is designed to assess
both understandability and actionability by providing a
series of review criteria for each of these domains. The
tool can be accessed at
www.ahrq.gov/professionals/prevention-chronic-
care/improve/self-mgmt/pemat/index.html. Clearly,
the clinician needs to engage the patient to partner with
them in the management of their health. Refer to
Boxes 16-1 and 16-2 to review effective education
methods used in teaching patients and their families
about their health challenges.

BOX 16-2 A CLINICIAN’S VIEW ON

PATIENT EDUCATION

Denise D. Tyler

Knowledge dissemination in nursing practice
includes sharing information with patients and
families so that they understand their healthcare
needs well enough to participate in developing
the plan of care, make informed decisions about
their health, and ultimately comply with the plan
of care, both during hospitalization and as
outpatients.

There are several effective methods for
educating patients and their families. Providing
one-on-one and classroom instruction are
traditional and valuable forms of education.
One-on-one education is interactive and can be
adjusted at any time during the process based
on the needs of the individual patient or family; it
can also be supplemented by written material,
videos, and Web-based learning applications.
Classroom education can be beneficial because
patients and families with similar needs or
problems can network, thereby enhancing the
individual experience. However, the ability to
interact with each member of the group and to
tailor the educational experience based on
individual needs may be limited by the size and
dissimilarities of the group. Individual follow-up
should be available when possible.

Paper-based education that is created, printed,
and distributed by individual institutions or
providers can be very effective because
materials can be distributed at any time and
reviewed when the patient feels like learning.
Many agencies, such as the CDC, have
education for patients available on their
websites. These documents can be reviewed
online, or they can be printed out by healthcare
providers or patients. Organizations can also
develop and distribute information and

instructions specific to their policies and
procedures. In addition, printed educational
material can be purchased from companies that
employ experts in the subject matter and
instructional design.

One of the more popular sources of patient
education information is the Internet. Many
hospitals and HCOs provide proprietary
information, such as directions to the facility,
information on procedures, and instructions on
what to expect during hospitalization, in this
manner. Other health organizations, such as the
NIH, provide detailed information on their
websites. Clinicians should be cautious when
recommending websites to patients and
families, because not all sites are reliable or
valid.

Many companies that provide clinical
information systems or electronic health records
also include patient education materials linked to
the clinical system via an intranet. Thus
standardized instructions that are specific to a
procedure or disease process can be printed
from this computer-based application. Discharge
instructions that are interdisciplinary and patient
specific can often be modified via drop-down
lists or selectable items that can be deleted or
changed by the clinician. This ability to modify
before printing provides more consistent and

individualized instruction. The computer-based
generation of instruction is preferable to free text
and verbal instruction because it also allows the
information to be linked to a coded nursing
language and, therefore, easily used for
measurement and quality assurance reporting.
Relevant triggers may be embedded in the
clinical information systems. For example, when
a patient answers “yes” to a question about
current smoking, smoking cessation information
should automatically be printed, or a trigger
should remind the nurse to explore this topic
with the patient and then provide the patient with
preprinted information on smoking cessation.

Integration of standardized discharge
instructions and patient education into the
clinical system is another way to improve the
compliance and documentation of education; it
also streamlines the workflow of clinicians.
Printing the information to give to the patient
should be seamless to the clinician who is
documenting in the patient’s record. The format
should be logical and easy to read. The more
transparent the process, the more efficient the
system and the easier it is to use for the
clinician. What I envision for the future is a
system that “remembers” the style of learning
preferred by patients and their families, prompts
the provider to print handouts, and programs the

bedside computer/video education system
based on previous selections and surveys. This
interactive patient and family education will be
integrated into the clinical system and the
patient’s personal health record.

Some providers have developed a list of credible
websites and apps that are shared with patients or
family members. Recommendations for websites might
include the U.S. Department of Health and Human
Services–sponsored healthfinder site
(www.healthfinder.gov), a website dedicated to
helping consumers find credible information on the
Internet. Other excellent sources of reliable information
are the National Institutes of Health (www.nih.gov),
the Centers for Disease Control and Prevention
(www.cdc.gov), Medline Plus
(www.medlineplus.gov), NIHSeniorHealth
(www.nihseniorhealth.gov), and the National Health
Information Center (www.health.gov/nhic). Some of
the apps (found on iTunes for iPhones or Google Play
for Android devices) that might be recommended
include Mayo Clinic on Pregnancy, WebMD Pain
Coach, MyFitnessPal, and Understanding Diseases.
These are great examples of the wealth of patient
information being developed as apps by hospitals and
other healthcare providers. More apps are being
developed every day to engage people in managing
and taking control of their health. Perhaps the most

important thing that healthcare professionals can stress
is that not all apps have credible and valid information.
We must encourage our patients to become savvy
users of electronic information sources.

Future Directions for Engaging
Patients
Predicting future directions for technology-based health
education is somewhat difficult because one may not
be able to completely envision the technology of the
future. One can predict, however, that some current
technologies will be used increasingly to support health
literacy, and new technologies will be developed every
day. For example, audio and video podcasts may
become more commonplace in health education and
be provided as free downloads from the websites of
HCOs.

Voice recognition software used to navigate the Web
may reduce the frustration and confusion associated
with attempting to spell complex medical terms.
However, the confusion and frustration may increase if
the patient or client is unable to pronounce the terms.
Voice interactivity should help to reduce the digital
access disparity associated with those who have
limited keyboard or mouse skills. For those persons
with visual impairments, some websites may provide
both audio and text information and support increased

text size for greater ease of reading (Anderson &
Klemm, 2008).

Many websites associated with government and
national organizations are also providing multiple-
language access to health information and decision-
support tools (U.S. National Library of Medicine,
2016). The multilanguage access broadens the
population to whom education can be provided, and
the decision-support programs allow users to access
results that are tailored to their age, risk factors, or
disease state (Anderson & Klemm, 2008).

As patient engagement strategies become more
commonplace, we will also see a movement toward
connected health. Those individuals who are frequent
email users may be interested in being able to
communicate with physicians and other healthcare
personnel via email rather than the telephone. This
idea may meet with some resistance from physicians
who perceive the email correspondence as
bothersome and time consuming. However, it is
possible that work efficiency might also increase if
patients and their needs are screened via secure email
before an office or clinic visit. For example, as a result
of an email correspondence in lieu of an initial office
visit, medications could be changed or diagnostic tests
could be performed before the office visit. In addition,
patients could be directed to an interactive screening
form housed on a secure website where they would

answer a series of questions that would help them
make a decision about whether they should call for an
appointment, head for the emergency room, or self-
manage the issue. If self-management is the outcome
of the screening tool, then the patient or caregiver
could be directed to a credible website for more
information. The idea is not to interfere with or replace
the face-to-face visit, but rather to supplement the
provider–patient relationship and perhaps streamline
the efficiency of healthcare delivery. McCray (2005)
also suggests that physicians may be resistant to
providing email consultations and recommending
health-related websites because of the potential for
malpractice liability. Other healthcare professionals
may share some of these same concerns. There is
some evidence that text message reminders delivered
via a cell phone are more effective and efficient as
appointment reminders than traditional phone calls
(Car, Gurol-Urganci, de Jongh, Vodopivec-Jamsek,
& Atun, 2012), and text message reminders related to
health behaviors such as diet and exercise might also
be effective. Similarly, in a descriptive research study
by Dudas, Pumilia, and Crocetti (2013), it was found
that parents of children who recently visited an
emergency department were interested in receiving
follow-up communication from healthcare providers by
text messaging and/or email. A major barrier to
widespread adoption of email and text messaging
among American healthcare providers is the fact that
reimbursement mechanisms for electronic health care

interventions are inadequate or nonexistent. This may
be an issue that is resolved in the near future, and
other healthcare professionals may soon be a part of
these patient engagement and connected health
trends. Piette (2007) described the use of interactive
behavior change technology to improve the
effectiveness of diabetes management. The goal of the
interactive behavior change technology is to improve
communication between patients and healthcare
providers and to provide educational interventions that
promote better disease management between office
visits. The combination of electronic medication
reminders, meters that track glycemic control
longitudinally, and personal digital assistant–based
calculators was found to support the behavioral
interventions necessary to better manage the diabetes.

As a conclusion to their study, Watson, Bell, Kvedar,
and Grant (2008) caution that even though patients
are part of the digital divide (lacking access or skill in
electronic communications and Internet use), one
cannot assume that they will be resistant to using other
forms of technology to support health. These authors
compared Internet users to non-Internet users and
found that both groups were willing to learn to use new
technology to manage type 2 diabetes, including
wireless communication devices for information sharing
with physicians.

Healthcare practitioners may soon embrace the use of

“information prescriptions” (D’Alessandro, 2010) that
direct patients and families to credible websites,
including government and HCO websites, and wikis
and blogs that may help them understand their health
issues or share information with and seek support from
others who have similar issues. “Information
prescriptions are prescriptions of focused, evidence-
based information given to a patient at the right time to
manage a health problem” (D’Alessandro, p. 81). The
National Health Service in the United Kingdom has
developed an information prescription generator that
can be used by providers or the public to access Web-
based health information
(www.nhs.uk/ipg/Pages/IPStart.aspx).

Wearable technologies are becoming increasingly
popular among tech-savvy patients. However, their
impact on overall health has yet to be realized. Garvin
(2016) stated, “As wearables and their applications
continue to multiply, a single and familiar question
emerges: Where exactly will wearable technology lead
us? Is this garnering of such gadgets and their wealth
of health data merely a trend, or is there real staying
power within these little devices to create substantial
impact in healthcare?” (para. 2). The most common
consumer-based wearables are fitness trackers, but
there are no clear guidelines as to how to integrate the
data these devices collect into a patient’s health record
and make them actionable. Examples of other devices
include smart shirts that track anxiety-triggered

breathing patterns and promote mindfulness (Garvin);
the Smart Stop device, which is designed to detect
cigarette cravings and deliver medication to eliminate
the craving; and smart contact lenses that measure
glucose levels in tears and alert the wearer to a change
in glucose level by changing color (Kosir, 2015). For a
full discussion of provider prescribed wearables and
remote health monitoring, see the telehealth chapter.

Newer technologies designed to engage patients
actively in rehabilitation activities were recently
reported on MedGadget (2016). For example, to better
engage patients in stroke rehabilitation activities,
researchers developed a game system that
encourages patients to use the affected limb to play the
game while restricting the good limb from participation.
Another system employs sensors on the affected limbs
and the patient’s motion is translated into art on the
screen. The feedback is immediate and readily
apparent, which seems to encourage patients to
participate more fully. Along these same lines, a series
of neurogaming technologies are being developed to
promote cognitive function. “Data generated from these
products also provide actionable information to inform
care delivery. Therapeutic neurogaming is the use of
neurogaming technologies for the purposes of health,
wellness, and/or rehabilitation” (Morsy, 2016, para. 2).
You can receive free daily updates on medical
technologies by subscribing to the newsletter produced
by MedGadget (www.medgadget.com).

Summary
It is clear that the consumer empowerment and
connected health movement will continue to drive the
need for access to quality health education and support
programs. In an ideal world, practitioners will design
educational materials that are user friendly, culturally
competent, interesting, dynamic, and interactive, and
that meet the skills, education needs, and interests of
the user.

THOUGHT-PROVOKING QUESTIONS

1. Choose two patient-engagement or
connectivity tools and discuss specifically
how you would use these to deliver care
in your practice.

2. Formulate a patient education plan for a
common chronic health challenge related
to your practice. Provide a rationale for
each approach and describe a technology
tool you would use to engage and
educate the patient and his or her family.

3. Reflect on connected health potentials in
your practice. What are you doing
currently that connects and engages your
patients in managing their health?
Describe in detail what you plan to do in
the next 6 months to 1 year.

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CHAPTER 17: Using
Informatics to Promote
Community/Population
Health

Dee McGonigle Kathleen Mastrian Margaret Ross Kraft
and Ida Androwich

Objectives
1. Provide an overview of community and

population health informatics.
2. Assess informatics tools for promoting

community and population health.
3. Explore the roles of federal, state, and

local public health agencies in the
development of public health informatics.

Key Terms

» Agency for Toxic Substances and
Disease Registry (ATSDR)

» Behavioral Risk Factor Surveillance
System

» Bioterrorism

» Centers for Disease Control and
Prevention (CDC)

» Community risk assessment (CRA)

» Crowdsourcing

» Epidemiology

» National Center for Public Health
Informatics (NCPHI)

» National health information network

» National Health and Nutrition
Examination Survey

» Public health

» Public health informatics

» Public health interventions

» Quality, research, and public health
(QRPH)

» Regional health information exchanges

» Risk assessment

» Social media

» Suicide Prevention Community
Assessment Tool

» Surveillance

» Surveillance data systems

» Syndromic surveillance

» Youth Risk Behavior Surveillance
System

Introduction
In late fall of 2002, severe acute respiratory syndrome
(SARS) appeared in China. By March 2003, SARS had
become recognized as a global threat. According to
World Health Organization (WHO) data, more than
8,000 people from 29 countries became infected with
this previously unknown virus and more than 700
people died. By 2004, the last SARS cases were
caused by laboratory-acquired infections. Because of
computerized global data collection, the potentially
negative impact of a widespread global epidemic was
averted.

Additionally, Renwick (2016) reported that

[b]y the end of 2015, more than 28,600
people had been infected [with Ebola],
killing more than 11,300. That figure was
much lower than projections the CDC
made a year before, which calculated that
as many as 1.4 million people could
become infected with Ebola by January
2015. Instead, the disease peaked in late
2014: in Liberia in September, Guinea in
October, and Sierra Leone in November.
By January 2016, Guinea, Liberia, and
Sierra Leone had been declared free of
Ebola. (para. 16)

As we lived through the Ebola outbreak, we realized
the need for timely information to be shared with the
world population, as well as the healthcare workers
responsible for caring for them. WHO (2015) stated
that “leading international stakeholders from multiple
sectors convened at a WHO consultation in September
2015, where they affirmed that timely and transparent
pre-publication sharing of data and results during
public health emergencies must become the global
norm” (para. 1).

More recently, the Zika virus has become a leading
public health concern. The Centers for Disease Control
and Prevention (CDC; 2016b) reported that their
Emergency Operations Center (EOC)

was activated for Zika on January 22,
2016, and moved to a level 1 activation—
the highest level—on February 8, 2016.
The EOC is the command center for
monitoring and coordinating the
emergency response to Zika, bringing
together CDC scientists with expertise in
arboviruses like Zika, reproductive health,
birth defects, and developmental
disabilities, and travel health. (para. 1)

The CDC’s EOC staff works in collaboration with local,
national, and international response partners to
analyze, validate, and efficiently exchange information
about the outbreak. The CDC (2015) public health
surveillance center “refers to the collection, analysis
and use of data to target public health prevention. It is
the foundation of public health practice” (para. 1). The
CDC provides interactive databases and surveys, as
well as methods to guide conducting and evaluating
surveillance systems and data standardization.

Many surveillance systems, loosely termed
“syndromic surveillance systems,” use data that are not
diagnostic of a disease but that might indicate the early
stages of an outbreak (see Figure 17-1). Outbreak
detection is the overriding purpose of syndromic
surveillance for terrorism preparedness. Enhanced
case finding and monitoring the course and population

characteristics of a recognized outbreak also are
potential benefits of syndromic surveillance. In recent
years, new data have been used by public health
officials to enhance surveillance, such as patients’ chief
complaints in emergency departments, ambulance log
sheets, prescriptions filled, retail drug and product
purchases, school or work absenteeism, and medical
signs and symptoms in persons seen in various clinical
settings. With faster, more specific, and more
affordable diagnostic methods and decision-support
tools, timely recognition of reportable diseases with the
potential to lead to a substantial outbreak is now
possible. Tools for pattern recognition can be used to
screen data for patterns needing further public health
investigation. For example, during the 2003 SARS
epidemic, the Centers for Disease Control and
Prevention (CDC) worked to develop surveillance
criteria to identify persons with SARS in the United
States, and the surveillance case definition changed
throughout the epidemic, to reflect increased
understanding of SARS (CDC, 2013).

Figure 17-1 Syndromic Surveillance System

Information acquired by the collection and processing
of population health data becomes the basis for
knowledge in the field of public health. There is an
ever-increasing need for timely information about the
health of communities, states, and countries.
Knowledge about disease trends and other threats to
community health can improve program planning,
decision making, and care delivery. Patients seen from
the perspective of major health threats within their
communities can benefit from opportunities for early
intervention.

This chapter focuses on the application of informatics
methods to public health surveillance. The availability

of clinical information for public health has been
fundamentally changed by the introduction of the
electronic health record (EHR) and health information
technology (IT), which now give public health “an
unprecedented opportunity to leverage the information,
technologies and standards to support critical public
health functions such as alerting and surveillance”
(Garrett, 2010).

Core Public Health Functions
The core public health functions are as follows:

The assessment and monitoring of the health of
communities and populations at risk to identify
health problems and priorities
The formulation of public policies designed to solve
identified local and national health problems and
priorities
To assure that all populations have access to
appropriate and cost-effective care, including health
promotion and disease prevention services, and
evaluation of the effectiveness of that care
(Medterms Medical Dictionary, 2007)

Public health focuses on health promotion and disease
prevention. According to the CDC Foundation (2016),
public health is the

science of protecting and improving the
health of families and communities
through promotion of healthy lifestyles,
research for disease and injury
prevention and detection and control of
infectious diseases. Overall, public health
is concerned with protecting the health of
entire populations. These populations can
be as small as a local neighborhood, or
as big as an entire country or region of
the world. (para. 1–2)

Historically, Dr. John Snow can be designated as the
“father” of public health informatics (PHI) (Figure 17-
2). In 1854, he plotted information about cholera
deaths and was able to determine that the deaths were
clustered around the same water pump in London. He
convinced authorities that the cholera deaths were
associated with that water pump; when the pump
handle was removed, the cholera outbreak ended. It
was Dr. Snow’s focus on the cholera-affected
population as a whole rather than on a single patient
that led to his discovery of the source of the cholera
outbreak (Vachon, 2005).

Figure 17-2 Public Health Informatics

Florence Nightingale should also be recognized as an
early public health informaticist. Her recommendations
about medical reform and the need for improved
sanitary conditions were based on data about morbidity
and mortality that she compiled from her experiences
in the Crimea and England. Her efforts led to a total
reorganization of how and which healthcare statistics
were collected (Dossey, 2000).

Just as information has been recognized as an asset in
the business world, so health care is now recognized
as an information-intensive field requiring timely,
accurate information from many different sources.
Health information systems address the collection,
storage, analysis, interpretation, and communication of
health data and information. Many health disciplines,
such as medicine and nursing, have developed their

own concepts of informatics. That trend has reached
the field of public and community health. PHI
represents “the effective use of information and
information technology to improve public health
practice and outcomes” (Public Health Informatics
Institute, 2015, para. 18). This area of informatics
differs from others because it is focused on the
promotion of health and disease prevention in
populations and communities. PHI efficiently and
effectively organizes and manages data, information,
and knowledge generated and used by public health
professionals to fulfill the core functions of public
health: assessment, policy, and assurance (Agency
for Toxic Substances and Disease Registry
[ATSDR], 2016). Public health changes the social
conditions and systems that affect everyone within a
given community. It is because of public health
initiatives that people understand the importance of
clean water, the dangers of second-hand smoke, and
the fact that seat belts really do save lives. PHI
emphasizes community-based solutions and promotes
community empowerment by advancing the state of the
art in community benefit projects (Public Health
Institute, 2016a). One of the community-based
projects—Building Healthy Communities: Hospital
Community Benefit Engagement—applies “findings
and lessons learned from the collection and analysis of
community benefit programming data in the 14 building
healthy community sites to create deeper collaboration
and partnership-building” (Public Health Institute,

2016b, para. 1). Community empowerment can be
realized through the collaborative collection and
analysis of data that lead to improved community
health outcomes and transformed public health.

The scope of PHI practice includes knowledge from a
variety of additional disciplines, including management,
organization theory, psychology, political science, and
law, as well as fields related to public health, such as
epidemiology, microbiology, toxicology, and statistics
(O’Carroll, Yasnoff, Ward, Ripp, & Martin, 2003, p.
5). PHI addresses the data, information, and
knowledge that public health professionals generate
and use to meet the core functions of public health.
Yasnoff and colleagues (2000) defined four principles
that continue to define and guide the activities of PHI:
(1) applications promote the health of populations, (2)
applications focus on disease and injury prevention, (3)
applications explore prevention at “all vulnerable points
in the causal changes,” and (4) PHI reflects the
“governmental context in which public health is
practiced” (p. 69).

Functions of public health include prevention of
epidemics and the spread of disease, protection
against environmental hazards, promotion of health,
disaster response and recovery, and providing access
to health care.

The initiative of integrating the healthcare enterprise to

ensure that healthcare information can be shared more
easily and used more effectively has inspired the
creation of the domain known as quality, research,
and public health (QRPH). Participants in this domain
address the repurposing of clinical, demographic, and
financial data collected in the process of providing
clinical care to the monitoring of disease patterns;
incidence, prevalence, and situational awareness of
such patterns; and the identification of new patterns of
disease not previously known or anticipated. Such data
can be incorporated within existing public health
population analyses and programs for direct outreach
and condition management through registries and
locally determined appropriate treatment programs or
protocols.

Community Health Risk
Assessment: Tools for
Acquiring Knowledge
As the public has become more aware of harmful
elements in the environment, risk assessment tools
have been developed. Such tools allow assessment of
pesticide use, exposure to harmful chemicals,
contaminants in food and water, and toxic pollutants in
the air to determine if potential hazards need to be
addressed. A risk assessment may also be called a
“threat and risk assessment.” A “threat” is a harmful
act, such as the deployment of a virus or illegal

network penetration. A “risk” is the expectation that a
threat may succeed and the potential damage that can
occur (PCMag.com Encyclopedia, 2007). “Risk factor
assessments complement vital statistics data systems
and morbidity data systems by providing information on
factors earlier in the causal chain leading to illness,
injury or death” (O’Carroll, Powell-Griner, Holtzman
& Williamson, 2003, p. 316).

The U.S. Environmental Protection Agency (EPA;
2016) “uses risk assessments to characterize the
nature and magnitude of health risks to humans (e.g.,
residents, workers, recreational visitors) and ecological
receptors (e.g., birds, fish, wildlife) from chemical
contaminants and other stressors, that may be present
in the environment” (para. 3) and are used to weigh the
benefits and costs of various program alternatives for
reducing exposure to potential hazards. They may also
influence public policy and regulatory decisions. Health
risk assessment is a constantly developing process
based in sound science and professional judgments.
There are usually four basic steps ascribed to risk
assessment (see also Figure 17-3):

Figure 17-3 Four-Step Risk Assessment Process

Modified from U.S. Environmental Protection Agency. (2016). Conducting

a human health risk assessment. Retrieved from

https://www.epa.gov/risk/conducting-human-health-risk-assessment

1. Hazard identification seeks to determine the
types of health problems that could be caused
by exposure to a potentially hazardous material.
All research studies related to the potentially
hazardous material are reviewed to identify
potential health problems.

2. Exposure assessment is done to determine the
length, amount, and pattern of exposure to the
potentially hazardous material.

3. Dose–response assessment is an estimation of
how much exposure to the potential hazard
would cause varying degrees of health effects.

4. Risk characterization is an assessment of the
risk of the hazardous material causing illness in

the population (California Environmental
Protection Agency, 1998).

The overall question the risk assessment has to
answer is, “How much risk is acceptable?” Risk factor
systems are used throughout the United States and
may be local, regional, or national in scope. Specific
risk assessment tools exist for specific health issues,
such as the Suicide Prevention Community
Assessment Tool, which addresses general
community information, prevention networks, and the
demographics of the target population and community
assets and risk factors. Other risk assessment tools
include the Youth Risk Behavior Surveillance
System, the Behavioral Risk Factor Surveillance
System, and the National Health and Nutrition
Examination Survey.

Determining the presence of risk factors in a
community is a key part of a community risk
assessment (CRA). Communities may be concerned
about which elements in the environment affect or may
affect the community’s health, the level of
environmental risk, and other factors that should be
included in public health planning. Ball (2003) defined
value as “a function of cost, service, and outcome” (p.
41). The value of a CRA derives from its ability to
provide information crucial to planning, build
consensus regarding how to mobilize community
resources, and allow for comparison of risks with those

of other communities. The goal of a CRA is risk
reduction and improved health. A CRA may identify
unmet needs and opportunities for action that may help
set new priorities for local public health units. It may
also be used to monitor the impact of prevention
programs.

Processing Knowledge and
Information to Support
Epidemiology and Monitoring
Disease Outbreaks
There is a need to define the role of federal, state, and
local public health agencies in the development of PHI
and IT applications. The availability of IT today
challenges all stakeholders in the health of the public to
adopt new systems that can provide adequate disease
surveillance; it also challenges people to improve
outmoded processes.

Preparedness in public health requires more timely
detection of potential health threats, situational
awareness, surveillance, outbreak management,
countermeasures, response, and communications.
Surveillance uses health-related data that signal a
sufficient probability of a case or an outbreak that
warrants further public health response. Although
historically syndromic surveillance has been used to
target investigations of potential infectious cases, its

use to detect possible outbreaks associated with
bioterrorism is increasingly being explored by public
health officials (CDC, 2013, 2014). Early detection of
possible outbreaks can be achieved through timely and
complete receipt, review, and investigation of disease
case reports; by improving the ability to recognize
patterns in data that may be indicative of a possible
outbreak early in its course; and through receipt of new
types of data that can signify an outbreak earlier in its
course. Such new types of data might include
identification of absences from work or school;
increased purchases of healthcare products, including
specific types of over-the-counter medications;
presenting symptoms to healthcare providers; and
laboratory test orders (CDC, 2012, 2013). The
University of Pittsburgh’s Real-time Outbreak and
Disease Surveillance Laboratory (RODS), for example,
developed the National Retail Data Monitor (NRDM)
system. The NRDM collects data on over-the-counter
medications and other healthcare products from 28,000
stores and uses computer algorithms to detect unusual
purchase patterns that might potentially signal a
disease outbreak (RODS Laboratory, 2013). A
comprehensive surveillance effort supports timely
investigation and identifies data needs for managing
the public health response to an outbreak or terrorist
event. Informatics tools are becoming increasingly
important in these public health efforts.

To appropriately process public health data, PHI has a

need for a standardized vocabulary and coding
structure. This is especially important as national public
health data are collected and data mining performed so
that data variables can be understood across systems
and between agencies. Health information
organizations (HIOs) have been established to support
data sharing via health information exchanges (HIE)
promoted by the meaningful use criteria of the EHR.
Central to these initiatives is the need for standardized
codes and terminologies that may be used by the HIOs
to map data from disparate sources (Hyde et al., 2013;
Shapiro, Mostashari, Hripcsak, Soulakis, &
Kuperman, 2011).

In the early 1990s, the CDC launched a plan for an
integrated surveillance system that moved from stand-
alone systems to networked data exchange built with
specific standards. Early initiatives were the National
Electronic Telecommunications System for Surveillance
and the Wide-ranging Online Data for Epidemiologic
Research. Six current initiatives reflect this early vision:

1. PulseNet USA: A surveillance network for food-
borne infections.

2. National Electronic Disease Surveillance
System: Facilitates reporting on approximately
100 diseases, with data feeding directly from
clinical laboratories, which allows for early
detection.

3. Epidemic Information Exchange: A secure

communication system for practitioners to
access and share preliminary health surveillance
information.

4. Health Alert Network: A state and nationwide
alert system.

5. Biosense: Provides improved real-time
biosurveillance and situational awareness in
support of early detection.

6. Public Health Information Network: Promotes
standards and software solutions for the rapid
flow of public health information.

Certainly, the events of September 11, 2001, which
indicated the need for the United States to increase its
efforts directed toward prevention of terrorism,
accelerated the need for informatics in public health
practice. Today, response requirements include fast
detection, science, communication, integration, and
action (Kukafka, 2006). In 2005, the CDC created the
National Center for Public Health Informatics
(NCPHI) to provide leadership in the field. This center
aims to protect and improve health through PHI (CDC,
2005; McNabb, Koo, Pinner, & Seligman, 2006). The
CDC (2016a) “provides leadership and crosscutting
support in developing public health information
systems, managing public health surveillance
programs and providing health-related data required to
monitor, control, and prevent the occurrence and
spread of diseases and other adverse health
conditions” (para. 1).

Information is vital to public health programming. The
data processed into public health information can be
obtained from administrative, financial, and facility
sources. Included in this data stream may be
encounter, screening, registry, clinical, and laboratory
and surveillance data. It has been recommended that
the functions of population health beyond surveillance
be integrated into the EHR and the personal health
record. Such an initiative might allow for population-
level alerts to be sent to clinicians through these
electronic record systems. Systems now being
developed allow for automated syndromic surveillance
of emergency department records and media
surveillance, which in turn supports early detection of
potential pandemic occurrences. Such systems were
tested during the 2009 H1N1 flu, 2014 Ebola, and 2015
Zika outbreaks. The public health–enhanced electronic
medical record can provide immediate detection and
reporting of notifiable conditions. The incorporation of
geographic information systems allows public health
data to be mapped to specific locations that may
indicate an immediate need for intervention (CDC,
2016a; Grannis & Vreeman, 2010).

Vital statistics from state and local governments are
also used for public health purposes. It should be noted
that databases created with public funds are public
databases that are available for authorized public

representatives for public purposes (CDC, 2016a;
Freedman & Weed, 2003).

The widespread implementation of EHRs is facilitating
the concept of a public health–enabled record, which
can automatically send patient information alerts from
the point of care to public health departments when
reportable symptoms, conditions, or diseases are
encountered. A public health–enabled EHR can be
bidirectional, allowing public health information and
recommendations for treatment to be accessible at the
point of care. One public health EHR prototype
addresses the information flow related to newborn
screenings (HealthIT.gov, 2013a; Orlova et al., 2005).

Potential applications of HIE to public health have been
described by HealthIT.gov (2013b) and Shapiro et al.
(2011). They include syndromic surveillance using data
generated from mandated and nonmandated
laboratory results, physician diagnoses, and
emergency or clinic chief complaints; strategies to
locate loved ones in mass-casualty events; and public
health alerts at the individual and population levels.

Applying Knowledge to Health
Disaster Planning and
Preparation

The availability of data and the speed of data exchange
can have a significant impact on critical public health
functions such as disease monitoring and syndromic
surveillance. Currently, surveillance data are limited
and historical in nature, although this situation is rapidly
changing. Nevertheless, special data collections are
needed to address specific public health issues, and
investigations and emergencies are still frequently
addressed and managed with paper. In the future, PHI
will make real-time surveillance data available
electronically, and investigations and emergences will
be managed with the tools of informatics (Yasnoff et
al., 2004). Surveillance data systems such as
infectious disease trackers that collect data on adverse
health effects are invaluable tools for public health
officials to tap for planning, evaluation, or
implementation of public health interventions. The
Agency for Toxic Substances and Disease Registry
(ATSDR), for example, is a federal agency that acts as
a repository for research and data regarding hazardous
materials. It “serves the public by using the best
science, taking responsive public health actions, and
providing trusted health information to prevent harmful
exposures and diseases related to toxic substances”
(ATSDR, 2016, para. 1). “Syndromic surveillance for
early outbreak detection is an investigational approach
where health department staff, assisted by automated
data acquisition and generation of statistical signals,
monitor disease indicators continually (real-time) or at
least daily (near realtime) to detect outbreaks of

diseases earlier and more completely than might
otherwise be possible with traditional public health
methods” (Buehler, Hopkins, Overhage, Sosin, &
Tong, 2004, para. 7). Traditionally, there has been no
common infrastructure to respond to pandemics, but
the development of health IT is creating opportunities
that go far beyond national boundaries to impact global
public health initiatives. In this vein, the U.S.
Department of Homeland Security (2015) has a
national strategy for pandemic flu that is designed to
meet three critical goals:

1. Detecting human or animal outbreaks that occur
anywhere in the world

2. Protecting the American people by stockpiling
vaccines and antiviral drugs while improving the
capacity to produce new vaccines

3. Preparing to respond at the federal, state, and
local levels in the event an avian or pandemic
influenza reaches the United States (para. 1)

In New York City, a primary care information project
funded by the CDC developed a multifaceted initiative,
the Center for Excellence in Public Health Informatics,
to address issues of measurement of meaningful use,
disease and outbreak surveillance, and decision
support alerts at the point of care (Buck, Wu,
Souliakis, & Kukalka, 2010; Hripcsak, 2015).

Informatics Tools to Support
Communication and
Dissemination
The revolution in IT has made the capture and analysis
of health data and the distribution of healthcare
information more achievable and less costly. Since the
early 1960s, the CDC has used IT in its practice; PHI
emerged as a specialty in the 1990s. PHI has become
more important with improvements in IT; changes in the
care delivery system; and the challenges related to
emerging infections, resistance to antibiotics, and the
threat of chemical and biologic terrorism. Two-way
communication between public health agencies,
community, and clinical laboratories can identify
clusters of reportable and unusual diseases. In turn,
health departments can consult on case diagnosis and
management, alerts, surveillance summaries, and
clinical and public health recommendations. Ongoing
healthcare provider outreach, education, and 24-hour
access to public health professionals may lead to the
discovery of urgent health threats. The automated
transfer of specified data from a laboratory database to
a public health data repository improves the timeliness
and completeness of reporting notifiable conditions.

Public health information systems represent a
partnership of federal, state, and local public health
professionals. Such systems facilitate the capture of

large amounts of data, rapid exchange of information,
and strengthened links among these three system
levels. Dissemination of prevention guidelines and
communication among public health officials, clinicians,
and patients has emerged as a major benefit of PHI. IT
solutions can be used to provide accurate and timely
information that guides public health actions. In
addition, the Internet has become a universal
communications pathway and allows individuals and
population groups to be more involved and take greater
responsibility for management of their own health
status.

Few public health professionals have received formal
informatics training, and many may not be aware of the
potential impact of IT on their practice. A working group
formed at the University of Washington Center for PHI
has published a draft of PHI competencies needed
(Karras, 2007). These competencies include the
following:

Supporting development of strategic direction for
PHI within the enterprise
Participating in development of knowledge
management tools for the enterprise
Using standards
Ensuring that the knowledge, information, and data
needs of project or program users and stakeholders
are met
Managing information system development,

procurement, and implementation
Managing IT operations related to a project or
program (for public health agencies with internal IT
operations)
Monitoring IT operations managed by external
organizations
Communicating with cross-disciplinary leaders and
team members
Participating in applied public health informatics
research
Developing public health information systems that
are interoperable with other relevant information
systems
Supporting use of informatics to integrate clinical
health, environmental risk, and population health
Implementing solutions that ensure confidentiality,
security, and integrity, while maximizing availability
of information for public health
Conducting education and training in PHI (Center
for Public Health Informatics, 2007)

Using Feedback to Improve
Responses and Promote
Readiness
Improvement of community health status and
population health depends on effective public and
healthcare infrastructures. In addition to information
from public health agencies, there is now interest in the

capture of information from hospitals, pharmacies,
poison control centers, laboratories, and environmental
agencies. Timely collection of such data allows early
detection and analysis, which can increase the rapidity
of response with more effective interventions. Yasnoff
et al. (2000) identified the “grand challenges” still
facing PHI as the development of national public health
information systems, a closer integration of clinical care
with public health, and concerns of confidentiality and
privacy. Since then, great strides have been made
towards a national public health information system,
but we currently are still striving to make this a true
reality. At present, there is a 10-year vision to achieve
an interoperable health IT infrastructure in the United
States (Office of the National Coordinator for Health
Information Technology, 2014).

Population health data must be considered an
important part of the infrastructure of all regional
health information exchanges, which are the building
blocks for a national health information network.
Organizations and agencies interested in promoting
and protecting the public’s health must commit to
collaboration and seamless data sharing (Office of the
National Coordinator for Health Information
Technology, 2014). Public health data include data
related to surveillance, environmental health, and
preparedness systems as well as client information,
such as data from immunization registries and
laboratory results reporting and analysis. These types

of data can provide information about outbreaks,
patterns of drug-resistant organisms, and other trends
that can help improve the accuracy of diagnostic and
treatment decisions and advance public health
research (LaVenture, 2005; National Institutes of
Health, 2016). A regional health information exchange
and national health information network can also
support public health goals through broader
opportunities for participation in surveillance and
prevention activities, improved case management and
care coordination, and increased accuracy and
timeliness of information for disease reporting
(LaVenture).

Much of the information is focused on reaction to
issues and timely intervention, rather than harnessing
information technology for disease prevention. Fuller
(2011) advocated for a shift to prevention informatics
by harnessing real-time social data and aggregating
and representing these data in a meaningful way so
that an appropriate prevention response can be
mounted. For example, Internet searches related to flu
symptoms might prompt a public health prevention
response such as a school closure to minimize spread.
Newer software tools to support mapping and real-time
data visualization include Riff and Ushahidi, each of
which supports “gathering of distributed data from the
web and other data streams” (Fuller, p. 40).
“Prevention informatics offers a useful paradigm for re-
imagining health information systems and for

harnessing the vast array of data, tools, technologies
and systems to respond proactively to health
challenges across the globe” (Fuller, p. 41).

Harnessing data from social media such as Twitter
and Facebook provides yet another example of using
citizen-generated information (crowdsourcing) in
community health. Merchant and colleagues (2011)
described how mining data generated in social media
can improve response to mass disasters by helping
responders locate people who need help and identify
areas where to send resources, build social capital,
and promote community resilience postdisaster.
“Tweets and photographs linked to timelines and
interactive maps can tell a cohesive story about a
recovering community’s capabilities and vulnerabilities
in real time” (Merchant et al., p. 291). These authors
caution, however, that social media should be used to
augment—not replace—current disaster response and
communication systems, as not all communications in
social media are entirely trustworthy. In addition to
utilizing social media posts, Benforado’s (2015)
presentation to the EPA on Citizen Science and
Crowdsourcing asked the question, “If you had 100,000
people to help you with your work, what would you
do?” (slide 2). Enlisting and empowering people can
promote volunteerism and advance science. There is
power in investing in citizen science approaches and
harnessing the efforts of volunteers.

Summary
Public health informatics strives to ensure that evolving
health data systems will meet the data needs of all
organizations interested in population health as
national and international standards are developed for
healthcare data collection. This includes
standardization of environmental, sociocultural,
economic, and other data that are relevant to public
health. Table 17-1 provides the names, addresses, and
URLs for important organizations dedicated to public
health data and informatics. Table 17-2 lists
abbreviations commonly used in PHI.

Table 17-1 Important PHI Sites

Name Address Website

American

Public

Health

Association

APHA, 800 I

Street, NW

Washington,

DC 20001

www.apha.org

Center for

Public

Health

Informatics

CPHI,

University of

Washington,

1100 NE

45th Street,

Ste 405,

Seattle, WA

98105

www.washington.edu/research/centers/256

Centers for

Disease

Control

and

Prevention

CDC, 1600

Clifton

Road,

Atlanta, GA

30333

www.cdc.gov

National

Center for

Public

Health

Informatics

NCPHI,

1600 Clifton

Road, NE

Mailstop E-

78, Atlanta,

GA 30333

https://web.archive.org/web/20110123075557/
http://www.cdc.gov/ncphi

Public

Health

Data

Standards

Consortium

c/o Johns

Hopkins

Bloomberg

School of

Public

Health, 624

N

Broadway,

Room 325,

Baltimore,

MD 21205

www.phdsc.org

Public

Health

Institute

PHI, 555

12th Street,

10th Floor,

Oakland,

CA 94607

www.phi.org

Table 17-2 Abbreviations Used in PHI

BRFSS Behavioral Risk Factor Surveillance System

CDC Centers for Disease Control and Prevention

CEPA California Environmental Protection Agency

CPHI Center for Public Health Informatics

CRA Community Risk Assessment

EPI-X Epidemic Information Exchange

HAN Health Alert Network

IOM Institute of Medicine

IT Information Technology

NCPHI National Center for Public Health Informatics

NEDSS National Electronic Disease Surveillance System

NETSS National Electronic Technology System for Surveillance

NHANES National Health and Nutrition Examination Survey

NHIN National Health Information Network

PH Public Health

PHDSC Public Health Data Standards Consortium

PHI Public Health Informatics

PHIN Public Health Information Network

PHRAP Pennsylvania’s Health Risk Assessment Process

QRPH Quality, Research, Public Health

RHIO Regional Health Information Exchanges

SPRC Suicide Prevention Community Assessment Tool

WONDER Wide-ranging Online Data for Epidemiologic Research

YRBSS Youth Risk Behavior Surveillance System

The future of practice in public health depends on how
efficiently and effectively public health data are
captured, analyzed, and disseminated for regional,
national, and global health planning and management.
In an ideal world, we would see seamless data
collection and sharing with a commitment to prevention
and global health planning.

THOUGHT-PROVOKING QUESTIONS

1. Imagine that you are a public health
informatics specialist and that you and
your colleagues are concerned about a
new strain of influenza. Which public
health data are used to determine the
need for a mass inoculation? Which data
will be collected to determine the success
of such a program?

2. What are the advantages and
disadvantages of using crowdsourced
social media data during a disaster
response?

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CHAPTER 18:
Telenursing and Remote
Access Telehealth

Audrey Kinsella Kathleen Albright Sheldon Prial and
Schuyler F. Hoss Kathleen Mastrian and Dee
McGonigle

Objectives
1. Explore the use of telehealth technology

in nursing practice.
2. Apply the Foundation of Knowledge

model to home telehealth.
3. Identify the socioeconomic factors likely

to increase the use of telehealth
interventions.

4. Describe clinical and nonclinical uses of
telehealth.

5. Specify and describe the most common
telehealth tools used in nursing practice.

6. Explore telehealth pathways and
protocols.

7. Identify legal, ethical, and regulatory
issues of home telehealth practice.

8. Describe the role of the telenurse.

Key Terms
» Call centers

» Central stations

» Chronic disease

» Home health care

» Home telehealth care

» Medication management devices

» Patient informed consent

» Peripheral biometric (medical) devices

» Personal emergency response systems

» Portals

» Real-time telehealth

» Sensor and activity-monitoring
systems

» Store-and-forward telehealth
transmission

» Telehealth

» Telehealth care

» Telemedicine

» Telemonitoring

» Telenursing

» Telepathology

» Telephony

» Teleradiology

» Web servers

Introduction
Telehealth, a relatively new term in the medical and
nursing vocabulary, refers to a wide range of health
services that are delivered by telecommunications-
ready tools, such as the telephone, videophone, and
computer. The most basic of telecommunications
technology, the telephone, has been used by health
professionals for many years, sometimes by nurses to
counsel a patient or by doctors to change a patient’s
plan of care. Because of these widespread uses,
people are already somewhat familiar with the value of

the direct, expedient contact that telecommunications-
ready tools provide for healthcare professionals. A
2013 press release by IMS Research reported that
telehealth monitoring was used for 308,000 patients in
the United States in 2012 and that the demand for
services on a worldwide basis is expected to reach 1.8
million patients by 2017. Dorsey and Topol (2016)
discussed the state of telehealth and shared that there
were over 2 million Department of Veterans Affairs (VA)
telehealth visits in 2014, that Kaiser Permanente of
California predicted that they will have more virtual
visits than face-to-face visits in 2016, and that the
Mayo Clinic expects to serve over 200 million patients
by 2020 using telehealth technologies globally. The
growing field of telehealth is of particular importance to
nursing in that there will be many future opportunities
for nurses to contribute to care delivery via telehealth
services. Let’s examine a potential nursing contribution
using the Foundation of Knowledge Model.

The Foundation of Knowledge
Model and Home Telehealth
There is much to learn about usual home
telehealthcare service delivery, particularly to the
elderly and chronically ill patients. Using the
Foundation of Knowledge model is key to learning how
to use telehealthcare tools with typical patients (elderly
patients, patients needing pointed care) and operate

effectively as telenurses. To understand the mechanics
and effectiveness of home telehealth delivery within the
Foundation of Knowledge model, one must begin with
a typical home telehealth case through which one can
explore the telenurse’s role in this model.

Case Study: The Role of a Home

Telehealth Nurse

Mrs. A. is an 84-year-old woman who was
recently discharged from the hospital with a
diagnosis that includes an exacerbation of
congestive heart failure (CHF). She also has
diabetes and hypertension. Mrs. A. was
discharged from the hospital on multiple
medications and lives alone.

Home care services were initiated with skilled
nursing care visits, some home health aide
support, and orders to include daily
telemonitoring of her vital signs. The telehealth
device will remotely monitor Mrs. A.’s blood
pressure, heart rate, oxygen saturation, and
weight. In addition, the patient will answer
customized questions about her disease on a
daily basis. This information will then be
transmitted daily to the home care agency,
where the telenurse can determine appropriate
clinical actions based on the data trends and

preset baseline alerts that indicate when set
parameters have been exceeded.

Knowledge Acquisition
As the case study illustrates, knowledge acquisition
involves the telenurse receiving the information from
the telehealth devices via a variety of communication
modes. For example, the telenurse receives the
patient’s vital signs taken in the home and the patient’s
responses to customized questions. All of this
information is transmitted to a remote server or site (a
central station or website) that is easily accessible to
the telenurse.

Knowledge Processing
As a result of the telenurse’s knowledge acquisition,
the next step to be followed is knowledge processing
(i.e., understanding a set of information and the ways it
can be applied to a specific task). In the case study, the
telenurse assesses the patient’s vital signs along with
subjective data received from the patient as a result of
the customized questions that Mrs. A. is asked. For
example, she might be asked if she feels more short of
breath on a given day as compared to normal. The
telenurse then combines this information with the
overall patient history and diagnosis to get an up-to-
date view of the patient’s status and considers where

this information fits into the clinical picture being
presented for this patient.

As an example, the telenurse notes the following:
Postacute heart failure patient shows trended data with
weight gain of 5 lb over 2 days, elevated blood
pressure, and decreased oxygen saturation, and
answers yes to questions about increased shortness of
breath and increased fatigue. After processing all of the
current information, the telenurse is able to target the
appropriate next steps involving knowledge generation
and knowledge dissemination.

Knowledge Generation
By using her own nursing skills and clinical knowledge
of the disease process, the telenurse considers all of
the data as they apply to Mrs. A. and decides the best
course of action to take and acts on the data. The
telenurse may, in addition, ask a variety of questions to
ensure that a complete and accurate decision about
next steps for the patient is made. These questions
might include the following:

Do I need to gather additional data?
Do I need to call the patient?
Do I need to call the physician and inquire about a
change in the current plan of care?

Knowledge Dissemination
Finally, the telenurse determines how the knowledge
will be used and disseminated. Various questions that
were posed in the knowledge generation stage are
acted on, including the following possibilities:

Calling the doctor
Obtaining a change in medication order
Calling the patient and instructing her in a
medication change
Reviewing activities that could have led to the
changes (e.g., eating salty foods)
Educating the patient on the disease process,
symptom management, and self-management
techniques
Continuing to monitor the patient on an ongoing
basis

As the case illustrates, the nurse used various
technologies to acquire data; interpreted the meaning
of the data, thus generating information and
knowledge; and then used that knowledge and wisdom
to intervene appropriately.

Nursing Aspects of Telehealth
Understanding telehealth and the potential use of
telehealth technology in nursing practice is necessary
in today’s changing healthcare arena. As this chapter

describes, nurses using telehealth have much greater
access to their patients’ conditions and needs and are
able to respond in a more timely way than is possible
using only face-to-face visits. Patients’ responses to
new medications, for example, can be tracked within
hours rather than the several days that elapse between
face-to-face visits. The telecommunications-ready tools
that can be used to achieve these results are described
here, and cases that have demonstrated successful
outcomes are highlighted.

Telehealth is still a new and evolving technology; while
the offsite interventions or contacts often lead to less
time being wasted on non-care-oriented tasks because
of the efficiencies offered by the technology
applications, its use must never be associated with less
care. It is also important to note that nursing activity in
telehealth still follows the same best practice standards
as those espoused in conventional care. One should
simply look at the use of telehealth tools as a means
for nurses to do their work better.

As the case study demonstrated, a home healthcare
nurse working with telehealth tools was able to detect
and respond to a patient’s condition more expediently
than if the nurse relied solely on scheduled home visits,
and thus was able to intervene to prevent a potentially
serious deterioration in the patient’s condition.

History of Telehealth
In the early 1960s, President John F. Kennedy gave
the National Aeronautics and Space Administration
(NASA) the goal of landing an American on the moon.
A surprise benefit of the space program was the
demonstration of effective remote monitoring of the
astronauts—and thus modern telehealth was born.

Although most of the advances in telehealth have
taken place in the last 20 to 30 years, Craig and
Patterson (2005) described much earlier examples,
such as the use of bonfires to alert neighboring villages
of the arrival of bubonic plague during the Middle Ages.
Postal services and telegraphs were used to transmit
health information in the mid-19th century, and 1910
marked the first transmission of stethoscope sounds
over a telephone. Radio communications were used to
provide medical support for crews on ships; the
Seaman’s Church Institute of New York (1920) and the
International Radio Medical Center (1938) are two
examples of organizations founded to provide health
support at a distance. These services were later
expanded to cover air travel (Craig & Patterson,
2005). The National Institutes of Mental Health
supported a program in the mid-1950s that connected
seven state hospitals in four different states via a
closed-circuit telephone system (Venable, 2005). As
technology evolved, its use in health care continued to
grow. The first reported use of television to monitor

patients in a clinical facility occurred in the 1950s,
which then led to the development of interactive
closed-circuit applications in the mid-1960s. These
early applications of television to health care occurred
within the facility but still had the benefit of extending
the reach of the caregivers because they did not need
to be in the same room to monitor their patients
effectively (Prial & Hoss, 2009).

In the 1970s, uses of more advanced forms of
telehealth in the medical field, referred to as
telemedicine, included teleradiology and
telepathology—radiologic and pathologic images
transmitted to specialists who were located at some
distance (Allan, 2006). As additional specialties, such
as dermatology and ophthalmology, entered the
telemedicine arena, telehealth use enabled even more
physicians to access information about their patients,
regardless of the distances between themselves and
the patients, and in sites other than conventional
healthcare settings.

Success in telehealth was achieved after decades
spent refining the technology, which resulted in clearer
imaging, more speedy transmissions, and accurate
replication of data from remote locations to a central
hub. The end results of telehealth interactions today
have helped to ensure that professionals, whether
working off site or directly with patients, can replicate

the usual clinical interactions in all specialties
regardless of the distance involved in the contact.

The ability to provide better healthcare access is the
number one benefit of using telehealth. By reducing the
need for face-to-face interaction with the patient, the
nurse, physician, or even technician can be much more
productive. When information is collected in the home,
it becomes much more convenient for the patient, and
the quality and timeliness of the information is
improved dramatically. Home telemonitoring should
be viewed as an enhancement to care, because it
allows more direct, physical intervention to occur only
when it is actually needed. Care is not directed by
prescheduled appointment or subjective perceptions of
condition, but instead can be determined by objective
measures of physical status. With telehealth, care can
also be delivered at the most appropriate site of care,
reducing reliance on emergency departments and
inpatient facilities (Prial & Hoss, 2009).

Driving Forces for Telehealth
A significant increase is expected in the use of
information technology tools in nursing venues in the
coming decades. This use is affected by a number of
factors in all of Western society. The following factors
are drivers of the growing trend toward telehealth and
technology use and will influence nursing practice
significantly in the next decades: demographics;

nursing and healthcare worker shortages; chronic
diseases and conditions; the new, educated
consumers; and excessive costs of healthcare services
that are increasing in need and kind.

Demographics
One hears it every day: The baby boomers are getting
older and people are living longer. In 2000, 13% of the
American population was older than age 65, and the
number of older adults is growing significantly.
According to the U.S. Bureau of the Census (U.S.
Department of Commerce, Bureau of the Census,
2006), 7,918 Americans turn 60 years old every day.
Consequently, by 2030, 19% of the U.S. population will
be 65 years old or older and the oldest-old (85 years or
older) will increase by 3 million persons between 2010
(5.8 million) and 2030 (8.7 million; U.S. Department of
Commerce, Bureau of the Census, 2010). Also on
the rise is the number of older Americans living with at
least one chronic disease or condition; they account for
4 out of every 5 people older than age 50 (American
Association for Retired Persons [AARP], 2009).
This trend should alert clinicians to the much greater
demand for planned professional care that will arise in
the coming years.

Case Study: Early Detection of a Change

in Condition

Mrs. C., an independent, 96-year-old woman,
has a history of rehospitalization because of
atrial fibrillation resulting from CHF and
hypertension.

After her most recent hospitalization, Mrs. C.
was treated and released into home care at an
agency in Washington. A home telemonitoring
system that tracks and transmits patients’ vital
signs was placed in her home. The primary goal
of placing this patient on the telemonitor was to
provide daily monitoring of her condition,
thereby avoiding unnecessary
rehospitalizations.

One morning, Mrs. C.’s telenurse detected an
alarmingly low oxygen saturation level in the
patient’s transmitted data. In response, the
nurse telephoned Mrs. C. and asked her to
retake her oxygen reading. The reading was
confirmed and the telenurse contacted the
patient’s physician, who requested immediate
transportation of the patient to the hospital
emergency room. Medics were called and Mrs.
C. was taken to the hospital, where she was
diagnosed with a pulmonary embolism.

The prompt response resulted from early
detection and timely intervention enabled by the
home telehealth equipment and a home health
nurse’s oversight. One notable fact in this case

is that although the primary goal of monitoring
patients is to avoid unnecessary hospitalization,
in this case the hospitalization was necessary
for the patient as a result of her elevated blood
pressure and compromised oxygen saturation
levels. The patient was still asymptomatic at the
time of detection. However, the telehealth
intervention and subsequent hospitalization
allowed for the embolism to be treated before
any serious damage occurred.

Under the traditional home care model, this
patient might have been seen by a nurse only
two to three times per week, and the clinician
does not have knowledge of the patient’s
condition in between visits. However, having
vital patient data tracked and transmitted daily
allowed for rapid response that resulted in a
positive outcome, perhaps a life-saving
intervention for this patient.

Nursing and Healthcare Worker
Shortages
The crisis related to the well-known nursing shortage
has two key aspects: a greater need for nurses by
more persons, particularly those living with sometimes
multiple comorbidities, and a significant decrease in the
number of young people entering the nursing

profession. Nationwide, the demand for nurses is
clearly exceeding the supply. A report by Buerhaus,
Auerbach, and Staiger (2009) stated that the
recession of the past few years may have helped to
ease the RN shortage in the short term, but suggested
that the aging of the RN workforce and the aging of the
population will likely combine to produce a shortfall of
nurses beginning in 2018, with the deficit reaching
nearly 260,000 by 2025.

The very serious shortage of healthcare workers in the
United States must be addressed with some foresight.
Although there is currently more focus on training
laypeople, such as aides and other paraprofessionals,
to perform certain nursing tasks, this venture certainly
cannot replicate the clinical expertise of trained nurses
skilled in nursing science. We must begin to look
seriously at using effective adjuncts to skilled care, with
telehealth being one of these important developments.
Some organizations have already begun to do so. For
example, a study by the Pennsylvania Homecare
Association and Penn State University (2004)
looked at how telehealth can be used to address
workforce issues in the home healthcare industry and
determined that telehealth use may enhance nurses’
job satisfaction and help to retain nurses in their
current positions.

Chronic Diseases and Conditions

Chronic conditions are the leading cause of illness,
disability, and death in the United States today. The
number of elderly persons living with chronic disease is
estimated at 140 million in the United States and
accounts for more than 80% of healthcare
expenditures (Dorsey & Topol, 2016). Both chronic
conditions and the number of persons with chronic
illnesses are expected to increase dramatically in the
United States in the next few decades. Many age
groups are also affected by chronic disease, not just
the elderly. As noted in a report from the Centers for
Disease Control and Prevention (CDC; 2005), by the
year 2030, 148 million Americans will have a chronic
illness, with at least one third of them being limited in
their ability to go to school or to live independently. You
can follow the CDC’s chronic disease surveillance
activities at this website:
www.cdc.gov/chronicdisease/stats/index.htm.
Securing appropriate, adequate, and affordable care
services for these populations should be a national
concern.

Educated Consumers
The wave of today’s aging baby boomers is steering
some of the usual health service practices toward a
very different course. Many of these individuals are
more educated than their parents and more
comfortable with the use of technology. They want to
become more informed and involved with their care

plans. These empowered consumers will be financially
motivated with the introduction of consumer-directed
healthcare plans that reward healthier lifestyles and
better disease management of chronic conditions. All
of these circumstances will further drive the use and
the innovation of new technologies to meet consumer
need. New plans for this new generation of consumers
very much lean toward meeting their demands for
when-needed, as-needed care, or care services
delivered on their own terms and timing.

Economics
When one connects the drivers of today’s healthcare
market—the demographics, nursing shortages, and
increased number of persons living with chronic
conditions and their extensive use of healthcare
services—with excessive costs of this health care, the
critical need for solutions becomes obvious. The U.S.
healthcare system spends $1.4 trillion per year on
conventional medical care. Much more will be spent
annually in the coming decades. One must ask: Taking
all of the driving factors of today’s healthcare market
into account, what needs to be done to address
healthcare issues in the United States and meet the
burgeoning numbers and needs of patients?

One solution is to develop a new clinical model for
American health care that includes technology. In
particular, telehealth technology should be included to

fill the gap resulting from an overabundance of patients
and a scarcity of healthcare providers. This concept is
indicated in Figure 18-1.

Figure 18-1 Technology Fills the Gap

Data from Honeywell

Consider the use of technology that might potentially fill
the current gaps in the healthcare system. Tools of
telehealth can, for example, help render needed
services without requiring in-person professional care
at all contacts. The remote or virtual visit made by
skilled clinicians is just one approach to using the
range of health technologies available today. More
needs to be learned about what telehealth is, how it
works, and which aspects have been successful so

that clinicians can plan to incorporate its use into
routine clinical care.

Telehealth Care
Let us start with a basic definition of telehealth care.
Keep in mind, however, that telehealth is an emerging
field, and definitions are subject to change and
improvement as technology evolves. The American
Telemedicine Association (ATA; 2010) provided the
following definition:

Telemedicine is the use of medical
information exchanged from one site to
another via electronic communications to
improve patients’ health status. Closely
associated with telemedicine is the term
“telehealth,” which is often used to
encompass a broader definition of remote
health care that does not always involve
clinical services. Videoconferencing,
transmission of still images, e-health
including patient portals, remote
monitoring of vital signs, continuing
medical education and nursing call
centers are all considered part of
telemedicine and telehealth. (para. 1)

The Health Resources Services Administration
(n.d.) offers this description of telehealth:

Telehealth is the use of technology to
deliver health care, health information or
health education at a distance. Common
applications include: teleradiology, in
which test results are forwarded to
another facility for diagnosis; continuing
professional education, including
presentations by specialists to general
practitioners; and home monitoring, a
supplement to home visits from nursing
professionals. The boundaries of
telehealth, though, are limited only by the
technology available—new applications
are being invented and tested every day.
(para. 1)

Indeed, “telehealth” is generally used as an umbrella
term to describe all of the possible variations of
healthcare services that use telecommunications.
Telehealth can refer to clinical and nonclinical uses of
health-related contacts. Delivery of patient education,
such as menu planning for patients with diabetes or the
transmission of medication reminders, is an example of
the health-promoting aspects of telehealth.

Clinical Uses of Telehealth

A few clinical uses for telehealth technologies and
some sample clinical applications include the following:

Transmitting images for assessment or diagnosis.
One example is transmission of digital images, such
as images of wounds for assessment and treatment
consults.
Transmitting clinical data for assessment,
diagnosis, or disease management. One example is
remote patient monitoring and transmitting patients’
objective or subjective clinical data, such as
monitoring of vital signs and answers to disease
management questions.
Providing disease prevention and promotion of
good health. Examples include case management
provided via telephone or smartphone app and
patient education provided through asthma and
weight management programs conducted in
schools.
Using telephonic or video interactive technologies
to provide health advice in emergent cases. One
example is performing teletriage in call centers or
real-time stroke consultation between a rural health
center and an academic medical center.
Using real-time video. One example is exchanging
health services or education live via
videoconference.

Telehealth Transmission Formats and

Their Clinical Applications
Nurses must become familiar with the many and varied
clinical and nonclinical transmission formats and
applications of telehealth technologies so that they can
make informed choices about the tools that are
available for their use, as needed. Among these
applications are store-and-forward telehealth, real-time
telehealth, remote monitoring, telephony, and mHealth.
The Center for Connected Health Policy has provided
some video overviews of the telehealth transmissions
and clinical applications (www.cchpca.org/videos).

Store-and-Forward Telehealth

In a store-and-forward telehealth transmission,
digital images, video, audio, and clinical data are
captured and stored on the client computer or device;
then, at a convenient time, the data are transmitted
securely (forwarded) to a specialist or clinician at
another location, where they are studied by the
relevant specialist or clinician. If indicated, the opinion
of the specialist or clinician is then transmitted back.
Based on the requirements of the participating
healthcare entities, this round-trip interaction could take
anywhere from a few minutes to 48 hours. In many
store-and-forward specialties, such as teleradiology, an
immediate response is not critical. Dermatology,
radiology, and pathology are common specialties
whose practices are conducive to store-and-forward

technologies. Transmission of wound care images for
assessment by specialty care nurses or other
specialists has become a frequently used and
important form of home telehealth nursing practice.

Real-Time (or Interactive) Telehealth

In real-time telehealth, a telecommunications link
between the involved parties allows a real-time or live
interaction to take place. Videoconferencing equipment
is one of the most common forms of technologies used
in synchronous telehealth. In addition, peripheral
devices can be attached to computers or to the
videoconferencing equipment to facilitate an interactive
examination. Use of computers for real-time two-way
audio and video streaming between centers over ever-
improving and cheaper communication channels is
becoming common. These developments have
contributed to lowering of costs in telehealth. See
Figure 18-2 for a depiction of this interaction.

Figure 18-2 Example of a Physician-to-Physician
Consult Using Telehealth

Reproduced from Ohio Supercomputer Center. (2008). Governor

Strickland, international panel of experts consider establishing Telehealth

Video Resource Center. Retrieved from

https://www.osc.edu/press/governor_strickland_international_panel_of_experts_consider_establishing_telehealth_video

Examples of real-time clinical telehealth applications
include the following:

Telemental health, which uses videoconferencing
technology to connect a psychiatric nurse with a
mental health client.

Telerehabilitation, which uses videocameras and
other technologies to assess patients’ progress in
home rehabilitation.
Telehome care, which uses video technologies to
observe, assess, and teach patients living in rural
areas.
Teleconsultations, which use a variety of
technologies to enable collaborative exchanges or
consultations between individuals or among groups
that are involved with a case. These teleconsults
may be transmitted live using videoconferencing
technology. They may, for instance, involve
teaching a certain technique to a less-experienced
clinician, or they may provide several clinicians with
an opportunity to discuss an appropriate approach
to a difficult case.
Telehospice or telepalliative care, which can use
real-time or remote monitoring to provide
psychological support to patients and caregivers.
Telehealth devices can also play a role in symptom
management, in effect helping end-of-life patients
achieve an optimal quality of life.

Remote Monitoring (Telemonitoring or Remote
Patient Monitoring)

In remote monitoring, devices are used to capture and
transmit biometric data. For example, a tele-
electroencephalogram device can monitor the electrical
activity of a patient’s brain and then transmit those data

to a specialist assigned to the case. This interaction
could occur either in real time or as a stored and then
forwarded transmission. Examples of telemonitoring
include the following:

Monitoring patient parameters during home-based
nocturnal dialysis
Cardiac and multiparameter monitoring of remote
intensive care units (ICUs)
Home telehealth—for example, daily home
telemonitoring of vital signs by patients and
subsequent transmission of those data that enables
offsite nurses to track their patients regularly and
precisely and address noticeable changes through
education and information suggestions about diet or
exercise
Disease management

Telephony

Telephone monitoring (telephony) is the most basic
type of telehealth. It can be described as remote care
delivery or monitoring in which scheduled patient
encounters via the telephone occur between a
healthcare provider and a patient or caregiver (Quality
Insights of Pennsylvania, 2005). More details about
interaction using telephony are discussed later in this
chapter.

mHealth

The use of mobile phones, tablets, and PDAs for
managing health is a rapidly advancing form of
telehealth. There are numerous applications (apps)
that target specific health behaviors and illnesses and
provide a platform for management at a distance. One
such management technique is a targeted text
message to remind patients to perform a certain
behavior, such as monitoring their peak flow to manage
asthma or to take medications. Other apps are more
specific to public health or provider education.
Weinstein and colleagues (2014) explained,

Current uses of apps on mobile devices
include the direct provision of care, real-
time monitoring of patient vital signs,
delivery of patient information to
practitioners and (where appropriate)
clinical researchers, and collection of
community healthcare data. Specialized
sensors and devices that work as
accessories to multiple health apps are
also seeing tremendous growth and
innovation. (p. 185)

Nonclinical Uses of Telehealth
Technologies
There are also many nonclinical uses of telehealth
technologies. Currently, these include distance

education including continuing medical and nursing
education, grand rounds, and patient education;
administrative uses including meetings among
telehealth networks, supervision, and presentations;
and research using the Internet and other online
sources for information and health data management.

All of these telecommunications-assisted activities
overcome obstacles of distance and provide access to
needed health-related information. Clearly, with
telehealth, the range of patient care possibilities
broadens significantly.

Telenursing
Where do nurses using telehealth, as in telenursing, fit
into today’s healthcare delivery arena? As early as
1998, Skiba referred to telenursing as the use of
telecommunications and information technology to
provide nursing services in health care and enhance
care whenever a physical distance exists between
patient and nurse or among any number of nurses. As
a clinical field, telenursing is part of telehealth and has
many points of contact with other medical and
nonmedical applications, such as telediagnosis,
teleconsultation, and telemonitoring. In their study, St
George et al. (2009) concluded, “In terms of the kinds
of calls received, the dispositions reached after triage
and clinical safety, we could detect no differences
between nurses working from home and those working

in the call centre” (p. 123). Telenurses serve as an
integral part of the healthcare delivery team, no matter
their location.

Applications of Telenursing in Home
Care
An early and still-accepted definition of home
telehealth care was provided by Kinsella (2004):
“Home telehealth care is clinician-driven remote care
delivery and education services that are delivered to
the home via telecommunications-ready tools” (p. 36).

As home telehealth care has evolved, this definition
has expanded to include a broader arena of delivery. In
fact, some have defined the “home” as anywhere
outside of an acute inpatient setting—a definition that
includes nursing homes, assisted living facilities, and
other living situations beyond the single-family home or
apartment. Wherever the home setting may be, people
want to be cared for there. Today’s burgeoning senior
population, in particular, has become quite vocal about
this preference, and estimates for preferences of aging
in place at home are around 87% (AARP, 2014).
Fortuitously, the reach of nurses using
telecommunications-ready tools in the home is now
remarkably extended. Not only have the settings for
home care expanded beyond what was usual (the
family home) in the last four decades of home health’s

formal existence, but the types of services delivered to
the home have also become more advanced. The
home care industry’s newest challenge is to work with
sicker patients, many of whom have been discharged
from hospitals to home earlier than in the past.

This challenge to extend the range of conventional
home care is why telehealth can be and needs to be
provided to a wide range of patients, including those
who have the following characteristics:

Are immobilized
Live in remote or difficult-to-reach places
Have chronic ailments, such as chronic obstructive
pulmonary disease (COPD), diabetes, and
congestive heart disease
Have debilitating diseases, such as neural
degenerative diseases (Parkinson disease,
Alzheimer disease, amyotrophic lateral sclerosis)

All of these patients may stay at home and be visited
and assisted regularly by a nurse via
videoconferencing, Internet, videophone, or other
telecommunications means. These
telecommunications-ready tools enable home
telenurses to follow through advanced levels of care,
as needed.

Still other varied applications of home telehealth care
involve the care of patients in immediate postsurgical

situations, those needing care of wounds and
ostomies, and handicapped individuals needing
physical therapy interventions or telerehabilitation. In
addition to this extended range of patients who can be
served with telehealth, many more patients can be
seen when telehealth is used. For example, in
conventional home health care, depending on the
distances of travel involved, one nurse may be able to
visit as many as 7 patients per day. Using telenursing,
however, one nurse can remotely visit or televisit 12–
16 patients in the same amount of time using
interactive telehealth. Over the last decade, the
efficiencies of telenursing have been well documented,
as have the resulting improved patient care outcomes
that can be expected by frequent telecontact.

Another outpatient application of telenursing is
telephony-based call centers, which may be operated
by managed care organizations, hospitals, and other
health organizations. Some call centers also include
telemonitoring services, which allow the patient to stay
at home and use different telehealthcare devices to
transmit biometric and other medical information back
to the call center. Monitoring can be intermittent or
continuous. This use of the teletechnology allows
clinicians to evaluate patients’ status and use the data
to make decisions to better manage patients’ health
conditions.

Many features of call centers’ services are comparable

to conventional hands-on care in the home. For
instance, call centers are typically staffed by RNs who
act as case managers or perform patient triage. These
professionals can provide information and counseling
to patients as part of a disease management program
and as a means to educate them on their disease
process. In effect, their goal is to offer appropriate
access to care (from nurses at the call centers) and
help patients to prevent avoidable emergency room
visits and rehospitalizations. An example of this
assistance includes a nurse calling (i.e., not waiting for
a patient to contact the call center) a recently
discharged patient with diabetes on a regularly
scheduled basis to evaluate progress at home, activity
tolerance, medication compliance, foot care, and diet
management. This empowering of patients toward self-
management is a very significant and needed part of
telenursing.

Home care telenursing can also involve other activities,
such as providing customized patient education in
dietary or exercise needs, nursing teleconsultations,
review of results of medical tests and examinations,
and assistance to physicians in the implementation of
medical treatment protocols. The work can be wide
ranging; for example, some home-based telecardiology
programs involve the patient, the family, the physician,
and a specialized cardiac monitoring center. A
multidisciplinary approach is used along with best
practice–defined protocols to manage the patient,

improve the patient’s quality of life, and reduce
healthcare costs, especially hospitalization costs.
Nurses play a key role in this network of care.

A relatively new role for advanced practice nurses is
that of a tele–intensive care nurse. These nurses
provide remote monitoring, oversight, and expert
consultation for patients in rural ICUs by examining
real-time data collected at the bedside. They look for
trends indicating that an intervention is needed and
then alert the bedside nurse of the need, thereby
providing an extra set of eyes and an advanced level of
expertise. “Tele-ICU provides expert-driven, evidence-
based, cutting-edge services to the monitoring and
treatment of critically ill patients” (Williams, Hubbard,
Daye, & Barden, 2012, p. 62). Goran (2011) studied
tele-ICU nursing competencies and emphasized that
effective listening and collaboration skills and the ability
to prioritize patient needs are among the most
important attributes of tele-ICU nurses. She also
cautions that nurses who function in these collaborative
roles need to continue to practice at the bedside to
keep their clinical skills sharp. In 2014, the ATA
released a clinical care guideline for TeleICU. In this
guideline, they identified three practice models:

Continuous Care Model: Continuous care is
monitoring of the patient without interruption for a
defined period of time (e.g., on an 8-, 12-, or 24-
hour basis).

Scheduled Care Model: Scheduled care occurs with
a periodic consultation on a predetermined
schedule (e.g,. during patient rounds).
Responsive (Reactive) Care Model: In this model,
virtual visits are prompted by an alert (e.g.,
telephone call, page, monitor alarm) and are
unscheduled (p. 6).

Access these guidelines, as well as other telehealth
guidelines, at
www.americantelemed.org/resources/telemedicine-
practice-guidelines/telemedicine-practice-
guidelines#.V5815vnyCM9. In addition, the American
Association of Critical-Care Nurses (AACN, 2013) has
developed the TeleICU Model of Success published in
the TeleICU Nursing Practice Guidelines. This model
emphasizes that the patient is central to all of the
interactions between providers, and is dependent upon
communication and collaboration among providers to
promote positive patient outcomes.

By reviewing all of these examples of telenursing
practice, one can see that nurses using telenursing can
broaden their involvement in the targeted care of their
patients. Some sources have predicted that home care
will soon become the hub of all patient activity: The
home will be where care that is begun in hospitals and
other settings will be managed over the very long term
and in the most cost-effective healthcare setting. Home
care telenurses can expect to play a vital and dynamic

role in the changing delivery systems that are likely to
be put in place in the coming decades.

Telehealth Patient
Populations*
Any patient who has a condition that must be
monitored is a candidate for home telemonitoring.
Patients with chronic illnesses have particularly
benefited from ongoing monitoring to prevent acute
episodes. Patients who are homebound or who have
limited access to transportation are also appropriate
candidates for such monitoring.

Patients with Chronic Diseases
Given demographics and advances in medical practice,
there has been unprecedented growth in the number of
patients with chronic diseases. Those patients are at
significant risk of having an acute episode when subtle
but significant changes in their medical condition occur.
The ability to identify these changes in a timely fashion
allows for changes in medication, lifestyle, or treatment
to occur. Identification of a 3-lb weight gain over 5 days
in a patient with CHF, for example, allows for
interventions that could prevent an emergency room
visit and subsequent hospitalization. The categories of
patients with chronic diseases who are most commonly

monitored today include those with CHF, COPD, or
diabetes, and those who require long-term wound care.

These patients, particularly those with higher acuity
levels, are at significant risk of having a medical crisis
that might necessitate emergency or unplanned acute
interventions. Many other patients with chronic
diseases are less susceptible to a health crisis, but
would greatly benefit from home telemonitoring to
improve care and reduce costs.

At-Risk Populations
Telemonitoring can be used effectively on patients who
are at greater risk for an episode of acute illness.
Patients who have a predisposition to disease are at
increased risk of medical problems associated with
employment, lifestyle, or location, and those patients
who have displayed early signs of potentially serious
health problems could be placed on preventive
monitoring. In such cases, monitoring is used to ensure
that interventions are timely and acute incidents
avoided. Such technology could be part of a healthcare
early warning system and could support preventive
models of care.

Isolated Patients
Home telemonitoring is effective for patients who
cannot physically access healthcare services. The

homebound elderly have been among the first to
benefit from this technology in conjunction with the
home health services they receive. With increasing
limits affecting the ability of patients to receive services
in the home because of staffing shortages and
coverage limitations, telemonitoring technology takes
on greater importance in managing homebound
patients.

Patients in remote geographic areas have been long-
time users of telemedicine interventions, such as
robodocs. According to Strauss (2010), “The Remote
Presence Robot (RP-7) from InTouch Health is a
mobile telemedicine unit that connects physicians and
specialists with patients and other doctors who are too
distant to consult with them in person” (para. 2). With
few rural healthcare facilities being built and access
problems becoming more difficult, the use of
technology in the home will increase. Even in suburban
and rural areas, access is becoming more problematic,
requiring greater use of home telemonitoring
interventions. A lack of primary care and emergency
resources in many urban core areas has prompted
many health systems to consider managing certain
patients through telemonitoring options and better
staging of patient access. Telemedicine also is effective
for patients in such institutions as prisons, for whom it
is logistically difficult to travel to traditional care sites.

Incarcerated Patients
Telehealth services are used extensively in seven
states to provide mandated medical services for prison
populations. These correctional telemedicine programs
are cost effective and promote public safety by not
having to transport prisoners to healthcare facilities for
care (Weinstein et al., 2014).

Hospitalized Patients
Home telemonitoring has proved effective in managing
the flow of patients into and out of hospitals and other
inpatient facilities. Patients are monitored to determine
when they are admitted, to predict how long they might
stay, and to prevent unfunded readmissions. Patients
undergoing semielective procedures can be better
staged with scheduling options when they are
monitored in the home before admission. If
deterioration of the patient’s condition is observed, a
procedure can be accelerated or planned interventions
changed.

Monitoring can also be used effectively in length-of-
stay reduction strategies. Physicians and surgeons are
more confident in discharging patients early when they
know that vital signs will be monitored and any decline
in condition noted in a timely fashion. Use of monitoring
effectively allows for an extension of step-down models
of care into the patient’s home. These length-of-stay

management strategies have been particularly useful
when hospital beds are in short supply.

Unplanned readmissions are a serious patient care and
financial management issue for hospitals. The use of
monitoring in the home has consistently reduced
unplanned and unfunded readmissions by enabling
healthcare providers to obtain reliable information on
the patient and intervene appropriately to keep the
patient at home.

Emergency Response Situations
Telemedicine will likely be a major component of
effective patient management in a major disaster,
large-scale nuclear or biochemical attack, or outbreak
of highly infectious disease. In such a situation,
traditional healthcare delivery systems may become
overwhelmed, and patients will need to be more
effectively triaged and managed by remote providers.
Telemedicine applications allow for a dramatic
extension of patient management and triaging options
and allow offsite providers to be involved in care. If an
infectious or communicable disease is involved, patient
isolation could be accomplished in the home using
telemedicine technology.

Concerned Patients and Families

Perhaps the largest potential market for home
telemonitoring is patients and families who want to
have reliable and objective information that allows for
their involvement in healthcare decision making. At one
extreme is a young person who wants to monitor
physiologic data as part of a personal wellness or
fitness program. At the other extreme are families that
want information on the status of a terminally ill loved
one in another city. In between there is a wide range of
opportunities for individuals and families to obtain
information that promotes realistic and meaningful
dialogue with healthcare professionals.

Assisted Living and Subacute Patients
In assisted living facilities or subacute care centers, a
kiosk can be used to obtain vital signs for large groups
of people. Vital signs reports can then be forwarded on
a regularly established schedule to physicians and
others involved in the patient’s care. This approach
allows for better individual care management and lends
itself to developing intervention strategies and
education options to benefit the entire population of a
facility. Some facilities have even used access to
telemonitoring systems as an inducement to attract
potential residents.

Employers and Wellness Programs

Health care is a vital concern for employers. They have
a direct financial interest in lowering costs and are
financial beneficiaries of long-term-illness preventive
strategies. If they can monitor their workers (e.g.,
offering telehealth options as a wellness program), they
will see many benefits for themselves, such as reduced
absenteeism and increased productivity. Effective
monitoring programs can ultimately lower healthcare
costs and associated insurance premiums. Some
companies are now exploring the creation of financial
incentives for employees who achieve healthcare
objectives, such as appropriate weight, reduced blood
pressure, and levels of exercise. Monitoring could very
well be used as a means of tracking performance in
this regard.

Tools of Home Telehealth
A wide and growing range of telecommunications-
ready tools are available for nurses’ and patients’ use
in the home. See Figure 18-3 for a depiction of how
these tools are combined to provide home telehealth
monitoring.

Figure 18-3 Tools for Home Telehealth Monitoring

Reproduced from Seeberg, T. M., Vedum, J., Sandsund, M., Austad, H.

O., Liverud, A. E., Vardøy, A. S. B., . . . Strisland, F. (2014). Development

of a wearable multisensor device enabling continuous monitoring of vital

signs and activity. Presented at IEEE-EMBS International Conference on

Biomedical and Health Informatics (BHI), Valencia, pp. 213–218. doi:

10.1109/BHI.2014.6864342

Central Stations, Web Servers, and
Portals
Central stations, Web servers, and portals are
various terms for the technologies presently used as
part of multifunctional telehealthcare platforms and
application servers. These clinical management
software programs receive and display patients’ vital
signs and other information transmitted from a medical
device, including blood pressure, weight, and glucose

information. Such transmission was initially most
commonly accomplished over plain old telephone
system lines (POTS); however, network access and
wireless communication are more commonly used as
technology advances and access improves.

Central stations and Web servers are key components
of telehealth that can be as minimal as a single screen
display or as comprehensive as software applications
that provide various functions including triaging the
data based on medical alerts, which allows clinicians to
quickly identify those patients requiring immediate
attention. Other features found in these packages allow
clinicians to build personal medical records for patients
and provide trended patient data and analysis reports
supporting improved patient outcomes using telehealth.
In addition, some of the software packages provide
remote programming capabilities that allow the clinician
to remotely program the medical device in the patient’s
home. Such an application can change monitoring
report times for patients, individualize alert parameters,
set up reminders, and send educational content to a
patient.

Peripheral Biometric (Medical) Devices
Peripheral biometric (medical) devices can consist
of fully integrated systems, such as a vital signs
monitor, or they may be stand-alone
telecommunications-ready devices, such as blood

pressure cuffs and blood glucose meters. These
devices plug directly into the household telephone jack
to send data to a central server location or use
Bluetooth technology to transmit data.

An ever-increasing number of peripheral devices are
being introduced to the market. Examples of other
peripheral devices seen in home telehealth today
include pulse oximeters; prothrombin time,
International Normalized Ratio meters; spirometers;
peak flow meters; electrocardiogram monitors; and
card readers and writers that use smart card
technology and enable multiple users to use one
device.

Telephones
Telephones are already the most familiar household
communications tool used in telehealth care. A
telephone device can be augmented for easier use by
patients, as needed, with a lighted dial pad, an auto-
dial system, or a louder ringer. Telephone systems are
still and will continue to be important when there is no
Internet access in the home.

Videocameras and Videophones
Videocameras and videophones are readily available
consumer items that can be used in telehealth for
show-and-tell demonstrations by nurses for patients or

to capture wound healing progress, among other
applications. Typically, these products operate as a
standard telephone or as a video picture telephone,
using standard telephone lines to transmit information
or interactions.

Currently, the image quality over a POTS is limited by
the bandwidth of POTS technology, which favors use of
such images for assessment rather than delivering
diagnostic-quality images. These imaging capabilities
will improve as integrated services digital network lines
become more widely available in the home
environment. Typically, medical centers and hospitals
have access to larger bandwidth capabilities for image
transmission and viewing, thus ensuring high-quality
diagnostic images and point-to-point consultations in
hospital- or medical center-based settings.

Personal Emergency Response
Systems
Personal emergency response systems are
signaling devices worn as a pendant or otherwise
made easily accessible to patients to ensure their
safety and to enable them to quickly access
emergency care when needed, usually in case of a fall.
A preset telephone number is alerted by the patient’s
pushing a button on the pendant; upon this signal,
predesignated emergency help is dispatched. Many

newer sensor options for tracking patients at home are
being incorporated into multifunctioning personal
emergency response systems devices, such as alerting
a central call center to water flooding or smoke in a
patient’s home. The next subsection provides details
on these sensors and monitors.

Sensor and Activity-Monitoring
Systems
Sensor and activity-monitoring systems can track
activities of daily living of seniors and other at-risk
individuals in their place of residence. These sensors
and monitoring systems can provide insight into
behavior changes that might signal changes or
deterioration of health status. Such technologies
consist of wireless motion sensors that are strategically
placed around the residence and can detect motion on
a 24-hour basis.

One authority on these technologies, David J. Stern
(2007), described their operation further. Data from
these sensors are wirelessly sent to a receiver and
base station that periodically transmits the information
to a centralized server through standard telephone
lines. Sophisticated algorithms analyze the data,
compiling data on each individual’s normal patterns of
behavior, including bathroom usage, sleep disturbance,
meal preparation, medication interaction, and general

levels of activity including fall detection. Deviations
from these norms can be important warning signs of
emerging health problems and the alerts provided can
enable caregivers to intervene early.

In addition to widely used fire, security, and home gas
detectors, other sensors can monitor appliances to
detect whether a household appliance is turned on or
off and can sometimes switch the appliance on and off
for the resident. Typical applications for affixing
programmable sensors can include lamps, television
sets, irons, and kitchen stoves. Such sensors might be
very valuable for ensuring the safety of elderly, forgetful
persons who live alone. One excellent example of
today’s sensor use for assistance with the elderly are
sensors placed in or on stovetops to alert the user
when he or she is standing too close to the equipment
or when the kettle or pot has boiled over. Benefits
realized from these technologies include enabling
people to live independently with an improved quality of
life. They can also provide peace of mind for other
family members living at a distance.

Medication Management Devices
Medication management devices address a well-
recognized major problem in health care: medication
management and compliance.

The failure of patients to take medications as
prescribed has become a national problem in health
care today. This noncompliance can have devastating
consequences, particularly for those patients living with
chronic illnesses. The National Pharmaceutical
Council (2013) estimates that the cost of
noncompliance with prescribed medications is $290
billion per year: 3 out of 4 people do not take their
medications as prescribed and 1 out of 3 people never
fills his or her prescriptions.

To address some of these very pressing problems, a
host of telecommunications-ready medication devices
have become available, and many more are in
development. Some are as simple as a watch that
reminds a person to take medications, others are pill
organizers with audible reminders, and some can be
programmed to dispense prefilled containers with
medications and alert a patient or caregiver of a
missed dose. Furthermore, some of these medication
tools send data from the device back to a central
server so that patient’s medication compliance can be
tracked. These telecommunications-ready devices can
organize, manage, dispense, or remind, and they will
play an increasingly important role in helping people
live independently and manage their disease
processes through medication compliance. For more
information on these devices, see the Informatics Tools
to Promote Patient Safety and Quality Outcomes
chapter.

Special Needs Telecommunications-
Ready Devices
Special needs telecommunications ready-devices can
include preprogrammed, multifunctional infusion pumps
for meeting a range of infusion needs, including
medications for pain management and other infusion
delivery needs, such as hydration and nutrition; peak
flow meters; electrocardiogram monitors; and so on.
Many such tools are in development to meet the more
demanding and challenging needs of today’s at-home
patients. The common goal of these tools is to increase
communications between nurse and patient and to
increase the nurse’s knowledge of the patient’s status
in a timely manner. Figure 18-4 illustrates the process
for managing home telehealth.

Figure 18-4 Managing Home Telehealth

Elderly patients at a consultation: © Monkey Business

Images/Shutterstock; telenurses looking at computer screen: ©

Rocketclips, Inc./Shutterstock; computer technicians: ©

dotshock/Shutterstock

Home Telehealth Software*
As important as the gathering of data is the organizing
of information to support decision making by clinical
professionals. The telehealth software supporting
home telehealth programs has become much more
sophisticated in recent years, allowing for greater
numbers of patients to be better managed by a single
clinician. Areas of significant improvement in software

include trending, triage, communications protocols,
access, and sharing.

Trending
One of the key advantages of home telemonitoring is
the creation of a digital health record that allows
information to be recorded over time. If a patient takes
his or her weight and blood pressure daily, most
software will graphically display these data over time
so that subtle trends can be observed. This type of
trend data is much more useful in identifying emerging
or developing conditions than snapshot data that are
collected every 6–8 weeks at a physician’s office.
Trend information can also be developed for groups of
patients or populations, allowing for population-based
analyses of interventions. For example, one might
gather trend information on patients with COPD,
patients of a particular physician, or all patients
receiving a certain medication.

Triage
Most home telemonitoring systems set an acceptable
range of values for an individual patient when he or she
is enrolled in the monitoring program. For example, if
oxygen saturation, blood pressure, or weight values go
above or below predetermined amounts, then the
software alerts the appropriate party. More
sophisticated software looks at readings from multiple

pieces of equipment on a single patient and can give
higher priority to patients at risk of an acute episode.
This helps clinicians better organize their work and
arrange for appropriate interventions.

Communications
Advanced telemonitoring software utilizes sophisticated
electronic notification protocols. It is often
predetermined when information will be communicated
and to whom it is sent. Sophisticated protocols can be
developed related to both routine and alert information,
thereby more effectively organizing communications
with physicians, nurses, and caregivers. Some systems
also have the capacity to communicate back to the
patient or seek additional information under
predetermined circumstances.

Data Access and Information Sharing
Many telemonitoring systems house information in
Web-based formats. This allows for easy access to the
data from any location that has access to the Internet.
Multiple parties can simultaneously share and view
data. Data can also be conveniently transmitted to
other clinicians and are updated almost immediately
when new values are received. Web-based records are
fully HIPAA compliant when appropriate protections
and controls are in place.

Home Telehealth Practice and
Protocols
The tools of telehealth described previously are
devices that enable remote care delivery, enhance
patient care, and improve outcomes. It is important to
note that the data received from these tools are
useless without some type of clinical oversight. Such
tools do not replace the nurse, but rather give the
nurse the ability to make more informed clinical
decisions based on reliable data and a comprehensive
picture of the patient’s status. In home care, they also
direct the clinical resources to patients based on need.
The resulting patient-centered approach to care
delivers improved patient outcomes and clinical
efficiencies.

Home telehealth is indeed a practice, albeit one that
represents a change in the current clinical model of
practice for home care. Use of the telehealth tools is
integrated into the practice to improve patient
outcomes. As with any tool, however, the effectiveness
is directly proportional to the appropriateness of the
tool’s application and use. Home telehealth programs
differ depending on the type of technology used and
the foci of the telehealth programs. However, every
program should have telehealth use criteria
established, including provisions for informed consent
and assessment of the appropriateness of telehealth

use for specific situations. The ATA regularly develops
and issues practice guidelines, which can be accessed
at the ATA’s website:
www.americantelemed.org/resources/telemedicine-
practice-guidelines/telemedicine-practice-
guidelines

Other professional organizations, such as the
American Nurses Association (ANA), the Association of
Colleges of Nursing (AACN), and the American
Academy of Ambulatory Care Nursing (AAACN), also
provide telehealth practice guidelines. Patient criteria
for telehealth should be governed by established
inclusion and exclusion guidelines, detailing who is
eligible and appropriate for each type of technology.
Other criteria include establishing policies and
procedures that address patient enrollment, education,
and equipment setup; patient and caregiver and home
assessment; patient informed consent; and privacy
and confidentiality rights. In addition, a clinical plan of
care that is specific to patient needs should be
developed. Telehealth pathways and protocols ensure
more focused work with patients and allow for targeted
interventions.

Clearly, by using a protocol for patients who regularly
use telehealth equipment for tracking their status,
nurses receive a good deal more targeted information
than can possibly be obtained during scheduled, in-
person visits. As a result, the use of telehealth tools,

together with clinical oversight and practice, allows for
more efficient and effective clinical management by
allowing the patient’s needs to drive the care. As home
telehealth protocols are used more extensively, the
improved clinical and operational efficiencies may
ultimately affect the home care agency’s bottom lines.

One must understand this clinically driven, as-needed
approach to care services more fully so that it is not
misunderstood as providing less care. In the above
case study, a proactive, patient-centered approach
enabled a home healthcare agency to identify early
exacerbations in a patient’s condition and take
appropriate action.

Case Study: Home Telemonitoring of

Multiple Illnesses

The patient is a 71-year-old male who has stage
4 cardiomyopathy/pulmonary hypertension,
atrial fibrillation, COPD, and type 2 diabetes
mellitus. He has been an active patient with a
home healthcare agency for several years, with
an admitting diagnosis of CHF.

Initially, the patient was seen three times a week
by an RN for CHF assessment and
management. The patient’s history included
frequent hospitalizations for exacerbation of
CHF and uncontrolled atrial fibrillation. He

experienced a total of four hospitalizations in the
year before placement of a telemonitoring
system in his home, after about 6 months of
receiving conventional home care.

Ever since the patient was placed on a
telemonitoring system for daily tracking more
than 8 months ago, he has not been
rehospitalized. The telemonitoring interactions
with his nurse have made him very conscious of
the role that his medications, diet, and fluid
restrictions play in his overall health status.

In addition, the telemonitor has proved its
benefits to local physicians. The patient’s family
physician, cardiologist, and pulmonologist all
were able to provide better care for the patient
by examining the tabular and graphical trends
that were elicited from the daily vital signs
monitor. This information aided in the titration
and addition of the various medications needed
to control the patient’s CHF and atrial fibrillation.
The physicians were able to ascertain the
response to the medication adjustments and
other treatment modalities, such as oxygen
titration. At the start of care, the patient’s weight
was 196 pounds; it is now at a stable 187
pounds, with the symptoms more controlled than
they have ever been.

The patient’s nurses, meanwhile, have peace of
mind knowing they can keep an eye on their
patient daily while making additional visits as
needed, with the documentation being provided
by the system to justify the additional nursing
visit. This tool can also be incorporated into the
nurses’ care plan, enabling a higher standard of
care to the patient.

At present, the patient is being case managed
by nursing staff visits that occur once per month.
He now enjoys a newfound peace of mind and
security and an improved state of health,
something this patient has not experienced in
more than a year.

Legal, Ethical, and Regulatory
Issues
Telehealth is affected by certain legal, ethical, and
regulatory issues of which nurses should be aware. In
the United States, interstate practice of telenursing, for
example, requires attending nurses to be licensed to
practice in all of the states in which they provide
telehealth services by directly interacting with patients.
This is particularly important when nurses work for
health systems that are located near state borders and
draw patients from both states. The Telehealth
Resource Center provides a nice overview of Licensure

and Scope of Practice issues; access it at
www.telehealthresourcecenter.org/toolbox-
module/licensure-and-scope-practice. In addition,
the Center for Connected Health Policy provides an
interactive map of current and pending state laws and
reimbursement policies; it can be accessed at
www.cchpca.org/state-laws-and-reimbursement-
policies. There is some evidence that these
regulations are slowly changing, so it is important for all
licensed professionals to be specifically aware of
legislation governing their practice.

In the 2016 report to Congress by the Medicare Patient
Advisory Commission (MEdpAC), there was discussion
of the need for streamlining interstate licensure for
physicians and nurses who provide telehealth services.
As an example, one physician had to maintain licenses
in 23 states (paid fees and met continuing education
[CE] requirements of individual states) in order to
provide TeleICU services. A possible solution is the
development of the federally sponsored physician
Interstate Medical Licensure Compact (IMLC) and
Nurse Licensure Compact (NLC) to facilitate portability
of licensure across state lines. However, this federal
initiative has met opposition from individual states who
are unwilling to share licensing authority.

Patient confidentiality and the privacy and safety of
clinical data must be given special consideration.
Informed consent releases to receive telehealth

services are a critical first step. Demiris, Doorenbos,
and Towle (2009) suggested that informed consent be
treated as a process and not a one-time event. They
argue that because telehealth is a completely new
experience, patients and families should have the
opportunity to revise their consent after they fully
understand its implications, especially the intrusiveness
of home monitoring. In addition, they suggested that
informed consent be obtained from all persons living in
the household because there are potential privacy
considerations for all who live in the home. When the
patient is presented with the informed consent form,
the nurse must assure the patient that physiologic data,
such as blood pressure readings that will be
transmitted over telephone lines or other public
communication means, will be kept confidential and
protected. In addition, for safety considerations,
pointed efforts must be continually undertaken by the
nurses’ agencies to upgrade their information systems
to ensure that a high level of data security is provided
at all times. Telehealth providers must adhere to all
data privacy and confidentiality guidelines and remain
vigilant to ensure that all involved parties, including the
technical staff assistants, have appropriate training in
privacy and confidentiality issues.

The Patient’s Role in
Telehealth

The range and sophistication of home telehealth tools
are expanding regularly, and a concern of nurses when
choosing appropriate tools for their patients is to ask,
Will my patient use this device? Elderly patients may
find the monitoring technology that may speak to them
in their homes and video cameras to assist in wound
care tracking, for example, to be a daunting
introduction to home health care. To assuage the
possible discomfort, these and other such tools have
undergone much iteration so that they are easier to use
and patients’ ability to turn them on and off is ensured.
When patients are scheduled for a televisit, these
devices can be turned on and used. This use by
patients is critical, of course, so that the necessary
information about them will be gathered and
transmitted, and so that their needs can be acted on by
telenurses.

Demiris et al. (2009) emphasized consideration of
usability issues when using telehealth applications with
elders who may have sensory, cognitive, and motor
disabilities. They suggest rigorous usability testing to
maximize the quality of the user experience and
special attention to design details for Web-based
interfaces, such as font choices and color schemes to
improve readability. Similarly, Kaplan and Litweka
(2008) emphasize the need for ethical design
principles:

How provider-centric or patient-centric is the

technology?
Does the shift to remote services promote
rationality and efficiency at the expense of values
traditionally at the heart of caregiving?
How does the design affect home life and family
dynamics?
To what extent should technology usage involve
attempts to manipulate users into different
behaviors?
How might the replacement of human contact by
new technologies be ameliorated?
To what extent is the deployment of technology an
end in itself, aimed not toward the improvement of
health or well-being, but to create market needs?
How do we identify the boundaries between
genuine solutions and futility in light of technologies
that may shift them? (p. 404)

Telehealth Research
Telehealth research focuses primarily on clinical
outcomes, such as effectiveness of telehealth
compared to usual care, cost effectiveness of
telehealth intervention, and patient and family
satisfaction. For example, Dansky, Vasey, and
Bowles (2008) studied the effects of home telehealth
care on several clinical outcomes in patients with heart
failure. They found that patients who received home
telehealth care had fewer hospitalizations and costly
emergency room visits during the study period and a

greater reduction in heart failure symptoms than the
control group. These authors suggested that the
frequent monitoring of symptoms afforded by telehealth
allowed for more frequent encounters than home visits,
providing more timely intervention when clinical status
changed and more frequent teaching and support by
nurses.

Similarly, Jia, Chuang, Wu, Wang, and Chumbler
(2009) studied the long-term effects of telehealth on
preventable hospital use and found a statistically
significant reduction in hospital use for the first 18
months of follow-up, but noted that the effects
diminished over the 4-year study period. There were no
differences found between telehealth and standard
care groups in a study of rates of infection, rejection,
and hospitalization in a group of transplant recipients,
leading the researchers to conclude that telehealth is
as effective as usual care for posttransplant follow-up
(Leimig, Gower, Thompson, & Winsett, 2008).
Telehealth was also shown to be effective in providing
support and problem-solving assistance for family
caregivers of patients who experienced polytrauma
(Bendixen et al., 2008) and persons with spinal cord
injuries (Elliott, Brossart, Berry, & Fine, 2008).

In a qualitative study of patient and physician
perspectives on treating rural depression, Swinton,
Robinson, and Bischoff (2009) concluded, “Although
an acceptable solution, both patients and PCPs

expressed reservations about using telehealth for the
treatment of depression because they felt that
technology-mediated communication would not lend
itself to establishing and maintaining the type of
provider–patient relationship that would allow treatment
to be effective” (p. 178). However, given the access
issues associated with rural communities, telehealth
provided an opportunity for intervention in cases where
traditional care was challenging. Telehealth was also
shown to be an effective alternative to usual care in
conducting hearing screenings at rural elementary
schools, thereby extending the reach and controlling
the costs of conducting hearing screenings (Lancaster,
Krumm, Ribera, & Klich, 2008).

Polisena, Coyle, Coyle, and McGill (2009) conducted
a meta-analysis of 22 studies that compared telehealth
to usual care in patients with chronic diseases; their
work included a cost-effectiveness analysis. These
authors concluded that in general telehealth can be
cost-saving for the health system and insurance
providers, but caution that because the overall
methodological quality of the studies was low, the
societal impact of telehealth remains uncertain.

Research into telehealth interventions clearly
demonstrates that telehealth is at least as effective as
usual care in managing chronic conditions in the home,
and in many cases is more cost-effective than home
visits. Demiris et al. (2009) suggested that more

studies are needed to focus on the patient–provider
relationship changes associated with such care,
especially the loss of human touch associated with
telehealth interventions. They also caution that
researchers who are studying telehealth in remote
populations must consider long-term sustainability of
telehealth support beyond the study period to ensure
that the “research does not exacerbate existing
disparities” in access to technologies (p. 132).

The Agency for Healthcare Research and Quality
(AHRQ) released a report authored by Totten and
colleagues (2016) titled Telehealth: Mapping the
Evidence for Patient Outcomes from Systematic
Reviews. The purpose of the report was to provide a
systematic review of evidence related to the impact of
telehealth on clinical outcomes. The evidence
suggested that

telehealth interventions produce positive
outcomes when used for remote patient
monitoring, broadly defined, for several
chronic conditions and for psychotherapy
as part of behavioral health. The most
consistent benefit has been reported
when telehealth is used for
communication and counseling or remote
monitoring in chronic conditions such as
cardiovascular and respiratory disease,
with improvements in outcomes such as

mortality, quality of life, and reductions in
hospital admissions. (p. vi)

To follow progress in telehealth research, bookmark the
sites provided in Box 18-1.

BOX 18-1 TELEHEALTH RESEARCH

AND INFORMATION CENTERS

Center for Telehealth and E-Health Law:
www.ctel.org
International Society for Telemedicine and
eHealth: www.isfteh.org
Telehealth Resource Centers:
www.telehealthresourcecenter.org
Telemedicine Information Exchange:
www.tmhguide.org/site/epage/93994_871.htm
UTMB Center for Telehealth Research and
Policy at University of Texas Medical Branch:
http://telehealth.utmb.edu
Virginia Telehealth Network:
www.ehealthvirginia.org

Evolving Telehealth Models
Previous telehealthcare deliveries were largely provider
initiated; however, we are beginning to see that
consumers will drive the way health care is delivered in

the future. Consider that tomorrow’s healthcare facility
might have no walls. The evolving roles of the Internet,
electronic and personal health records, mobile health,
health information exchanges, and telehealth all will
support a more integrated healthcare model. This
convergence of trends and solutions will continue to
expand with the introduction of new business practice
models, such as retail clinics and direct-to-consumer
telehealth services.

Retail clinics, such as CVS’s MinuteClinics and
Walgreens’ Healthcare Clinics, began to emerge in
2001 and have grown steadily to about 1,800 in
number (Bachrach & Froelich, 2016). These clinics
focus on prevention services such as vaccines;
treatment of minor injuries, minor illnesses, and aches
and pains; and health monitoring and medication
management services for chronic illnesses. The clinics
offer affordable, accessible, walk-in, and after-hours
care, and are helping to fill the primary care gap
created by the Affordable Care Act. Adding telehealth
services is allowing these clinics to expand their
services. In 2015, CVS announced a partnership with
several telehealth organizations—American Well,
Teladoc, and Doctor on Demand—to provide onsite
telehealth consultations for CVS clinic providers:

CVS Health is piloting several different
telehealth opportunities, including making
telehealth physician care accessible

through CVS Health digital properties.
CVS Health will also explore enabling
MinuteClinic providers to consult with
telehealth physicians to expand the
scope of care offered at MinuteClinic. In
addition, MinuteClinic will continue to
provide telehealth care to patients in CVS
retail stores and will explore serving as a
site for in-person exams to facilitate
telehealth medical visits. (CVS Health,
2015, para. 4)

These telehealth organizations also provide
downloadable telehealth apps for consumers to consult
directly with board-certified doctors via smartphones,
tablets, and computers. For more information, please
visit www.amwell.com, www.doctorondemand.com,
and www.teladoc.com.

Polinski and colleagues (2015) surveyed 1,734 patients
to assess satisfaction and preference for telehealth
visits in CVS MinuteClinics. They reported overall
satisfaction with telehealth because of its convenience
and quality of care, and that one-third of the
respondents preferred telehealth to an actual provider
visit.

Several new trends include more robust mobile devices
that connect with each other (Internet of Things) to

provide real-time data on a patient’s fitness and
exercise to his or her physician’s offices. The difficulty
with these devices is ensuring security of data
transmissions, as well as the possibility of
overwhelming physicians with data (TechTarget, n.d.).

The Telemed Tablet is a Food and Drug
Administration–approved device that provides access
to a pool of specialists for consultation in rural clinics,
at the bedside in hospitals, or in emergency rooms. It
also allows on-call providers to consult remotely. More
information about this product can be found at
http://info.americanwell.com/the-telemed-tablet-
brochure.

An interesting software application developed by
Extreme Health is a motion-tracking technology that
enables tracking and analysis of positions assumed by
patients in front of a webcam as they perform their
prescribed home exercise regimens.

Extreme Health’s unique technology
improves the physiotherapy process for
outpatients and care-givers by enabling
patients to conducts their exercise
sessions at home on their chosen
devices while receiving feedback on
quality of performance. Meanwhile, the
clinician receives the patient’s data,
configures exercises and monitors

performance and progress, allowing the
clinic to provide better care for
physiotherapy outpatients. (ATA, 2016,
para. 2)

Parting Thoughts for the
Future and a View Toward
What the Future Holds
Telehealth is here to stay and will become increasingly
important in the future. The barriers to telehealth must
be addressed soon. As the ATA (2015) suggested, the
following are priorities for the 21st Century Healthcare
Package:

Allow for Medicare payments as a standard benefit
without geographic restrictions
Phase in flexibility for Medicare telehealth at
Accountable Care Organizations and provide
coverage for:

* Remote critical care (primarily hospital ICU)
services

* Stroke bundle, including remote diagnosis

* Home-based remote patient monitoring and
physician video visits in home care

* Home and outpatient telerehabilitation

* Telemental screening and counseling for
depression

Improve beneficiary access under fee-for-service
payments, targeting:

* Telestroke diagnosis

* Physician “visual” services by revising the
asynchronous restrictions

* Telehealth for recertifications of need for home
health care and durable medical equipment

Revise the Medicare Chronic Care Initiative to
include:

* Remote patient monitoring

* Initiatives for hospital readmissions reduction

* Waivers for telehealth restrictions to allow a
state with a Medicaid “health home” project (two
or more chronic conditions) to also serve
comparable Medicare beneficiaries

* Promotion of specialty medical homes to
provide bundled and coordinated Medicare
services for a specific long-term illness, chronic
medical condition, or medical subspecialty, such
as Parkinson’s, multiple sclerosis, or specific
cancers

Consider other federal telehealth improvements,
such as:

* Options for high-risk pregnancy telehealth

networks

* Consolidating U.S. Department of Health and
Human Services (USDHHS) telehealth grants,
especially for telehealth networks, telehealth
resource centers, licensure portability, and
evidence-based tele-emergency networks

* Promoting autism telehealth networks to
improve care quality and accessibility

* License portability for USDHHS health
professionals: USDHHS employees and
contractors would need only state licenses to
provide official services in the United States

The care continuum will need to be supported by a
clinical and caregiver structure that uses the data
collected from patients to make better and more
informed healthcare decisions. Health parameter data
could be used by the end user for personal direct care
decision making, or it may be used by a member of the
healthcare community to determine appropriate
healthcare interventions.

The technology of today will be different from the
technology of tomorrow, as access to broadband
communications systems, acceptance of technology,
and mobility and data transfer continue to evolve. As a
result of emerging needs, many companies will enter
the market and offer a wide range of information

technology tools, ranging from embedded and worn
sensors to remote monitoring devices. User interfaces
will become increasingly sophisticated and more
patient-centric.

Clearly, by making key information readily accessible,
solutions across all areas (home health, hospitals, and
a range of other settings) will facilitate collaboration in
care delivery and health information. Products that
integrate into consumers’ and patients’ everyday lives
to improve the quality of life will continue to emerge.
Telehealth and telenursing will play an important role in
improving quality of life and care for the patients
served.

Foremost, nurses must be open to change and willing
to embrace ever-evolving practice models. Tools
should always be used to improve care delivery models
so as to make more targeted contact with and about
patients. In an ideal world, there will be seamless
integration of clinical data systems and robust data
exchange to provide quality care for patients no matter
their location.

Summary
Telehealth is a rapidly developing mode of health
service delivery in which nurses can expect to play a
significant role. The most promising area of
concentration for nurses is in home telehealth care, an

area that is expected to provide extensive care to the
burgeoning numbers of American elderly persons living
with challenging chronic diseases and conditions.
Many telecommunications-ready tools to assist nurses
in delivering this care are currently available, and their
effectiveness in maintaining or improving patients’
health outcomes is well documented. Today’s nurses
are providing telehealth services to typical home care
patients (elderly patients, patients needing regular and
targeted care) and operating effectively as telenurses.
The practice of telehealth will provide opportunities for
telenurses to become key players in care management
across the healthcare continuum.

THOUGHT-PROVOKING QUESTIONS

1. Will the increased use of telehealth
technology tools be viewed as
dehumanizing patient care, or will it be
viewed as a means to promote more
contact with healthcare providers and as
new ways for people to stay connected
(as in online disease support groups),
thereby creating better long-term disease
management and patient satisfaction?

2. Which types of resistance to new
technologies might be evident among
patients, caregivers, and nurses? Which
evidence and strategies might help to
diminish these resistances?

3. As telehealth technology advances
toward seamless data access regardless
of distance or health system, how can
patient privacy rights and the
confidentiality of personal medical data be
protected?

4. Consider a recent patient care scenario
and describe how it could have been
managed at a distance.

* Which training would be needed?

* Which equipment would be used?

* How would the patient and his or her
family respond to home
telemonitoring?

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This section is adapted from Prial & Hoss (2009).

This section is adapted from Prial and Hoss (2009).

*

*

SECTION V: Education
Applications of Nursing
Informatics

Chapter 19 Nursing Informatics and Nursing
Education

Chapter 20 Simulation, Game Mechanics, and
Virtual Worlds in Nursing Education

Nursing informatics (NI) provides more tools and
capabilities than can at times be imagined. Just as NI
has changed the way nursing is administered and
practiced, so it has also dramatically affected nursing
education practices.

Nursing education is evolving with the increased
integration of NI and other technology tools to promote
learning. The tools that are available must be used
prudently by reflecting on and applying knowledge on
teaching styles, learning styles, and other pedagogic
concerns. As informatics capabilities continue to
expand, a phenomenal amount of potential for virtual
reality–embedded education looms on the horizon.
Once the purview of gamers and geeks, virtual reality
has exploded onto the academic scene. The use of
virtual reality has the potential for cross-pollination

between fields of inquiry across the curriculum, the
university, and even learning systems. Many university
departments will experiment with virtual reality in hopes
of staying current and appealing to their young and
demanding “Generation Next” constituency. However,
much of society loves the feel of books too much to
dismiss them as archaic. There is room for both books
and technology in education. Students, educators, and
administrators will ultimately return to a modified form
of face-to-face classroom teaching, even with the
availability of newer and more adventuresome teaching
technologies. Furthermore, after fast, highburn
technologies stop flooding the marketplace and big
business provides opportunities for proprietary online
universities, modified traditions will take their place,
creating new spaces for nontraditional students and
members of the Net Generation, with both being
anxious for technology use in the classroom for very
different reasons.

The material in this book is placed within the context of
the Foundation of Knowledge model (Figure V-1) to
meet the needs of healthcare delivery systems,
organizations, patients, and nurses. Nursing education
promotes scholarship and evidence-based teaching
and learning. Through the sound integration of
information management and technology tools,
teaching and learning strategies promote the social
and intellectual growth of the learner. As teachers and
learners quest for knowledge, the need for pursuit of

lifelong learning is instilled. Teachers and learners
involved in the process of education are also involved
with all levels of the model. Typically, they acquire and
process data and information and generate and
disseminate knowledge within the frame of reference of
their educational institution. Their knowledge
generation remains on a limited,
individual/course/school basis unless they become
involved with developing publications and educational
research that informs others in the nursing profession.

Figure V-1 Foundation of Knowledge Model

Designed by Alicia Mastrian.

The reader of this section is challenged to ask the
following questions: (1) How can I apply the knowledge

I gain from my education to benefit my patients and
enhance my practice? (2) How can I help my
colleagues, patients, and fellow students understand
and use the current technologies to promote learning?
(3) How can I use my wisdom to help create the
theories, tools, and knowledge of the future?

CHAPTER 19: Nursing
Informatics and Nursing
Education

Heather E. McKinney Sylvia DeSantis Kathleen
Mastrian and Dee McGonigle

Objectives
1. Describe nursing education in relation to

the Foundation of Knowledge model.
2. Explore knowledge acquisition and

sharing.
3. Assess technology tools and delivery

modalities used in nursing education and
in continuing education.

4. Compare and contrast knowledge
assessment methods.

Key Terms

» Advocate

» Asynchronous

» Audiopod

» Blended

» Blog

» Collaboration

» Compact disk read-only memory (CD-
ROM)

» Computer-assisted instruction (CAI)

» Computer-based

» Continuing education

» Copyright

» Digital versatile disk/digital video disk
(DVD)

» Distance education

» E-learning

» Email

» Electronic mailing list

» Evidence

» Face-to-face

» Fair use

» Foundation of Knowledge model

» Hybrid

» Hypertext

» Information literacy

» Instant message (IM)

» iPod

» MP3 aggregator

» Multimedia

» Net Generation

» Online chats

» Podcast

» Portal

» Portfolio

» Problem-based

» Professional networking

» Real time

» Really simple syndication (RSS)

» Reflective commentary

» Resource description framework (RDF)

» Role playing

» Scenario

» Simulations

» Smartphone

» Tutorial

» Videopod

» Virtual reality

» Web-based

» Webcast

» Web-enhanced

» Webinar

» Web publishing

» Wiki

Introduction: Nursing
Education and the Foundation
of Knowledge Model
Nursing informatics facilitates the integration of
information, data, and knowledge to support nurses,
patients, and other providers in their various settings
and decision-making roles. The Foundation of
Knowledge model specifically prompts nurses to

extend their theoretical and metaphorical knowledge
into practical, holistic determinations based on a variety
of factors and contexts. Because competencies in
informatics include but are not limited to information
literacy, computer literacy, and the ability to use
strategies and system applications to manage data,
knowledge, and information, the ability of nursing
students to use computer-mediated communication
skills is essential to their success in the nursing field
and as a means to improve patient safety.

The rise of telecommunications, computer-mediated
communications, and virtual technologies has opened
up opportunities for improving communication and
extending care within the healthcare industry (Barnes
& Rudge, 2005). Proponents of instructional
applications of computer technology view it as a way to
erase geographic boundaries for students, enhance the
presentation of content, improve learning outcomes,
and even tailor instruction to individual learning needs.
When carefully matched with curricular objectives,
technology becomes an efficient and affordable avenue
through which nursing faculty may provide useful
knowledge to their students, thereby facilitating the
learning process (Hebda & Czar, 2013). Now going far
beyond the simple applications of word processing
software or spreadsheets, technology applications
have evolved greatly, taking advantage of modern
capabilities to provide nursing and related healthcare
students with simulations, complex multimedia, virtual

reality–assisted clinical scenarios, and a host of
information and literature-gathering Internet tools.

Knowledge Acquisition and
Sharing
The shift from computer literacy to information literacy
and management has drawn attention to interactivity
and design as the most important components of
interactive Web-enhanced and Web-based courses in
providing effective learning environments. Thurmond
(2003) and Thurmond and Wamback (2002)
discussed the four types of interactions related to Web-
enhanced courses based on their literature reviews: (1)
learner– learner, (2) learner–content, (3) learner–
instructor, and (4) learner–interface interactions
(Thurmond & Wamback, 2002, para. 1). In traditional
learner–learner exchanges, students interact with one
another to troubleshoot, work out challenges, and
exchange solutions generated from different
perspectives. Traditional and familiar, both learner–
content and learner–instructor interactions expect
students to work directly with course content or the
faculty member and then participate in relevant course
activities, such as tests and reviews. Learner–interface
interaction includes the ways students access their
coursework and their ultimate success or failure in
finding, retrieving, and using what they need
(Thurmond, 2003; Thurmond & Wambach 2002).

See Figure 19-1 for a graphic depiction of these
interactions. When Web enhanced, these interactions
include online chats, forum discussions, participation
in electronic mailing list groups, instant messaging,
blogging, and use of email, all of which ask the student
to engage, digest, use, and disseminate information in
new ways.

Figure 19-1 Types of Interactions in Web-Based
Courses

Data from Juliano, R. (2016). Best practices guide to converting face to

face courses to a distance learning format: Educational technology.

Retrieved from http://www.manula.com/manuals/rachael-juliano/best-

practices-guide-to-converting-face-to-face-courses-to-a-distance-

learning-format/1/en/topic/educational-technology

Evolution of Learning
Management Systems

In the 21st century, nursing informatics emphasized
technology usability, functionality, and accessibility in
education and practice. Computer-assisted
instruction (CAI) arrived early on the scene and has
had an enormous impact on nursing informatics and
nursing education, with many CAI programs offering
individualized instruction in the form of customizable
scenarios, frameworks, and programs for study.
Additionally, CAI contributed to better understanding of
material by supporting all learning styles, types, and
paces. Consequently, nursing skills–development
needs presented endless potential for software
development, making the effective use of software and
hardware by educators and students a prime necessity
(Riley, 1996).

Recall that software comprises the instructions that
direct a computer’s hardware to work, whereas
hardware consists of physical computer components,
such as a mouse, keyboard, and monitor. Software
essentially translates commands into computer
language, allowing the hardware to perform its
functions. Without hardware and software, computer
technologies are moot; moreover, without software,
hardware does not function (McHugh, 2006).
Applications software refers to the various programs
individuals use to communicate with others, do work,
play games, or watch multimedia on a computer. The
most common software package sold with computers is
an office package, which generally includes a word

processing program, spreadsheet capability, a
presentation graphics program (e.g., PowerPoint), and
some kind of database management system. Software
packages are available on compact disk read-only
memory (CD-ROM), on digital versatile disk/digital
video disk (DVD), or, now most commonly, through
the Internet, allowing the user to download the software
directly from a vendor’s website (McHugh, 2006).

When evaluating software or hardware for purchase,
careful assessment of the products and services will
help an educator, administrator, or student make the
best choices. Most important when evaluating software
is to understand how well the software’s functionality
for computer-assisted learning matches the learning
goals and objectives. Although many programs are
available for assisting a nurse educator who is
evaluating software for particular learning purposes,
the main criteria concern content (Is the information
accurate? Is it relevant?), format (How is information
visually presented? Is it in frames? Does it come with
graphics?), documentation style (What is the tone? Is it
scholarly and applicable?), and strategies (Is the
software useful for all students, including remedial
students and accelerated students?) (Edwards &
Drury, 2000).

Hardware decisions depend on the way a computer
system will be used, in addition to considerations
related to cost, ease of use, and durability (Clochesy,

2004). Systems purchased for personal use may differ
dramatically from those purchased for online learning
laboratories or smart classrooms. Because the
technology inherent to workstations, servers, and
computers in general tends to change quite rapidly,
discussing large system decisions with an information
technology expert is likely to yield a better-informed
decision. Some factors to consider include where the
system will be stationed (e.g., at home for personal use
or in a learning laboratory for use by many students),
how many desktops there will be (e.g., one or a few
dozen), if it will be networked to a school’s internal
system, if printing will be available, and which level of
security is needed (Hebda & Czar, 2013).

As computer-supported learning gained popularity,
education innovators realized the need for additional
functionality. Integrated learning systems evolved from
the earlier uses of computer-based instruction, and
offered tracking, content management, and more
individualized instruction (Wikipedia, 2016). These
early systems primarily supported the administration of
the course and content and provided convenience for
instructors. According to Brown, Dehoney, and
Millichap (2015),

Higher education is moving away from its
traditional emphasis on the instructor,
however, replacing it with a focus on
learning and the learner. Higher

education is also moving away from a
standard form factor for the course,
experimenting with a variety of course
models. These developments pose a
dilemma for any LMS [learning
management system] whose design is
still informed by instructor-centric, one-
size-fits-all assumptions about teaching
and learning. They also account for the
love/hate relationship many in higher
education have with the LMS. The LMS is
both “it” and “not it”—useful in some ways
but falling short in others. (p. 2)

Brown and colleagues also describe the Next
Generation Digital Learning Environment (NGDLE) as
reimagining the education system. Key characteristics
of the NGDLE include:

Interoperability and integration: These allow for
seamless exchange, transfer, and utilization of
content; the addition of learning tools; and the
aggregation, integration, and analysis of learning
data.
Personalization supports the ability of instructors,
departments, and students to configure the learning
environment to meet specific needs.
Analytics, advising, and learning assessment: This
component supports learning assessment and

assessment of competency-based education and
provides data analysis tools for these assessments.
It also integrates progress planning and advising
functions.
Collaboration may occur within the course among
students and instructors, but in the NGDLE
collaboration may also occur among disciplines,
institutions, and professions, particularly if the
system adheres to interoperability standards.
Accessibility and universal design: This component
takes into account special needs of persons with
disabilities and supports prospective design of
accessible features and components.

Delivery Modalities
Nursing educators are discovering that today’s
students may not always respond in the same ways the
educators did during their own tenure as students.
Technology-savvy students from the millennial age
demand instant information delivered in an entertaining
fashion—an expectation built on extensive exposure to
email, text messaging, online chatting, and the Internet
(Ridley, 2007). Additionally, many nursing departments
are facing an increase in student enrollment and a
corresponding growth in faculty. Although new nursing
faculty bring significant clinical experience to their
academic positions, also apparent for some is an
underlying tension and unfamiliarity with technologic
advances, outcomes-based accreditation initiatives,

and teaching itself. Schools of nursing are scrambling
to provide professional development for busy nursing
faculty and introducing them to best practices in
teaching (Shaffer, Lackey, & Bolling, 2006). See
Figure 19-2 for an overview of key digital skills for
nurse faculty.

Figure 19-2 Ideal Digital Skills for Faculty

Reproduced from Educational Technology and Mobile Learning. (2016).

Another excellent poster featuring 10 digital skills for teachers. Retrieved

from http://www.educatorstechnology.com/2016/02/another-

excellent-poster-featuring-10-digital-skills-for-teachers.html

Learning is a multispatial function, and in the age of
technology innovation, instructional delivery can inhabit
many forms in both physical and virtual spaces.
Spaces in academia are no longer defined by a class
or its content, but instead by the learning the class is
trying to promote. To this end, learning spaces should
support multiple modes of learning and delivery,
including reflection, discussion, and experience, and
should facilitate face-to-face and online interaction
within and beyond classrooms. Truly innovative
delivery, whether face-to-face classroom interaction,
online engagement, or a blended hybrid of technology
and traditional classroom teaching, supports learning
activities rather than standing independently of them
(Oblinger, 2005).

Face-to-Face Delivery
Ridley (2007) suggests that although it is the most
widely used teaching method among nurse educators,
traditional face-to-face lecture yields only a 5%
information retention rate over a 24-hour period, a rate
that compares unfavorably with demonstration (30%),
discussion groups (50%), practice activities (75%), and
peer teaching (90%; as cited in Sousa, 1995).

Additionally, the inability of physical space to keep
pace with evolution of learning models inhibits the
benefits gained from face-to-face interaction between
teacher and student. For example, collaborative

learning grinds to a halt when class is held in a room
with chairs bolted to the floor, facing a lectern
(Oblinger, 2005); this kind of spatial arrangement
prohibits a sense of classroom community by inhibiting
easy peer interaction, reducing students’ ability to see
one another, and concentrating all attention on the
professor.

Conversely, in a collaborative learning environment,
the professor guides conversation and sets up
discussion, acting less as classroom authority and
more as facilitator, helping students maintain focus,
gently guiding discussion, and ultimately empowering
students to push knowledge boundaries in a safe and
secure atmosphere of peer support. This inductive,
epistemological approach promotes active, critical
thinking skills and assists students in learning not just
facts, but how to learn. As future healthcare
professionals determined to rely on quantification and
rationale, nursing students will benefit from face-to-face
classroom interaction that hones their ability to
manufacture new personal truths through interaction
with people and ideas in ways that cannot always be
measured and counted.

Ridley (2007) suggests that such interactive,
cooperative learning strategies might include gaming,
role playing, and problem-based learning. Because
games are nonthreatening and fun, they promote
critical thinking and teamwork by pushing students to

work together in groups to find answers and achieve
success. Role playing is similar in that it allows
students to try on real-life scenarios by filling either pre-
scripted or ad-libbed roles (doctor, nurse, patient,
clinician, and so forth) without the fear or pressure of
putting another’s life at risk while trying to determine
the best course of action or find a solution for a
fictitious patient’s health issue.

Problem-based learning, a well-accepted form of
interactive learning, takes assignments out of a
contextual vacuum and applies real-life scenarios to
problems or challenges. Students work in groups to
solve the dilemma presented by real patient cases and
build on prior knowledge, using higher-level thinking
skills and progressive inquiry to resolve the problem
(Ridley, 2007). This enhances the student’s critical
skills for acquiring and maintaining knowledge in
practice.

Online Delivery
E-learning, online learning, and Web-based education
have caused a significant shift in student–teacher
relationships in nursing education. According to
Oblinger (2005), not only are learning spaces no longer
physical or formal, especially on campuses with
wireless capabilities, but nursing students also expect
to make use of wide ranges of cutting-edge technology
during their academic tenure, exchanging the

traditional “sage on the stage” for a technologically
savvy “guide on the side” (Leasure, Davis, & Thievon,
2000) who gives up the role of gatekeeper and instead
promotes and facilitates dialogue as central to
teaching–learning (Aquino-Russell, Maillard Strüby,
& Reviczky, 2007).

Student-centered and no longer limited to the domain
of the classroom, laboratory, or even a patient’s
bedside, online learning allows educators to translate
theory into practice, creating a virtual classroom space
that promotes collaboration, engagement, discussion,
and analysis. Detractors of online learning initiatives
suggest, however, that sharing an online space
undermines the student–teacher relationship, makes
building peer relationships difficult, and generally
disrupts the normal classroom dynamic, thereby
creating an unfamiliar, uncomfortable atmosphere.
Despite these concerns, studies show that not only do
Web-based courses continue to gain in popularity, but
they also enhance learning in ways that encourage
students to share personal experiences and support.
Researchers cite many factors that make online
learning laudable, with accessibility and convenience
being two of the most frequently cited issues (Aquino-
Russell, Maillard Strüby, & Reviczky, 2007).

The asynchronous and time-independent elements of
Web-based courses respond to the huge need for
flexible class times among today’s growing population

of nontraditional learners. Additionally, Web-based and
place-independent learning allows participation by
anyone, anywhere in the world, with access. Exposure
to online learning during healthcare professional
education programs will facilitate continuing
professional education during the practice tenure.
Related to this issue is the democratizing effect of
online learning, such that all students have the same
opportunity to participate without judgment. Web-based
classes provide an easily accessible permanent record,
a convenience for both teachers and learners (Aquino-
Russell, Maillard Strüby, & Reviczky, 2007).

It is important to use tools that facilitate learning, such
as the introduction of social media into nursing
education. Twitter (www.twitter.com) can be used to
focus and hone student perspectives. Each posting or
tweet cannot exceed 140 characters. As they critically
think about what they want to add to the discussion,
students must act as wordsmiths to express their views
succinctly given the character limitation; that is, they
must present their viewpoints concisely. Other social
media that can be used in education include the
following sites:

Diigo (www.diigo.com), a social bookmarking tool
to collect, tag, and share online sources (Meyer,
2015)
Feedly (www.feedly.com), an online feed
aggregator to notify the subscriber of new content

on blogs and websites of interest (Meyer, 2015)
Flickr (www.flickr.com), for photo sharing
Glogster (www.glogster.com), a graphical blog
Instagram (www.instagram.com), for customizing
and sharing photos and videos (Meyer, 2015)
Pinterest (www.pinterest.com), a social
bookmarking tool used to prime discussions
(Meyer, 2015)
Pixton (www.pixton.com), to create comics or
cartoons
Prezi (www.prezi.com), to create zooming
presentations
Scoop.it (www.scoop.it), an online content curation
tool used to collect Web resources, comment on
them, and publish the source and commentary
(Meyer, 2015)
Slideshare (www.slideshare.net), a community for
sharing presentations
YouTube (www.youtube.com), to watch and share
videos
VoiceThread (www.voicethread.com), to share
images, videos, documents, and commentary
(Meyer, 2015)
Wordle (www.wordle.net), to create word clouds
from text

These sites can be used by students to facilitate their
presentations and team collaboration. The use of social
media not only exposes the students to their use but
also promotes the development of skills that will

support professional collaboration as students enter
the practice arena. Meyer (2015) reported that using
social media in education helps students put concepts
in context, maintains currency in course content, and
fosters a sense of community. Figure 19-3
demonstrates the purposes and time required for
proper use of social media.

Figure 19-3 Social Media Time Estimates

Data from The Social Observer. (2016). Find 10 tips that help you take

time to be social. Retrieved from

Hybrid or Blended Delivery

Traditional courses are more frequently being offered
as online, virtual classes (i.e., distance education)—
learning that occurs elsewhere than in the traditional
classroom and consequently requires special course
design, planning, techniques, and communication. A
hybrid of this delivery mode includes learning in which
traditional classroom time is enhanced or broken up
with online components, thereby creating a class in
which blended hybrid learning occurs. Forms of hybrid
learning include Web-enhanced learning, such as
asking students to blog responses to a reading or
class discussion, and learning that takes place in and
makes use of smart classrooms (e.g., teaching in a
wired room equipped with classroom learning
technologies, such as the Blackboard Learning
System).

Smart classrooms, also known as digital and
multimedia classrooms, integrate computer and
audiovisual technologies by providing a ceiling-
mounted projector with an access point at the front of
the room, an instructor podium or workstation, sound,
and network access. An enhanced smart classroom
also provides networked student workstations instead
of traditional desks, allowing students to follow along
online and perform network or Web searches, chat,
blog, or myriad other activities as dictated by the
professor. For example, at the Penn State College of
Nursing, users can access announcements, course
materials, faculty information, websites, and other tools

through the electronic course management system,
enabling the nursing faculty to extend learning beyond
the physical classroom walls.

Competency-Based Learning
More robust learning management systems (LMSs) are
particularly well suited to support competency-based
learning. Nursing competencies have been well defined
by professional and accrediting organizations such as
Quality and Safety Education for Nurses (QSEN); the
American Association of Colleges of Nursing (AACN),
through its Technology Informatics Guiding Education
Reform (TIGER) initiative and the essentials of nursing
education delineated for undergraduate and graduate
study; and informatics competencies promoted by the
Healthcare Information and Management Systems
Society (HIMSS). As the U.S. Department of
Education (2014) explained,

Transitioning away from seat time, in
favor of a structure that creates flexibility,
allows students to progress as they
demonstrate mastery of academic
content, regardless of time, place, or
pace of learning. Competency-based
strategies provide flexibility in the way
that credit can be earned or awarded,
and provide students with personalized
learning opportunities. (para. 1)

Database technologies within LMSs offer the ability to
track competency achievement, as Pijl-Zieber, Barton,
Konkin, Awosoga, and Caine (2014) explain: “Such
technologies could be shared, at least to some degree,
between nursing student and nursing instructor, much
like clinical evaluation tools are shared on paper, to
jointly track skills, knowledge, abilities, critical thinking,
clinical reflection, and developing competence” (p.
677).

Technology Tools Supporting
Education
Certain social trends emerging from the morass of both
traditional and innovative technology tools include the
use of technologies attempting to meet the needs of
members of the Net Generation or Millennial
Generation. These are students who have grown up
inside a wired world of instant access and online
everything who are connected, digital, experiential, and
social learners. Through the use of software, hardware,
drivers, dedicated servers, plug-ins, and an Internet
connection, students can chat, collaborate, play
games, or interact electronically with a peer in some
way, all with little to no learning curve or effort.
Because visual media are now the vernacular of this
highly digital culture, students and faculty are also
embracing technology tools that allow for the creation
and interpretation of visual images (Oblinger, 2005).

Such tools might take the shape of interactive tutorials,
a created city within a virtual reality landscape, high-
fidelity simulations, serious games, or even a
multimedia action maze that prompts users to choose
different outcomes within a scenario. Regardless of the
particular tool employed, technology can perform only
as well as the pedagogy that drives it, thus creating a
need for integration, support, and sustainability within
nursing education programs willing to implement new
instructional and assessment strategies
(Bassendowski, 2005).

Tutorials
The modern tutorial mimics lectures by guiding users
through a series of objectives or tasks, usually allowing
the user to do the work at his or her own pace
(Edwards & Drury, 2000). Tutorials generally stand
alone as autonomous multimedia that may use
animation, text, graphics, sound, questions, and
different kinds of interactivity to engage and intrigue the
user. They tend to promote active learning by
prompting the user to answer sets of questions, follow
clickable hypertext, or complete quizzes. For example,
users might be asked to fill in worksheets after
reviewing anatomy concepts, take a quiz, post an
answer to a question, or even click through a scenario
by choosing the best course of action in a mock clinical
situation.

Some tutorials, such as those used by medical
students at the Morgan Stanley Children’s Hospital of
New York, are designed to be brief (10 minutes),
interactive, very focused, and immediately relevant. In
this case, medical students bustling through a busy
clinical rotation who accessed the tutorials actually
raised examination grades (Pusic, Pachev, &
MacDonald, 2007).

Because most students benefit from being able to
contextualize a lesson’s framework and purpose, the
most effective tutorials provide users with
understandable navigation, such as a table of contents
at its beginning, or additional navigational aids, such as
icons, buttons, or text that indicate where and how they
need to progress (Dewald, 1999). Effective tutorials
surpass the simple presentation of information in a
Web-based format; they instead address certain
pedagogic and student-centered needs by identifying
and taking into consideration specific factors, such as
instructional content, the educator’s purpose and
teaching goal, the initiative’s overall purpose, the
potential need for special conceptual input, the
learners’ ultimate objectives in completing the tutorial,
and the standards that determine what qualifies as
successful completion of the tutorial (DeSantis, 2002).

Although most tutorials are created to stand alone,
some may also benefit and supplement face-to-face
instruction, such as the interactive information skills

tutorial developed at the Institute for Health and Social
Care Research in Salford, United Kingdom. This
tutorial divides a traditional lecture series into chunks,
incorporating questions that would normally arise
during the session into the text, and providing
hyperlinks. This organization allows users to browse to
different parts of the tutorial, open a database in a new
window to perform a practice search, and access other
features (Grant & Brettle, 2006). Tutorials in all their
iterations urge students to hone and develop effective
critical thinking skills. Short tutorials may also be
created on an organization’s intranet to educate
practicing professionals on a new policy, procedure,
organizational initiative, or healthcare technology.
Since the tutorial is electronic, access and time spent
on the tutorial can be easily tracked.

Case Scenarios
Professional organizations are increasingly
recommending performance-based assessments of
students in professional degree programs, and
enacting case scenarios provides an opportunity for
students to practice procedural responses and improve
patient safety. The case scenario, a form of problem-
based learning, has evolved and is now available
through simulation software and virtual reality
programming. This kind of learning assessment, in
which students must respond within context to a
perceived situation rather than a theoretical or fact-

based question, allows educators to gauge procedural
knowledge; it allows them to determine how well a
student executes a skill or applies concepts and
principles to specific situations (Garavalia, 2002). For
example, in a clinical context, a student could explain a
specific procedure, but such knowledge is declarative
rather than procedural and, therefore, for some
evaluators, not as valuable. Conditional knowledge is
often also reflected in procedural knowledge,
demonstrating a student’s ability to know when and
why action is or is not taken, and how. As more
programs move toward interprofessional education,
case scenarios are a great way for students to hone
collaboration skills and gain understanding of the roles
of other professionals.

Portfolios
Viewed in the 1980s as realistic evaluative tools of
student accomplishment and learning, portfolios in
healthcare professional education are growing in
popularity as useful tools for documenting students’
exposure to educational experiences. A portfolio
allows a student to document a variety of sometimes
unquantifiable skills, such as creativity, communication,
and critical thinking. Further, portfolios can reflect
achievement of goals, self-evaluation, and professional
development, also providing a way for returning
students to log and document past work or life
experiences in a creative but structured way without

taking a standardized test. The usefulness of a portfolio
for an undergraduate depends on a structured system
of organization: an identification page with a résumé, a
table of contents, separate and clearly marked
sections, and so forth. In this way, portfolios can
monitor program outcomes, positively influence
employment and graduate school admission, and
provide a clear snapshot of a student’s strengths and
abilities. See Box 19-1 for an overview of electronic
portfolios, and specific information on developing a
professional portfolio.

Box 19-1 WHAT IS AN ELECTRONIC

PORTFOLIO?

Glenn Johnson and Jeff Swain

Today’s information technology infrastructure
allows users to easily build Web-based
collections that include evidence of their
knowledge and skills. Users can upload artifacts
that represent evidence of their learning
experiences both inside and outside of the
classroom. Electronic portfolios (e-portfolios)
may also contain a blog element where students
reflect on their total experience and demonstrate
growth in their areas of study.

E-portfolios can be built using a range of
different technologies. Some individuals use

PowerPoint presentations to capture and
present evidence. Web-based e-portfolios are
built using common Web publishing tools to
create webpages, such as Web 2.0 or open
source tools; the webpages are then published
on the Internet (Barrett, 2012). In addition, an
increasing number of institutional e-portfolio
systems have emerged through which users can
log in and then upload, enter, and share
information or evidence related to their
experiences. Examples of such systems include
the following:

Association for Authentic, Experiential and
Evidence-Based Learning: www.aaeebl.org
Digication: www.digication.com
Facebook: www.facebook.com
iWebfolio: www.iwebfolio.com
LiveText: www.livetext.com
MySpace: www.myspace.com
PebblePAD: www.pebblepad.com
TaskStream: www.taskstream.com/pub
TypePad: www.typepad.com

WHY CREATE AN E-
PORTFOLIO?
Although academic institutions may use e-
portfolios for assessment of student learning, for
the individual, e-portfolios are all about

opportunity. Such opportunities might include
supporting a working relationship with a mentor,
networking with other professionals, or
representing certain qualities and characteristics
to prospective employers. In all of these cases,
having gone through the process of developing
an e-portfolio requires critical examination of
which qualities make individuals who they are
and why these qualities are important to them
and their profession. It is important for all
professionals to have a foundational
understanding of where they are in their career
trajectory and how this fits their long-term
professional goals.

Practically speaking, e-portfolios are efficient.
When introducing oneself in an email message,
a self-starting individual who has taken the
initiative to develop and publish an e-portfolio
can add this line to the message: “Here is a link
to my e-portfolio.” The recipient can click on this
link, which automatically opens that individual’s
e-portfolio in a Web browser. Metaphorically, the
senders of such messages have just walked into
the recipient’s office with information that
illustrates who they are, what they know, what
they can do, and what they value as important;
they have just walked in with what could be a
multimedia showcase of their qualities. The
Internet is a very powerful communication

medium, and individuals with professional e-
portfolios are simply taking advantage of this
fact.

E-PORTFOLIOS IN HIGHER
EDUCATION
As an instructional strategy, portfolios have been
around for a long time. Instructionally, portfolios,
whether electronic or paper based, require
students to demonstrate or provide evidence
that they have attained specific learning
outcomes. For instance, in the arts, portfolios
have been used to demonstrate the depth and
breadth of the work of an artist. Although
performance-based programs of study are more
likely to be familiar with the concept of the
portfolio as a demonstration of what a student
knows and can do, other areas of study have
also begun to adopt this method of assessment.

Portfolios can be particularly helpful in areas
where higher-level thinking and analysis are
essential. For instance, being a good healthcare
professional encompasses much more than
simply being able to get high scores on
examinations. Professionals need to be able to
collect information, analyze the information
presented, relate it to past experience, apply
related knowledge, and evaluate various

options, and from this present a diagnosis and a
plan of action. In short, healthcare professionals
need to be able to think critically and make
informed decisions. In learning to become a
healthcare professional, portfolios can be used
to capture, support, and improve this type of
thinking as it develops.

Like the artist, the healthcare professional
student can connect, share, and present cases
and findings and include with this evidence the
reflective commentary that serves to unveil
how he or she arrived at a decision, which
information or experiences were vital, and how
his or her action plan evolved. However, given
the vast variety of evidence that individuals
might potentially use to represent themselves,
what should one select and how should this be
shared?

E-PORTFOLIOS FOR PROFESSIONAL
DEVELOPMENT

Using an e-portfolio to support professional
networking involves a predetermined and
focused purpose. This purpose may be to foster
better communication between oneself and a
mentor, or it may be to establish how what a
professional is doing fits with the goals of the
institution or perhaps an institution for which the
individual would like to work. A professional e-

portfolio is evidence based and uses this
evidence to make a case that highlights the
individual’s capacity not only to perform, but also
to grow and develop professionally, within his or
her chosen field.

THE E-PORTFOLIO PROCESS

The four steps involved in developing an e-
portfolio are recursive in nature, meaning that
during the process one can backtrack to fill in
missing pieces or reevaluate earlier decisions
that were made. The four steps are (1) collect,
(2) select, (3) reflect, and (4) connect. See
Figure 19-4 for an image of the portfolio
creation process.

Figure 19-4 Portfolio Creation Process

Collect

Evidence should demonstrate what a person
knows, what he or she can do, or the values that
the person holds as being important. When it
comes to developing e-portfolios, it is important
to think of evidence in very broad terms. This
evidence might include the results of what
someone has learned in courses taken as a
student, especially in terms of demonstrating a
new skill or increased knowledge of a subject.
More importantly, evidence can come from
experiences that take place outside of the
classroom. For instance, someone may have
been involved in an internship or clinical
observation where he or she had the opportunity
to connect what was learned in the classroom
with how this information is applied in a real-
world setting. Not only is such an experience
valuable, but it also represents the individual’s
understanding of how this knowledge can be
applied; thus it enhances others’ perception of
the depth of what the person knows.

Résumés are evidence documents. They are
very important, and every professional should
have an updated copy available. However,
résumés simply list an individual’s experiences
or accomplishments. E-portfolios, by
comparison, go beyond the résumé to
emphasize personal attributes that are very

important in the specific profession. These
attributes include, but are not limited to,
interpersonal skills, leadership skills,
appreciation of diversity, ability to work in a
team, and self-sufficiency. These attributes are
difficult, if not impossible, to demonstrate in a
résumé. When reflective commentary
accompanies evidence of an individual’s
involvement, these attributes and values can
become the highlights of an e-portfolio.

Select

Everyone has his or her own unique pool of
evidence from which to pull, and over time this
evidence pool can become quite large. What will
someone choose to feature and why? Putting
together a professional e-portfolio requires that
two intertwining questions related to purpose
and audience be addressed.

What is the purpose? What is it that someone is
attempting to gain by putting an e-portfolio
together? Is the purpose related to personal
development (i.e., feedback and advice about
the professional direction that is being taken)? Is
the purpose to connect with colleagues? An
individual may, for example, be interested in
using his or her e-portfolio to find a job or to gain
admission into a graduate program.

Although an e-portfolio can link to everything
that a person has accomplished, this may not be
the best strategy. Instead, it is essential that an
individual consider the audience and establish a
plan that enables the person to select the most
appropriate pieces of evidence for his or her
particular purpose and audience. A helpful way
to start is to select the top five pieces of
evidence that support the plan. Next, the
individual should consider why he or she
selected these pieces of evidence. What is it
about each piece of evidence that makes it
representative of who the individual is, what he
or she knows, what he or she can do, and what
he or she values as important?

Reflect

Reflection and reflective commentary take an e-
portfolio to the next level. This component may
take the form of a single reflective statement, or
it may be attached to the evidence throughout
the e-portfolio. Reflective comments should
open up a window into why an individual thinks
this evidence is important, the ways in which the
individual values what he or she learned, or why
the person thinks it is important for the larger
profession. For instance, the individual may
present an experience where he or she was
challenged to provide assistance. Describing

this experience would be important; however,
the reflective comments can extend this
description, enabling the person to talk about
the alternatives considered as the basis for how
he or she made a decision to provide the
specific type of assistance and the manner in
which it was provided. By itself, a description of
this experience is good. With reflective
comments, readers have a much more thorough
perception of and insight into an individual’s
professional thinking. This is where having a
blog element as part of an e-portfolio becomes
extremely powerful.

Unlike static webpages, a blog page is a space
designed to be interactive. The blog owner posts
commentary, thoughts, and experiences for
others to read and respond to. Regular entries
on a blog give others a reason to return to one’s
e-portfolio site over and over again. It is an
opportunity to share one’s perspective on topics
of interest and critical to the chosen field. A blog
is a place where conversation happens. It
provides a nice counterbalance to the static
webpages, such as a résumé and project
pieces.

Most blogging platforms allow users to select
from a range of templates that include a
blogging element along with static webpages.
Such platforms as WordPress, Moveable Type,

and Google are free for at least the basic
service, enabling the user to create a dynamic
e-portfolio without having to build webpages.
Most platforms allow entries to be in both text
and multimedia format, so the blog becomes the
perfect place for personal expression. A blog is
quickly becoming a standard part of an e-
portfolio.

Connect (Connections) and Feedback

The connection and feedback step is important
to validate the assertions someone makes about
what it is he or she knows, understands, or
values. Individuals may choose to receive
feedback from those who are close to them and
from here reach out to others who may provide
different perspectives. For instance, if a
healthcare professional was thinking about
using his e-portfolio to apply for a position, he
might want to start by first getting feedback from
friends and family. He might also share his e-
portfolio with a mentor or faculty member,
raising the bar by getting professionally
grounded feedback before sharing the e-
portfolio with a prospective employer.

CHALLENGES AND ISSUES:
PRIVACY AND SECURITY

The ease and popularity of both Web-based
social networking and professional e-portfolio
tools also raises several challenges and issues
for users. Never before has information for
individuals been so accessible, and never
before has such personal information been so
readily made public. For this reason, issues
related to privacy and security need to be
addressed. What might be appropriate socially
can be deadly in a professional context.

E-PORTFOLIO PROCESS:
SUMMARY COMMENTS
In summary, one might think about the process
of developing a professional e-portfolio as
boiling down to the telling of a rather simple
story, albeit a story that has three parts: looking
back, looking around, and looking ahead.
Readers should think of their own evidence pool
as they answer these questions:

1. Looking back: What have you done? In
which activities and with which
organizations have you been involved?
Where have you been? With whom have
you worked? How did this help get you
where you are today?

2. Looking around: In what are you currently
involved? Why are you doing this? What

are you getting out of it?
3. Looking ahead: Where would you like to

be in 2 years? Where would you like to be
in 5 years? Why do you feel this way?
What makes you think your goals are
realistic?

REFERENCE

Barrett, H. (2012). ePortfolios.
Retrieved from
http://www.electronicportfolios.org/eportfolios/index.html

Simulations
Used within healthcare circles for more than 15 years,
simulations in nursing education have experienced a
recent upsurge in popularity, in part due to the more
widespread availability of high-quality simulation
equipment and a reduction in price for this technology.
Ranked by fidelity, or the level of realism the equipment
resembles, simulation may take various forms: from
computer-based simulation, in which software is used
to simulate a subject or situation (e.g., an interactive
tutorial featuring a nurse–patient situation), to full-scale
simulation, in which all the elements of a healthcare
situation are recreated using real physiology, people,
and interaction to resemble an environment as closely

as possible to immerse students in the experience
(Seropian, Brown, Gavilanes, & Driggers, 2004).
Simulation scenarios aid nursing instructors in
assessing competency achievement. For a more
comprehensive discussion of simulation as a
teaching/learning tool, please see Chapter 20,
Simulation, Gaming Mechanics, and Virtual Worlds in
Nursing Education.

Virtual Reality
In traditional virtual reality, the user receives multiple
sensory inputs, either mediated or generated by a
computer, through visual stimulation (glasses, goggles,
and screens), audio input (earphones, microphones,
and synthesizers), and touch (smells, gloves, and
bodysuits). A form of simulation training once
considered a science fiction technology of the future,
the use of virtual reality healthcare training is
increasing.

Because virtual worlds foster unintentional learning
through gamer-like technology in which students
discover and create knowledge to accomplish
something, rather than experiencing traditional
outcome-based learning, their experiences may result
in greater comprehension and deeper knowledge. In a
virtual clinical scenario, for example, a simulated,
immersive environment presents invaluable learning
opportunities for the student who is assuming the role

of healthcare provider. Faculty can monitor the
interaction and interrupt as necessary to provide advice
or suggestions, while students negotiate the real and
virtual world components of the scenario and their
avatar patients, thereby becoming aware of how, why,
and when to apply specific skills within a clinical setting
(EDUCAUSE, 2006).

Because so much of the data nurses rely on are
complex, and so many patient cues are lacking in
concrete language or responses, the animated,
immersive, three-dimensional environment of virtual
worlds allows students to practice skills, try new ideas,
and learn from their mistakes while receiving feedback
from educators within a globally networked classroom
environment. Virtual reality tools are a great way to
implement competency-based education. Some
students may struggle to participate in virtual
communities for various reasons. Increasing comfort
with multidisciplinary learning among students and
educators improves patient safety and encourages the
refinement of best practices for effective integration of
these tools into mainstream education (EDUCAUSE,
2006). Chapter 20, Simulation, Gaming Mechanics,
and Virtual Worlds in Nursing Education, provides a
more comprehensive discussion of this technology.

Internet-Based Tools

The general consensus in nursing education suggests
that any technology that allows users to interact and
engage both materials and one another is useful. More
specifically, the Foundation of Knowledge model
qualifies this observation with the caveat that
technology must display user-friendly capabilities to
provide benefits to its users, thereby allowing students
not just to find information and one another online, but
also to engage, challenge, and institute their
discoveries. Providing nursing students with easy-to-
use, free Internet tools for reaching the first step in this
process (gaining access to materials and peers) has
been addressed by the proliferation of communication
technologies available to any user with an Internet
connection. Beyond the gadgetry, with the
development of new strategies, practices, applications,
and resources in technology comes the need for
instructional strategies that not only appeal to this
newer generation of students, but also enhance
learning. Such strategies, when coupled with easily
accessible and highly functional tools, encourage
nursing students to see beyond the right answer and to
seek out information that encourages them in
developing approaches to issues and resolutions for
problems (Bassendowski, 2005).

Digital Books (eBooks)
While most instructors continue to assign print
textbooks for course content reading, there is a clear

trend toward the development and use of digital books.
As Denoyelles, Raible, and Seilhamer (2015)
explained, “While some e-textbooks simply reproduce
the print experience, others leverage interactive
capabilities such as simulation, polling, discussions,
and learning analytics” (para. 1). Affordability is one
key advantage of eBooks. There is also the possibility
of embedded content in the eBook that could provide a
link to a multimedia video or a website. Unfortunately,
the availability of quality eTexts in many disciplines is
lacking. It is a trend worth following in the future.

Webcasts and Webinars
A webcast is a broadcast of a typically live
presentation delivered by way of the Web. Webcasts
offer great potential for helping students and faculty to
engage both information and one another globally, by
tapping into students’ multiple intelligences to enable
them to access what they need. Because of the
growing ease of producing streaming video and
subsequently delivering it via larger bandwidth,
Webcasts have grown in popularity and are especially
favored by programs that feature distance education
components. Although some institutions create their
own Webcast delivery system, most users rely on a
few standard providers that, in turn, present the
Webcast online. Although these presentations are
often delivered live, allowing audience members to
participate in the broadcast, many instructors use

Webcasts as an access point for prerecorded archives
of lectures and presentations by experts whom their
students would not otherwise have the opportunity to
see or hear. Studies show that students
enthusiastically embrace Webcast technology,
accessing archived presentations more repeatedly than
traditionally filmed sessions of guest lecturers; this
dynamic level of engagement aids students in better
grasping the subject matter. Like much dynamic
technology, Webcasts are an innovative component
that keeps students engaged but tends to work best
when learners are provided with learning outcomes
before viewing them (Bell, 2003).

A webinar is a Web-based seminar that uses Web
conferencing software that allows educators to share
their computer screen and files and interact with their
students. According to Moreau (2013), “depending on
what type of webinar service you decide to use, there
are interactive sections that the audience can use to
ask questions” (para. 5). Webinars are typically
delivered live but can be recorded. Moreau equates
this presentation form to Skype. In our geographically
dispersed, online world of learners, webinars provide
another avenue for sharing and collaborating.

There is a key difference between webcasts and
webinars. Webcasts present material to the audience
with limited or no interactivity. By comparison, webinars
are generally live, interactive, educational sessions.

Both of these venues provide access to the educator
and, depending on the level of interactivity, sometimes
to other learners.

Searching
One of the most common and proliferative search tools
in technology today is the wiki. Wikis are websites or
hypertext document collections that allow users to edit
and add content in an open-ended forum. The appeal
of (and objection to) wikis resides in their ability to let
anyone with an interest and an Internet connection
participate in a once-exclusive community of
knowledge creators and seekers. As an environment
that encourages practice and learning, wikis support
learning communities where students collaborate
online (Skiba, 2007). Higher education has evolved
from a place of straightforward knowledge transmission
to a place where one strives to become a member of
an expert community, and wikis promise to create
opportunities for individuals to participate in this
community in heretofore untapped ways.

The most objectionable aspects of wikis are their lack
of organizing principle (many are organized
alphabetically) and the ability for anyone to edit entries,
the latter of which creates new intellectual property
right challenges. Wikipedia, for example, is the best-
known wiki project on the Web; it is an online
encyclopedia of sorts whose open access policy

regarding its content keeps educators and
professionals wary of inaccurate information to be
found there (Skiba, 2007). Wikipedia works well as an
initial source of information on a topic or as a quick
overview reference, but it should not be relied on as a
sole source of information. For more information on the
appropriate use of Wikipedia, see this online tutorial:
https://libraries.psu.edu/how-use-wikipedia-tutorial.

Instant Messaging
Instant messaging, one of many collaborative Web
chat tools available to any user with a computer and
Internet access, continues to establish itself as a
working, useful tool for informatics learning, providing
instant access to and communication among people,
information, and technology. Although some instant
message (IM) services provide voice and video
messages, all instant messaging clients provide text in
real time, allowing users to interact in the form of an
on-screen conversation through a technology that is
free, is already quite popular with users, is Web based,
does not require additional hardware or software, and
has a very low learning curve for those few to whom it
is unfamiliar. Beyond having a real-time conversation,
instant messaging (IMing) an individual allows the user
to share links, pictures, and files. This kind of easy
accessibility allows students, when logged on, to
collaborate; seek real-time help from professors or
librarians; and engage others working on questions,

studying for clinical examinations, or reviewing
information or notes (Chase, 2007).

Chats and Online Discussions (Blogs)
Real-time chats occur all over the Internet, at each
hour of every day. The best-known chat tools are
instant messenger clients, but chatting also refers to
real-time discussion venues in which users meet in
virtual chat rooms to engage in conversations by
posting messages; this provides a comfortable,
recognizable way of communicating for Net Generation
students used to surfing the Web and interacting
online. In a chat, students can meet, discuss, and
engage one another over any given topic. Chats take
various forms, the most complex of which involve
highly evolved virtual communities in which users step
into various rooms where they interact with other
individuals who are in the room at the same time.
Initially the exclusive purview of gamers or hardcore
programmers creating private online communities, chat
rooms now exist for a wide variety of topics and
interests.

Web logs, also known as “blogs,” have emerged as
low-investment and easy-to-use writing tools that,
through their very setup and appearance, enhance
health professionals’ communication, writing, reading,
information-gathering, and collaboration skills (Maag,
2005). Blogs are a kind of online journal, created by

individuals who then invite comments from visitors to
that Web space. Compared to technically complex
online projects, such as tutorials and various
multimedia, blogs are immediate, free to set up and
access with an Internet connection, and easily
negotiable by even the technically ambivalent. By their
very nature, blogs present a built-in discussion area to
the user, so they are especially useful for study groups
interested in reflecting on material and evaluating ideas
in a collective, collaborative way (Shaffer, Lackey, &
Bolling, 2006). Blogs are a great way for students and
professionals to reflect on and share clinical
experiences and questions with each other. It is
important, however, to be mindful of protecting private
health information and share within the confines of
HIPAA guidelines.

Electronic Mailing Lists
One low-investment information-gathering tool for use
by nursing professionals is membership in an
electronic mailing list. These electronic discussion
groups use email to communicate and promote
communication and collaboration with others interested
in a particular field of study (Hebda & Czar, 2013).
Electronic mailing lists have very few requirements to
participate—usually just a free subscription and email
capability. Such lists are available on any subject, but
most share common features, such as the need to
subscribe and then log in to participate. The

moderators of an electronic mailing list have specific
instructions on how to post messages and how to set
subscription controls. Posting information means that
when a user replies to a topic thread, he or she
generally has sent information to every member of the
list. Like other technologies, the capabilities of
electronic mailing lists continue to change and expand,
providing ongoing viability for use in nursing education.

Portals
Similar to electronic mailing lists in the way they deliver
specific information to one’s email, a portal allows the
personalization of a specific website. Portals organize
information from webpages into simple menus so that
users may choose what they want to view and how
they want to view it (Hebda & Czar, 2013). For
example, WebMD is one of the most popular and best-
known portals, allowing users to create accounts,
bookmark their favorite information, and sign up for
email notifications. Portals, like most Web
technologies, require an Internet connection and a free
subscription that allows the user to log in. Portals rely
on the registration of users in order to collect
information from them to personalize features for each
individual user (Hebda & Czar).

Podcasts: Audiopods and Videopods

A podcast is an audio recording linked to the Web that
is then downloaded to an MP3 player (Gordon, 2007),
a smartphone, or a computer where the listener then
accesses the recording or video. An outgrowth of the
Apple iPod market, podcasts are developed and
delivered by way of the Internet and require minimal
investment—namely, a microphone, an Internet
connection, and (often free) editing software.

Beyond possibilities for global accessibility to whatever
information the user may record, podcasts allow for
automatic updates in the form of a really simple
syndication (RSS) (also known as “resource
description framework (RDF) site summary”) feed
that lets subscribers receive automatic notification
whenever a podcast is updated (Gordon, 2007). Refer
to Box 19-2 for more information.

BOX 19-2 PODCASTS

Jackie Ritzko

A basic Web search using the search term free
nursing podcast produced over 1 million hits on
one search engine. But what does this mean in
the context of nursing informatics? The
implication is that there are many resources on
the Internet that somehow involve podcasts with
a nursing focus. How these sites might be of use
to a professional in the nursing field is the focus

of this feature. Before any discussion of the
educational uses of a technology tool can take
place, however, there needs to be an
understanding of the hardware, software,
training, and support that are required to use the
tool, as well as the history of the development of
the tool.

Podcast is a term coined from the words iPod
and broadcast. iPod is the name given to a
family of portable MP3 players from Apple
Computer. MP3 is a common file format for
electronic audio files. Audio files—in particular,
MP3 files—can contain verbal speech, music, or
a combination of both. MP3 files can be played
or listened to using an MP3 player. MP3 players
can be portable devices, such as the iPod, or
simply software that is installed and used on a
computer, tablet, or smartphone. Thus a podcast
is simply an MP3 file that can be played on an
MP3 player. Broadcast, in its simplest usage,
refers to the ability to send out. In terms of
podcasts, broadcasting is the ability to share
MP3 files in such a way that the files are
delivered to the user whenever new versions are
available through a subscription. This ability to
share resources and access the most up-to-date
resources is a great advantage, especially for
the educational community.

We will now discuss podcasts in terms of

function, ranging from the more basic to the
more advanced functions: finding podcasts,
listening to podcasts, creating podcasts, and
sharing podcasts. Finding podcasts at a minimal
level requires only an Internet connection and a
Web browser. As noted earlier, a basic Web
search for the term nursing podcast found many
sites. Performing a basic Web search, however,
may provide a user with only limited search
capabilities. An MP3 aggregator is a program
that can facilitate the process of finding,
subscribing to, and downloading podcasts. One
popular aggregator is Apple Computer’s iTunes,
which is a free program available as a download
from apple.com. Although iTunes is widely used,
it is not the only program of this type. A program
such as iTunes gives the user the ability to
search for podcasts based on many criteria,
including category, author, or title. The iTunes
program provides access to audio downloads
that may be either songs or podcasts. In both
cases, users may find downloads that are free
and those that require payment.

Because podcasts are largely MP3 audio files
(Advanced Audio Coding [AAC] is a newer
format, but is not as widely used), an MP3
player is needed to listen to a podcast. As
noted, this can be done on a smartphone, a
computer with an MP3 player, or a portable MP3

player. Podcasts can be downloaded in two
ways: manually or by subscribing to a podcast.
In the case of a subscription, once a new track
is added to the podcast, iTunes automatically
delivers it to a computer. Continuing to use
iTunes as an example, once a podcast is found,
it can also be manually downloaded from iTunes
to a computer. Once on the computer, it can be
listened to or transferred to a portable device, or
accessed via a tablet or smartphone.

Users may also choose to produce or record
podcasts. As with most technology solutions,
hardware and software requirements typically
must be met to create podcasts. The hardware
for recording a podcast can vary. In a stationary
setup, a microphone can be connected to a
desktop or laptop computer. Stand-alone audio
recorders can also record podcasts, and some
MP3 players contain built-in recorders. Free
recording software is available for most
computer platforms.

Sometimes a podcast is created for the sole use
of the creator. More often, however, a podcast is
created with the intention of it being shared with
and listened to by others. Podcasts can be
stored on Web servers for distribution and can
also be shared via tools, such as iTunes. Within
iTunes, for example, educational institutions are

able to host podcasts in the area known as
iTunesU.

Podcasts have many uses in education in
general and in nursing education in particular.
Informal learning can take place when a nursing
student listens to nursing podcasts. Listening to
or creating podcasts may be a formal class
assignment, providing new ways to interact with
course material.

Short discussions of what is new in the field may
appear as podcasts on the Internet, in particular
on news and research sites. Learners may rely
on the portability of MP3 players to take learning
with them on the road. Commuters and walkers
and joggers are often seen listening to MP3
players. Because creating podcasts is relatively
easy and inexpensive, such presentations can
be produced by students as review files for
common terms or used as ways for students to
self-assess their ability to discuss topics. The
uses of podcasts from an educational
perspective are limitless.

Bringing the discussion of podcasts back to the
Foundation of Knowledge model, for each task
or process in the model, one can see how
podcasts fit with that concept. Podcasts can be
used to acquire new knowledge from sources on
the Web. Listening to podcasts provides

learners with another tool for learning in addition
to readings and lectures, thereby addressing a
wider audience whose members have varying
learning styles. Because podcast creation is
simple and inexpensive, podcasts are an ideal
way to generate and disseminate knowledge.

Audiopods

Audiopod is a term used to describe a traditional or
audio-based podcast. Participating in podcasting can
exercise not just basic technology skills, but also
writing, editing, and speaking skills. Writing scripts for a
podcast can be an excellent exercise in critical thinking
and information delivery, whereas the technology itself
allows global access to information by faculty,
teachers, and students anywhere at any time (Gordon,
2007). Both faculty and students can create audiopods
with little difficulty, and most use podcasts to share
additional class materials, updates, and even entire
lectures (Oblinger, 2005).

Videopods

Similar to an audiopod in setup and accessibility, a
videopod is a podcast that provides video in addition
to audio functionality. Faculty might use videopodcasts
to demonstrate concepts, interview experts in the field,
and even assess student progress (Gordon, 2007).
Libraries and other institutions have even begun using

the videopod as a learning alternative to the ubiquitous
and often mocked information video, finding that highly
mobile students are more readily embracing this
technology (Oblinger, 2005).

Multimedia
As technologically savvy students continue to demand
accessible, interactive learning tools to keep them
engaged, an increasing number of instructors are
experimenting with and incorporating multimedia into
their courses. Generally, multimedia refers to a
computer-based technology that incorporates
traditional forms of communication to create a
seamless and interactive learning environment, such
as interactive tutorials, streaming video, and problem-
solving programs. Nursing education has long relied on
traditional multimedia, such as slide presentations,
overhead projections, and training videos, for
continuing education (CE) of staff, classroom
learning, and patient education (Edwards & Drury,
2000). Now, however, new advances in multimedia
allow faculty to add such innovations as simulations
and virtual reality to their healthcare training, providing
a way for students to learn procedural skills, such as
insertion of needles and physical assessment, without
any risks to an actual patient.

Research suggests that the seeing, hearing, doing, and
interacting afforded by multimedia facilitate learning

retention, with multimedia being at least as effective as
traditional instruction, but offering the benefit of greater
learner satisfaction. Authoring software—that is,
programs that allow users of varied technical skill to
design and create webpages and movies—has greatly
facilitated the use of multimedia by faculty (Hebda &
Czar, 2013). Nevertheless, the most effective
multimedia relies on the careful and pedagogically
appropriate combination of textual material, graphics,
video, animation, and sound (Edwards & Drury, 2000)
—a distinctly separate skill set from teaching and
instructing. Some schools of nursing have instructional
designers on staff to assist nursing faculty with the
development of multimedia to support learning.

Beyond providing a flexible method of delivery for
instructional information, multimedia promises to
motivate students by requiring them to analyze
evidence in ways that require higher-order thinking and
problem-solving skills. Similarly, faculty can begin to
think about their classes in new ways and
accommodate different student learning styles
(Oblinger, 2005). Box 19-3 provides an overview of
the capabilities of smartphones and their use in
education.

BOX 19-3 SMARTPHONES AND OTHER

SMART DEVICES IN NURSING

EDUCATION

Dee McGonigle and Kathleen Mastrian

Smartphones are another tool for the
educational arena. As Yu (2012) stated, “Smart
phone technology, with its pervasive acceptance
and powerful functionality, is inevitably changing
peoples’ behaviors” (para. 6).

Our educational uses of a technology such as
smartphones cannot only affect the learning
episode but also influence how we prepare
students to embrace and use technologies
appropriately. As educators, we want our
students to remain competitive in a highly
technologically dependent world. Nursing is a
data- and information-driven profession, and
nurses must rely on technologies to provide the
data and information necessary to provide safe
and high-quality care to our patients.

If students have smartphones, we can share
text, graphics such as PowerPoint
presentations, podcasts, and other audio/video
media with them prior to the learning episode.
When all students have access to the same
information, it enhances the dialogue and topical
discussion centered on that information. Nursing
educators can use smartphones to distribute
announcements, reminders, and even pertinent

notes that the students need. Students can also
be polled using these devices. Smartphones can
even replace huge textbooks with electronic
files. Smart devices and their calendars and
messaging features help both educators and
students organize their lives and keep their
hectic schedules straight. The use of smart
technologies can facilitate interactions around
the world. Students can consult with other
students and experts from anywhere on the
globe. As this brief list of applications suggests,
we have only just begun to think of ways in
which to incorporate smartphones into our
learning episodes.

In conclusion, we would like to leave you
thinking about a money-saving alternative for
many schools. Instead of requiring a laptop
computer, what if your school required every
student to have a smartphone? Could we
replace the expensive computer labs on our
campuses while better connecting our online
and blended students to their educational
milieu?

REFERENCE

Yu, F. (2012). Mobile/smart phone
use in higher education.
Retrieved from
http://www.swdsi.org/swdsi2012/proceedings_2012/papers/Papers/PA144.pdf

Promoting Active and
Collaborative Learning
Because of the shift within the teaching–learning
context from the individual seeking answers to the
group trying to construct new knowledge from available
information, the most effective learning solutions
require new digital communication skills, new
pedagogies, and new practices (Costa, 2007). A
collaborative, student-centered approach uses the best
tenets of inductive teaching by imposing more
responsibility on students for their own learning than is
assumed in the traditional lecture-based deductive
approach. These constructivist methods are built on
the widely accepted principle that students are
constantly constructing their own realities rather than
simply absorbing versions presented by their teachers.
Collaborative methods often involve students’
discussion of questions and in-class problem solving,
with much of the work (in and out of class) done by
students in groups rather than individually (Felder &
Prince, 2007).

Johnson and Johnson (1990) have identified five
significant elements for successful collaborative
learning that are still pertinent today:

1. Face-to-face interaction between students,
allowing them to build on one another’s
strengths

2. Mutual learning goals that, in turn, prompt
students to exhibit positive interdependence
rather than individualized competition

3. Equal participation in the work process and
personal accountability for the work one
contributes

4. Regular debriefing sessions as a group after
meetings or presentations during which time
feedback is shared and observations analyzed

5. Use of cooperative group process skills learned
in the classroom

Although collaborative learning relies heavily on
student investment and participation, institutions must
ultimately create the best physical and electronic
settings where collaboration is encouraged. This can
be achieved with a sound educational and technologic
infrastructure, reliance on proved working models,
adaptable physical spaces, and even pedagogic
support in the form of preceptors or mentors.

Especially useful for nursing students is the
collaborative fieldwork model in which two or more
students share a clinical setting and the same fieldwork
educator. In this model, learning happens in a
reciprocal fashion, with students constructing
knowledge by watching each other and exchanging

ideas. The most effective fieldwork experiences are
highly structured with clear outlines of responsibilities,
duties, and expectations, ensuring that the experience
matches the learner’s expectations. All activities
performed by students, such as conducting
evaluations, are done jointly, so that peers provide
each other with objective feedback, leading to eventual
increased self-confidence (Costa, 2007). In this way,
suggests Costa, individuals with different viewpoints
and experiences create a space where new knowledge
emerges and existing knowledge can be restructured
(as cited in Cockrell, Caplow, & Donaldson, 2000).

Libraries have also begun to recognize their role in
students’ success with and predisposition toward
collaborative learning by creating redesigned spaces
that reflect students’ need to huddle in small groups, sit
closely together without barriers, chat about their work,
and view digital information without physical
hindrances, such as carrels or work stalls. A leader in
this movement has been Indiana State University,
whose new information commons features completely
overhauled furniture, software, monitors, processing
power, and wireless access to the university’s network.
Students can now collect as a group at kidney-shaped
tables; better see the information loaded on the flat-
screen monitors; make use of brainstorming, design,
and planning software; and discuss their work in a
chat-friendly zone. Some faculty members have even
scheduled classes at the learning stations, and

students, including those in nursing, have responded
enthusiastically to the evolved space (Gabbard,
Kaiser, & Kaunelis, 2007).

In addition to adaptable physical spaces that
encourage discussion and group work, students
require a supportive infrastructure that provides
essential elements necessary to successful research
and scholarship. These include professional
development support in the form of workshops that
help students acquire or refresh skill sets; presentation
opportunities; and hardware, software, and resource
support. One such example involves the participation
by nursing students at the University of Texas Medical
Branch School of Nursing in the Scholarly Talk About
Research Series (STARS), in which students and
faculty give presentations of their work before
presenting those materials at professional conferences
(Froman, Hall, Shah, Bernstein, & Galloway, 2003),
thereby eliciting collegial feedback, collaborative
troubleshooting, and shared research ideas. Imagine
how powerful such a process would be in a cross-
discipline healthcare education school.

Simply adopting a collaborative, inductive method of
learning, however, will not necessarily lead to better
learning and more satisfied students. As with any form
of instruction, collaborative teaching methods need
skilled and careful implementation. Because students
are initially often resistant to instruction that makes

them more responsible for their own learning, those
who attempt to implement an inductive learning method
should adhere to best practices, such as providing
adequate scaffolding—that is, extensive support and
guidance when students are first introduced to the
method and gradual withdrawal of that support as
students gain more experience and confidence in its
use (Felder & Prince, 2007).

Nursing preceptors and mentors, for example, can
provide this kind of scaffolded support as clinically
active role models (Armitage & Burnard, 1991) and
problem-solving advocates and collaborators (Gagen
& Bowie, 2005). As individuals who are primarily
concerned with the teaching and learning aspects of
the relationship, preceptors help students learn by
acting as clinical practitioner role models from whom
the students can copy appropriate skills and behaviors.
Kramer (1974) introduced the concept of nurse
preceptor to address the theory and practice gap—that
is, the difference between what is taught in class and
what actually happens in nursing practice. Preceptors
enhance clinical competence through direct role
modeling, which is especially valuable in a field where
competence and clinical ability are paramount
(Armitage & Burnard, 1991). Mentors, similar to
preceptors, provide equally valuable assistance to
nursing students in the form of a facilitator. Mentors are
most often used in nursing and education to support
new professionals who are trying to fulfill the rigors of a

new position while negotiating the stress inherent to a
new environment (Gagen & Bowie, 2005). According
to Jokelainen, Turunen, Tossavainen, Jamookeeah,
and Coco (2011), “student mentoring in nursing clinical
placements integrates environmental, collegial,
pedagogical and clinical attributes” (para. 6). Mentors
tend to address student needs through open
conversation, student advocacy, feedback on student
progress, facilitation, teaching, and general support
(Neary, 2000).

Generally, these and other forms of institutional support
promote students’ adoption of a meaning-oriented
approach to learning, as opposed to a surface or
memorization-intensive approach. Collaborative,
inductive learning promotes intellectual development
that challenges the dualistic thinking that characterizes
many entering college students, which holds that all
knowledge is certain, professors have it, and the task
of students is to absorb and repeat it (Felder & Prince,
2007, p. 55). Further, this kind of learning helps
students acquire the self-directed learning and critical
thinking skills that characterize the best scientists and
engineers (Felder & Prince, 2007). The active,
engaging elements of collaborative learning increase
self-confidence, promote autonomy in students, and
foster a commitment to lifelong learning (Costa, 2007)
—all necessities for the success of a new millennial
information-literate student.

Knowledge Dissemination and
Sharing
Sharing stories and experience from a clinical point of
view accomplishes much more than simply promoting
camaraderie or empathy (although this kind of
engagement is infinitely valuable in its own way);
sharing experiences of clinical learning can help
convey life-saving information to other clinicians in a
way that is more memorable and palatable and less
imposing than warnings delivered outside a social
context. Clinical and caring knowledge, often rooted in
everyday exchanges, become socially embedded such
that those with experience in particular clinical settings
share common knowledge and understanding. The
social embeddedness of caring and clinical knowledge
is a result of shared and shaped collective
understanding of practice and sometimes provides an
alternative view.

The power of pooled knowledge in combination with
knowledge produced in dialogue with others helps to
limit tunnel vision and is a powerful strategy for
maximizing the clinical knowledge of a group. Whether
the nurse is networking, presenting, or seeking CE or
recertification, an understanding of socially embedded
knowledge coupled with the multiple perspectives of
skilled practitioners allows for a rich and vibrant

opportunity to apply nursing skill effectively (Benner,
Tanner, & Chelsa, 1997).

Networking
Considered crucial to career development because of
opportunities for collaboration and information
exchange, networking encourages professional support
by making successful professionals accessible to their
colleagues. Further, developing interactive professional
networks between academic and clinical nurses can
benefit practice in diabetes, stroke, and mental health
care, and in community nursing—a field where
practitioners are encouraged to collaborate
(Gillibrand, Burton, & Watkins, 2002).

The value of networking to members of male-
dominated professions, such as law, business, and
medicine, resides in opportunities to make contact with
fellow professionals and, in turn, further one’s career.
This observation is especially poignant for nursing, a
predominantly female profession that, until recently,
has rarely reaped the benefits of formal networking
(Nicholl & Tracey, 2007).

Because nurses tend to gather their information from
personal networks, such as colleagues or professional
meetings, the increased availability of technology to
assist in networking has greatly facilitated information
exchange. Blogs, email, websites, electronic mailing

lists, and other communicative technologies have
opened up an endless stream of collaboration and
networking possibilities, allowing nurses to more easily
access and learn from colleagues’ experiences. Using
the Internet allows for the discovery of information
heretofore unavailable through traditional information
sources (Pravikoff & Levy, 2006), helping nursing
professionals decide whether, for example, pursuing
research opportunities or collaboration on specific
professional projects seems viable.

Formal networks, such as the International Nurse
Practitioner/Advanced Practice Nursing Network
(INP/APNN), unveiled in 2000, promote the exchange
of knowledge, resources, and expertise in an effort to
enhance the presence of nursing in primary health
care. Created in response to the globalization of nurse
practitioner and advanced practice nursing network
(APNN) roles, the network enables the enhancement
and advancement of practice both for countries just
beginning to initiate advanced practice nursing (APN)
roles and for those with experienced practitioners
(Affara, Cross, & Schober, 2001).

Membership and participation in professional
associations also provide ways to network and
advance one’s profession. Professional associations
represent venues through which members may set
standards for professional practice, establish codes of
ethics, become involved in advocacy, engage in CE

opportunities, access job banks, subscribe to
professional journals, and act as a common voice for
the profession. For example, the American Nursing
Association of Occupational Health Nurses is
instrumental in maintaining healthcare issues on the
political agenda. There are also several opportunities
for nurses to network in specific informatics
associations, such as American Nursing Informatics
Association (ANIA) and the nursing work group
associated with HIMSS. Research shows that nurses
sometimes hesitate to join professional organizations
because of barriers associated with cost, distance to
meetings, lack of activities in their geographic area,
and inability to attend meetings. Because networking
creates fertile areas for the development of new ideas,
partnership, jobs, and strategies, both national and
state associations would benefit from creating greater
opportunities for healthcare practitioners to earn CE
credit and network with others in their field (Thackeray,
Neiger, & Roe, 2005).

Presenting and Publishing
Much in the way the AACN maintains standards for
nursing education, professional journals also hold their
contributors to similarly rigorous standards and provide
a valuable venue in which nursing professionals might
share ideology and innovations in the field. With the
proliferation of online journals and the availability of
nursing information via multiple media, publishing

remains an excellent way to participate in the
dissemination of professional information. Both nursing
magazines and journals reach considerable audiences;
journal distinctions lie in their authorship and audience.
Although journal articles are written by and for
scholars, with refereed or peer-reviewed journals
requiring a blind review by a group of reviewers to
eliminate bias, magazine articles may be written by a
professional in the field, an editor, freelancer, or other
author. Publishing provides excellent opportunities to
extend knowledge and share research.

Similar to publishing, making presentations at
contemporary professional conferences allows nursing
educators and students to gain experience and share
scholarship with colleagues. Presentations must meet
certain standards for an audience to find them credible
and effective. Because an audience retains 50% of
what they see and hear in a presentation versus 20% if
they only hear it, experts suggest the use of
audiovisual aids to create the most effective
professional presentations (Bergren, 2000). A
noteworthy presentation could involve multiple levels of
complexity, from a simple PowerPoint slide to an
animated tutorial. Because technology and well-
designed visuals cannot make up for lack of
preparedness or research, however, presenters should
be aware of their target audience and details of the
research being presented. Regardless of the medium
or presentation style, audiovisual presentations should

be designed consistently and simply, using colors and
fonts that are easy to read and understand and
audience-appropriate language.

Conferences often host poster presentations that
enable contributors to share research findings,
innovations, and exemplar programs in a low-
investment but visually captivating way. Because
posters are primarily visual, with little or no verbal
supplementation, most important for consideration are
room elements, such as size, space limitations, and
lighting. The best nursing practitioner posters feature
consistent visual components, such as appropriately
sized, readable font and simple colors, and are based
on a research concept or clinical objective (Berg,
2005). A high-tech alternative to a paper poster is an
electronic poster—that is, a continuously running
PowerPoint presentation either projected for larger
audiences or left to run from a laptop or desktop for
smaller audiences (Bergren, 2000). Both publishing
and presenting provide opportunities for the nursing
practitioner to disseminate new knowledge and stay
abreast of information in the field. Some educational
institutions provide opportunities for undergraduates to
showcase projects and research at undergraduate
research conferences. These conferences are
excellent ways for developing professionals to hone
knowledge dissemination skills that will serve them well
in their professional practice.

Continuing Education and
Recertification
Nationally, nursing employers and institutions have,
because of budgetary constraints, begun to eliminate
CE programs traditionally reliant on classes,
conferences, and workshops; consequently, reliance
on outside agencies and technology has increased to
meet this need. The traditional approach to obtaining
CE credits has included home study offered by
professional journals and organizations in which the
client reads articles, answers related questions, and
sends in the test form and fee. Although fairly
straightforward, this technique provides little in the way
of peer interaction (Hebda & Czar, 2013). With the
ubiquitous technology influx and the accessibility it
affords, obtaining CE credits through e-learning is
considered a beneficial delivery method for mandatory
educational programs and other programs that provide
employees with opportunities to maintain or improve
skills. Benefits of e-learning for CE training include the
ability to access information at any time (thus creating
a flexible schedule) and experience instant feedback
and individualized instruction by seeking out specific,
additional information as needed.

E-learning can also benefit administrative support of
CE credits by providing instantly accessible
computerized records and other tracking features, such

as records of success and completion, associated
costs of program development, and staff productivity.
Allowing nursing professionals to complete mandatory
training on demand represents a huge benefit of e-
learning, with the best programs allowing for
customization to accommodate program revisions and
regulation changes (Hebda & Czar, 2013).

In some cases, acquiring CE credits may also help the
nurse achieve recertification. Available through myriad
professional organizations, recertification ensures that
nurses are staying current in their fields and some
specialties; for example, the field of pediatric nursing
requires annual recertification to maintain professional
status. During recertification, the Pediatric Nursing and
Certification Board offers each certified pediatric nurse
(CPN) options for ensuring she or he is maintaining
national standards within the specialty of pediatric
nursing (Pediatric Nursing Certification Board,
2007).

As an added benefit, some hospitals provide higher
salaries to nurses who maintain certification.
Additionally, 90% of nurse managers indicate they
would prefer to hire a certified nurse over a noncertified
nurse. The trend in Magnet hospitals to encourage,
reward, and promote certified nurses is spreading to
other facilities and healthcare settings, with retirement
centers and home health agencies now beginning to
seek certified nurses because of the perceived extra

benefit to their customers and the marketing advantage
obtained from hiring nurses with guaranteed levels of
competence (Peterson, 2007). For a comprehensive
list of nursing certifications provided by the American
Nurses Credentialing Center (ANCC), visit
www.nursecredentialing.org/certification.aspx.

Exploring Information Fair Use
and Copyright Restrictions
As we adopt more technology-based tools in
education, we need to be mindful of what constitutes
fair use of materials and copyright laws. Nurse
educators should be careful to model ethical behaviors
by attributing works to their rightful authors as they
acquire and use education materials. Fair use refers to
a legal concept that permits the use of copyrighted
works for specific purposes without obtaining
permission from the author or without paying for the
use of the work. Originally, fair use evolved for written
work and allowed for uses that include journalists
reporting the news, teaching, or scholarly research. As
digital technology and the Web burst upon the scene,
fair use expanded to apply to the copying and
redistribution of digital media, including photographs,
graphics, music, videos, audio, and software or
computer programs.

Four factors must be considered in determining
whether a particular use is fair. These factors are
derived directly from the fair use provision
(www.copyright.gov/fls/fl102.html) of Section 107 of
the U.S. Copyright Law (U.S. Copyright Office, n.d.):

1. The purpose and character of the use, including
whether such use is of commercial nature or is
for nonprofit educational purposes

2. The nature of the copyrighted work
3. The amount and substantiality of the portion

used in relation to the copyrighted work as a
whole

4. The effect of the use upon the potential market
for, or value of, the copyrighted work

The first factor tends to favor educational institutions
and nonprofit entities. The second factor relates to the
nature of the work: Courts have consistently protected
creative works and those that have not yet been
published. The third factor that must be considered
relates to the amount of use. Typically you should
determine how much of the overall work you are using;
if it represents the core or essence of the work, you
should not replicate or use it. The fourth and final factor
relates to the effect on the creator’s market share. If
you are using a substantial portion of a text or software
work that is offered for sale, you can adversely affect
its owner’s earning potential. The term itself should

make you reflect on all of these factors and decide
whether your proposed use is fair.

Copyright refers to the exclusive right of the creator of
a work to distribute, sell, publish, copy, lease, or
display that work in whatever manner he or she so
chooses. Copyright laws are not only misinterpreted,
but are constantly being challenged by our advancing
technological capabilities. Even though you use
American Psychological Association (APA) formatting,
for example, and cite the authors, you might be
overstepping your rights and infringing on the author’s
copyright; you might not be accused of plagiarism, but
you should always cite where you obtained your
information or digital media.

All users of others’ work, in whatever medium, must
fully understand, be well aware of, and comply with
copyright and fair use principles. Typically, you should
try to think of what is reasonable use and always make
sure that you cite the authors. Reflect on all four fair
use factors before making your decision to use
another’s work for educational purposes. Remember,
also, that you are serving as a role model regarding
copyright and fair use behaviors for your students.

The Future
There are several exciting and interesting education
technology trends to monitor in the future. Virtual

reality–embedded education has exploded onto the
academic scene and offers the potential for
interdisciplinary inquiry and sharing across the
curriculum, university, and globally. Makerspaces are
labs provided on university campuses (and in some
healthcare institutions) to allow students and
healthcare workers to experiment with developing new
technologies or modifying existing technologies and
equipment to better fit needs. These spaces are
frequently equipped with 3D printers and lots of tools
and materials that allow for rapid prototyping of ideas.
Here is an example of a makerspace innovation from
the University of Texas:

Taking 10–20 minutes at a time from
regular shift work, one nurse
demonstrated a prototype he has built
over time for a self-operating irrigation
system that could be used for burn
patients and free up staff to engage in
other tasks. Usually a manual task, a
patient with a severe burn requiring 11
hours of irrigation prompted this nurse to
come up with a better solution. While still
in development, the potential of this tool
to help alleviate the suffering of a single
patient or to free up significant time in the
event of a disaster is unquestionable.
(Siddiqui, 2016, para. 4)

Several universities around the country, such as
University of South Florida, University of Pittsburgh,
Yale University, and Arizona State University, are
sponsoring healthcare innovation competitions. Other
universities are partnering with industry leaders to
sponsor student ideas for healthcare innovations.
Another trend, The Internet of Everything (IoE) is
touted as the next step beyond the connections of
physical things (Internet of Things, or IoT):

IoT focuses only on sensor networks—
machines communicating with other
machines, and the data created as a
result. As things add capabilities (such as
context-awareness, increased processing
power, and energy independence), and
as more people and new information are
connected, IoT becomes IoE, a network
of networks where billions, or even
trillions, of connections create
unprecedented opportunities and new
risks. (Selinger, Sepulveda, & Buchan,
2013, p. 3)

Education innovations related to the IoE hold promise
for improving education processes, outcomes, and
instruction. For example, mobile devices and
wearables allow for the collection of learner behaviors,
and this data can be translated into targeted,

personalized learning. Data generated from the IoE
may also be used for professional development to
improve teaching and curricular approaches and
effectiveness. These are but a few of the education
technology trends to watch for in the future.

Summary
This chapter highlighted the technology tools and
delivery modalities that support nursing education. It is
clear that nursing education is evolving and will be
structured by competency achievement and supported
by technologies. In an ideal world, nurses will work
against the assumption that technology runs itself and
take proactive roles in helping to design the education
and technologies necessary best to prepare them for
real-world scenarios. Consider that flash is not
substance, and drama is not depth; technology
performs only as well as the pedagogy that undergirds
and sustains it. Plan for and use technology with care
so that its best features consequently enrich your
experiences as an educator or learner.

THOUGHT-PROVOKING QUESTIONS

1. What are some of the forces behind the
push toward a more wired learning
experience in nursing education?

2. Which of the technologies discussed here
most appeals to you? Why?

3. Explore one of the newer learning
technologies in more depth. How would
the use of this technology to benefit you
in your practice or education setting? Why
do you find this tool useful? From your
perspective, how could you enhance this
tool?

4. Jean, a diabetes nurse educator, recently
read an article in an online journal that
she accessed through her health
agency’s database subscription. The
article provided a comprehensive
checklist for managing diabetes in older
adults, which Jean prints out and
distributes to her patients in a diabetes
education class. Does this constitute fair
use or is it a copyright violation? Explain
your answer.

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CHAPTER 20: Simulation,
Game Mechanics, and
Virtual Worlds in Nursing
Education

Dee McGonigle Kathleen Mastrian Brett Bixler and
Nickolaus Miehl

Objectives
1. Distinguish among learning environments

as simulations, virtual worlds, or games.
2. Describe the role of simulation in nursing

informatics education.
3. Compare and contrast simulations, virtual

worlds, and games as informatics tools
for nursing education.

4. Assess strategies for choosing among a
simulation, virtual world, or game as the
best choice for instructional delivery in a
given educational situation.

5. Explore the role of simulation, virtual
worlds, and games in nursing education.

6. Differentiate between using a live clinical
information system or simulated
electronic health records for educational
purposes.

Key Terms
» Assessment

» Augmented-reality games (ARGs)

» Avatar

» Clinical information systems

» Database

» Debrief

» Dynamic webpage shells

» Edutainment

» Enactment

» Engage

» Feedback

» Fidelity

» Game

» Game mechanics

» Gameplay

» Latex-based simulation

» Massive multiplayer online role-playing
games

» Multiuser dungeon

» Nonplayer character (NPC)

» Object-oriented multiuser dungeon

» Pre-brief, enactment, debrief, and
assessment (PEDA)

» Pre-brief

» Scaffolding

» Second Life

» Serious game

» Server

» Simulated documentation

» Simulations

» Simulation scenario

» Simulator

» Three-dimensional (3D)

» Virtual simulation

» Virtual world

Introduction
The use of latex-based and virtual simulation (Figures
20-1 and 20-2), virtual worlds, and game mechanics in
nursing education continues to increase. Many schools
and staff education departments have employed these
techniques to provide efficient, effective, and engaging
educational experiences for their students and staff.
More schools and other educational entities are
realizing the benefits of these educational modalities.
The monumental National Council of State Boards of
Nursing (NCSBN; Hayden, Smiley, Alexander,
Kardong-Edgren, & Jeffries, 2014) simulation study
brought national attention to the need to enhance,
extend, or replace clinical and practicum hours with
other effective means such as simulation. In this
chapter, we will explore simulated documentation,
simulation, virtual worlds, and game mechanics used in
teaching nursing informatics competencies and nursing
education.

Figure 20-1 Latex-Based Simulation

Figure 20-2

Courtesy of WILL Interactive

Even though there are many nursing students, nursing
educators, and nurses using these technologies, there
is not a clear understanding of the terminology
associated with these learning modalities. It is
important that we are on the same page when we are
discussing these technologies and their impact on
nursing informatics and nursing education.

Simulations are imitations of real-life events or
circumstances; in nursing education, simulations
are used to replicate a clinical scenario to provide
an opportunity for practice in a mock situation. This
can be done via role play, web-based applications,
with manikins (latex-based simulation), or virtual
simulation in a virtual world.
A simulator is a mechanical or electronic device that
provides an environment in which a simulation can
occur.
Simulated documentation refers to any simulated
electronic format or electronic health record (EHR)
that is accessed and used by the learner to actually
document simulated nursing care for educational
purposes.
A simulation scenario is a situation or case
developed in a simulation setting to mimic an actual
practice situation.
A game is a structured activity undertaken for
enjoyment.
In education, edutainment is the combination of

“education” and “entertainment”; that is, when we
make learning fun.
Game mechanics are the rules, instructions,
directions, and constructs that the learner interacts
with while playing the game. For educators, it is
essential that any game mechanics they use are
engaging and satisfying for the learner.
Gameplay is how the learner interacts with or plays
the game. This is extremely important to
understand in order to appreciate how the game
functions and how the learners function, play, and
learn.

As you progress through the chapter you will delve into
simulated documentation, simulation, game
mechanics, and virtual worlds.

Simulation in Nursing
Informatics Education
The patient call bell is ringing; you enter the room to
find the patient verbalizing complaints of chest
tightness. In a moment, the patient becomes
unresponsive and a code is called. The team quickly
responds, initiating resuscitation measures per
advanced cardiac life support (ACLS) protocol. You
review the EHRs with the attending physician while
simultaneously discussing your assessment before the
code. After a short while, the resuscitation efforts are

successful and the patient is stable enough for transfer
to the intensive care unit. You complete your
documentation in the patient’s EHR, the simulation
scenario ends, and the debriefing begins. The
instructor provides feedback on not only actions taken
within the simulation scenario, but also on the use of
the EHR as an important resource for patient
information and documentation.

Perhaps it is the first day of a new course and, rather
than a lecture-based class with an accompanying
textbook, the instructor uses an active learning
approach with case studies delivered through an EHR
interface to facilitate the learning and application of
clinical concepts. In this example, rather than being
part of an entire simulation scenario, the EHR itself is
the learning tool providing learners with a hands-on
learning opportunity centered on accessing and using
the information contained within the patient record.
Choi, Park, and Lee (2016) concluded that academic
EMRs (AEMRs) would improve students’
understanding of clinical practice; “the findings of this
study will provide important developments by applying
an AEMR, which will augment students’ informatics
competencies and critical thinking, into the nursing
curricula to better prepare the future workforce” (p.
264).

Nursing Informatics

Competencies in Nursing
Education
In the late 1990s, it was identified that healthcare
professionals needed to possess both skill and
knowledge of informatics (American Association of
Colleges of Nursing, 1997; Gassert, 1998; Pew
Health Professions Commission, 1998). Additionally,
information technology has been identified as a key
measure in improving patient safety and quality of care
(American Academy of Nursing, 2003; Institute of
Medicine, 2000). In response to this increasing
demand for practitioners to become skilled in this area,
coupled with the absence of research-based
informatics competencies, a Delphi study was used to
identify informatics competencies for nurses at four
different levels of practice (Staggers, Gassert, &
Curran, 2002). In essence, this seminal study created
informatics competencies for entry-level nurses
through informatics specialists and innovators, with a
focus on computer skills, informatics knowledge, and
informatics skills.

Although informatics competencies for nurses have
been identified, the degree to which schools of nursing
have woven them into the curriculum varies greatly
(Carty & Ong, 2006). In a study conducted by Fetter
(2009), a survey of graduating senior nursing students
ranked the following competencies with which they had

no experience or minimal skill: (1) using applications to
document, (2) creating an electronic care plan, (3)
valuing informatics knowledge for practice, (4) valuing
informatics knowledge for skill development, and (5)
using applications for data entry. Hunter, McGonigle,
and Hebda (2013) developed the online self-
assessment tool, TIGER-based Assessment of Nursing
Informatics Competencies (TANIC); this instrument
assesses the Level I: Beginning Nurse and Level 2:
Experienced Nurse competencies. McGonigle,
Hunter, Hebda, and Hill (2014) developed the Nursing
Informatics Competency Assessment (NICA) for Level
3 (L3): Informatics Nurse Specialist and Level 4 (L4):
Informatics Innovator based on the seminal work of
Staggers, the current literature, and expert input. This
online self-assessment was noted in the 2015
American Nurses Association (ANA) Nursing
Informatics: Scope and Standards of Practice, Second
Edition. These self-assessment tools are discussed in
Chapter 7, Nursing Informatics as a Specialty.

The question then becomes, which best practices will
ensure that students become prepared in informatics?
In a position statement by the National League for
Nursing (2008), results from a survey of nursing
educators and administrators indicated that only 50–
60% of respondents said that informatics was
integrated throughout the curriculum and that
experience with nursing informatics was provided
during clinical rotations. Findings also suggested that

little clinically related informatics content and few such
learning experiences were provided in nursing
programs. Use of technology tools containing care-
planning software and clinical information systems
were least likely to be incorporated into the courses.
This continues to be an issue, and one area of concern
is the nursing informatics preparation of the faculty.
Rajalahti, Heinonen, and Saranto (2014) made
several recommendations, including the following: “A
description of nursing informatics competencies for
nurse educators is needed at a national and global
level. Advanced nursing informatics programmes are
needed in the nurse educators’ training programme” (p.
64). Nursing faculty must be prepared to use these
technologies. With emerging technologies in nursing
and healthcare education, the use of these
technologies, including simulation, to allow students to
use informatics in an active manner, and in an
authentic and realistic learning context, is one potential
approach to remedy these shortcomings.

A Case for Simulation in
Nursing Informatics Education
and Nursing Education
A simulation recreates a real-life set of conditions or
events with as much fidelity as possible (Alessi,
1988). Aldrich (2010) contended that simulations
develop cognition (learning-to-know skills), ethics and

roles (learning-to-be skills), and application capabilities
(learning-to-do skills). Unlike games, however,
simulations are not necessarily designed to be fun.

Simulations contain four major components: pre-brief,
enactment, debrief, and assessment (PEDA; refer to
Table 20-1). Every simulation should have these
elements in order to prepare and assess students while
also facilitating learning through doing and reflection.
The most important translational PEDA component is
the debrief. When done well, debriefing helps the
learner reflect on the authentic experience and
solidifies the learning by facilitating the transfer of
theory and skills to their real practice setting. Harris,
Shoemaker, Johnson, Tompkins-Dobbs, and
Domian (2016) believed that simulation could assist
family nurse practitioner (FNP) students with their role
transition from generalist to advanced practice by

Table 20-1 Simulation PEDA (Pre-brief, Enactment,
Debrief, Assessment)

Each simulation must have four components:

1. Pre-brief

2. Enactment

3. Debrief

4. Assessment

Pre-brief The student receives the simulation information: goal,

educational outcomes, and related course/program

outcomes. The simulation should be explained and

focused for the student. They should know how to

prepare for the activity and be told what is expected,

provided with the background necessary to be able to

fully enact their role in the activity, and given specifics

about how they will be assessed. They must also be

provided with the timeframe within which the

simulation must be completed.

Enactment The simulation area is prepared to facilitate the

activity. The student enacts the role assigned and/or

completes their assigned activities during the

established timeframe.

Debrief Debriefing is “a student-centered discussion during

which the participants and observers reflect on

performance during the scenario and make

recommendations for future practice” (Mastrian, Mc
Gonigle, Mahan, & Bixler, 2011, p. 351). The
debriefing can be done one-on-one and/or with entire

teams. Faculty can help students during and after

their activities by focusing on breakdowns and areas

of growth to hone future learning episodes (Tanner,

2006).

Objectives:

Following the completion of each activity, it is

important to:

1. Answer student questions.

2. Address student perspectives, perceptions,

and concerns.

3. Emphasize and reinforce specific learning

outcomes.

4. Create authentic linkages to the “real world.”

5. Assess student learning: What did they

learn?

6. Validate what they learned.

Questions for Discussion

Ask the student to reflect on the simulation activity:

both how they felt during the activity and how they feel

now that the activity is completed.

1. What did the student enjoy the most and the

least about the activity?

2. What were the student’s perceptions

regarding the activity?

a. Can students describe the emotions they

experienced while completing the activity?

b. How do the students describe the

interpersonal interactions or the enactment

of their role?

3. What were the major points of the activity?

4. Did the student experience any problems that

impacted their ability to make the necessary

decisions during the activity?

a. How could you prevent these problems in

the “real world”?

b. If you cannot prevent them, how could you

avoid them in the “real world”?

5. What did the student learn?

a. What did the student learn that was new to

them?

b. Did things that the student already knew

take on new meanings after the activity?

c. Was there a specific aspect of the activity

where the student learned the most?

d. Reflect on their perceived learning and

validate what was learned.

6. Would the student recommend any changes

to enhance the activity? If yes, what changes

and how would each change enhance the

activity?

7. What will the student take away with them

after having completed this activity?

Assessment The student should be provided with a detailed

explanation of how they will be assessed and graded

that relates to the goal, educational outcomes, and if

applicable, course/program outcomes. Detailed

rubrics are recommended. The assessment process

must be shared during pre-briefing. If the activity is not

being graded, a self-assessment should be provided

for the students so they know how to evaluate their

own performance.

Developed by Dee Mc

Gonigle.

“Allowing FNP students opportunities to gain
confidence in a risk-free environment.
Providing FNP students an entire comprehensive
office-based or acute patient care experience.
Reinforcing classroom content and bridging the
theory to practice gap” (p. 14).

Simulations may be experiential and task based, where
the learner takes on a first-person role and executes a
self-chosen series of decisions, manipulating the
variables in the simulation toward a desired outcome

(Gredler, 1996; Weatherford, n.d.). Simulations may
also be symbolic scenarios, where the learner directly
manipulates variables, sees the results of changes,
and then makes decisions on how to continue in the
simulation. Spreadsheets are often used for this type of
simulation. Symbolic simulations are good choices for
discovering principles, misconceptions, and
relationships, and for fostering understanding,
prediction, and solution development (Mastrian et al.,
2011).

Simulations may use a process known as scaffolding
(Jonassen, 1999; Podolefsky, Moore, & Perkins,
2013) to assist in acquiring the accepted level of
proficiency. An example of scaffolding is when
corrective feedback is initially used, correcting user
mistakes and ensuring success, and then the feedback
fades away when it is no longer needed.

Medical simulations use realistic three-dimensional
computer models of humans to investigate new
medical possibilities and to test assumptions (learning-
to-know skills). Simulations of drawing blood and
complex medical operations are used to teach
learning-to-do skills.

In general terms, a simulator can perhaps best be
described as a tool designed to emulate some aspect
of the clinical practice environment, which may be
focused on a single task or designed to mimic a

complete patient care situation (Gaba & DeAnda,
1998). At its essence, it is any device that is used to
create a realistic learning experience for the learner but
that removes the risk associated with learning during
hands-on patient care. A simulator offers the unique
ability to create a realistic learning environment that is
safe, structured, and supportive for the learner (Bligh
& Bleakley, 2006).

Simulators encompass a broad range of devices, such
as partial task trainers (e.g., an IV insertion arm);
screen-based simulations, including simulated EHRs,
simulated documentation, and simulated environments
replicating a realistic patient care area (virtual
simulation); and complex computer-driven human
patient simulation manikins (latex-based simulation).
Web-based virtual standardized patients are also
increasing in use. It is important to understand which of
these products you are using: one in which you enter
and interact in a virtual world, access a web-based
product, or interact in a latex-based lab. Although each
of these simulation modalities can be used alone,
collectively they can be powerful learning tools when
used together to create a realistic patient care
scenario. When designing simulation learning
environments, “[i]nnovative educators design learning
environments that encourage active engagement in the
learning process. . . . Active engagement creates a
personal connection with the learning experience and
motivates the learner to take greater responsibility in

the learning process” (Fisher, 2016, p. 9). The goal of
simulation, according to Gaba (2004), is a seamless
immersion into the simulated practice environment
during which learners are drawn into the reality of the
environment or task at hand. Hertel and Millis (2002)
noted that this is a cooperative process whereby
learners come together in an authentic setting and
begin to learn from one another. Darragh et al. (2016)
recommended realistic scenarios that elicit
autonomous problem solving and decision making to
immerse and engage the participants in active learning
and critical thinking. Refer to Figure 20-3.

Figure 20-3 Simulation Can Bridge the Gap

Considering the realistic nature of simulation and its
hands-on active approach to learning, it seems that the
use of simulation modalities can be a powerful tool in
moving student nurses—indeed, any practitioners—
toward achieving the informatics competencies. Recall

the examples given at the beginning of this chapter. In
the first example, the EHR is part of a larger simulation
scenario that mimics a real-life clinical case. In the
second example, the EHR itself functions as a
simulator and becomes a true-to-life learning tool. In
either case, simulation is used to incorporate nursing
informatics into the context of patient care, thereby
giving students an authentic learning experience that
can be applied in clinical practice.

According to the NCSBN National Simulation Study
(Hayden et al., 2014), 50% simulation can be
effectively used in various program types, in different
geographic areas, and in urban and rural settings with
good educational outcomes. The NCSBN study results
and the lack of available or quality clinical/practicum
placements are prompting the move to integrate more
simulation into nursing education. Virtual and latex-
based simulations are valuable educational assets at
all levels of nursing education. They provide a safe,
authentic environment to develop knowledge, skills,
and attitudes prior to interacting with actual patients.
There is no risk to patients, and students can practice
and receive assessment and feedback for controlled
episodes, including unusual events. Simulation relates
well to adaptive learning methods, such as branching
logic, that allow the learner to guide the learning. The
nurse educator can tailor the simulation to the learning
needs of the students, providing deliberate practice
with feedback. The learner can learn, relearn, and

hone skills while safely practicing in dynamic and
complex situations with a view to decreasing and
eliminating mistakes.

Incorporating EHRs into the
Learning Environment
There are two main approaches to the incorporation of
an EHR into the learning environment, whether used
within a simulated clinical environment as part of a
patient care scenario or as a stand-alone learning tool.
First, the EHR can be created specifically for simulation
purposes; options range from a well-developed
Microsoft Access database to commercially available
products designed specifically for simulation purposes.
Second, the simulation may use a real EHR system,
either within a hospital-based simulation center or
through a partnership with a healthcare facility or an
EHR vendor.

There are certain advantages and disadvantages to
each simulated documentation solution (see Figure
20-4). As Brown (2005) noted, whereas “live”
documentation systems provide learners with a realistic
experience and can be incorporated into the learning
environment, they also present certain drawbacks: (1)
they are designed for the patient care environment, not
the learning environment, and therefore lack an
efficient feedback mechanism for learners; (2) they are

designed to work in real time, not simulated time,
creating issues with data recall, especially when a
record may be used repeatedly over a period of
months or years; and (3) if a system is overly complex,
it may unintentionally focus the learning on the specific
system, rather than the process of data retrieval and
documentation. Refer to Research Brief 1 for more on
the challenges of teaching clinical documentation skills
in an EHR.

Figure 20-4 Simulated Documentation Nurse/Patient

You are working as a team. This is Mr. Poli and as your simulated patient,

you will be saving him from falling when you assist him to the restroom

and determining why he is unsteady. At the end of your shift, you will

document the nursing care you provided to this patient. When you leave,

Mr. Poli will Tweet about his experience with each of you as his nurse and

post comments about the care you provided. Not only is it important to

simulate what the nurse must document, but also what our patients

document and how they use social media to describe their care

experience. It is important that you realize that patients take note of our

actions and use social media to share their opinions and observations.

Think about your best and worst experiences in health care. It might be

something you experienced yourself or with a loved one. Where and what

would you share through social media?

RESEARCH BRIEF 1

Faculty perceptions of the challenges of
teaching undergraduate students proper clinical
documentation in both paper-based and
electronic systems are described in a qualitative
research study by Mahon, Nickitas, and Nokes
(2010). In this study, participants (N = 25) were
interviewed using both open- and closed-ended
questions, and results were analyzed using a
constant comparative method. The most
common method of teaching documentation
skills was some variation of demonstration–
return–demonstration method. Faculty were
concerned about the amount of time taken
honing documentation skills in the actual clinical
area, indicating a median of 2 hours of an 8-
hour clinical day was taken up with this task,
and shared that there was seemingly little
documentation taught in the classroom or
laboratory. Faculty relied heavily on experts in
the clinical setting and used their documentation
as models for students to emulate. In the case
of the electronic health record documentation,
on-site nursing experts proficient in the use of
the system were especially useful as role
models. However, faculty remained concerned
that using the electronic system and the endless
drop-down menus might actually interfere with

the development of nursing expertise and critical
thinking.

One critical issue that was shared by faculty with
regard to electronic documentation was that the
clinical facility provided the instructor with only
one access code, so that all of the students in
the clinical group used the same code to
document, and there was limited access to
computers on the clinical unit. The faculty was
very concerned about the legal and ethical
issues for appropriate documentation and for the
provision of care, such as on-time medication
administration in a group of 8–10 students with
one access code.

The authors suggested the need to integrate
information competencies throughout the
curricula and to provide opportunities for faculty
development in informatics. They suggested that
“faculty competencies in the area of informatics
must be identified and standardized” and that
faculty must learn to “model self-efficacy: the
patience, support and persistence that
characterize individual development within a
professional discipline” (p. 620).

The full article appears in Mahon,
P. Y., Nickitas, D. M., & Nokes, K.
M. (2010). Faculty perceptions of
student documentation skills

during the transition from paper-
based to electronic health records
systems. Journal of Nursing
Education, 49(11), 615–621.

A qualitative research study by Kennedy,
Pallikkathayil, and Warren (2009) described the
experiences and development of nursing
process skills in nursing students (N = 5) using
the Simulated E-hEalth Delivery System
(SEEDS) learning innovation. In the SEEDS
learning innovation, students were given written
case studies and asked to enter the patient data
in a simulated electronic health record and
generate a care plan for the patient and family.
The authors concluded, “The technology
provided an interactive venue for developing
nursing process skills by linking assessment
data from case studies with foundational
concepts in nursing” (p. 99). “The exercise was
authentic, dynamic, and learner centered” (p.
99). As a result of the themes discovered in this
qualitative study, the authors proposed two
hypotheses for future research to explore
learning outcomes resulting from the use of a
simulated e-health system:

There is greater interaction among
technologically competent students who use
electronic documentation for patient data

during clinical conferences. These students
interact more freely with other students and
their faculty members and experience
enhanced learner satisfaction. These
students also demonstrate superior nursing
process skills than students using traditional
postclinical group discussion about patient
care.
Technologically competent students also
have higher test scores on specific topics
than students who use paper and pencil
means to organize the assessment data and
develop care plans.

The full article appears in
Kennedy, D., Pallikkathayil, L., &
Warren, J. J. (2009). Using a
modified electronic health record
to develop nursing process skills.
Journal of Nursing Education,
48(2), 96–102.

Note: The SEEDS project began in 2002 and continues at time

of writing; according to the University of Kansas Medical

Center (2016), “The impetus for this partnership arises from the

Institute of Medicine (IOM) reports published in late 1999 and

early 2001 addressing the quality, error and waste in the U.S.

health care system” (para. 1).

One system designed specifically for simulation is the
Web-based medical chart (WMC), as described by
Brown (2005). This system requires four components:
(1) a database, (2) dynamic webpage shells, (3) a
server, and (4) computers with access to the Internet.
With this system, a Microsoft Access database is
created to hold administrative information about the
simulation scenario and other pertinent overview
information accessible only by the instructor, as well as
simulated patient data, simulated patient
documentation, student documentation entries, and
learner feedback from instructors. Each time a learner
logs into the WMC system via the Internet, the server
custom-creates the requested page using the existing
database information, user-specific information, and
the webpage shells to create a realistic EHR for use by
the student. Although this type of system offers a great
deal of flexibility, because it is custom created by the
end user (but is certainly a cost-effective solution), it
requires that the simulation instructor have a strong
background in computer science and information
technology to create and maintain the database and
supporting materials.

One example of a commercially available solution is
Elsevier’s Simulation Learning System (2010). This
system includes all of the elements needed for
preparing, programming, running, and debriefing a
simulation scenario, including a fully functional EHR.
The EHR is linked to the simulation scenario and

contains all of the pertinent patient information for
learners to access before or during the simulation
scenario. This system also incorporates the ability for
learners to document just as they would in an actual
clinical setting, with the capability of submitting the
documentation to the instructor for evaluation and
feedback. A major strength of this type of system is that
it is a prepackaged Web-based solution that does not
need to be created from scratch.

Additionally, there are many learning systems designed
for simulation that contain all of the necessary tools for
the instructor or simulation center staff to build the
simulation scenario, including (but not limited to)
programming guides, staging and scripting information
for the scenario, and debriefing guides. Two potential
disadvantages with any commercially available
solution, however, are the cost to purchase it, which
varies depending on the product and vendor, and the
ability for or cost associated with customization.

Although the main disadvantages of a live system were
discussed at the beginning of this section, the use of a
real EHR system clearly provides learners with a truly
authentic experience. One innovative solution to bridge
this gap was developed out of an academic–business
partnership between the Cerner Corporation and the
University of Kansas School of Nursing. The Simulated
E-hEalth Delivery System (SEEDS) incorporated the
use of Cerner Corporation’s clinical information system

and PowerChart application (Connors, Weaver,
Warren, & Miller, 2002; University of Kansas
Medical Center, 2016). This system was specifically
adapted for educational purposes to address the
learner’s informatics needs. Similar to the WMC
system discussed previously, instructors developed the
patient data stored within the Cerner Corporation’s
clinical information system database, creating virtual
patients within the system. Students could navigate
through the system and view pertinent patient data and
then document assessment information and create a
plan of care within the PowerChart application.
Additionally, the instructor could access student
documentation for evaluation and feedback. According
to the University of Kansas Medical Center (2016),
“[SEEDS] marks the first time that a live-production,
clinical information system designed for care delivery is
being used in a simulated way for teaching curriculum
content to health professional students” (para. 1). Refer
to the Research Brief 1 for a discussion of a study on
the use of the SEEDS approach.

Challenges and Opportunities
The adoption and use of simulation technologies
present unique advantages and disadvantages. Using
simulated medical records, either as a stand-alone
learning tool or in conjunction with a complete
simulation scenario, provides the learner with an
opportunity for a realistic, hands-on learning

experience. Major considerations when looking to
adopt a simulated EHR include (1) cost, (2) ease of
use for the instructor and learner, (3) technical support
from the vendor, (4) time to build or develop the patient
database, (5) additional simulation materials included
with the package, (6) flexibility of the system to be
customized and used as a stand-alone tool or in the
setting of a full-scale simulation scenario, and (7)
overall fidelity or realism.

In 2006, a coalition consisting of experts from the fields
of health care, informatics, business and industry, and
nursing proposed the Technology Informatics Guiding
Education Reform (TIGER) initiative (TIGER, 2007).
The aim of this group is to advance the integration of
informatics core competencies into nursing education
so as to provide better and safer care to patients.
Seven key steps were established to meet the 10-year
vision of the TIGER initiative. Of particular interest is
the call to take an active role in the design and
integration of informatics tools that are “intuitive,
affordable, usable, responsive and evidence-based” (p.
5). This approach will promote truly new and innovative
strategies for informatics education and create
significant opportunities for collaboration between
industry, academia, and clinical practice.

The Future of Simulation in
Nursing Informatics Education

Simulation will clearly play an important role in the
development of informatics competencies for student
nurses and practitioners. One theme of simulation-
based learning is practicing just as a nurse would in the
actual clinical setting. With regard to facilitating the
growth of informatics competencies, it is no different. If
there are expectations regarding the use of clinical
information systems and EHRs in the clinical setting,
then the opportunity also exists for the incorporation of
such tools into the classroom and simulated clinical
setting.

Aside from using the simulated EHR in the setting of a
clinical simulation scenario, there are also opportunities
to incorporate the simulated EHR into the classroom in
new and innovative ways. As mentioned in the
beginning of the chapter in the second scenario, the
EHR can be used as an active learning tool within the
classroom. Rather than requiring students to absorb
information from a book, the EHR can become a
powerful way for learners to make important
connections about caring for patients with a specific
disease process or to learn concepts of
pathophysiology or pharmacology.

Game Mechanics and Virtual
World Simulation for Nursing
Education

Introduction
The use of game mechanics in educational games and
virtual world simulation for education continues to grow,
with a great deal of research effort and funds directed
toward the discoveries of their best uses. Educational
games and virtual world simulations all share some
characteristics, and it is difficult to find a pure
experience in any of the genres. Simulations may have
game-like qualities, and virtual worlds may be used to
present a simulation.

Case Scenario
Joe sits down at the computer and logs into StratWorld,
a virtual world that enables the user to create his or her
own team, then compete against other teams created
by other StratWorld players. The developers of
StratWorld create interesting challenges, part
intellectual and part brute force, which teams strive to
solve before other, competing teams solve them first.

After Joe logs on, he is presented with a three-
dimensional (3D) view of a forest. Directly in front of
him is a 3D figure that looks very much like Joe, except
for broader shoulders, a more rugged face, and better
skin complexion. This is Joe’s avatar, his
representation of self in StratWorld. Joe can change
his avatar’s appearance as he wishes, but he likes to
stick to something close to the real thing. The members

of one of his opposing teams in StratWorld all prefer to
appear as masses of glowing tubes. Joe thinks they
are strange.

Today, he is recruiting for his virtual team, so he ducks
into his inventory (a place to store items his avatar can
wear and use) and dons his manager’s jacket. “Joe’s
Team” is proudly displayed on the back. Joe is proud of
the jacket; he created the lettering himself in a graphics
program and uploaded it to StratWorld, then added it to
a plain jacket and gave a copy to all new members of
his team. As in many virtual worlds, clothes do make
the man, woman, or thing.

Using the arrow keys and the mouse to manipulate his
avatar, Joe begins to make his avatar walk down the
forest trail. He is looking to recruit an Ogre for his team
to beef up their physical offensive capabilities and
replace the recent loss of Charlie the Unicorn. Ogres
are big and strong, perfect for the task. Joe is a little
nervous. He has never been to this part of StratWorld
before, and explorations in new areas can be fraught
with peril. After a brief sojourn, Joe comes upon an
Ogre sitting in a daisy-strewn clearing, picking his teeth
with a small sapling ripped from the ground. “Ogre!”
Joe shouts. “I need someone to smash through things
for my team. Interested?”

“What in it for me?” the Ogre asks, thumping his chest
with the remains of the sorry sapling, splintering it in

oblivion. “Darn! That was good toothpick!” The chirps of
birds, the drone of insects in the foliage, all normal
background noise here, suddenly stop. Joe picks up on
this environmental clue and, just as in the real world
when this happens, knows he is in danger.

Joe ponders the question. He knows he is talking to a
nonplayer character (NPC), one that seems to have a
brain behind the 3D façade, but in reality has very
clever programming attached to it so that it can seem
to carry on an intelligent conversation. Some
companies call this artificial intelligence, but both the
creators of these environments and the scholars who
study them hotly debate the proper use of that term.
Joe also knows that the world is constructed so that he
has to balance his profits from game wins with
overhead costs, such as player salaries and equipment
maintenance. He needs to make an offer to the Ogre.
An offer of too little will insult the Ogre, and a fight
between it and Joe is the probable result. Joe’s avatar
could die, an inconvenience that will cost him time and
loss of reputation with other StratWorlders. A generous
offer will probably be accepted, but might bankrupt Joe
over time. Joe needs to balance his needs and costs,
and also think outside the box. It is a complex problem-
solving situation!

“Okay, Ogre, here’s the deal. Pay is $900 a month, and
. . .” Joe attempts to continue, but the Ogre quickly
rises in an aggressive manner. “Wait! Let me continue!

I know that’s a little less than normal, but I’ll throw in a
nice, new sapling each week for tooth maintenance!
How about it?”

The Ogre sits back down and eyes Joe warily. “Just
need to pick tooths, not maintain ants. Contract for . . .”
(the Ogre pauses to quickly count his fingers) “10
months?”

“Sure, sure, but if you are injured, you go to half-pay
until you can play again,” Joe answers.

“I still get toothpick each week, even if hurt?”

“Absolutely. I mean, yes.”

The Ogre leans forward on its haunches. “Sound good!
You go. I follow.”

“One more thing, Ogre. What do I call you?” Joe asks.

“Daisy! You managers sure stupid!”

Joe takes Daisy back to his office by teleporting there,
a way to move from one place to another with a simple
click of a button. Joe pulls up a map of StratWorld,
locates the land he owns, and clicks on it for
instantaneous transport. Joes sends Daisy the Ogre
down to practice smashing down walls in his training
field, and then pauses for a moment to admire his

recreation of his grandfather’s old roll-top desk. He
recreated it from an old photograph just for his office in
StratWorld. Looking out the window, he sees Daisy
running out on the training field. He sits down at his
desk to go over his team’s statistics. With the addition
of Daisy to the team, Joe needs to recalculate all his
strategies. He needs to determine how he can acquire
a sapling each week for Daisy: Where will he get one,
and how much will it cost? Then he needs to send out
an acceptance to a recent invitation from the game
developers to participate in next week’s challenge. A
win will be sweet, but it will be a busy week of
preparation!

Before Joe hunkers down to work, he sends an instant
message to Kathy, an admirable opponent in
StratWorld against whom he has competed several
times. Typing furiously and with a certain glee, he
writes, “Hi, Kathy, guess what? I’m gonna DUST your
team in the next challenge!” Kathy’s reply is swift:
“Bring it on, Joe, bring it on!”

Case Scenario Discussion

This is a brief description of what occurs in many online
virtual environments today. People create a presence
in the environment, then manipulate events for a
desired outcome. They explore, build things, interact
with others, and try to achieve goals. The story is
fictional; there is no StratWorld, but games do exist

where people build teams and compete against one
another. So, is StratWorld a simulation, a virtual world,
or a game? What do you think? Think about
simulations you have experienced or heard of, games
you have played, and anything you have read about
virtual worlds. Try looking up some definitions online.
Write down your thoughts and come up with some
justifications that back your decision.

Game Mechanics and
Educational Games
Game mechanics are, simply put, the rules and
limitations in which a game takes place. It is imperative
that the rules are clearly stated in the instructions so
the players know what is expected of them and the
rules that the game itself much follow. The mechanics
determine how the players or learners interact with the
rules and how the game responds to the players’ or
learners’ moves or behaviors within the game, thus
connecting the players’ or learners’ actions to the
purpose of the game. People voluntarily play games
because they are fun and embody many motivational
aspects (Mastrian et al., 2011). Great games provide
an optimally challenging state between boredom and
frustration (Csikszentmihalyi, 1990). Games exist
within a set of rules (Kelley, 1988; Salen &
Zimmerman, 2003), and players receive feedback
from their interactions in the game and rule space.

An educational game—one designed for learning—is a
subset of both play and fun, and is sometimes referred
to as a “serious game” (Zyda, 2005). It is a melding of
educational content, learning principles, and computer
games (Prensky, 2001) that should emphasize the
value of the experience (Nemerow, 1996). Mungai,
Jones, and Wong (2002) stated that the flow of an
educational game may be under the designer’s control
more than a noneducational game, and feedback
should be used to stress competency, not just
achievement. The trick in designing an educational
game is to maintain the same fun state found in
noneducational games (Koster, 2004). “Contemporary
teachers wishing to incorporate game-based learning
whether doing so within a virtual environment, through
video games, or by leveraging mobile apps and other
technologies are at the forefront of a paradigm shift”
(Bauman, 2016, p. 110)

Many different types of games exist, and each type has
a different potential for educational use (Mastrian et
al., 2011). To learn to respond quickly and hone
reflexes, action games may be used. Adventure games
may be used to discover the unknown, such as
diagnosing a patient’s illness. Construction and
building games could be used for building complex
mental constructs that can be understood only through
knowledge of their constituent parts and the ways in
which they interrelate. Strategy games are great for
nursing education teaching moments where careful,

up-front planning is critical and on-the-fly adjustments
to one’s plan may be needed to ensure its success.

In role-playing games, the player takes on the role of
one or more characters and improves them while
progressing through a storyline. Today, massive
multiplayer online role-playing games are very
popular, using the Internet to provide a shared,
simultaneous experience for dozens or even hundreds
of players. Role-playing games are an excellent way
for nursing educators to guide students through any
situation where a sequenced step-by-step introduction
to the parts of the job or skill is required.

Fairly new are casual games, also known as mini-
games. These games are designed to be played in a
short time span, or for a few minutes a day over
several days, weeks, or even months. Many online
browser–based games fit this category. Casual games
may be useful for continuous reinforcement of basic
concepts, for emulating a slowly changing
environment, and for modifying the player’s attitudes
on a given topic over a period of time. To date, these
games remain largely untapped as educational tools.

There are also gaming simulations. A simulation game
uses game mechanics to imitate or copy real-ife
activities or actions in the form of a game. Refer to
Research Brief 2 for a mixed methods, quantitative,

and qualitative study on the health and safety of home
healthcare professionals, including nurses.

RESEARCH BRIEF 2

Darragh et al. (2016) stated that the rapid
increase in home healthcare services is driving
a need for additional trained home healthcare
professionals. The training must be effective for
managing personal health and safety hazards
encountered when providing healthcare services
in the home environment. The process of
developing and evaluating an interactive virtual
simulation training system to educate home
healthcare professionals, including nurses, was
described.

Sixty-eight home healthcare professionals
participated in the study, with the majority being
white (71%), female (95%), and with an average
age of 49 years (with a standard deviation of
11.8 years). Sixty-seven percent worked in Ohio
and Kentucky. The participants represented
RNs, aides and homemakers, administrators,
educators, occupational therapists, and physical
therapists.

A mixed-methods design, qualitative and
quantitative, using an interdisciplinary,
participatory design methodology was used to
develop a virtual simulation training system to

train home healthcare professionals to identify
and manage health and safety hazards in the
home using a gaming simulation learning
approach. The participants identified the layout
and features of a typical client home to the
interdisciplinary research team. Once the
working version of the virtual simulation training
system was created, ongoing assessment of
usefulness, usability, and desirability continued
to develop and modify the system.

Quantitatively, the researchers used the
Modified Home Healthcare Worker
Questionnaire (MHHWQ), and the usefulness,
usability, and desirability (UUD) survey.
Qualitative data collection consisted of
structured focus groups and individual
interviews. The participants described 353
hazard management dilemmas and explained
multiple types of ‘‘making do’’ solutions for the
hazards, most of which were classified as ‘‘less-
than-optimal.”

The simulation game facilitated active learning
and critical thinking processes crucial for these
professionals as they are typically highly
autonomous professionals who work
independently in unpredictable environments
where they must problem solve to create
solutions to unforeseen or complex events that

affect their health and safety, as well as the
health and safety of their clients.

In order to prepare professionals using health
and safety trainings, the training must focus on
realistic scenarios, flexible solutions, and
independent problem-solving activities. The
virtual simulation training system includes
immersion and engagement through a process
of identification, response, problem solving, and
feedback. The professionals had to assess the
environment for hazards in multiple rooms, then
received feedback both about correct
identification and right and wrong answers,
problem-solving about potential strategies, and
assessment of progress in both a training and
evaluation environment; this facilitated
deliberate practice, which is a powerful
component of skill acquisition.

The researchers concluded that participatory
methods are a useful and effective way to
design a virtual simulation training system that is
interactive, engaging, and informative. Since this
project is ongoing, their long-term goal was to
improve the health and safety of home
healthcare professionals who work in client
homes.

The full article appears in Darragh, A., Lavender, S., Polivka, B.,

Sommerich, C., Wills, C., Hittle, B., . . . Stredney, D. (2016).

Gaming simulation as health and safety training for home health

care workers. Clinical Simulation in Nursing, 12(8), 328–335.

doi:10.1016/j.ecns.2016.03.006

Virtual Worlds in Education
Cohen and colleagues (2013) define a virtual world
as follows:

Virtual worlds are live, online, interactive
3-dimensional environments in which
users interact using speech or text via a
personalised avatar. Access requires a
modern computer and Internet
connection. Healthcare practitioners are
increasingly utilising virtual worlds and
other web-based technologies for
educational purposes, including
resuscitation training, conferences,
surgical education and team-working for
multidisciplinary healthcare providers. (p.
79)

A 3D virtual world often mimics a real-world
environment, although it may also include impossible
abilities, such as flying unaided (Mastrian et al., 2011).
Users of virtual worlds are often quick to stress that
these creations in and of themselves are not games,
although this confusion is easy to understand because

virtual worlds share many of the same interface
characteristics as 3D action and role-playing games.

The best use of virtual worlds for educational purposes
may occur when there is a need for an immersive
experience coupled with a need for social interaction.
For example, in the virtual world of Second Life, one
university has developed a virtual hacienda for
students learning Spanish (Clark, 2009). Students
interact with the environment and the objects in the
hacienda while speaking to one another in Spanish,
thereby participating in authentic learning activities.
Some of the Second Life scenarios used by another
college of nursing include a real human resources
representative whom the student must call; the pair
must discuss the situation and the student then
determines a solution based on the representative’s
input. This activity immerses the students in their role
and fully engages them in the learning episode. Cohen
et al. (2013) tested the use of a virtual world as a
training site for emergency preparedness and
coordination for first responders in major incidents
(such as a terrorist attack), and concluded that

[m]ajor incident exercises are complex in
nature and expensive and they thereby
require novel methodologies to aid
training and preparation. This study has
established the feasibility of developing
low-cost, immersive, accessible virtual

environments for major incident
preparation using a systematic approach.
Both the environment and scenarios were
deemed realistic and acceptable for
training and testing of existing plans by
clinicians. (pp. 83–84)

Virtual worlds need not be 3D. Predecessors to the 3D
environment include the multiuser dungeon, object-
oriented multiuser dungeon, and multiuser shared
hallucination. All of these environments are text based,
so that the user receives environmental information as
passages of text and manipulates objects and talks to
others by typing text commands. Multiuser dungeons,
object-oriented multiuser dungeons, and multiuser
shared hallucinations are still in use today.

Choosing Among Simulations,
Educational Games, and
Virtual Worlds
Simulations, educational games, and virtual worlds all
have a great deal of overlap. Games may be placed in
virtual worlds, and simulations may have game-like
elements. Yet, these three tools also have distinctive
characteristics. By examining several of these key
characteristics (goal orientation, competition, the fun
factor, and exploratory learning and social interaction

affordances), it becomes easier to choose the correct
tool for teaching purposes.

Games are goal oriented and may be competitive in
nature. They should be fun and perhaps a bit
fantastical and light-hearted. A particular game may or
may not include exploratory learning and social
interaction. Although simulations are also goal
oriented, the competition is generally subdued.
Simulations are generally more realistic and are not
necessarily fun to use. A particular simulation may or
may not include exploratory learning and social
interaction. Virtual worlds in and of themselves do not
have goals or competition; it is up to the player to
construct them and add them to the world. Virtual
worlds are not by default fun, although they may
include the fantastical. Virtual worlds generally lend
themselves to exploratory learning and social
interaction. When educators develop virtual worlds for
education, they can control the scenarios or activities
experienced by the learners. Virtual worlds used for
simulation also include a debrief for their learners and
this debriefing process solidifies the learning.

The Future of Simulations,
Games, and Virtual Worlds in
Nursing Education

The use of simulations, games, and virtual worlds in
Western society continues to increase. The
combination of best practices supported by sound
research, the ever-growing power of technology, and
learners who grew up using these environments will
lead to greater use of these tools for learning (New
Media Consortium, 2007).

In addition, games are becoming less expensive to
produce and consume. Game development engines,
which were long in the hands of only major game
development companies, are now available at a cost
that many users and organizations can afford. Some
games come with built-in development tools, an
attempt by the game producers to use free labor to
extend their product (Dyer-Witheford & de Peuter,
2009). The growth of indie (independent) game
companies is leading to a plethora of cheap, yet high-
quality, games. The same holds true for virtual worlds.
New virtual worlds spring up all the time. Many offer
free, if limited, accounts, and educators are exploring
these spaces with increasing regularity, building
fantastic learning environments.

Companies are tapping mobile devices as another
avenue to push out their games. These devices are
already used for a variety of communication and social
functions, so why not build on that with casual games
that rely on social interactions? Expect to see much
more happening in this space in the near future.

Another related area of growth is in augmented-reality
games (ARGs). Augmented reality occurs when one
uses a device, such as a smartphone, to overlay
additional information on the real world (Klopfer &
Squire, 2008). For example, one might use the camera
in the phone to view the stars at night and see on the
phone’s screen both the stars and the constellation
labels and linking lines between the stars in a
constellation. ARGs exploit this concept in game-like
ways, bringing people together physically and virtually
to solve a series of challenges. In education, ARGs
may be used to provide a fun way to collect and
analyze data, to collaborate with other students, to
access information resources, and to provide a new
way to look at the world.

Serious games may also have a place in helping
practicing nurses maintain or hone skills. Baker (2009)
suggested that gaming has a place in continuing
education. The science of nursing practice encourages
us to ask questions, promote dialogue, share lessons
learned willingly and openly, and make the outcomes of
our patients constructive and positive. Rigorous or
high-quality evaluation and research into the teaching
and learning techniques offered by serious games can
offer insight into future changes not conceived of at this
moment. For example, if a serious game could
effectively assist nurses in maintaining the skill set
required to care for a patient who is experiencing

hypothermia, would that be worth the investment? If a
game could reduce medication errors in the operating
room by 50–75% compared to what has been
demonstrated in the past, would that have value? If it
were found that after implementation of a serious
game, a facility experienced zero errors in right-site,
right-procedure, and right-patient events during a 10-
year period, would this be of value (Baker, 2009, p.
173)?

Other new games that can be used to educate health
professionals have been discussed by Skiba (2008).
She described Foldit, a game that challenges players
to fold proteins as part of a research experience for Life
and Death in the Age of Malaria, a game that simulates
advice nurses would give to world travelers on health
maintenance strategies, and 3dMD, designed to
facilitate skills training in teamwork for military
environments.

Best uses of all of these technologies and approaches
related to nursing education remain a bit murky
(Bauman, 2016, p. 110). Fortunately, a great deal of
research, whose findings will guide future educators
toward the most effective uses of educational games,
simulations, and virtual worlds, is under way. In an
ideal world, educators would have a plethora of
available, well-designed, and educator-certified games
to choose from that mesh with the educational
objectives of their classes, courses, and curricula.

Summary
Simulated experiences in nursing education contain the
PEDA elements to provide important opportunities for
students to hone critical-thinking and clinical skills in a
safe and supportive environment. Simulation scenarios
may also provide a better variety of clinical and
practicum experiences than those available in a real
setting, and they also provide nursing faculty the
opportunity to track student progress and development
against specific learning objectives. Nurse educators
can share simulation scenarios and experiences and
thus contribute to the body of nursing education
knowledge to improve education practice. Simulations,
games, and virtual worlds have a great deal of potential
as educational tools that can augment, supplement, or
even replace traditional methods of teaching. As
educators become more skilled in the use of these
tools, and as designers share their creative works with
others, we can expect to see these tools used more
frequently in the coming decade.

THOUGHT-PROVOKING QUESTIONS

1. Consider your experience and learning
with regard to EHRs. If you were to
design a learning program centered on
the use of EHRs, what would it look like?
Consider this from the viewpoint of an

educator, a student, a clinician, and a
healthcare administrator.

2. Think about the clinical courses you have
taken as a student. Which opportunities
and challenges exist regarding the use of
an EHR as a major learning tool in
conjunction with, or perhaps even
replacing, the required textbook?

3. If you were to design a simulation
scenario incorporating the use of an EHR,
which informatics competencies would
you focus on and why?

4. Games are supposed to be fun and
voluntary. How can educators force a
game on a student and expect it to
remain fun and engaging?

5. It can take several hours of gameplay to
learn the mechanics of some games, and
even longer for the more complex games.
If subject-matter learning can occur only
after this initial game-mechanics learning
occurs, how can educators justify the
amount of time a learner must spend
within the game just to get to the point
where learning begins?

6. If you were choosing between a latex-
based simulation and a virtual simulation,
what would you list as each of their
advantages and disadvantages? Would
PEDA elements be present for both?

7. How do educators acquire the training
needed not just to get by in these new
environments, but rather flourish, thrive,
and mold the environments for their
purposes?

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SECTION VI: Research
Applications of Nursing
Informatics

Chapter 21 Nursing Research: Data Collection,
Processing, and Analysis

Chapter 22 Data Mining as a Research Tool

Chapter 23 Translational Research: Generating
Evidence for Practice

Chapter 24 Bioinformatics, Biomedical
Informatics, and Computational Biology

Nursing informatics (NI) provides more tools and
capabilities than can at times be imagined. Just as
NI has changed the way nursing is administered and
practiced, so it has also dramatically altered research
practices.

Nursing research has evolved with technology. In the
era of evidence-based practice, clinicians must
continue to think critically about their actions. What is
the science behind interventions? Things must no
longer be done a certain way just because they have
always been done that way. Instead, one should
research the problem, use evidence-based resources,

critically select electronic and non-electronic
references, consolidate the research findings and
combine and compare the conclusions, present the
findings, and propose a solution. The nurse may be the
first to ask why, thereby becoming a key player in
making change happen.

NI enhances and facilitates collaboration; improves
access to online libraries; provides research tool
transparency for collection, analysis, and dissemination
of research knowledge; and facilitates the development
of a common data language. It provides organizational
and informational support to advance translational
research, helping to fill the gap between research
findings and practice implementation. Repeat studies
are needed to provide meaningful meta-analyses and
systematic reviews of evidence to advance practice.
Technology advancement in the area of incorporating
evidence into clinical tools must continue. Removing
the barriers to knowledge-seeking behavior and
providing access to evidential resources promotes
knowledge use and, in the end, improves patient
outcomes. In addition, NI provides support for powerful
research techniques such as data mining and research
involving biological processes and genomics that hold
the promise of discovering new knowledge to improve
clinical practices.

The material in this book is placed within the context of
the Foundation of Knowledge model (Figure VI-1).

Nursing research is conducted to generate knowledge
that is used to meet the needs of healthcare delivery
systems, organizations, patients, and nurses. In
relation to the model, the nurse researcher is involved
with every aspect—from acquiring (collecting) and
processing (analyzing) data and information, to
generating knowledge, to disseminating the results or
findings (knowledge). Through this work, the
researcher generates knowledge for the nursing
profession. Knowledge generation is extremely
important in the advancement of nursing science.

Figure VI-1 Foundation of Knowledge Model

Designed by Alicia Mastrian.

CHAPTER 21: Nursing
Research: Data
Collection, Processing,
and Analysis

Heather E. McKinney Sylvia DeSantis Kathleen
Mastrian and Dee McGonigle

Objectives
1. Describe nursing research in relation to

the Foundation of Knowledge model.
2. Explore the acquisition of previous

knowledge through Internet and library
holdings.

3. Explore information fair use and copyright
restrictions.

4. Assess informatics tools for collecting
data and storage of information.

5. Compare tools for processing and
analyzing quantitative and qualitative

data.

Key Terms
» American Library Association

» Copyright

» Cumulative Index to Nursing and Allied
Health Literature

» Educational Resources Information
Center

» Fair use

» Foundation of Knowledge model

» Handheld devices

» Information literacy

» MEDLINE

» PsycInfo

Introduction: Nursing
Research and the Foundation
of Knowledge Model

The Foundation of Knowledge model suggests that
the most important aspect of information discovery,
retrieval, and delivery is the ability to acquire, process,
generate, and disseminate knowledge in ways that
help those managing the knowledge reevaluate and
rethink the way they understand and use what they
know and have learned. These goals closely reflect the
Information Literacy Competency Standards for Higher
Education, published by the American Library
Association (ALA) in 2003 in response to changing
perceptions of how information is created, evaluated,
and used.

According to the ALA (2000), an information-literate
individual is able to do the following:

Determine the extent of information needed
Access the needed information effectively and
efficiently
Evaluate information and its sources critically
Incorporate selected information into one’s
knowledge base
Use information effectively to accomplish a specific
purpose
Understand the economic, legal, and social issues
surrounding the use of information and access and
use information ethically and legally

In addition, new challenges arise for individuals
seeking to understand and evaluate information

because information is available through multiple
media (graphical, aural, and textual). The sheer
quantity of information does not by itself create a more
informed citizenry without complementary abilities to
use this information effectively. Most significantly,
information literacy forms the basis for lifelong learning,
serving as a commonality among all learning
environments, disciplines, and levels of education
(Association of College and Research Libraries
[ACRL], 2000, 2016). These standards and challenges
are still applicable today.

Case Study

During rounds, Charles encounters a rare
condition he has never personally seen and only
vaguely remembers hearing about in nursing
school. He takes a few moments to prepare
himself by searching the Internet. That evening,
he does even more research so that he can
assess and treat the patient safely. He searches
clinical databases online and his own school
textbooks. Most of the information seems
consistent, yet some factors vary. Charles wants
to provide the highest quality of patient care and
safety. He wonders which resources are best,
which are the most trusted, and which are the
most accurate.

Knowledge Generation
Through Nursing Research
Information literacy is an intellectual framework for
finding, understanding, evaluating, and using
information (refer to Figure 21-1). These activities are
accomplished in part through fluency with information
technology and sound investigative methods, but most
importantly through critical reasoning and discernment.
The ACRL (2016) has suggested that “information
literacy initiates, sustains, and extends lifelong learning
through abilities which may use technologies but are
ultimately independent of them” (para. 8).

Figure 21-1 Information Literacy

As nursing informatics (NI) combines all four nursing
practice areas (clinical, research, administration, and
education), the ability to recognize the need for a
specific kind of information and then locate, evaluate,
and effectively use that information within the NI
paradigm will catapult nurses ahead of other
healthcare professionals in applying and engaging
various facets of technology (ACRL, 2016). However,
because so few nurses have formal training in

technology but still represent a disproportionate
number of users, the ways in which nursing research
integrates healthcare technology within NI creates an
unseen challenge (McHaney, 2007). This potentially
enormous impact on the future of health care and
technology will determine the success of information-
literate nurses: those who have learned how to learn
and who understand the intricacies of how knowledge
is organized, retrieved, and used in such a way that
others can learn from them (ACRL, 2016). It is
important that nurse educators prepare nursing
students for information-literate practice in technology-
laden healthcare environments. Stephens-Lee and
colleagues (2013) stressed that “[n]ursing students
require opportunities to help them develop NI skills and
abilities to prepare them for contemporary workplaces”
(para. 39). Nash (2014) stated,

If we desire nurses who practice the art of
nursing as well as the science of nursing,
we must make it a priority to address the
issue of integrating those interpersonal
and critical thinking skills we value into an
increasingly complex, high-tech, fast-
paced healthcare system that often works
against us practicing at our very best. (p.
13)

Nursing students today use technology in their
personal lives, and they know that

technology allows them to share photos
(Flickr), exchange files and images, send
videos (YouTube, Snapchat), bookmark
(Quorum or Diigo, Pinterest), micro-blogs
or short postings (Twitter, Tumblr,
MySpace), blog (Blogger), socialize
(Facebook, Vimeo, Instagram), search
(Google, Google+), and network
professionally (Altogether, LinkedIn,
Yahoo Groups). (Merrill, 2015, p. 72)

Nursing faculty must be able to adapt their teaching in
this new technology era so that they engage their
students and help them assimilate technology as they
prepare for their professional nursing roles. Focusing
on nurses providing direct patient care, Piscotty et al.
(2015) stated that “finding methods that can help
nurses offer safe and effective care using technology is
an absolute necessity” (p. 287). As nurses enact their
role as administrators, researchers, educators, and/or
clinical staff members, integrating technology in the
current technology-laden information era is paramount.

Acquiring Previously Gained
Knowledge Through Internet

and Library Holdings
In an environment characterized by rapid technological
change coupled with an overwhelming proliferation of
information sources, nurses face an enormous number
of options when choosing how and from where to
acquire information for their academic studies, clinical
situations, and research. Because information is
available through so many venues, libraries, special-
interest organizations, media, community resources,
and the Internet in increasingly unfiltered formats,
healthcare practitioners must inevitably question the
authenticity, validity, and reliability of information
(ACRL, 2016).

Often, the retrieval of reliable research and information
may seem to be a daunting task in light of the
seemingly ubiquitous amount of information found on
the Web. Focusing on specific information venues not
only aids this search but also assists in negotiating the
endless maze of resources, allowing a nursing
practitioner to find the best and most accurate
information efficiently.

Professional Online Databases
Professional databases represent a source of online
information that is generally invisible to all Internet
users except those with professional or academic
affiliations, such as faculty, staff, and students. These

databases, which range from specific to general, act as
collection points by aggregating information, such as
abstracts and articles from many different journals; two
such databases include the Cumulative Index to
Nursing and Allied Health Literature (CINAHL) and
MEDLINE. CINAHL, for example, specifically includes
information from all aspects of allied health, nursing,
alternative medicine, and community medicine. The
MEDLINE database contains references to more than
22 million journal articles and is maintained and
produced by the National Library of Medicine. Other
databases, such as PsycInfo from the American
Psychological Association and the Educational
Resources Information Center (ERIC) database, may
also benefit nursing. Many databases also offer full-text
capabilities, meaning that entire articles are available
online. The articles and abstracts contained within
these databases have already withstood the rigors of
publication in professional journals and, therefore, are
considered viable and authentic peer-reviewed
sources.

Libraries with subscriptions to databases often employ
library professionals who are able to help patrons sift
through the vast amounts of available electronic
information; using the expert research capabilities of a
health science librarian at one’s local university is the
best way to learn how to conduct database searches
that yield the most efficient and useful results. Also
useful are websites that provide tutorials on best

searching practices specifically for medically oriented
databases, such as the tutorials provided by EBSCO
support to search the CINAHL database.

Search Engines
Search engines allow users to surf the Web and find
information on nearly anything, although many
researchers steer clear of search engines because of
the vast amounts of unsubstantiated information they
are likely to uncover. Because no legitimacy needs to
be provided for any information that appears on the
Web, an author can make claims, substantiated or not,
and still use the Web as a publishing venue. Despite
the pitfalls associated with search engines in general,
they can yield a bounty of useful information when
used with discretion.

Different search engines will produce different results
when used for the same research. For example, one
popular search engine ranks its results by number of
hits a page or site has received. Whereas the most
popular research results are likely to be relevant, the
order in which results appear does not indicate quality
or viability of the source.

Different Web address (domain) suffixes (.com, .edu,
.org, .gov, and so forth) indicate who is responsible for
creating the website. Although a .edu site is hosted by
an educational institution and for that reason may

seem legitimate, consider that it could also belong to a
student stating personal opinion, gossip, or guesswork.
In contrast, .gov sites are maintained by the
government and nearly always have professional
contact information. Web hosts develop new domain
suffixes constantly, so although looking at the suffix can
be useful, it should not be the sole deciding factor
when choosing to trust information.

One should never blindly trust information found on a
webpage. When possible, check the date of the most
recent update (How old is the page?), contact
information (Is a bibliography or list of sources
provided?), links to external sources (Do they seem
relevant?), and previous attained knowledge from other
reputable sources (Is the information too
unbelievable?).

Fees and information retrieval charges should be
approached with skepticism. Private companies do
offer information aggregation services for a fee. In
these cases, users pay a flat monthly fee for access to
collections of articles in a particular field. What users
(especially those affiliated with an academic institution)
may not realize is that they are likely to have free
access to the same, if not more complete, information
through their institution’s library system.

Some legitimate databases and traditional newspapers
that maintain a Web presence do provide access for a

small fee, but just as many others simply ask users to
register to see articles for free. Many nursing students
and professionals affiliated with a university may find
that their university library has already purchased
access for the student body.

Electronic Library Catalogs
Nearly all higher education institutions have placed
their library catalogs online. Although this is an obvious
convenience for many students, some nursing
professionals unused to working completely online may
be intimidated by an e-catalog. Library professionals at
the tiniest university and the busiest community college
are available to demonstrate how to navigate a basic
search of their library’s catalog. Asking for assistance
in learning how to access the vast assortment of
journals, books, databases, and other resources
available at one’s college library is an excellent idea.
Students in nursing programs at larger universities will
likely find free classes that specifically teach users how
to navigate and use the online catalog. If smaller
colleges and universities do not offer these services,
one should take advantage of the library’s online
tutorials, help pages, frequently asked questions
pages, and online reference service (if available). Local
public libraries often have subscriptions to popular
databases and offer free classes on searching
techniques to patrons, providing yet another free
access point to the best information for one’s research

needs. Making full use of available library resources
serves to strengthen information literacy skills, enabling
learners to master content and extend their
investigations, become more self-directed, and assume
greater control over their own learning (ACRL, 2016).

Fair Use of Information and
Sharing
Copyright laws in the world of technology are
notoriously misunderstood. The same copyright laws
that cover physical books, artwork, and other creative
material apply in the digital world. Have you ever given
a friend a flash drive that contains a computer game or
some other type of software that you paid for and
registered? Have you ever downloaded a song from
the Internet without paying for it? Have you ever copied
a section of online content from a reference site and
used that content as if it was your own? Have you ever
copied a picture from the Internet without asking
permission from the photographer who took the
picture? Have you ever copied and pasted information
about a disease or drug from a website and then
printed out the information to give to a patient or family
member? These are all examples of the type of
copyright infringements enabled by technology that
occur almost without thought.

The value of creative material—whether it is written
content, a song, a painting, or some other type of
creative work—lies not in the physical medium on
which it is stored, but rather in the intangibles of
creativity, skills, and labor that went into creating that
item. The person who created the material should be
properly credited and possibly reimbursed for the use
of the material. How would musicians be reimbursed
for their music if everyone just downloaded their songs
illegally from the Internet? Imagine that you created a
game to teach patients with type 1 diabetes how to
manage their diet, and other nurses copied and
distributed that game without getting your permission to
do so. How would you feel?

Almost all software, music, and movies (either digital or
in hard copy [CDs or DVDs] form) come with
restrictions on how and why copies can be made. The
license included with the software clarifies exactly
which restrictions are applicable. The most common
type of software license is a “shrink wrap” license,
meaning as soon as the user removes the shrink wrap
from the CD or DVD case, he or she has agreed to the
license restriction. Most computer software developers
allow for a backup copy of the software to be made
without restriction. If the hard drive fails on the user’s
computer, the software can usually be reinstalled
through this backup copy. Some software companies
even allow the purchaser of a software package to
transfer it to a new user. In this case, the software

typically must be uninstalled from the original owner’s
computer before the new owner is free to install the
software on his or her computer. Most of these
restrictions depend on the honesty of the user in
reading and following the licensing agreement. As a
result of widespread abuses, however, the music and
film industries commonly include hardware security
features in their products that block users from making
a working copy of a music CD or movie DVD.

The bottom line: Copyright laws also apply to the digital
world, and copyright violations can lead to prosecution.
Advances in technology have made the sharing of
information easy and extremely fast. A scanner can
convert any document to digital form instantly, and that
document can then be shared with people anywhere in
the world. Nevertheless, the person who originally
created that document has the right to approve of the
sharing of the work. Carefully read the fine print of any
software purchased and be sure to clarify any
questions regarding how that software can be copied.
Avoid downloading music illegally from the Internet,
and do not use information from the Internet without
permission to do so or without citing the reference
appropriately. Healthcare organizations that allow
access to the Internet from a network computer should
ensure that users are well aware of and compliant with
all copyright and fair use principles.

Informatics Tools for
Collecting Data and Storage of
Information
Nurses are already intimately familiar with data
collection as daily agents of patient care
documentation, patient monitoring, and interview data
(Chang, 2001; International Council of Nurses,
2012). In this way, formal nursing datasets are actually
made up of gathered information, such as healthcare
definitions, classification, and nursing information.
Before data can be analyzed or critically reviewed to
determine outcomes or assessment, they must be
collected and aggregated. According to the Cleveland
Clinic (2010):

[C]ollaborative nursing-led research is
enhanced by the ability to support these
projects with patient data that is more
easily extracted electronically. Supporting
these efforts and initiatives is a dedicated
team of clinical and system analysts who
provide support for the development and
management of information databases,
systems and processes to bring efficiency
to nursing-driven quality and research
endeavors through informatics. (para.
12–13)

Nurses may generate and record data from their own
observations or with the assistance of various devices.
Free text (informational data, such as drug dosages
administered, resources used, and problems
diagnosed) is recorded electronically. Free text is then
interpreted and organized by some standardizing
principle, either manually or by computer. In this way,
data (often qualitative data that cannot be traditionally
measured in a numeric sense) can be organized and
processed. A central issue to the generation and
analysis of free text data is the lack of a generally
accepted set of terminology to capture nursing data.
Data actually become information when these separate
components are interpreted, organized, combined, and
structured within a specific context to convey particular
meanings (Hovenga & Sermeus, 2002; Kempe,
2013).

Database management systems consist of software
designed to collect, sort, organize, store, retrieve,
select, and aggregate data. Nursing and health data
may be classified into four basic types: (1) resource
data (e.g., financial information); (2) patient and client
demographics; (3) activity data (clinical data); and (4)
health service provider data. These primary data may
be either recorded manually or collected electronically,
with manual collection providing a greater opportunity
for error. When data are electronically recorded, this
process follows a programmed set of instructions built
into the software, thereby cutting down substantially on

collection error. Of paramount importance in the
collection process are the data collection form and the
computer interface used for inputting the data; these
affect the completeness, consistency, and accuracy of
the resulting data (Hovenga & Sermeus, 2002;
Kempe, 2013).

Quantitative data collection tools or instruments include
questionnaires, interviews, surveys, quizzes,
assessments, email interviews, and Web-based
surveys, all of which generate numerical data rather
than text-based data. Questionnaires—one of the most
popular means of data collection—can be administered
in hard copy, on paper, or programmed into a website
where individuals may answer the questions
electronically (Chang, 2001; Statistics Canada,
2014). Other electronic data collection tools include
handheld devices and onsite laptops. A key benefit of
using electronic data collection is the ability to transmit
data to another computer directly for compilation and
analysis, thereby cutting down on the risk of error
(Hebda, Czar, & Mascara, 2005; Kania-Richmond,
Weeks, Scholten, & Reney, 2016; Teale, Young, &
Sleigh, 2013).

Of course, one must always be cognizant of the need
to protect the privacy of participants by deidentifying
data collected for research and by having tools in place
to provide secure transmission and storage of private
information. Some researchers are finding rich

qualitative data on public and freely available patient
support sites and blogs. An important issue associated
with such Internet-based data collection is whether
participants actually are who they say they are, and
whether they actually have the variable of interest or
are just pretending to be someone or something they
are not. Remember that the same rules for protecting
human subjects apply no matter where the data are
accessed or collected, and that all research involving
human subjects should be formally approved by the
appropriate institutional review board (IRB). Many IRBs
have specific policies in place that govern electronic
data collection and storage to ensure that the rights
and privacy of research participants are protected
(Office of the Vice President for Research at Penn
State, n.d.).

An excellent example of innovative electronic data
collection is the system used by participants in the
Nightingale Tracker System pilot study, in which
nursing students traveling to rural clinical sites
submitted information via handheld devices while miles
away from their preceptor-supervisors. The results of
this study suggest that, despite some technical
challenges associated with the hardware, using the
handheld technology enhanced students’ learning
(especially in the area of physical assessment),
increased their confidence in practicing in community-
based settings, and provided efficient data input
capabilities (Black & Merrill, 2015; Ndiwane, 2005).

Harder-to-measure, nonnumerical qualitative data can
be collected electronically in the form of a narrative or
diary-like entry. Much in the way free text is analyzed
and sorted, this narrative dialogue is assessed and
then coded, looking for patterns and themes that
represent the phenomenon under study. For example,
a nurse researcher may be interested in studying the
lived experiences of women recently diagnosed with
breast cancer and, therefore, may ask them to keep a
diary of their thoughts, questions, and treatment
experiences.

Tools for Processing Data and
Data Analysis
Data analysis is the process by which data collected
during the course of a study are processed to identify
trends and patterns of relationships. Descriptive
statistics allow the researcher to organize information
meaningfully, thereby facilitating insight by describing
what the data show (Hebda, Czar, & Mascara, 2005).
Figure 21-2 describes the importance of descriptive
statistics. There exist a range of tools to facilitate such
analysis, including specialized databases, word
processing/spreadsheet/database applications, and
statistical packages (Hovenga & Sermeus, 2002;
Latinen, 2014).

Figure 21-2 The Importance of Descriptive Statistics

Quantitative Data Analysis
Quantitative data focus on numbers and frequencies,
with the goal of describing a situation or looking for
more robust relationships such as correlations and
specific variable contributions to an outcome. This aim
stands in contrast to qualitative analysis, which focuses
on experiences and meaning. Although the kind of data
generated by quantitative collection is fairly
straightforward and easy to analyze (responses to

questionnaires, experiments, and psychometric tests),
quantitative data analysis has come under criticism.
Psychologists, for example, prefer to use a
combination of quantitative and qualitative data,
backing up research participants’ explanations with
statistically reliable information obtained by numerical
measurement (Holah.co.uk, n.d.).

In quantitative studies, variables represented by data
are collected in numerical form. These values are then
entered into specific fields that have predetermined
meanings or are coded. Various quantitative data
analyses can be applied to nursing research, such as
intervention research, quality improvement studies, and
outcomes research. One of the most popular statistical
packages for this kind of analysis is the Statistical
Package for Social Sciences (SPSS). Depending on
the research goal, the researcher may use different
types of analysis. Different statistical goals may require
hypothesis testing, model building, descriptive and
exploratory analyses, and others. For example,
hypothesis testing is based on assumptions regarding
the relative truth of the hypothesis, so a data analysis
would compare actual outcomes with purported
hypotheses.

Qualitative Data Analysis
Extremely varied in nature, qualitative data can include
nearly any information that can be captured and is not

numerical (Trochim, 2006a). Qualitative data are more
concerned with describing meaning than with drawing
statistical inferences; what is lost in reliability (faulty
transcription, forgotten details, and so forth) is gained
in validity (Holah.co.uk, n.d.). Although qualitative
data rely on judgments, they can still be manipulated
numerically, much in the same way that quantitative
data can be open to judgment (Trochim, 2006b).

Some major types of qualitative data include in-depth
interviews, direct observation, and written documents.
Interviews include individual and focus group
interviews and may be recorded in some way.
Interviews differ from direct observation in their
interactive nature. Direct observation differs from case
to case and often means the researcher does not make
contact with the respondent. Written documents might
include a variety of written materials, including memos,
newspaper clippings, conversation transcripts, and
books (Trochim, 2006a).

Computers can aid greatly in the storage, tabulation,
and retrieval of qualitative data by acting as the
equivalent of an electronic filing cabinet (Hebda, Czar,
& Mascara, 2005). Data analysis can also be aided by
simple data management programs, such as Excel,
Access, or NVivo, in which a user can categorize data
and link categories with key words. Data can be
converted into information and knowledge by either
inductive or deductive reasoning. Most qualitative

methods use an inductive approach in which the
researcher generates hypotheses (versus the
deductive approach typical of quantitative studies, in
which hypotheses are tested). Data analysis in
quantitative studies may allow the researcher to make
inferences to a population beyond the sample, as long
as the sample was representative of the population. In
contrast, generalizing to a larger population is not a
goal of qualitative research. Rather, in qualitative
research the goals are exploration and deeper
understanding of a phenomenon that has not been
widely studied (see Figure 21-3).

Figure 21-3 Quantitative Versus Qualitative Research

Two relatively new approaches to quantitative research
are cohort research and case control research. Cohort
research is a type of study in which two groups of
people are identified, one with an exposure of interest
and another without the exposure. The two groups are
followed forward to determine whether the outcome of
interest occurs. Groups are defined based on whether
they have had an exposure to a particular risk factor.
Case control research, in contrast, is a type of study in
which patients who have an outcome of interest and
patients who do not have the outcome are identified;
the researcher then looks back in time (typically using
health records) to determine exposures and
experiences that could have contributed to the
outcome occurring or not occurring (Brown, 2014).

The Future
The future of NI is growing as fast as technology itself.
The more nurses participate in the development
process of healthcare technology, the more efficient
and effective NI may become. Nurses are urged to take
an active role in the profession by providing real-world
feedback during the design process and after
implementation. Such practical insights will provide
valuable data for technology evaluation and
advancement in the field of nursing informatics.

Summary

This chapter discussed the value of information literacy
as an essential research tool and its relationship to
knowledge generation and lifelong learning. The reader
is now acquainted with informatics tools useful for
acquiring new knowledge and assessing previous
knowledge and tools useful for collecting and storing
and analyzing information to generate knowledge. In
an ideal world, information literacy and informatics
tools will be used as a critical skill set for increasing
healthcare efficiency, effectiveness, and safety in the
21st century.

THOUGHT-PROVOKING QUESTIONS

1. How does information literacy affect NI in
the 21st century?

2. Provide a detailed description of how NI
facilitates both qualitative and quantitative
research.

3. Reflect on copyright law and why it is
needed. Suppose you determine that
photographs or other images can be
replicated based on your assessment of
fair use, but your administrative assistant
refuses to photocopy them because he
feels that it is copyright infringement and
against company policy. Describe in detail
how you would handle this situation.

References
American Library Association (ALA).

(2000). Information literacy
competency standards for higher
education. Chicago, IL : Author.

Association of College and Research
Libraries (ACRL). (2000). Information
literacy competency standards for
higher education. Retrieved from
https://arizona.openrepository.com/arizona/handle/10150/105645

Association of College and Research
Libraries (ACRL). (2016). Information
literacy competency standards for
higher education. Retrieved from
http://www.ala.org/acrl/standards/informationliteracycompetency

Black, C., & Merrill, E. (2015, Fall). Using
mobile devices in nursing education.
The ABNF Journal, 78–84.

Brown, S. (2014). Evidence-based
nursing: The research–practice
connection (3rd ed.). Burlington, MA :
Jones & Bartlett Learning.

Chang, B. L. (2001). Computer use in
nursing education. In V. Saba & K.
McCormick (Eds.), Essentials of
computers for nurses: Informatics for
the new millennium (3rd ed., pp. 445–
456). New York, NY : McGraw-Hill.

Cleveland Clinic. (2010). Nursing
informatics. Retrieved from
http://my.clevelandclinic.org/nursing/informatics.aspx

Hebda, T., Czar, P., & Mascara, C. (2005).
Handbook of informatics for nurses &
health care professionals (3rd ed.).
Upper Saddle River, NJ : Prentice Hall.

Holah.co.uk. (n.d.). Quantitative and
qualitative data. Retrieved from
http://www.holah.karoo.net/quantitativequalitative.htm

Hovenga, E. J. S., & Sermeus, W. (2002).
Data analysis methods. In J. Mantas &
A. Hasman (Eds.), Textbook in health
informatics: A nursing perspective (pp.

113–125). Amsterdam, Netherlands :
IOS Press.

International Council of Nurses. (2012).
Closing the gap: From evidence to
action. Retrieved from
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Your-Practice/Research-Toolkit/ICN-
Evidence-Based-Practice-
Resource/Closing-the-Gap-from-
Evidence-to-Action.pdf

Kania-Richmond, A., Weeks, L., Scholten,
J., & Reney, M. (2016). Evaluating the
feasibility of using online software to
collect patient information in a
chiropractic practice-based research
network. Journal of the Canadian
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105.

Kempe, S. (2013). The data – information
– knowledge cycle. Dataversity.
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http://www.dataversity.net/the-data-
information-knowledge-cycle

Latinen, H., Kaunonen, M., & Astedt-Kurki,
P. (2014). Methodological tools for the
collection and analysis of participant
observation data using grounded
theory. Nurse Researcher, 22(2), 10–
15.

McHaney, D. F. (2007, June–August).
Embracing the integration of
technology and care. Alabama Nurse,
34(2), 1.

Merrill, E. (2015). Integrating technology
into nursing education. The ABNF
Journal, 26(4), 72–73.

Nash, B. (2014, November/December).
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of technology. Ohio Nurses Review,
12–13.

Ndiwane, A. (2005). Teaching with the
Nightingale Tracker technology in
community-based nursing education: A
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Office of the Vice President for Research
at Penn State. (n.d.). IRB guideline X:
Guidelines for computer- and Internet-
based research involving human
participants. Retrieved from
https://www.research.psu.edu/irb/policies/guideline10

Piscotty, R., Kalisch, B., & Gracey-
Thomas, A. (2015). Impact of
healthcare information technology on
nursing practice. Journal of Nursing
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Statistics Canada. (2014). Data collection
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3

Stephens-Lee, C., Lu, D., and Wilson, K.
(2013). Preparing students for an
electronic workplace. Online Journal of
Nursing Informatics (OJNI), 17(3).
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Teale, E., Young, J., & Sleigh, I. (2013). A
point of care electronic stroke data
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Trochim, W. M. K. (2006a). Qualitative
data. Research Methods Knowledge
Base. Retrieved from
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Trochim, W. M. K. (2006b). Types of data.
Research Methods Knowledge Base.
Retrieved from
http://www.socialresearchmethods.net/kb/datatype.php

CHAPTER 22: Data
Mining as a Research
Tool

Dee McGonigle and Kathleen Mastrian

Objectives
1. Describe big data.
2. Assess knowledge discovery in data.
3. Explore data mining.
4. Compare data mining models.

Key Terms
» Algorithms

» Bagging

» Big data

» Boosting

» Brushing

» Classification

» Classification and regression trees
(CART)

» Data mining

» Datasets

» Decision tree

» Drill down

» Exploratory data analysis (EDA)

» Machine learning

» Meta-learning

» Multidimensional databases

» Neural network

» Online analytic processing (OLAP)

» Scoring

» Six Sigma/Lean

» Stacking

» Unstructured data

Introduction: Big Data, Data

Mining, and Knowledge
Discovery
Data mining methods have been developed over time
using research. As data mining evolves, we have not
only become able to navigate our data in real time, but
have also progressed beyond mere access to
retrospective data with navigational improvements.
Using data warehousing and decision support, we
could, for example, answer the question, “What was
the most commonly diagnosed disease in our nine-
hospital system last April?” We could then drill down to
one hospital. As we have developed big data collection
capabilities, data capture, data transmission, storage
capabilities, powerful computers, statistics, artificial
intelligence, high-functioning relational database
engines with data integration, and advanced
algorithms, we have realized the ability to data mine
our big data to predict and deliver prospective and
proactive information. We can begin to predict by
answering a question such as “What is likely to be the
most commonly diagnosed disease next month and
why?” Data mining includes tools for visualizing
relationships in the data and mechanizes the process
of discovering predictive information in massive
databases.

Pattern discovery entails much more than simply
retrieving data to answer an end user’s query. Data

mining tools scan databases and identify previously
hidden patterns. The predictive, proactive information
resulting from data mining analytics then assists with
development of business intelligence, especially in
relation to how we can improve. Much of our big data is
unstructured data; unstructured big data reside in text
files, which represent more than 75% of an
organization’s data. Such data are not contained in
databases and can be easily overlooked; moreover, it
is difficult to discern trends and patterns in such data.
Data mining is an iterative process that explores and
models big data to identify patterns and provide
meaningful insights.

As we evolve the tools with which we can collect,
access, and process data and information, it is
necessary to concomitantly evolve how we analyze
and interpret the data and information. IBM (2013)
describes big data in a way that is easy to understand:

Every day, we create 2.5 quintillion bytes
of data—so much that 90% of the data in
the world today has been created in the
last two years alone. This data comes
from everywhere: sensors used to gather
climate information, posts to social media
sites, digital pictures and videos,
purchase transaction records, and cell
phone GPS signals to name a few. This
data is big data. (p. 1)

According to Tishgart (2012), “More data means more
knowledge, greater insights, smarter ideas and
expanded opportunities for organizations to harness
and learn from their data” (para. 2). Data mining is the
process of using software to sort through data to
discover patterns and ascertain or establish
relationships. This process may help to discover or
uncover previously unidentified relationships among
the data in a database with a focus on applications.
This information can then be used to increase profits or
decrease costs, or a combination of the two. In health
care, it is being used to improve efficiency and quality,
resulting in better healthcare practices and improved
patient outcomes. As we hone our analytical skills, we
will be able to clarify and explain patterns in our big
data related to improved patient responses to select
treatments for optimal patient outcomes. We can then
drill down for each treatment to examine the conditions
the patient presented with and the number of visits they
made. The data can then be explored to refine the
output. For example, it would be very important to
know more about each patient, such as if they had
other conditions or diseases (comorbidities) that could
affect their outcomes as well as their age, gender,
educational level, and so on. Moskowitz, McSparron,
and Celi (2015) stated,

Beyond simple user principles, trainees
do not learn the skills and concepts
necessary for the optimal use of EMRs,
including knowledge creation and
personalized clinical decision making
through analysis of large data sets. To
date, this is largely because such
systems have not been designed or
implemented with these goals in mind. In
the coming era of “Big Data,” our
community of medical educators and
researchers must leverage digital
systems for this purpose and find a way
to prepare trainees for this critical role.
(para. 9)

Their next steps concluded that “[t]he time has come to
leverage the data we generate during routine patient
care to formulate a more complete lexicon of evidence-
based recommendations and support shared decision
making with our patients” (para. 19).

Data mining projects help organizations discover
interesting knowledge. These projects can be
predictive, exploratory, or focused on data reduction.
Data mining focuses on producing a solution that
generates useful forecasting through a four-phase
process: (1) problem identification, (2) exploration of
the data, (3) pattern discovery, and (4) knowledge

deployment, or application of knowledge to new data to
forecast or generate predictions. Data mining is an
analytic, logical process with the ultimate goal of
forecasting or prediction. It mines or unearths
concealed predictive information, constructing a picture
or view of the data that lends insight into future trends,
actions, or behaviors. This data exploration and
resulting knowledge discovery foster proactive,
knowledge-driven decision making. See Figure 22-1,
which illustrates how raw data is transformed to
knowledge.

Figure 22-1 Transforming Raw Data into Knowledge

Reproduced from Login Works. (2016). The process of data mining.

Retrieved from http://www.loginworks.com/data-mining-services-

various-type

Problem identification is the initial phase of data
mining. The problem must be defined, and everyone

involved must understand the objectives and
requirements of the data mining process they are
initiating.

Exploration begins with exploring and preparing the
data for the data mining process. This phase might
include data access, cleansing, sampling, and
transformation; based on the problem you are trying to
solve, data might need to be transformed into another
format. To assure meaningful data mining outcomes,
you must comprehend and truly understand your data.
The goal of this phase is to identify the relevant or
important variables and determine their nature.

Sometimes known as model building or pattern
identification, pattern discovery is a complex phase of
data mining. In this phase, different models are applied
to the same data to choose the best model for the
dataset being analyzed. It is imperative that the model
chosen should identify the patterns in the data that will
support the best predictions. The model must be
tested, evaluated, and interpreted. Therefore, this
phase ends with a highly predictive, consistent pattern-
identifying model.

The final phase, knowledge deployment, takes the
pattern and model identified in the pattern discovery
phase and applies them to new data to test whether
they can achieve the desired outcome. In this phase,
the model achieves insight by following the rules of a

decision tree to generate predictions or estimates of
the expected outcome. This deployment provides the
organization with the actionable information and
knowledge necessary to make strategic decisions in
uncertain situations.

Data mining develops a model that uses an algorithm
to act on datasets for one situation where the
organization knows the outcome and then applies this
same model to another situation where the outcome is
not known—an extension known as scoring. Data
mining is concerned with extracting what is needed,
and it applies statistics so that organizations can gain
an advantage by manipulating information for practical
applications. In our information-overloaded healthcare
world, all too often we find ourselves grasping for
knowledge that is currently nonexistent or fleeting.
Data mining is a dynamic, iterative process that is
adjusted as new information surfaces. It is a robust,
predictive, proactive information and knowledge tool
that, when used correctly, empowers organizations to
predict and react to specific characteristics of and
behaviors within their systems.

Data mining is also known as knowledge discovery and
data mining (KDD), knowledge discovery in data, and
knowledge discovery in databases. The term
“knowledge discovery” is key, as data mining looks at
data from different vantage points, aspects, and
perspectives and brings new insights to the dataset.

This analysis then sorts and categorizes the data, and
finally summarizes the relationships identified. In
essence, then, data mining is the process of finding
correlations or patterns among the data.

Health care, as noted earlier, generates big data. Data
mining tools, in turn, are able to analyze enormous
databases to determine patterns and establish
applications to new data. Healthcare organizations
clearly need to invest more in big data and data mining
analysis: The “big data market [reached an estimated]
$2.2 billion in 2011, [but] only 6% of that investment
came from health care” (Tishgart, 2012, para. 2).

The healthcare sector has discovered data mining
through the realization that knowledge discovery can
help to improve healthcare policy making, healthcare
practices, disease prevention, detection of disease
outbreaks, prevention of sequelae, and prevention of
in-hospital deaths. On the business side, healthcare
organizations use data mining for the detection of
falsified or fraudulent insurance claims. According to
Manyika et al. (2011),

If US healthcare were to use big data
creatively and effectively to drive
efficiency and quality, the sector could
create more than $300 billion in value
every year. Two-thirds of that would be in

the form of reducing US healthcare
expenditure by about 8 percent. (para. 2)

If they are to develop a successful data mining
process, organizations must have the data needed to
create meaningful information. In health care, we are
honing our ability to analyze our data by making sure
that those data are comprehensive and complete, meet
our needs, and are cleansed and prepared for the data
mining process. Many facilities are using data
warehouses to store data and facilitate this pre–data
mining process. We are learning to ask the right
questions during the data mining process to gain a
thorough understanding of our data. The following
pages introduce the concepts, techniques, and models
used in data mining.

KDD and Research
According to IBM (2013), big data does not just refer to
size, but rather “is an opportunity to find insights in new
and emerging types of data and content, to make your
business more agile, and to answer questions that
were previously considered beyond your reach” (p. 6).
Data mining for knowledge discovery is not new; it has
been used for some time in research. However, we
now have advanced analytical software designed to
facilitate data mining. The knowledge discovery
capabilities continue to evolve. Goodwin et al. (1997),

for example, reported on their collaborative data mining
research, which explored the relationship between
clinical data and adult respiratory distress syndrome
(ARDS) in critically ill patients. DeGruy (2000)
indicated that big data in health care needed to be
analyzed using KDD tools and applications to
determine trends and relationships, with the ultimate
goal of decreasing healthcare costs while improving
quality. Berger and Berger (2004) suggested that
nurse researchers are positioned to use data mining
technologies to transform the repositories of big data
into comprehensible knowledge that will be useful for
guiding nursing practice and facilitating interdisciplinary
research.

Madigan and Curet (2006) described the
classification and regression trees (CART) data
mining method for analyzing the outcomes and service
use in home health care for three conditions: chronic
obstructive pulmonary disease, heart failure, and hip
replacement. They found that four factors—patient age,
type of agency, type of payment, and ethnicity—
influenced discharge destination and length of stay.

Over the last several decades, the KDD capability has
improved as the analytical power of data mining tools
has increased, thereby facilitating the recognition of
patterns and relationships in big data. Trangenstein,
Weiner, Gordon, and McNew (2007) described how
their faculty used data mining to analyze their students’

clinical logs, which enabled them to make
programmatic decisions and revisions and rethink
certain clinical placements. Zupan and Demsar (2008)
described the open source tools developed by data
mining researchers that they felt were ready to be used
in biomedical research. Fernández-Llatas et al. (2011)
described workflow mining technology as a means to
facilitate relearning in dementia processes. Lee et al.
(2011) discussed the application of data mining to
identify critical factors such as nursing interventions
related to patient fall outcomes. Lee, Lin, Mills, and
Kuo (2012) used data mining to determine risk factors
related to each stage of pressure ulcers and identified
five predictive factors: hemoglobin level, weight, sex,
height, and use of a repositioning sheet. Based on the
results of this data mining analysis, nurses can better
target their interventions to prevent pressure ulcers.
Green et al. (2013) identified differences in limb
volume patterns in breast cancer survivors; their results
have the potential to influence clinical guidelines for the
assessment of latent and early-onset lymphedema.

As these examples suggest, we must continue to
employ data mining and interprofessional collaboration
to reduce inefficiencies, improve quality, and support
transformations using data-driven models of care.

CASE STUDY

In a large teaching hospital, there is a high rate
of readmission for patients with congestive heart
failure (CHF) who are being treated at the
facility. The chief nursing officer (CNO) wants to
know the cause of the readmissions, as the rate
at this facility is almost twice that of competing
healthcare entities in the area. The CNO works
with the nursing researchers at the university to
address this situation.

The researchers begin to scour the electronic
health records (EHRs) of more than 15,000 CHF
hospitalizations in the past 4 years to determine
the cause of the situation. As they begin to
understand this dataset, they are able to build a
data mining model using algorithms to discover
patterns and relationships in the data. Based on
the old data, they determine that the key factor
for readmission was the length of time it took to
follow up at home with discharged patients.

In response to this new knowledge, a program in
which nurses contact patients with CHF the day
after their discharge by phone was developed,
and a home visit is scheduled for the second
day postdischarge to ensure a smooth transition
to home or an assisted living facility. This follow-
up within the first 4 days of discharge has
reduced readmissions by 40%. The model that
was used with the old data is being applied to
the new data.

Data Mining Concepts
Bagging is a term for the use of voting and averaging
in predictive data mining to synthesize the predictions
from many models or methods or the use of the same
type of a model on different data. This term can also
refer to the unpredictability of results when complex
models are used to mine small datasets.

Boosting is what the term infers—a means of
increasing the power of the models generated by
weighting the combinations of predictions from those
models into a predicted classification. This iterative
process uses voting or averaging to combine the
different classifiers.

Data reduction shrinks large datasets into manageable,
smaller datasets. One way to accomplish this is via
aggregation of the data or clustering.

Drill down analysis typically begins by identifying
variables of interest to drill down into the data. You
could identify a diagnosis and drill down, for example,
to determine the ages of those diagnosed or the
number of males. You could then continue to drill down
and expose even more of the data.

Exploratory data analysis (EDA) is an approach or
philosophy that uses mainly graphical techniques to
gain insight into a dataset. Its goal varies based on the
purpose of the analysis, but EDA can be applied to the
dataset to extract variables, detect outliers, or identify
patterns.

Feature selection reduces inputs to a manageable size
for processing and analysis, as the model either
chooses or rejects an attribute based on its usefulness
for analysis.

Machine learning is a subset of artificial intelligence
that permits computers to learn either inductively or
deductively. Inductive machine learning is the process
of reasoning and making generalizations or extracting
patterns and rules from huge datasets—that is,
reasoning from a large number of examples to a
general rule. Deductive machine learning moves from
premises that are assumed true to conclusions that
must be true if the premises are true.

Meta-learning combines the predictions from several
models. It is helpful when several different models are
used in the same project. The predictions from the
different classifiers or models can be included as input
into the meta-learning. The goal is to synthesize these
predicted classifications to generate a final, best-
predicted classification—a process also referred to as
stacking.

Predictive data mining identifies the data mining project
as one with the goal of identifying a model that can
predict classifications.

Stacking or stacked generalization synthesizes the
predictions from several models.

Data Mining Techniques
It is important to understand your data before you
begin the data mining process so that you can choose
the best technique and get the most from the data
mining. The commonly used techniques in data mining
are neural networks, decision trees, rule induction,
algorithms, and the nearest neighbor method.

A neural network represents a nonlinear predictive
model. These models learn through training and
resemble the structure of biological neural networks;
that is, they model the neural behavior of the human
brain. Computers are fast and can respond to
instructions or programs over and over again. Humans
use their experience to generalize the world around
them. Neural networks are a way to bridge the gap
between computers and humans. Neural networks go
through a learning process or training on existing data
so that they can predict, recognize patterns, associate
data, or classify data.

A decision tree is so named because the sets of
decisions form a tree-shaped structure. The decisions
generate rules for classifying a dataset. CART and chi
square automatic interaction detection (CHAID) are two
commonly used types of decision tree methodologies.
See Box 22-1 and Figure 22-2 for an overview of
decision tree analysis.

Figure 22-2 Decision Tree Analysis Output

BOX 22-1 DECISION TREE ANALYSIS

Steven L. Brewer, Jr.

Decision trees are a statistical technique based
on using numerous algorithms to predict a
dependent variable. These predictions are
determined by the influence of independent
variables. Decision trees help researchers
understand the complex interactions among
variables generated from research data. The
entire dataset is split into child nodes based on
the impact of the independent predictors. The
most influential variable is situated at the top of
the tree; the subsequent nodes are ranked by
the significance of the remaining independent
predictors.

Graphically, decision trees produce a tree (as
illustrated in Figure 22-2) that consists of a root
node and child nodes. The tree is an inverted,
connected graphic. The graphic representation
of the decision tree helps general users, such as
practitioners, understand the complex
interrelationships between the independent and
dependent variables in a large dataset.

Within the graphical display, there are three
major components: the root node, the child
node, and the terminal node. The root node
represents the dependent variable, and the child

nodes represent the independent variables. The
root node is essentially the base of the tree or
the top node. It contains the entire sample, while
each child node contains a subset of the sample
within the node directly above it. In Figure 22-2,
the root node represents a sample of women
who were either reassaulted or not reassaulted
in a domestic violence database. Data in the
root node are then partitioned and passed down
the tree.

The number of child nodes will vary depending
on the classification procedure that is used to
determine how the data are split. In Figure 22-2,
the first child node is “women’s perception of
safety.” This node suggests that the most
influential predictor in domestic violence
reassault for this sample is the women’s
perception of safety. The tree produces
additional child nodes based on the responses
to that variable. Node 1 represents the women
who responded “no” when asked whether they
felt safe in the relationship. For this node,
women had a 90% chance of being reassaulted.
In contrast, node 2 represents the women who
responded “yes” when asked whether they felt
safe in the relationship. These women had only
a 72% chance of being reassaulted.

The decision tree in Figure 22-2 splits the entire
sample into subsamples, which in turn allows for

different predictions for different groups within
the sample. For example, women who felt safe
in their relationship (node 2) and experienced
controlling behaviors (node 6) had an 80%
chance of being reassaulted. In contrast, women
who did not feel safe (node 1) and were in a
relationship characterized by controlling
behaviors (node 4) had a 97.3% chance of
being reassaulted. The splitting of the data
continues until the data are no longer sufficient
to predict the remaining variables or there are
no additional cases to be split.

Classification trees share commonalities with
nonlinear traditional methods such as
discriminant analysis, cluster analysis,
nonparametric statistics, and nonlinear
estimation; however, the technique differs
significantly from linear analyses. In general, the
decision tree technique does not rely on
“multiplicative” or “additive” assumptions such
as regression to predict the outcome of y. The
flexibility of classification trees is one
characteristic that makes them attractive to
researchers. The trees are not bound or limited
to examining all predictor variables
simultaneously. Therefore, each predictor
variable can be examined as a singularity to
produce univariate splits in the tree. Additionally,
classification trees can handle a mixture of

categorical and continuous variables when
univariate splits are used. While this flexibility
offers advantages over traditional methods,
classification trees are not limited to univariate
splits.

Decision trees have become a popular
alternative to methods such as regression and
discriminate analysis for data mining big data.
Such trees use algorithms from one of the
numerous classification procedures to separate
the data into different branches or child nodes
that predict y. The dependent variable (y) is
represented by the root node.

These algorithms have three main functions: (1)
they explain how to separate or partition the
data at each split, (2) they decree when to stop
or end the splitting of data, and (3) they
determine how to predict the value of y for each
x in a split. The child nodes are separated into
homogenous groups by the algorithms from
different classification procedures. This process
of partitioning is the main purpose of
classification procedures. First, the procedure
clusters and creates child nodes. Second, it
ranks them based on their predictive values of y.
Hence, the most influential variable(s) will be
located at the base of the tree. From this point,
the classification procedures further expand the
child nodes by finding the next best factor. The

tree is expanded until the algorithm is unable to
find a clearly distinguishable split within the
data.

Based on the results of the sample decision tree
analysis presented in Figure 22-2, practitioners
would conclude that women should be attuned
to their perception of safety in a relationship, as
those who feel unsafe have a much higher
chance of another assault.

Decision trees are a powerful tool that can be
used to mine large datasets and discover
previously unknown relationships among the
data. The predictive relationships uncovered by
the decision tree analysis may be useful in
directing approaches to future care
interventions.

Rule induction is based on statistical significance.
Rules are extracted from the data using if-then
statements, which become the rules.

Algorithms are typically computer-based recipes or
methods with which data mining models are
developed. To create the model, the dataset is first
analyzed by the algorithm, looking for specific patterns
and trends. Based on the results of this analysis, the
algorithm defines the parameters of the data mining

model. The identified parameters are then applied to
the entire dataset to mine it for patterns and statistics.

Nearest neighbor analysis classifies each record in a
dataset based on a select number of its nearest
neighbors. This technique is sometimes known as the
k-nearest neighbor.

Text mining for text is equivalent to data mining for
numerical data. Because text is not always consistent
in health care owing to the lack of a generally accepted
terminology structure, it is more difficult to analyze.
Text documents are analyzed by extracting key words
or phrases.

Online analytic processing (OLAP) generates
different views of the data in multidimensional
databases. These perspectives range from simplistic
views such as descriptive statistics, frequency tables,
or comparative summaries to more complicated
analyses requiring various forms of cleansing the data
such as removing outliers. OLAP is also known as fast
analysis of shared data.

Brushing is a technique in which the user manually
chooses specific data points or observations or subsets
of data on an interactive data display. These selected
data can be visualized in two-dimensional or three-
dimensional surfaces as scatterplots. Brushing is also
known as graphical exploratory data analysis.

Data Mining Models
To generate predictions and infer relationships, the
dataset, statistics, and patterns identified in existing
data must be applied to new data. A data mining model
is developed by exercising more than algorithms on
data. Specifically, the data mining model consists of a
mining structure plus an algorithm. The data mining
model remains empty until it applies the algorithm or
processes and analyzes the data provided by the
mining structure. This model stores the information
obtained from a statistical analysis of the data,
identifying patterns and gaining insights. It then
contains metadata that specify the name and definition
of the model, the server location or other place where it
is stored, definitions of any filters applied when
processing the model, columns from the mining
structure that were used to build the model, and the
algorithm used to analyze the data. The columns, their
data types, any filters, and the algorithm used are all
choices that are made in the data mining process, and
each of these decisions can greatly influence the data
mining results. The same data can be used to create
many models; one type of model could organize the
data into trees, for example, whereas another type of
model might cluster the data in groups based on the
rules applied. Different results can be achieved from
the same mining structure, even though it is used in
many models, based on the filtering method or analysis

conducted. Therefore, each decision made along the
way is very important.

There are many models. In this chapter, we will review
the following models: Cross-Industry Standard Process
for Data Mining (CRISP-DM), Six Sigma/Lean, and
SEMMA (Sample, Explore, Modify, Model, Access).

CRISP-DM
The CRISP-DM model follows a path or series of steps
to develop a business understanding by gaining an
understanding of the business data collected and
analyzed. The six steps are business understanding,
data understanding, data preparation, modeling,
evaluation, and deployment.

The CRISP-DM model begins with an understanding of
the business. The situation must be assessed to
establish the data mining goals and produce the project
plan. You must be able to answer the following
questions: What are the business objectives? What are
the requirements? Have we specifically defined the
problem? The answers to these questions help
transform the business perspective knowledge into a
data mining problem definition and initial plan to meet
the objectives.

Data understanding begins with the preliminary data
collection and assimilation of the data. It is during this

step that the data will be described and explored to
facilitate the user’s comprehension of the data. As the
user gains familiarity with the data, data quality issues
are identified and the quality of the data is verified.

The data are cleansed and transformed during the data
preparation step. First, one must select the data,
attributes, and records to be used. These data are then
cleansed, constructed, integrated, and properly
formatted. At this point, the final dataset is constructed
from the data; this dataset will be processed by the
model.

Modeling involves selection of the modeling methods
and their application to the prepared dataset.
Parameters are calibrated, a test design is generated,
and the model is built and assessed. This step might
require you to revisit data preparation if the format of
the data does not meet the specific requirements of the
methods.

During the evaluation step, the degree to which the
objectives were met is assessed from a business
perspective. A key question: Were any important
business issues not considered? The model was built
for high-quality data analysis. To see whether this goal
has been met, the process is reviewed, results
evaluated, and the model interpreted. This is where
you determine whether the model should be
implemented or whether more iterations must occur

before its deployment. The project may not be
completed, or a new data mining project might be
initiated. If the project is deployed, this step is when
you must decide how the results from the data analysis
will be used.

Deployment is the final step, in which the model is
finally implemented. The plan must be monitored and
maintained and the project reviewed. The six-step
process should yield a reliable, repeatable data mining
process. The knowledgeable insights gained from the
implementation of the model must be organized and
presented in such a way that they can be used. The
final project report is generated to document the
process and share this enhanced knowledge of the
data.

The CRISP-DM model employs a process that has
been proven to make data mining projects both more
rapid and more effectual. Using this model helps to
avoid typical mistakes while assessing business
problems and detailing data mining techniques.

Six Sigma
Six Sigma/Lean are data-driven methods to eliminate
defects, avoid waste, or assess quality control issues.
(Although they are often considered in tandem, we will
be discussing only Six Sigma here.) It aims to
decrease discrepancies in business and manufacturing

processes through dedicated improvements. Six Sigma
uses the DMAIC steps: define, measure, analyze,
improve, and control.

The first step defines the goals of the project or the
goals for improvement. During this step, you can use
data mining techniques to discover prospective ideas
for implementing the project.

In the measure step, exploratory and descriptive data
analyses are used on the existing system to enhance
the understanding of the data. Reliable, valid, and
accurate metrics with which to measure goal
achievement in each of the steps are identified.

The analysis step should assess the system to identify
discrepancies between the current big data and the
goal. Statistical methods guide this analysis.

Improvements must be made to the current system to
attain the organizational goals. The use of project
management skills facilitates the application of the new
methodology and processes. Statistical methods
assess the improvements and any deficiencies that
exist.

The final step of the model is control. Controlling the
system is important so discrepancies are remedied
before they cause a disruption.

The Six Sigma model applies a different mentality to
the same old business model or way of thinking. The
DMAIC steps that are implemented typically result in
success.

SEMMA
According to SAS (n.d.), “The acronym SEMMA—
sample, explore, modify, model, assess—refers to the
core process of conducting data mining” (para. 1). This
model is similar to Six Sigma but concentrates more on
the technical activities characteristically involved in
data mining.

The first step is to sample the data. Sampling is
optional but creates a more robust data mining effort.
Using “[a] statistically representative sample of your
data, SEMMA makes it easy to apply exploratory
statistical and visualisation techniques, select and
transform the most significant predictive variables,
model the variables to predict outcomes, and confirm a
model’s accuracy” (SAS, n.d., para. 1). Creating a
target dataset shrinks the data to a manageable size,
yet maintains the important information necessary to
mine.

The exploration of the data seeks to discover
discrepancies, trends, and relationships in the data. It
is at this point that ideas about the data should emerge
to help the organization understand the data and its

implications for the organization’s business. In health
care, for example, it would be important to determine
how many people use the emergency department each
year and how many of those people are admitted,
released, and return, and to identify any disparities in
care and diagnoses. What did you discover? What are
the trends and relationships that emerge from the data
mining?

After exploring, you should modify your data based on
the information discovered. It might be important to
modify the data based on groupings such as “all people
who are diagnosed with congestive heart failure who
present with shortness of breath” if the trending and
relationships indicate that this subgroup is significant.
Other variables can also be introduced at this time to
help gain a further understanding of the data.

The data are modeled to predict outcomes based on
analytically searching the data. Combinations of data
must be identified to predict desired outcomes.

During the assessment phase, the data as well as the
models are assessed for not only the reliability of the
discoveries, but also the usefulness of the data mining
process. Assessment is key to determine the success
of the data mining approach.

SEMMA focuses on the tasks of modeling. This
approach has been praised for its ability to guide the

implementation of data mining. Conversely, it has been
criticized for omitting the critical features of the
organization’s business. SEMMA is logical and can be
robust from sampling through assessment.

Based on the needs of the organization, a variety of
models can be used in combination. A coordinated,
cooperative environment is necessary for complicated
data mining projects, because they require
organizational commitment to ensure their success. As
described in this section, models such as CRISP-DM,
Six Sigma, and SEEMA have been designed as
blueprints to deal with the dilemma of how to integrate
data mining techniques into an organization. They
facilitate the gathering of data, the analysis of those
data, the conversion of the data into information, and
the dissemination of this information in a format that is
easy to digest and understand so as to inform
organizational decision making. It is imperative that the
results of the data mining process be implemented and
any resultant improvements monitored and evaluated.

Benefits of KDD
KDD can enhance the business aspects of healthcare
delivery and help to improve patient care. Some
examples of how KDD can be applied effectively follow:

A durable medical equipment company analyzed its
recent sales and enhanced its targeting of hospitals

and clinics that yielded the highest return on
investment (ROI).
Several plastic surgery suites were bought by the
same group of surgeons. They wanted to know how
those organizations were the same and how they
were different. They ran analytics for disparities
while looking for patterns and trends that led them
to develop standardized policies and modify
treatment plans.
Analytic techniques were used in the clinical trials of
a new oral contraceptive to aid in monitoring trends
and disparities.
Hidden patterns and relationships between death
and disease in selected populations can be
uncovered.
Government spending on certain aspects of health
care or specific disease conditions can be analyzed
to discover patterns and relationships and to
distinguish between the real versus desired
outcomes from the investment.
Patient data can be analyzed to identify effective
treatments and discover patterns or relationships in
the data to predict inpatient length of stay (LOS).
Data can be analyzed to help detect medical
insurance fraud.

Even though KDD can be complex, this process tends
to yield a potent knowledge representation. As
analytics evolve, KDD will almost certainly become

easier to use, more efficient, and more effective in
facilitating data mining in health care.

Data Mining and Electronic
Health Records
As EHRs become more prevalent, the data contained
therein can be mined for many different clinical and
organizational purposes. We have already established
the use of data-driven decision making in patient care
as supported by sophisticated EHR functions such as
clinical decision support and clinical pathways. Looking
beyond the management of individual patient health
care, however, we see that EHR data mining can help
with managing population health, assist with and inform
administrative processes, provide metrics for quality
improvement, support value-based reimbursement,
and provide data for registry software that helps with
population health management. O’Connor (2015)
stated, “Analytics is driving innovative solutions that
extract, aggregate and ‘interpret’ the massive volume
of data stored within EHR systems into actionable,
useful information physicians can use to improve
quality of care and make better-informed decisions in
the exam room” (para. 3). He also suggested the
following uses of EHR data in physician practices:

1. Demographic analytics support efficient
diagnosing.

2. Combining disparate data types creates
opportunities to strengthen financial planning.

3. Tracking the patient flow enables productivity
improvements.

4. Improving system performance in an
interconnected world. Information in an EHR
comes from diverse sources, hospitals, prior
doctors, third-party payers, and other
organizations.

5. Comparing your organization’s performance to
peers and national standards allows you to
discover strengths and weaknesses in your
operation (para. 4).

Registries are also being used to identify care gaps in
patient populations in a physician practice or other
healthcare organization. As Terry (2015) explained,
some EHRs have a built-in registry function, while
others interface with third party registries. Registries
are designed to:

Provide lists of subpopulations, such as patients
with hypertension and diabetes
Identify patients with care gaps, based on evidence-
based guidelines
Support outreach to patients who have care gaps
Provide feedback on how each physician is doing
on particular types of care, such as the percentage
of their diabetic patients who have their Hba1c
levels or blood pressure under control

Generate quality reports for the practice (para. 17)

Another type of clinical data mining designed to
improve patient outcomes is a retrospective look at
clinical data in an EHR, known as temporal event
analysis (Gotz, Wang, & Perer, 2014). As Gotz et al.
explained,

Our approach consists of three key
components: a visual query module, a
pattern-mining module, and an interactive
visualization module. We combine these
three technologies together within a
single framework that enables ad hoc
event sequence analysis. With this
capability, users are able to discover
patterns of clinical events (e.g.,
sequences of treatments or medications)
that most impact outcome. Moreover, our
approach allows users to better
understand how those associations
change as patients progress through an
episode of interest. (p. 150)

In addition, data in an EHR can be used for
administrative process improvement. Rojas, Munoz-
Gama, Sepúlveda, and Capurro (2016) conducted a
literature review on administrative process mining. “The
application of process mining in healthcare allows

health experts to understand the actual execution of
processes: discovering process models, checking
conformance with medical guidelines, and finding
improvement opportunities” (p. 234). Process mining is
a relatively new use of data generated in hospital
information systems and is dependent on event logs
generated in the system. As Rojas and colleagues
explained,

Activities are recorded in event logs for
support, control and further analysis.
Process models are created to specify
the order in which different health
workers are supposed to perform their
activities within a given process, or to
analyze critically the process design.
Moreover, process models are also used
to support the development of [health
information systems], for example, to
understand how the information system is
expected to support the process
execution. (p. 225)

It is clear that we have only begun to imagine how EHR
data mining can inform healthcare practices and
support quality improvement.

Ethics of Data Mining

Data mining in health care is dependent on the use of
private health information (PHI). Practitioners engaging
in data mining must ensure that such data are
deidentified and that confidentiality is maintained.
Because most data mining depends on the aggregation
of data, maintaining individual patient confidentiality
should be relatively straightforward. You can follow
changes and specific requirements for compliance with
HIPAA at this website:
http://www.hhs.gov/ocr/privacy/hipaa/understanding/special/research/index.html

Summary
Big data is everywhere—we collect and store data
every second of every day. The data in big clinical
datasets can get lost, however, diminishing its value.
Therefore, in health care, it is imperative that we use
KDD to analyze these datasets and discover
meaningful information that will influence our practice.
Our existing data repositories are ripe for the picking;
they contain hidden patterns, trends, and undiscovered
nuggets that we must mine to continue to hone our
understanding and improve health care.

Data management is essential so that this process can
begin with clean, good data. The decisions that are
made when conducting the analysis and when
developing the model and algorithms enable us to
predict and discover patterns and trends in the data,
thereby making them meaningful. We must be able not

only to extract meaningful information and knowledge,
but also to share and disseminate what we are learning
and the new knowledge we are generating.

THOUGHT-PROVOKING QUESTIONS

1. Reflect on these terms: database, data
warehouse, and data mining. What do
they have in common? How do they
differ?

2. Describe an issue associated with
healthcare data that impedes the
construction of meaningful databases and
inhibits the data mining process. Which
strategies would you use to remedy this
situation? Thoroughly describe one
strategy and its potential outcomes.

3. Suggest a data mining project for your
practice. Which information would you like
to have about your practice area that
could be extracted using data mining
strategies?

4. Data mining is associated with numerous
techniques and algorithms. How can you
make sure that you select and develop
those that best fit your data?

References

Berger, A. M., & Berger, C. R. (2004).
Data mining as a tool for research and
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Computers Informatics Nursing, 22(3),
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DeGruy, K. B. (2000). Healthcare
applications of knowledge discovery in
databases. Journal of Healthcare
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69. PubMed ID: 11066649

Fernández-Llatas, C., Garcia-Gomez, J.
M., Vicente, J., Naranjo, J. C., Robles,
M., Benedi, J. M., & Traver, V. (2011).
Behaviour patterns detection for
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Goodwin, L., Saville, J., Jasion, B., Turner,
B., Prather, J., Dobousek, T., & Egger,
S. (1997). A collaborative international
nursing informatics research project:
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patients. Studies in Health Technology
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Gotz, D., Wang, F., & Perer, A. (2014). A
methodology for interactive mining and
visual analysis of clinical event
patterns using electronic health record
data. Journal of Biomedical
Informatics, 48, 148–159.
doi:10.1016/j.jbi.2014.01.007

Green, J., Paladugu, S., Shuyu, X.,
Stewart, B., Shyu, C., & Armer, J.
(2013). Using temporal mining to
examine the development of
lymphedema in breast cancer
survivors. Nursing Research, 62(2),
122–129. PubMed ID: 23458909

IBM. (2013). Big data at the speed of
business. Retrieved from http://www-
01.ibm.com/software/data/bigdata

Lee, T., Lin K., Mills, M., & Kuo, Y. (2012).
Factors related to the prevention and
management of pressure ulcers.

Computers Informatics Nursing, 30(9),
489–495. PubMed ID: 22584879

Lee, T., Liu, C., Kuo, Y., Mills, M., Fong, J.,
& Hung, C. (2011). Application of data
mining to the identification of critical
factors in patient falls using a Web-
based reporting system. International
Journal of Medical Informatics, 80(2),
141–150. PubMed ID: 21115393

Madigan, E., & Curet, O. (2006). A data
mining approach in home healthcare:
Outcomes and service use. BMC
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PubMed ID: 16504115

Manyika, J., Chu, M., Brown, B., Bughin,
J., Dobbs, R., Roxburgh, C., & Byers,
A. (2011). Big data: The next frontier
for innovation, competition, and
productivity. McKinsey Global Institute.
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http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation

Moskowitz, A., McSparron, J., & Celi, L.
(2015). Preparing a new generation of

clinicians for the era of big data.
Harvard Medical Student Review, 2(1),
24–27. Retrieved from
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a-new-generation-of-clinicians-for-
the-era-of-big-data

O’Connor, S. (2015). 5 EHR data analytics
you aren’t paying attention to.
Advanced Data Systems Corporation.
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ehr-data-analytics-you-arent-paying-
attention-to

Rojas, E., Munoz-Gama, J., Sepúlveda,
M., & Capurro, D. (2016). Process
mining in healthcare: A literature
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Terry, K. (2015). Mining EHR data for
quality improvement. Medical
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PubMed ID: 18194717

CHAPTER 23:
Translational Research:
Generating Evidence for
Practice

Jennifer Bredemeyer Ida Androwich Dee McGonigle
and Kathleen Mastrian

Objectives
1. Clarify the differences between evidence-

based practice and translational
research.

2. Explore models for introducing research
findings into practice.

3. Assess barriers to research utilization in
practice.

Key Terms

» Agency for Healthcare Research and
Quality (AHRQ)

» Clinical informatics

» Clinical research informatics

» Context of care

» Evidence

» Evidence-based practice (EBP)

» Iowa model

» Meta-analysis

» National Guideline Clearinghouse
(NGC)

» Open Access Initiative

» Qualitative studies

» Quantitative studies

» Randomized controlled trial (RCT)

» Research utilization

» Research validity

» Translational bioinformatics

» Translational informatics

» Translational research

Introduction
Mr. James is an 87-year-old man with osteoarthritis in
his knees. He is frail and very thin and requires
assistance getting out of bed. Mary, a new registered
nurse, is making her rounds with her team members
and nurse’s aide. Realizing Mr. James is at risk for skin
breakdown and falls, she reviews the agency policy
manual regarding pressure ulcer prevention and fall
prevention. Which other resources could Mary consult
if she wanted more information on preventing these
issues? If Mary wanted to know what the current
research suggests about preventing each of these
conditions, how would she obtain this information?

This chapter introduces the concept of translational
research and its role in evidence-based practice with
specific emphasis on nursing informatics. Before
pursuing the content in this chapter, the reader should
already have an understanding of nursing research, the
Foundation of Knowledge model, and knowledge
generation through nursing research. Key words and
definitions used in this chapter are described briefly
next. Classic sources (5 years or older) are used to
enhance the reference base.

If I limit what I speak about to what I know
from experience to be true rather than
what I think I am expected to say or what

I am pressured to say, then I will have a
contribution to make. (Camus, 1943)

Clarification of Terms
Evidence-based practice, translational research, and
research utilization are all terms that have been used
to describe the application of evidential knowledge to
clinical practice. The following paragraphs explore the
definitions of each term. Although these terms are
related, they have slightly different meanings and
applications.

Evidence-based practice (EBP), developed originally
for its application to medicine, is defined by Sackett et
al. (1996) as “The conscientious, explicit and judicious
use of current best evidence in making decisions about
the care of individual patients” (p. 71). The “best
evidence” in this context refers to more than just
research. Goode and Piedalue (1999) stated that
evidence-based practice should be combined with
other knowledge sources and “involves the synthesis of
knowledge from research, retrospective or concurrent
chart review, quality improvement and risk data,
international, national, and local standards, infection
control data, pathophysiology, cost effectiveness
analysis, benchmarking data, patient preferences, and
clinical expertise” (p. 15). EBP starts with a clinical
question to resolve a clinical problem (see Figure 23-

1). For example, published research studies are used
in healthcare quality initiatives as the evidence behind
the development of practice algorithms designed to
decrease practice variability, increase patient safety,
improve patient outcomes, and eliminate unnecessary
costs. Use of EBP promotes the use of clinical
judgment and knowledge in relation to the patient’s
contextual situation and preferences, with procedures
and protocols being linked to scientific evidence rather
than based on what is customary practice or opinion.

Figure 23-1 Evidence-Based Practice

Research utilization is the use of findings from one or
more research studies in a practical application

unrelated to the original study (Polit & Beck, 2008, p.
29), resulting in the generation of new knowledge.
Stetler (2001) defines research utilization as the
“process of transforming research knowledge into
practice” (p. 274). Research utilization can be self-
limiting if research is inconsistent or not enough
research is available to develop a consensus regarding
the answer to the clinical question (Kirchhoff, 2004).

Translational research (science) describes the
methods used in translating medical, biomedical,
informatics, and nursing research into bedside clinical
interventions. Refer to Figure 23-2. Woolf (2008)
described translational research in two ways:

Figure 23-2 Translational Research Pathway

T1: the transfer of clinical research to its first testing
on humans
T2: the transfer of clinical research to an everyday
clinical practice setting

Difficulties in translating research to the T2 setting exist
when research applications do not fit well within the
clinical context or practical considerations constrain the
application in a clinical setting. Translational research
is complicated by the follow-up analysis, practice, and
policy changes that occur when adopting research into
practice; consequently, available evidence-based
healthcare practices are often not fully incorporated
into daily care (Titler, 2004, 2010). Organizational
culture influences the changes made to a clinical
application and establishes the groundwork and the
support for change-making activities (Titler, 2004). The
study of ways to promote the adoption of evidence in
the healthcare context is called “translation science”
(Titler, 2010).

Translational bioinformatics is the “development of
storage, analytic, and interpretive methods to optimize
the transformation of increasingly voluminous
biomedical data, and genomic data, into proactive,
predictive, preventive, and participatory health
(American Medical Informatics Association [AMIA],
2016c, para. 1). It integrates biological and clinical data
and the evolution of clinical informatics methodology to
include biological observations. “The end product of
translational bioinformatics is newly found knowledge
from these integrative efforts that can be disseminated
to a variety of stakeholders, including biomedical
scientists, clinicians, and patients” (AMIA, 2016c, para.
1).

Clinical informatics is the “application of informatics
and information technology to deliver healthcare
services. It is also referred to as applied clinical
informatics and operational informatics” (AMIA, 2016a,
para. 1).

Clinical research informatics is defined by AMIA
(2016b) as involving the use of informatics in the
discovery and management of new knowledge relating
to health and disease. “It includes management of
information related to clinical trials and also involves
informatics related to secondary research use of
clinical data. Clinical research informatics and
translational bioinformatics are the primary domains
related to informatics activities to support translational
research” (para. 1).

History of Evidence-Based
Practice
Research results are crucial to furthering EBP. The
concept of using randomized controlled trials and
systematic reviews as the gold standard against which
one should evaluate the validity and effectiveness of a
clinical intervention was introduced in 1972 by Archie
Cochrane, a scientist and a physician (Cochrane,
1972). Cochrane’s experiences as a prisoner of war
and medical officer while interning during World War II

led to his belief that not all medical interventions were
needed and some caused more harm than good.
Cochrane viewed the randomized clinical trial as a
means of validating clinical interventions and limiting
the interventions to those that were scientifically based,
effective, and necessary (Dickersin & Manheimer,
1998).

Cochrane’s colleague, Iain Chalmers, began compiling
a comprehensive clinical trials registry of 3,500 clinical
trial results in the field of perinatal medicine. In 1988,
after being published in print 3 years earlier, the
registry became available electronically. Chalmers’s
methods for compiling the trials databases became a
model for future registry assembly. Eventually, the
National Health Service in the United Kingdom,
recognizing the value of and need for systemic reviews
for all of health care, developed the Cochrane Center.
The Cochrane Collaboration was initiated in 1993 and
expanded internationally to maintain systematic
reviews in all areas of health care (Dickersin &
Manheimer, 1998). Many universities subscribe to the
Cochrane Collaboration database, making this
information easily accessible to students, faculty, and
nurses who work for university hospital systems. Visit
www.cochrane.org for a link to the latest Cochrane
evidence.

Evidence

The randomized controlled trial (RCT) is considered
the most reliable source of evidence. Yet, RCTs are not
always possible or available; consequently, nurses
must use critical analysis to base their clinical decision
making on the best available evidence (Baumann,
2010). The updated Stetler model of research
utilization (Stetler, 2001) identified internal and
external forms of evidence. External evidence
originates from research and national experts, whereas
internal forms of evidence originate from nontraditional
sources, such as clinical experience and quality
improvement data.

Evidence includes standards of practice, codes of
ethics, philosophies of nursing, autobiographic stories,
esthetic criticism, works of art, qualitative studies, and
patient and clinical knowledge (Melnyk, Fineout-
Overholt, Stone, & Ackerman, 2000). French (2002)
summarizes evidence as “truth, knowledge (including
tacit, expert opinion and experiential), primary research
findings, meta-analyses and systematic reviews” (p.
254). Nurses may additionally draw on evidence from
the context of care, such as audit and performance
data, the culture of the organization, social and
professional networks, discussion with stakeholders,
and local or national policy (Rycroft-Malone et al.,
2004, p. 86).

Concern has been voiced by nurse theorists that
nurses are being influenced too much by the medical

model in accepting the RCT as the only true source of
evidence, thereby “reverting to the medical
perspective” rather than incorporating “theory-guided
evidence and diverse ways of knowing” (Fawcett,
Watson, Walker, & Fitzpatrick, 2001, p. 115). The
context change from medicine to nursing requires
nurses to apply other knowledge and nursing theory.
The use of research results as the sole basis for
clinical decision making ignores other types of
evidence inherent in nursing practice (Scott-Findlay &
Pollock, 2004).

To use evidence in practice, the weight of the research,
also called research validity, must be determined.
Evidence hierarchies have been defined to grade and
assign value to the information source. For example,
an evidential hierarchy developed by Stetler et al.
(1998) prioritized evidence into six categories:

1. Meta-analysis
2. Individual experimental studies
3. Quasi-experimental studies
4. Nonexperimental studies
5. Program evaluations, such as quality

improvement projects
6. Opinions of experts

The hierarchy identifies meta-analysis as the highest-
quality evidence because it uses multiple individual
research studies to reach a consensus. It is interesting

to note that opinions of experts are considered the
least significant in this hierarchy, yet nurses most often
seek the opinion of a more experienced colleague or
peer when searching for information regarding patient
care (Pravikoff, Tanner, & Pierce, 2005).

Qualitative research allows one to understand the way
in which the intervention is experienced by the
researcher and the participant and the value of the
interventions to both parties (O’Neill, Jinks, & Ong,
2007). Qualitative research is not always considered in
EBP, because methods for synthesizing the evidence
do not currently exist. The Cochrane Qualitative
Research Methods Group (CQRMG) has developed
search, appraisal, and synthesis methodologies for
qualitative research (Joanna Briggs Institute, n.d.)
and provides a database of articles related to
methodological research (Cochrane Collaboration,
2016).

Bridging the Gap Between
Research and Practice
The time between research dissemination and clinical
translation may be significant, and this delay may
adversely affect patient outcomes. Bridging the gap
between research and practice requires an
understanding of the key concepts and barriers, access
to research findings, access to clinical mentors for

research understanding, a reinforcing culture, and a
desire on the part of the clinician to implement best
practices (Melnyk, 2005; Melnyk, Fineout-Overholt,
Stetler, & Allen, 2005). In the Iowa model of EBP,
research and other evidential sources are adopted
directly in the practice setting with the goal of
developing a standard of care and team decision
making (Schaffer, Sandau, & Diedrick, 2013; Titler,
2007). Additionally, the groundwork required to create
a conceptual framework supportive of an EBP includes
workplace culture change and support of the change
through leadership (Stetler et al., 1998). Beliefs and
attitudes, involvement in research activities, information
seeking, professional characteristics, education, and
other socioeconomic factors are potential determinants
of research utilization (Estabrooks, Floyd, Scott-
Findlay, O’Leary, & Gushta, 2003); however, meta-
analysis points out that too much original research and
not enough repetition of previous studies fails to
advance the knowledge base.

Developing countries are often constrained
economically from accessing research sources. Such
organizations as the Cochrane Collaboration provide
free reviews to fill this void. Even so, knowledge
dissemination strategies and education are required to
take advantage of these resources (Cochrane
Collaboration, 2004).

Barriers to and Facilitators of
Evidence-Based Practice
Tacia and colleagues (2015) concluded there were six
challenges or barriers to the application of EBP:
“institutional and/or cultural barriers, lack of knowledge,
lack of motivation, time management, physician and
patient factors, and limited access to up to date, user-
friendly technology and computer systems” (p. 93).
Nurses may also see the job of interpreting research as
too complex or see the organizational culture as a
barrier to implementation of EBP (Kieft, de Brouwer,
Francke, & Delnoij, 2014; McCaughan, Thompson,
Cullum, Sheldon, & Thompson, 2002). Many believe
that inpatient direct care nurses lack basic knowledge
of EBP and must have access to and assistance with
technical resources.

Yet, Melnyk and colleagues (2009) noted that a
number of factors also facilitate the use of EBP. These
driving forces include knowledge and skills in EBP;
having a conviction that there is a value to using
evidence in practices; and practicing in a supportive
culture with tools available to sustain evidence-based
care, including access to computers and databases,
evidence-based content at the point of care, and the
presence of EBP mentors. Tacia et al. (2015) noted
that interprofessional collaboration, mentorship, and
administrative support were necessary for the adoption

of EBP. It is imperative that we remove the barriers and
support nurses using EBP, as well as continuing to
mentor and work with those who are just beginning to
initiate EBP in their practice.

The Role of Informatics
Computers are used in all areas of research: (1)
literature search databases, such as CINAHL; (2)
online literature reference lists, such as RefWorks; (3)
data capture, collection, and coding; (4) data analysis;
(5) data modeling; (6) meta-analysis; (7) qualitative
analysis; and (8) dissemination of results (Saba &
McCormick, 2006). The context for nursing informatics
has expanded to support dramatic changes in the way
science is accomplished. Information need and the
collaborative component of interdisciplinary research
rely heavily on technology and informatics.
Technologies such as social networking have also
improved collaboration. The use of technology and
informatics in facilitating interdisciplinary and
translational research is a key architectural component
of the National Institutes of Health’s (NIH’s)
reengineering of the clinical research enterprise as part
of its road map initiative for medical research (NIH,
2009). As technology continues to advance, so do the
informatics tools available to researchers. The
Institute of Translational Health Sciences (2016)
offers a deidentified clinical data repository, data quest,

and research electronic data capture (REDCap), which
is

a rapidly evolving web tool developed by
researchers for researchers in the
translational domain. REDCap features a
high degree of customizability for your
forms and advanced user right control. It
also features free, unlimited survey
functionality, a sophisticated export
module with support for all the popular
statistical programs, and supports HIPAA
compliance. (para. 1)

Clinical research informatics at the Oregon Clinical &
Translational Research Institute (2016) accelerates
translational research “by providing informatics tools to
leverage clinical data (Epic) for research and to
develop state-of-the-art clinical research data collection
and management software and expertise. These tools
support a diverse array of research including bench-to-
bedside, clinical, and healthcare systems research”
(para. 1). Translational informatics refers to the
application of research informatics to translational
research in order to close the gap from research to the
bedside to improve the health of patients and the
community.

An informatics infrastructure is critical to EBP. Bakken,
Stone, and Larson (2008) discussed expanding the
context of informatics to genomic health care, shifting
research paradigms, and social Web technologies.
Ensuring the global collaborative nature of nursing
research for 2010–2018 requires an expansion of the
nursing research agenda to user information needs,
data management, information support for nurses and
patients, practice-based knowledge generation, and
design evaluation methodologies. Giuse et al. (2005)
described the evolving role of the clinical informationist
(informaticist) as being a partner on the healthcare
team who provides timely clinical evidence for the
clinical workflow. Although not specific to nursing
informatics, the NIH provides awards under its Clinical
and Translational Science Award (CTSA) program to
accelerate the transfer of research to the clinical setting
(NIH, 2016). The Quality and Safety Education for
Nurses (QSEN; 2013) cites key competencies
(knowledge, skills, and attitudes) in both EBP and
informatics. With the goal of promoting the use of
research findings and tool use based on these findings,
the Agency for Healthcare Research and Quality
(AHRQ) became an active participant in pushing
evidence forward into practice. The AHRQ is a
government-sponsored organization with the mission of
reducing patients’ risk of harm, decreasing healthcare
costs, and improving patient outcomes through the
promotion of research and technology applications
focused on EBP. In 1999, AHRQ implemented its

Translating Research into Practice Initiative (TRIP) to
generate knowledge about evidence-based care
(AHRQ, 2001). In the second Translating Research
into Practice Initiative (TRIP-II), the focus shifted to
improving health care for underserved populations and
using information technology to shape translational
research and health policy. AHRQ, in partnership with
the American Medical Association and the American
Association of Health Plans, developed the National
Guideline Clearinghouse (NGC). NGC is a
comprehensive database of evidentially based clinical
practice guidelines and related documents that are
regularly published through the NGC electronic mailing
list and are available on the NGC website
(https://guideline.gov). The NGC website allows
users to browse for the clinical guidelines, view
abstracts and full-text links, download full text clinical
guidelines to personal digital assistant (PDA) devices
and smartphones, obtain technical reports, and
compare guidelines. PubMed4Hh (PubMed for
handheld devices) is a powerful and free application for
smartphones that provides access to the national
Library of Medicine and supports PICO searches,
clinical queries, and multilanguage searches with links
to consensus abstracts.

In addition, a growing number of printed and electronic
resources are available to assist in creating guidelines
and offering information about EBP. A selection of
existing websites is shown in Table 23-1.

Table 23-1 The Role of Informatics: Online Evidence-
Based Resources

Website Description

Academic Center for Evidence-Based Practice (ACE)

www.acestar.uthscsa.edu
The School of

Nursing at the

University of

Texas Health

Science Center

at San Antonio

sponsors the

Academic

Center for

Evidence-

Based Practice.

The center’s

ultimate goal is

to bring

research to

practice to

improve patient

care,

outcomes, and

safety. The

center is also

home to the

ACE star model

of knowledge

transformation.

The Agency for Healthcare Research and Quality www.ahrq.gov The Agency for
Healthcare

Research and

Quality

contains a

wealth of

information

regarding

healthcare

quality. There is

no charge for

access to the

site or its

resources.

BMJ Clinical Evidence

http://clinicalevidence.bmj.com/x/index.html
The BMJ

publishing

group provides

clinical

databases by

prescription.

The BMJ

Clinical

Evidence site

allows the

download of

some clinical

papers and

some

interesting risk

tools without

charge.

The Center for Evidence-Based Practices (CEBP)

www.evidencebasedpractices.org
The Center for

Evidence-

Based

Practices of the

Orelena Hawks

Puckett

Institute

focuses on

research to

practice

initiatives

related to early

intervention,

early childhood

education,

parent and

family support,

and family-

centered

practices.

Centre for Evidence-Based Medicine www.cebm.net The Centre for
Evidence-

Based

Medicine,

located in

Oxford in the

UK, is devoted

to developing

and promoting

evidence-based

resources for

healthcare

professionals.

In addition to

free articles,

the site also

provides free

teaching

resources and

presentation.

CINAHL www.cinahl.com CINAHL
information

systems offers

a multitude of

online services,

which include

website link

sources,

CINAHL’s

online nursing

and allied

health

database,

document

delivery, and

search

services.

The Cochrane Collaboration www.cochrane.org The Cochrane
Collaboration

provides

reviews for

free, but full-

text articles are

by subscription.

Entrez Pub

Medwww.ncbi.nlm.nih.gov/pubmed

Entrez Pub

Med is a

service

provided by

The National

Library of

Medicine

(NLM). The

NLM was

developed by

the National

Center for

Biotechnology

Information

(NCBI), which

provides

access to life

science

journals and

MEDLINE

citations. Some

of the journal

links are free,

and some

require a

subscription.

Information & Resources for Nurses

Worldwidewww.nurses.info/specialty_evidenced_based_orgs.htm

This website

provides

searchable

links to

evidence-based

practice

organizations

by specialty.

The Iowa Model of Evidence-Based

Practicewww.nnpnetwork.org/ebp-resources/iowa-model

This website

provides a brief

overview of the

Iowa Model for

Evidence-

Based Practice

(for members

only).

The Joanna Briggs Institute www.joannabriggs.org The Joanna
Briggs Institute

was

established in

1996 as a

resource for

best care

practices.

Joanna Briggs

was first matron

of the Adelaide

Hospital in

Australia and is

recognized for

her financial

and

organizational

support. The

Joanna Briggs

Institute is a

leader in

developing

evidence-based

practices.

The Johns Hopkins Bloomberg School of Public Health,

Evidence-Based Practice

Centerwww.jhsph.edu/research/centers-and-institutes/johns-

hopkins-evidence-based-practice-center

The Johns

Hopkins

Evidence-

Based Practice

Center was

established in

1997 and is

one of 14 such

centers

producing

comprehensive,

systematic

reviews for the

AHRQ.

Pub

Med Centralwww.ncbi.nlm.nih.gov/pmc

Pub

Med Central

(PMC) is a free

digital archive

of science-

related articles

managed by

the NCBI. Bio

Med Central

(an open-

source online

archive) may

be accessed

here.

Trip databasewww.tripdatabase.com The Trip

database is a

clinical search

tool to allow

clinicians to

identify the best

evidence for

clinical practice.

World Views on Evidence-Based

Nursinghttp://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1741-

6787

Through

Blackwell

Publishing, this

magazine,

sponsored by

Sigma Theta

Tau

International, is

dedicated

exclusively to

evidence-based

nursing articles.

The magazine

is also offered

online by

subscription.

Developing EBP Guidelines
Several models have been developed to guide
organizations into translating research into practice.
Brief descriptions of these models are provided in
Table 23-2. As an example, Titler (2007) identified the
steps in the Iowa model for translating research into
practice as (1) identifying the problem, issue, or topic in
nursing practice; (2) research and critique of related
evidence; (3) adaptation of the evidence to practice; (4)
implementation of the EBP; and (5) evaluation of
patient outcomes and care practices. Careful analysis
and discussion of the research or other forms of
evidence in this scenario may reveal that given the
context, implementation may not be practical.
Following implementation, results must be monitored to
determine whether the application works for the
context. Thoughtful discussion of the findings will help
the clinical team determine if further research is
warranted or if further change is needed. As a practical
application, evidence-based standards for care are

developed by hospitals to meet the American Nurses
Association/American Nurses Credentialing Center
standards for achieving Magnet hospital recognition.

Table 23-2 Comparison of Model Approaches to
Evidence-Based Practice

Stetler Model
(Stetler, 2001)

ACE Star Model
(Stevens, 2004)

The Iowa Model of
Evidence-Based
Practice to Promote
Quality Care (Titler
et al., 2001)

1. Preparation

2. Validation

3. Cooperative

evaluation

4. Decision

making

5. Translational

application

6. Evaluation

1. Discovery

2. Evidence

summary

3. Translation

4. Integration

5. Evaluation

1. Select the

trigger as

impetus for

practice

(knowledge

focused or

practice

focused)

change.

2. Determine if

the topic is

worth

pursuing for

the

organization

and if not,

pursue new

trigger.

3. Determine if

there is

significant

research

base. If so,

change,

otherwise

conduct

research or

seek more

research.

4. If change is

appropriate

for practice,

implement

change.

5. Monitor

results.

6. Disseminate

results.

Data from Stetler, C. B. (2001). Updating the Stetler model of
research utilization to facilitate evidence-based practice. Nursing

Outlook, 49(6), 272–279; Stevens, K. R. (2004). ACE star model of
EBP: Knowledge transformation. Retrieved July 2010 from

http://www.acestar.uthscsa.edu/Learn_model.htm; Titler, M. G.,
Kleiber, C., Steelman, V., Rakel, B., Budreu, G., Everett, L., . . .

Goode, T. (2001). The Iowa model of evidence-based practice to

promote quality care. Critical Care Nursing Clinics of North America,

13(4), 497–509.

Information technology is important in synthesizing the
research regardless of the model. Bakken (2001)
recommended (1) standardized nomenclature required
for the electronic health record (standardized
terminologies and structures); (2) digital sources of

evidence; (3) standards that facilitate healthcare data
exchange among heterogeneous systems; (4)
informatics processes that support the acquisition and
application of evidence to a specific clinical situation;
and (5) informatics competencies (p. 1999). Bakken’s
recommendations encouraged the development of an
infrastructure that creates a database of experiential
clinical evidence.

Meta-Analysis and Generation
of Knowledge
Systematic reviews combine results from multiple
primary investigations to obtain consensus on a
specific area of research. Studies are discarded from
the review if they are not considered sound, thereby
creating a reliable end result. The strength of the
systematic review is its ability to corroborate findings
and reach consensus. Systematic reviews show the
need for more research by revealing the areas where
quantitative results may be lacking or minimal. Bias
may occur if the selected studies are inadequate, if all
sources of evidence are not investigated, or if the
publications selected are not adequately diverse (Lipp,
2005). The BMJ Clinical Evidence Blog
(http://blogs.bmj.com/ce) has stressed the
importance of getting evidence into health service
decision making, but to beware of evidence spin that
adds bias to the reporting of the evidence.

Meta-analysis, a form of systematic review, uses
statistical methods to combine the results of several
studies (Cook, Mulrow, & Haynes, 1997). Quantitative
studies are typically used. According to Glass (1976),
meta-analysis is the statistical analysis of a large
collection of analysis results from individual studies for
the purpose of integrating the findings (p. 3).

Kraft (2006) described the documentation search
strategy for meta-analysis as beginning with the
identification of the studies through a search of
bibliographic databases, identification of meta-analysis
articles that match the search criteria, elimination of
those articles that do not match the search criteria,
review of the reference lists in the meta-analysis for
other articles that may relate to the topic, and review of
each article for quality and content. Additional sources
should include unpublished works, such as
conferences and dissertation abstracts, with the goal of
obtaining as many relevant articles as possible.
Gregson, Meal, and Avis (2002) identified the steps of
a meta-analysis as (1) defining the problem, followed
by protocol generation; (2) establishing study eligibility
criteria, followed by literature search; (3) identifying the
heterogeneity of results of studies; (4) standardizing
the data and statistically combining the results; and (5)
conducting sensitivity testing to determine whether the
combined results are the same. The often-cited
criticism of meta-analysis is that emphasis is on
quantitative studies, not qualitative studies.

Additionally, the analysis is only as good as the studies
used (Gregson, Meal, & Avis). Collection and
dissemination of these meta-analysis and systematic
reviews are available in paper and on the Internet,
although many such databases require a subscription.

The term “open access” refers to a worldwide
movement to make a library of knowledge available to
anyone with Internet access. The Open Access
Initiative came about in response to the tremendous
cost of research library access. Libraries pay large fees
for journal subscriptions, and the richness of library
references is limited to what the budget allows. The
cost of keeping current with research has caused
library subscriptions to decline (Yiotis, 2005). Open
access adds to the controversy, with some journals
charging authors for publication of their work, which in
itself may provide a financial barrier to publication in
this form.

According to Suber’s (2015) open access overview,
open access refers to digital literature that is available
to anyone with Internet access free of charge. There
are two vehicles for open access: archives and
journals. Open access journals are generally peer
reviewed and freely available. The publishers of open
access journals do not charge the reader, but rather
obtain funds for publishing elsewhere. Open access
journals may charge the author or depend on other

forms of funding, such as donations, grants, and
advertising, to publish.

The Future
Our future depends on a prepared workforce ready to
meet the challenges of tomorrow. This will require a
focus on informatics, bioinformatics, clinical research,
translational research, other research methods, and
evidence-based practice. In this data-driven healthcare
delivery system in which we work, we must adopt data
standards. Given the vast amounts of data, Bakken et
al. (2008) identified areas of focus for nursing
informatics in knowledge representation, data
management, analysis, and predictive modeling in
genomic health care and the need for policies and
procedures to protect data acquisition, dissemination,
privacy, security, and confidentiality, as well as
education in these areas. Informatics tools support
nursing practice, education of healthcare consumers,
and knowledge generation. The technology is available
now to incorporate evidence into reference links
embedded in electronic clinical care plans.
Incorporation of personalized clinical desktops to allow
each clinician to have appropriate references (similar to
Internet ad bot technology) provided to him or her may
be possible. The other challenge includes developing
and maintaining interprofessional collaborative
environments that truly operate in a cooperative and
open manner. Time, research, and technology will tell.

Summary
These are amazing times. Technology has taken us
faster and further than we ever thought possible.
Healthcare jobs have become more technical and more
complicated. In some ways, technology has increased
the margin for error. Some healthcare practitioners will
continue to rely on little scraps of paper and
nonsystematic methods to keep themselves and their
patients safe. Unfortunately, individuals who become
so tied to these things close their mind to new
innovations. The evolving quality culture and increased
patient safety concerns are dragging healthcare
workers forward. For the benefit of our patients, health
care must move forward.

Collaboration, improved access to online libraries,
research tool transparency, a common data language,
organizational and informational support, and
continued research are a short list of needed items to
advance translational research. Repeat studies are
needed to provide meaningful meta-analysis and
systematic reviews. Technology advancement in the
area of incorporating evidence into clinical tools must
continue. Removing the barriers to knowledge-seeking
behavior and providing access to evidential resources
will promote knowledge and, in the end, improve
patient outcomes.

THOUGHT-PROVOKING QUESTIONS

1. Twelve-hour shifts are problematic for
patient and nurse safety, yet hospitals
continue to keep the 12-hour shift
schedule. In 2004, the Institute of
Medicine (Board on Health Care
Services & Institute of Medicine, 2004)
published a report that referred to studies
as early as 1988 that discussed the
negative effects of rotating shifts on
intervention accuracy. Workers with 12-
hour shifts experienced more fatigue than
workers on 8-hour shifts. In another study
done in Turkey by Ilhan, Durukan, Aras,
Turkcuoglu, and Aygun (2006), factors
relating to increased risk for injury were
age of 24 years or younger, less than 4
years of nursing experience, working in
surgical intensive care units, and working
for more than 8 hours. As a clinician
reading these studies, what would your
next step be?

2. The use of heparin versus saline to
maintain the patency of peripheral
intravenous catheters has been
addressed in research for many years.
The American Society of Health System
Pharmacists (ASHSP) published a
position paper in January 2006

advocating its support of the use of 0.9%
saline in the maintenance of peripheral
catheters in nonpregnant adults. It seems
surprising that this position paper
references articles that advocate the use
of saline over heparin dating from 1991.
What do you believe are some of the
barriers that would have caused this
delay in implementation?

In the era of EBP, healthcare providers must continue
to think critically about their actions. What is the
science behind their interventions? Healthcare workers
must no longer do things one way just because they
have always been done that way. Research the
problem; use evidence-based resources; critically
select electronic and nonelectronic references;
consolidate the research findings and combine and
compare the conclusions; present the findings; and
propose a solution. One will be the first to ask why and
may be a key player in making change happen.

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Titler, M. G., Kleiber, C., Steelman, V.,
Rakel, B., Budreu, G., Everett, L., . . .
Goode, T. (2001). The Iowa model of
evidence-based practice to promote
quality care. Critical Care Nursing
Clinics of North America, 13(4), 497–
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CHAPTER 24:
Bioinformatics,
Biomedical Informatics,
and Computational
Biology

Dee McGonigle and Kathleen Mastrian

Objectives
1. Describe bioinformatics, biomedical

informatics, and computational biology.
2. Appreciate the intertwining of

bioinformatics and health care in
biomedical informatics.

3. Imagine the future of health care based
on genomics.

Key Terms
» Alleles

» Bioinformatics

» Biomedical informatics

» Computational biology

» Datasets

» Genome

» Genomics

» Haplotypes

» HapMap

» Human Genome Project

» Informaticists

Introduction
The National Center for Biotechnology Information
(NCBI; 2004) states that “Biology in the 21st century is
being transformed from a purely lab-based science to
an information science as well” (para. 5). What must be
remembered when delving into the new informatics
frontier is that biological systems are information
systems. Consider that DNA essentially is a storehouse

of information. Unlocking that information and learning
how that information is transcribed to RNA and
ultimately expressed as proteins promises interesting
and cutting-edge developments in understanding
diseases and managing them at the molecular level.
This chapter introduces the reader to the exciting world
of bioinformatics and provides a beginning
understanding of the frontiers unleashed by the
collection, mapping, storage, and sharing of genetic
data.

Bioinformatics, Biomedical
Informatics, and
Computational Biology
Defined
Three terms are frequently used: (1) bioinformatics,
(2) biomedical informatics, and (3) computational
biology. As terms continue to be bandied about, it is
important to comprehend what they mean to
understand better these evolving fields. According to
the University of Texas at El Paso (2010) website,
“Bioinformatics is an interdisciplinary science with a
focus on data management and interpretation for
complex biological phenomena that are analyzed and
visualized using mathematical modeling and numerical
methodologies with predictive algorithms” (para. 1). A
website operated by the University of Minnesota
(2012) stated:

Bioinformatics is defined here as an
interdisciplinary research area that
applies computer and information science
to solve biological problems. However,
this is not the only definition. The field is
being defined (and redefined) at present,
and there are probably as many
definitions as there are bioinformaticians
(bioinformaticists?). (para. 1)

The myriad of definitions for the “moving target named
bioinformatics” (University of Minnesota, 2012, para.
2) is reflected in those developed from 2000 to 2009.
According to NCBI (2004), “Bioinformatics is the field of
science in which biology, computer science, and
information technology merge to form a single
discipline. The ultimate goal of the field is to enable the
discovery of new biological insights” (para. 5). Network
Science (2009) believed that

[a]n absolute definition of bioinformatics
has not been agreed upon. The first level,
however, can be defined as the design
and application of methods for the
collection, organization, indexing,
storage, and analysis of biological
sequences (both nucleic acids [DNA and
RNA] and proteins). The next stage of
bioinformatics is the derivation of

knowledge concerning the pathways,
functions, and interactions of these genes
(functional genomics) and proteins
(proteomics). (para. 14)

Mulligen et al. (2008) wrote that

BioInformatics (BI) is a less mature
scientific discipline which aims to
research and develop algorithms,
computational and statistical techniques
which solve biological problems.
Significantly, BI has experienced an
exponential growth as a result of its
importance to the understanding and
interpretation of data generated by
“omics” technologies. (para. 6)

The complete sequencing of the human genome has
led to systems biology referred to as “omics” and has
elevated scientists’ ability from studying one gene or
protein to studying fundamental biological processes
(Box 24-1).

BOX 24-1 OMICS

Kelly (2008) describes that “‘ome’ and ‘omics’
are suffixes that are derived from genome”
(para. 1). National Public Radio (2010) credits

botanist Hans Winkler with merging “the Greek
words ‘genesis’ and ‘soma’ to describe a body of
genes” (para. 1) in 1920. The term “genome”
was born from this combination, and genomics
arose as the study of the genome.

Kelly (2008) continues to explain:

Scientists like to append these to
any large-scale system (or really,
just about anything complex), such
as the collection of proteins in a
cell or tissue (the proteome), the
collection of metabolites (the
metabolome), and the collection of
RNA that’s been transcribed from
genes (the transcriptome). High-
throughput analysis is essential
considering data at the “omic”
level, that is to say considering all
DNA sequences, gene expression
levels, or proteins at once (or, to
be slightly more precise, a
significant subset of them). (para.
1)

The National Human Genome Research Institute
(NHGRI; 2015) describes bioinformatics as a branch of
biology concerned with the acquisition, storage,

display, and analysis of the information found in nucleic
acid and protein sequence data. Computers and
bioinformatics software are the tools of the trade.
Based on these definitions, one can get a flavor for
what bioinformatics entails. It is clear that the definition
of bioinformatics varies, and that there is no single
definition that everyone agrees with at the present
time.

Biomedicine applies bioinformatics to promote health.
According to the website of the Ohio State University
Medical Center (2010), “Biomedical informatics is the
study and process of efficiently gathering, storing,
managing, retrieving, analyzing, communicating,
sharing, and applying biomedical information to
improve the detection, prevention, and treatment of
disease” (para. 2). The Vanderbilt University (2016)
website suggested that

Biomedical Informatics is the
interdisciplinary science of acquiring,
structuring, analyzing and providing
access to biomedical data, information
and knowledge. As an academic
discipline, biomedical informatics is
grounded in the principles of computer
science, information science, cognitive
science, social science, and engineering,
as well as the clinical and basic biological
sciences. (para. 1)

Oregon Health & Science University (OHSU; 2016)
defined biomedical informatics as “the field that is
concerned with the optimal use of information, often
aided by the use of technology, to improve individual
health, health care, public health, and biomedical
research” (para. 1). Bioinformatics can be viewed as a
biological science or computer science. According to
the Bioinformatics Organization (2011),
bioinformatics as a biological science can be defined
as “any use of computers to characterize the molecular
components of living things” (para. 2). As a computer
science, bioinformatics is the use of “computers to
store, retrieve, analyze or predict the composition or
the structure of biomolecules” (Bioinformatics
Organization, para. 3).

Biomedical informatics is a growing field, with
significant applications and implications throughout the
biomedical and clinical worlds. The authors believe that
biomedical informatics is the application of
bioinformatics to health care.

Computational biology is the action complement of
bioinformatics and, therefore, biomedicine. NCBI
(2004) stated:

Ultimately, however, all of this information
must be combined to form a

comprehensive picture of normal cellular
activities so that researchers may study
how these activities are altered in
different disease states. Therefore, the
field of bioinformatics has evolved such
that the most pressing task now involves
the analysis and interpretation of various
types of data, including nucleotide and
amino acid sequences, protein domains,
and protein structures. The actual
process of analyzing and interpreting
data is referred to as computational
biology. Important subdisciplines within
bioinformatics and computational biology
include:

The development and implementation
of tools that enable efficient access to,
and use and management of, various
types of information
The development of new algorithms
(mathematical formulas) and statistics
with which to assess relationships
among members of large data sets,
such as methods to locate a gene
within a sequence, predict protein
structure and/or function, and cluster
protein sequences into families of
related sequences. (para. 6)

In 2000, the National Institutes of Health’s (NIH)
Biomedical Information Science and Technology
Initiative Consortium defined bioinformatics and
computational biology. Members of the consortium
believed that no definition could completely eliminate
overlap with other activities or preclude variations in
interpretation by different individuals and organizations.
Ultimately, they defined bioinformatics as the research,
development, or application of computational tools and
approaches for expanding the use of biological,
medical, behavioral or health data, including those to
acquire, store, organize, archive, analyze, or visualize
such data. The same group defined computational
biology as the development and application of data-
analytical and theoretical methods, mathematical
modeling and computational simulation techniques to
the study of biological, behavioral, and social systems.
The Biomedical Information Science and Technology
Initiative (BISTI) continues “as the focus of biomedical
computing issues at the NIH” (NIH, 2016b, para. 1).

Bioinformatics tools help biomedical informaticists
and healthcare personnel tackle the analysis of large
datasets. The authors believe that biomedical
informatics uses bioinformatics, whereas computational
biology is its action complement. By using
bioinformatics and computational biology to analyze
and interpret intricate biological events, biomedical
informaticists promote health and improve patient care.
Biomedical informatics and bioinformatics may seem

similar but if one thinks of biomedical informatics as
focusing on health care and patients, it helps
distinguish between the two. Biomedical informaticists
use bioinformatics methods to integrate large biological
and medical datasets to facilitate understanding of the
human body and its biological functioning; these efforts
are geared toward improving health by defeating
disease.

Why Are Bioinformatics and
Biomedical Informatics So
Important?
The future of health care is based on genomics.
Bioinformatics and computational biology have
provided the tools to make it possible to analyze and
interpret complex biological processes. Through these
developments, several projects have advanced
understanding of the human genome, haplotypes,
and the genomic changes related to disease.

In 2006, the Cancer Genome Atlas Project began (NIH,
2016a). This pilot cost $100 million to map the genomic
changes in brain, lung, and ovarian cancers to assess
the feasibility of a full-scale effort to systematically
explore the entire spectrum of genomic changes
involved in every major type of human cancer. The goal
of this project is to develop a resource that will be used

to develop new strategies for preventing, diagnosing
and treating the disease.

The goal of the International HapMap Project (2006) is
to

develop a haplotype map of the human
genome, the HapMap, which will describe
the common patterns of human DNA
sequence variation. The HapMap is
expected to be a key resource for
researchers to use to find genes affecting
health, disease, and responses to drugs
and environmental factors. The
information produced by the Project will
be made freely available. (para. 1)

This international partnership of scientists has taken
blood samples from clusters of related people, such as
parents and children, from different international
regions. Using these samples, the researchers have
been able to catalog some of the common variations in
DNA and investigate inherited alleles. As the name
implies, a haplotype map identifies a set of closely
linked alleles on a chromosome that tend to be
inherited together. Refer to Figure 24-1.

Figure 24-1 International HapMap Project

Modified from National Human Genome Research Institute. (2012).

International HapMap project. Retrieved from

https://www.genome.gov/10001688/international-hapmap-project

The International HapMap Project states:

Most common diseases, such as
diabetes, cancer, stroke, heart disease,
depression, and asthma, are affected by
many genes and environmental factors.
Although any two unrelated people are
the same at about 99.9% of their DNA
sequences, the remaining 0.1% is
important because it contains the genetic
variants that influence how people differ
in their risk of disease or their response
to drugs. Discovering the DNA sequence

variants that contribute to common
disease risk offers one of the best
opportunities for understanding the
complex causes of disease in humans.
(para. 3)

A major contribution has been the Human Genome
Project (HGP), which began in 1990 and was
completed in 2003 (HGP, 2010). The U.S. Department
of Energy and the NIH coordinated this program, which
had the following goals:

Identify all of the approximately 20,000–25,000
genes in human DNA
Determine the sequences of the 3 billion chemical
base pairs that make up human DNA
Store this information in databases
Improve tools for data analysis
Transfer related technologies to the private sector
Address the ethical, legal, and social issues (ELSI)
that may arise from the project (para. 2)

According to NHGRI (2015), “One of the most
important aspects of bioinformatics is identifying genes
within a long DNA sequence” (para. 1). It was clear that
the speed of DNA sequencing would have to be
realized sooner in order to decrease costs. The
process was refined so the sequencing was improved.

It took 4 years to sequence the first billion bases but
just 4 months to sequence the second billion bases.

During the month of January 2003, 1.5 billion bases
were sequenced. As the speed of DNA sequencing
increased, the cost decreased from $10 per base in
1990 to $0.10 per base at the conclusion of the project
in April 2003 (NHGRI, 2015).

One of the most important aspects of bioinformatics is
identifying genes within a long DNA sequence. Until the
development of bioinformatics, the only way to locate
genes along the chromosome was to study their
function in the organism (in vivo) or to isolate the DNA
and study it in a test tube (in vitro). Bioinformatics
allows scientists to make educated guesses about
where genes are located simply by analyzing sequence
data using a computer (in silico) (NHGRI, 2015).

The other major piece brought out through the HGP
was the realization that ESLI arise from studying
human genomes. The participants in the HGP set
aside a percentage of their annual budgets to research
ESLI (HGP, 2008). Box 24-2 and Figure 24-2 identify
some of the questions raised regarding ESLI.

Figure 24-2 Ethical, Social, and Legal Implications
(ESLI)

Box 24-2 ESLI QUESTIONS RAISED BY

THE HUMAN GENOME PROJECT

Who should have access to personal genetic
information, and how will it be used?
Who owns and controls genetic information?
How does personal genetic information affect
an individual and society’s perceptions of
that individual?
How does genomic information affect
members of minority communities?
Do healthcare personnel properly counsel
parents about the risks and limitations of
genetic technology?

How reliable and useful is fetal genetic
testing?
What are the larger societal issues raised by
new reproductive technologies?
How will genetic tests be evaluated and
regulated for accuracy, reliability, and utility?
(Currently, there is little regulation at the
federal level.)
How do we prepare healthcare professionals
for the new genetics?
How do we prepare the public to make
informed choices?
How do we as a society balance current
scientific limitations and social risk with long-
term benefits?
Should testing be performed when no
treatment is available?
Should parents have the right to have their
minor children tested for adult-onset
diseases?
Are genetic tests reliable and interpretable
by the medical community?
Do people’s genes make them behave in a
particular way?
Can people always control their behavior?
What is considered acceptable diversity?
Where is the line between medical treatment
and enhancement?
Are genetically modified foods and other
products safe to humans and the

environment?
How will these technologies affect
developing nations’ dependence on the
West?
Who owns genes and other pieces of DNA?
Will patenting DNA sequences limit their
accessibility and development into useful
products?

Data from Human Genome Program. (2008). Human Genome

Project information: Ethical, legal, and social issues. Retrieved

from

http://www.ornl.gov/sci/techresources/Human_Genome/elsi/elsi.shtml

Even though the HGP has ended, researchers
continue to improve DNA sequencing. Specifically, they
continue to advance the bioinformatics and
computational biology tools that are used in biomedical
informatics. However, as Butte (2008) laments, “There
is an absolute paucity of people trained to make use of
these resources, to build the infrastructure, to ask
these novel questions, and to even answer these
questions” (p. 173).

These three projects were pivotal in genomics. The
HGP focused on the DNA sequence from a single
individual, the HapMap project focused on variation in
the genome and on human populations, and the
Cancer Genome Atlas Project is concerned with how

cancer affects the genomes. As a result of these
seminal projects and a unique culture of data sharing
previously unknown among biological researchers,
molecular data and measurement tools are now
publicly available. Two examples of publicly available
databases are the Gene Expression Omnibus, which is
maintained by the National Center for Biotechnology
Information at the National Library of Medicine, and
Array-Express, which is maintained by the European
Bioinformatics Institute (Butte, 2008). As new
researchers with both biology and computational
expertise emerge, bioinformatics and computational
biology projects will contribute new insights into
disease mechanisms and therapeutic interventions.

What Does the Future Hold?
We have seen numerous advances ranging from
possible treatments for Parkinson’s diseases,
unprecedented detail of the genetics of type 2
diabetes, the NIH creating an atlas of human
malformation syndromes in diverse populations, NIH
researchers identifying striking genomic signatures
shared by five types of cancer, and NIH scientists
discovering the genetic cause of rare allergy to
vibration (NHGRI, 2016). However, it will take many
more years of researching and applying bioinformatics
and computational biology before the information in the
human genome is understood in detail. Because these
applications have the ability to allow one to analyze

and interpret complex biological processes,
researchers are on the path to understanding the
etiology of disease and of treatment interventions at
the molecular level.

Consider a typical day on any clinical unit. The
advanced practice nurse who wants to prescribe a drug
for a patient begins by reviewing the patient’s genetic
test results. The advanced practice nurse knows that
this information must be assessed before prescribing
so that a drug that will treat the patient’s illness
successfully without producing harmful side effects can
be selected. The patient will receive only the
medication that he or she needs, and one that is
designed to interfere with or enhance the specific
molecular processes that are the signature for the
patient’s particular health challenge. The advances that
bioinformatics and biomedical informatics promise will
dramatically impact healthcare delivery as it is known.
As explained by Rajappa, Sharma, and Saxena
(2004):

Understanding molecular mechanisms
leads to better classification of disease
and better management. A drop of blood
from a hypertensive patient gives gene
expression profile by cDNA microarray
analysis. It may reveal SNPs
[singlenucleotide polymorphisms] related
to hypertension and others which

predispose a patient to diabetes mellitus
or myocardial infarction and the clinician
can determine which drugs are beneficial
and which are harmful. This scenario has
a whale of difference from the current
“trial and error” method of matching a
patient with antihypertensives. (p. 128)

This vision from 2004 has become a reality and the
scope of treatments and interventions continues to
expand. Our expectations and hopes are being met
and surpassed.

Nurses can be involved in bioinformatics in many ways,
including as nurse researchers helping to map
molecular processes and as educators and advocates
helping patients and families to understand these
complex biological processes. For more information
about the roles of nurses in this exciting new field, visit
the website of the International Society of Nurses in
Genetics (www.isong.org).

Summary
The focus of this text is on nursing informatics, but one
can clearly see the connection between biomedical
informatics and nursing informatics. The discipline of
bioinformatics and its use in biomedical informatics
epitomize the integration of computer science,

information science, computational biology, and health
care. These new applications deal with the resources,
devices, strategies, and methods needed to optimize
the acquisition, processing, storage, retrieval,
generation, and use of information in health and
biomedicine. Biomedicine and its applications of
bioinformatics support and manage all healthcare
behaviors. They affect how clinicians deliver health
care to the infirmed, prevent disease, promote health,
conduct research, and provide formal education for
entry-level practitioners and continuing education for
those who are currently practicing. The field of
biomedical informatics—that is, bioinformatics
capabilities coupled with health care—includes
informatics and computational biology algorithms and
tools and clinical guidelines. This knowledge can be
applied to the areas of nursing, pharmacy, laboratory,
dentistry, medicine, and public health. Those living the
profession of nursing know that the practice of nursing
is intertwined with the management and processing of
information including the new knowledge being
generated by biomedical informatics.

On the biomedical side of informatics, one must be
cognizant of the fact that medical data typically are
extracted from personal, confidential, and legally
protected medical records. The protection of human
subjects must be paramount and all ESLI issues must
be addressed.

Biomedical informatics provides knowledge about the
effects of DNA disparities among individuals. Being
able to study human genomes and biological
processing at the molecular level will revolutionize how
conditions are diagnosed and care is provided. It is
helping to prevent disease. If one can better
understand an organism’s biological processes and
genetic coding, one can better prevent or treat medical
conditions. Clinical care as it is known will change; it
will become genomics based.

THOUGHT-PROVOKING QUESTIONS

1. After reading this chapter, you know that
the study of genomics is helping clinicians
to understand better the interaction
between genes and the environment. This
new information and knowledge will
continue to help clinicians find ways to
improve health and prevent disease. How
do you envision patient care will change
based on genomics in 10 years, 20 years,
or 50 years in the future?

2. Review the ethical, social, and legal
issues (ESLI) raised by the Human
Genome Project presented in Box 24-2.
Prepare a similar list of ESLI questions to
apply to the public health databases
being developed for health information
exchanges. Can you appreciate how

these ESLI questions are widely
applicable to protecting information
gathered from human subjects?

References
Bioinformatics Organization. (2011).

Bioinformatics. Retrieved from
http://www.bioinformatics.org/wiki/bioinformatics

Butte, A. (2008). Translational
bioinformatics: Coming of age. Journal
of the American Medical Informatics
Association, 15(6), 709–714. Retrieved
from CINAHL database.

Human Genome Program (HGP). (2008).
Human Genome Project information:
Ethical, legal, and social issues.
Retrieved from
https://ghr.nlm.nih.gov/primer#hgp

Human Genome Program (HGP). (2010).
Human Genome Project information.
Retrieved from
http://web.ornl.gov/sci/techresources/Human_Genome

International HapMap Project. (2006).
About the International HapMap
Project. Retrieved from
https://www.genome.gov/10001688/international-
hapmap-project

Kelly, R. (2008). What are “omics”
technologies? Retrieved from
http://www.reagank.com/2007/03/what_are_omics_technologies.php

Mulligen, E., Cases, M., Hettne, K.,
Molero, E., Weeber, M., Robertson, K.,
& Maojo, V. (2008). Training
multidisciplinary biomedical informatics
students: Three years of experience.
Journal of the American Medical
Informatics Association, 15(2), 246–
254. PMCID: PMC2274784. doi:
10.1197/jamia.M2488

National Center for Biotechnology
Information (NCBI). (2004).
Bioinformatics. Retrieved from
http://www.csub.edu/~psmith3/teaching/505-
1.pdf

National Human Genome Research
Institute (NHGRI). (2015).
Bioinformatics: Finding genes.
Retrieved from
https://www.genome.gov/25020001/online-
education-kit-bioinformatics-
finding-genes

National Human Genome Research
Institute (NHGRI). (2016). Newsroom:
Current news releases. Retrieved from
https://www.genome.gov/10000475/current-
news-releases

National Institutes of Health (NIH).
(2016a). The Cancer Genome Atlas
(TCGA) Project. Retrieved from
https://cancergenome.nih.gov

National Institutes of Health (NIH).
(2016b). NIH Biomedical Information
Science and Technology Initiative:
About BISTI. Retrieved from
https://www.bisti.nih.gov/Pages/Home.aspx

National Public Radio. (2010). Where the
word genome came from. Retrieved

from
http://www.npr.org/templates/story/story.php?
storyId=128410577

Network Science (NetSci). (2009). Terms
and definitions in bioinformatics.
Originally retrieved from
http://www.netsci.org/Sciebce/Bioinform/definitions.html
and currently preserved at
http://petang.cgu.edu.tw/Bioinfomatics/MANUALS/Terms%20and%20Definitions%20in%20Bioinformatics.htm

Ohio State University Medical Center.
(2010). College of Medicine, School of
Biomedical Science: Biomedical
informatics. Retrieved from
https://medicine.osu.edu/bmi/Pages/index.aspx

Oregon Health & Science University
(OHSU). (2016). What is biomedical
informatics? Retrieved from
http://www.ohsu.edu/xd/education/schools/school-
of-medicine/departments/clinical-
departments/dmice/about/what-is-
biomedical-informatics.cfm

Rajappa, M., Sharma, A., & Saxena, A.
(2004). Bioinformatics and its

implications in clinical medicine: A
review. International Medical Journal,
11(2), 125–129. Retrieved from
CINAHL database.

University of Minnesota. (2012). What is
bioinformatics? Retrieved from
http://www.binf.umn.edu/about/whatsbinf.php

University of Texas at El Paso. (2010).
College of Science: Bioinformatics.
Retrieved from
http://bioinformatics.utep.edu

Vanderbilt University. (2016). Department
of Biomedical Informatics. Retrieved
from
https://medschool.vanderbilt.edu/dbmi

SECTION VII: Imagining
the Future of Nursing
Informatics

Chapter 25 The Art of Caring in Technology-
Laden Environments

Chapter 26 Nursing Informatics and the
Foundation of Knowledge

You might wonder why we are including a chapter
on caring as we discuss the future of nursing
informatics. The authors believe that nurses are
taught to care and hone their ability to care for patients
as they practice; however, in light of technologies that
can sometimes be disruptive, the art of caring can
become compromised or lost. We want to refocus
nurses on the art of caring, while enhancing the
science of nursing using informatics tools.

We challenge you to reflect on what you know and
what you are learning and to think of where you are
going in relation to your own practice and nursing
informatics knowledge. Just as our professional and
personal lives overlap at times, so do our social and
professional informatics and networking experiences.
We cannot assume that what we do or use in our

personal lives is appropriate or even useful in our
professional practice. This section begins with a
chapter (The Art of Caring in Technology-Laden
Environments) that considers the heart of what nurses
do—caring.

The section ends with a chapter on Nursing Informatics
and the Foundation of Knowledge. In this chapter you
will examine emerging technologies that will impact the
future of health care. The generation and management
of organizational knowledge will be described in
relation to quality implications. Although not explicitly at
each point addressing the four key areas of the
Foundation of Knowledge model, the sections of this
chapter do consider how emerging technologies may
address the four areas of (1) knowledge acquisition, (2)
knowledge processing, (3) knowledge generation, and
(4) knowledge dissemination and feedback. We also do
not focus explicitly on changes in health care and
nursing technologies, but rather on the more general
changes that might be adapted or adopted for use by
nurses or within health care.

The information in this chapter refocuses what you
have learned about the many facets of nursing
informatics and the interfacing of nurse knowledge
workers and technology. The Foundation of Knowledge
model provides a framework for examining the dynamic
interrelationships among data, information, and
knowledge used to meet the needs of healthcare

delivery systems, organizations, patients, and nurses.
The importance of knowledge management in nursing
is emphasized by taking this one last opportunity to
ensure that the reader understands and appreciates
the value of knowledge management in the nursing
profession and the role that technology has in
knowledge acquisition, knowledge generation,
knowledge dissemination, and knowledge processing.

The nursing informatics specialty is the synthesis of
nursing science, information science, computer
science, and cognitive science for the purpose of
managing, disseminating and enhancing healthcare
data, information, knowledge, and wisdom to improve
collaboration and decision making, provide high quality
patient care and advance the profession of nursing.

After reading the first six sections of this book, you
should have a good idea of the current state of the
science of nursing informatics. Now this final section
challenges you to think about the future. Each reader
should envision his or her current practice setting and
the nursing informatics applications he or she uses.
What will come next? What should come next?

The material within this text is placed within the context
of the Foundation of Knowledge model (Figure VII-1)
to meet the needs of healthcare delivery systems,
organizations, patients, and nurses. The first chapter in
this text, Nursing Science and the Foundation of

Knowledge, provides a thorough overview of the
Foundation of Knowledge model—a framework that
embraces knowledge so that readers can develop the
wisdom necessary to apply what they have learned.
Wisdom is the application of knowledge to an
appropriate situation. In the practice of nursing science,
one expects action or actions directed by wisdom.
Wisdom uses knowledge and experience to heighten
common sense and insight, allowing one to exercise
sound judgment in practical matters. Wisdom is
developed through knowledge, experience, insight, and
reflection. Wisdom is sometimes thought of as the
highest form of common sense resulting from
accumulated knowledge or erudition (deep, thorough
learning) or enlightenment (education that results in
understanding and the dissemination of knowledge).
Wisdom is the ability to apply valuable and viable
knowledge, experience, understanding, and insight
while being prudent and sensible. Knowledge and
wisdom are not synonymous. Knowledge abounds with
others’ thoughts and information, whereas wisdom is
focused on one’s own mind and the synthesis of one’s
own experience, insight, understanding, and
knowledge.

Figure VII-1 Foundation of Knowledge Model

Designed by Alicia Mastrian.

Reflect on the model while reading through this final
section. You are challenged to ask, “How can I use my
wisdom to help create the theories, tools, and
knowledge of the future?”

CHAPTER 25: The Art of
Caring in Technology-
Laden Environments

Kathleen Mastrian and Dee McGonigle

Objectives
1. Explore caring theories as they apply to

the art of nursing.
2. Acknowledge the potential disruption of

technology to the therapeutic nurse–
patient relationship.

3. Define presence and caring presence.
4. Formulate strategies to enhance caring

presence.

Key Terms
» Active listening

» Art of nursing

» Caring

» Caritas processes

» Centering

» Presence

Introduction
Nursing is hard work. Depending on the site of
practice, it can be both physically and mentally taxing.
Nurses are masters at multitasking—that is, performing
several caring functions simultaneously during a
patient encounter. Some nursing interventions are
readily apparent and easily described, such as
collecting vital signs data and changing dressings,
while others are less visible yet equally important, such
as interpreting the vital signs data, generating
knowledge about the patient’s situation, and then using
that knowledge to inform practice. Equally invisible, yet
important to the therapeutic caring environment, are
the little things that nurses say, project, and do in the
caring episode. In this chapter, we pause to reflect on
the art of caring. We emphasize the need to preserve
this central and unique function of nursing and suggest
ways that nurses can ensure that the caring functions

do not become a lost art as technologies are
introduced into patient care environments.

We derive a definition of nursing science from the
American Nurses Association’s definition of nursing.
Nursing science is the ethical application of knowledge
acquired through education, research, and practice to
provide services and interventions to patients to
maintain, enhance, or restore their health, and to
acquire, process, generate, and disseminate nursing
knowledge to advance the nursing profession. Caring
functions, such as therapeutic communication,
listening, touch, and mindfulness, are an integral part
of nursing science, as they also help patients to
maintain, enhance, or restore their health. While the
new technologies such as smart pumps, bar-code
medication administration systems, electronic health
records (EHRs), wearables, and smartphones being
introduced into our practice environments are designed
to increase efficiency, promote safety, and streamline
the work of nursing, we need to ask: To what extent do
these technologies disrupt the nurse–patient caring
encounter? How can we continue to care effectively for
our patients and promote a healing environment while
incorporating the advantages and efficiencies that
technologies provide?

Caring Theories

Anne Boykin and Savina Schoenhofer (2015)
defined caring as an “altruistic, active expression of
love and. . .the intentional and embodied recognition of
value and connectedness” (p. 343). In their framework,
theory of nursing as caring, caring is created from each
moment the nurse is committed to nurture the person.
Regardless of the challenges presented to a nurse,
such as technology, time restraints, staffing issues, or
difficult patients, a nurse needs to reach deep inside
him/herself to make the commitment to know the
person as caring. A nurse needs to be able to enter
into each nursing situation with the intentional
commitment to fully care for the person.

Let us also explore caring as a concept with the
seminal work of Jean Watson. As Dr. Watson
described:

The Theory of Human Caring was
developed between 1975 and 1979 while
I was teaching at the University of
Colorado. I tried to make explicit that
nursing’s values, knowledge, and
practices of human caring were geared
toward subjective inner healing
processes and the life world of the
experiencing person. This required
unique caring–healing arts and a
framework called “carative factors,” which
complemented conventional medicine but

stood in stark contrast to “curative
factors.” (Watson, 2015, p 322)

It is important to remember that Watson developed her
theory during a time when the nursing profession was
struggling to define itself and identify the unique
contributions of nursing to patient care. In the theory of
human caring, Watson defined caring as “healing
consciousness and intentionality to care and promote
healing” and caring consciousness as “energy within
the human–environmental field of a caring moment”
(Watson, 2015, p. 323). Think about the use of the
word “energy” in these definitions and pause to
appreciate the level of cognitive energy that nurses
expend as they care for patients. Nursing is hard work!

Watson further described the evolution of her theory
from the original 10 carative factors to what she now
calls caritas processes. As her work expanded, she
recognized the need for “love and caring to come
together for a new form of deep transpersonal caring.”
In the evolving theory, she has emphasized that the
“relationship between love and caring connotes inner
healing for self and others” (Watson, 2015, p. 324).
The 10 caritas processes enumerated by Watson are
summarized here:

1. The practice of loving kindness and equanimity
within the context of caring consciousness

2. Being authentically present and enabling and
sustaining the deep belief system and subjective
life world of self and one being cared for

3. Cultivation of one’s own spiritual practices and
transpersonal self, going beyond ego self,
opening to others with sensitivity and
compassion

4. Developing and sustaining a helping–trusting,
authentic caring relationship

5. Being present to, and supportive of, the
expression of positive and negative feelings as a
connection with deeper spirit of self and the one
being cared for

6. Creative use of self and all ways of knowing as
part of the caring process; to engage in artistry
of caring–healing practices

7. Engaging in genuine teaching–learning
experience that attends to unity of being and
meaning, attempting to stay within others’
frames of reference

8. Creating a healing environment at all levels (a
physical and nonphysical, subtle environment of
energy and consciousness, whereby wholeness,
beauty, comfort, dignity, and peace are
potentiated)

9. Assisting with basic needs, with an intentional
caring consciousness, administering “human
care essentials,” which potentiate alignment of
mind–body–spirit, wholeness, and unity of being

in all aspects of care, tending to both embodied
spirit and evolving spiritual emergence

10. Opening and attending to spiritual–mysterious
and existential dimensions of one’s own life–
death; soul care for self and the one being cared
for (Watson, 2015, p. 325)

Think about a recent patient encounter. Were you fully
present in the moment and conscious of the individual
and his or her uniqueness? Did you smile and greet the
patient by name and acknowledge visitors? Did you
place your tablet to the side, lean forward, and
attentively listen to the concerns of the patient and
family and offer them the opportunity to ask questions?
Did you explain what you were doing with and for the
patient, and why? (See Figure 25-1.) Conversely, did
you focus your attention on the tablet and talk at the
screen as you clicked on the drop-down menus to
document the patient encounter? Did the technology
create a barrier between you and the patient and
his/her family? Did you depend solely on monitoring
technologies to create your interpretation of the
patient’s experience? Was your assessment of the
patient’s current situation colored by the objective
representation of the person created by the monitoring
technologies present in the room (O’Keefe-McCarthy,
2009)? “The overwhelming presence of technology at
the clinical bedside has the power to become the
strongest reference point that nurses use to inform,
direct, interpret, evaluate, and understand nursing

care” (O’Keefe-McCarthy, p. 787). We must
remember that “Technology, however, does not take
into consideration the specific symptom presentation
unique to the person experiencing the illness.
Technology’s use is not meant to replace the person-
to-person interaction that is essential in any nurse–
patient encounter” (p. 792).

Figure 25-1 Active Listening

© Monkey Business Images/Shutterstock

Patient-centered care (PCC) is another way of
describing the need for practitioners to focus on the
subjective experience of patients with health
challenges. Liberati et al. (2015) defined patient
centeredness as “a collective achievement that is

negotiated between patients and multiple health
providers, comprising of social practices and
relationships that are woven together through the
material and immaterial resources available in specific
organizational contexts” (p. 47). They suggest that a
focus on PCC may have three specific outcomes:

Patients can provide their subjective experience as
an input to improve several, often undermined,
aspects of healthcare delivery.
Care providers might develop their capacity for
reflexivity, which could improve their understanding
of the implications of their actions.
Patients and practitioners can thus provide insights
into the overall health organization on how to
innovate processes and facilities to better respond
to local needs.

We will examine reflection on practice in more detail
later in the chapter.

Central to the caritas processes described by Watson
and the discussion about technology-mediated care by
O’Keefe-McCarthy is the concept of a caring presence.
Strategies for developing and enhancing caring
presence are discussed in the latter part of this
chapter.

The humanistic nursing theory developed by Paterson
and Zderad also offers some insight into the less

visible aspects of nursing care (Kleiman, 2010). These
authors suggested that the basis of nursing is the
response to the call for help in solving health related
concerns.

This call, a foundational concept of
humanistic nursing, can be heard where
nursing is offered, coming to our attention
as a subtle murmur of pain, sorrow,
anxiety, desperation, joy, laughter, even
silence, that expresses the state-of-being
of the protagonists in the drama of health-
care delivery, our patients and ourselves.
(Kleiman, 2010, p. 338)

Nurses hear the call and respond with their entire
being. Their knowledge, experiences, ethics, and
competencies shape the interaction with the patient as
they respond.

In humanistic nursing we say that each
person is perceived as existing “all-at
once.” In the process of interacting with
patients, nurses interweave professional
identity, education, intuition, and
experiences, with all their other life
experiences, creating their own tapestry
which unfolds during their responses.
(Kleiman, 2010, pp. 341–342)

Pause to reflect on how you create your own tapestry
during patient interactions.

Nursing care requires conscious awareness of self and
the uniqueness of each of our patients. It requires
emotional energy expenditure as we seek to find ways
to meet the calls of our patients. We need to be aware
of the potential for inadvertently dehumanizing the
patient experience in our technology-laden practice
environments. According to Kleiman (2010), “The
context of Humanistic Nursing Theory is humans. The
basic question it asks of nursing practice is: Is this
particular intersubjective–transactional nursing event
humanizing or dehumanizing?” (p. 349). We must be
fully present and self-aware in every patient encounter,
seeking to deliver exactly what is needed in every
situation. Yes, nursing is hard work, but when we are
able to respond with our whole being, we may find that
our patients and families are more satisfied with the
care we provide and that we also experience personal
satisfaction and find joy in our profession.

Presence
Presence is the act of being there and being with our
patients—fully focusing on their needs. “Presence is an
interpersonal process that is characterized by
sensitivity, holism, intimacy, vulnerability and
adaptation to unique circumstances” (Finfgeld-
Connett, 2008, p. 528). Paterson and Zderad

explained presence as establishing a relationship by
fully being available and open to the experiences of
another (Penque & Snyder, 2014). Penque and
Snyder (2014) defined three types of presence:
physical presence, full presence, and transcendent
presence. A nurse who is physically present is largely
competent in carrying out care, efficient with
interventions, but inattentive to communication and
nonverbal cues projected by the patient and family.
When fully present, a nurse will greet the patient by
name, communicate appropriately with the patient, and
pay attention to what is being said and not said during
the encounter. When nurses practice transcendent
presence, they will first center themselves, clearing
their mind of all potential distractions, and then use the
patient’s name and gentle touch to convey interest and
responsiveness while carrying out the necessary
physical interventions.

Paterson and Zderad felt presence was a vital element
of their theory of humanistic nursing (Penque &
Snyder, 2014). Presence requires one to be open and
responsive to the situations around them. If a nurse is
fully present to the patient in front of them, they will be
able to notice the subtle changes that may not be
evident if the nurse would only be physically present.
The connection loss may cause the patient to feel that
the nurse is detached from the situation. Penque and
Snyder (2014) gave an example of presence from the
book Tuesdays with Morrie by Mitch Albom (1997):

I believe in being fully present. That
means you should be with the person
you’re with. When I’m talking with you
now, Mitch, I try to keep focused only on
what going on between us. I am not
thinking about something we said last
week.

I am not thinking about what’s coming up
this Friday. I am not thinking about doing
another Koppel show, or about
medications I’m taking. I am talking to
you; I am thinking about you. (pp. 135–
136)

Strategies for Enhancing
Caring Presence
Our patients have complex problems and needs. They
may be scared, angry, resistant to change, or happily
oblivious to the extent of their health challenges. We,
too, have complex personal lives with many competing
roles and issues that consume our energies. Our
workplace may be short-staffed, resulting in care
assignments that stretch us to our maximum. We may
be struggling to learn to use the new technologies that
are introduced nearly daily into our practice

environments. As a result, we may feel disorganized,
tired, angry, and emotionally spent.

We need to take care of ourselves first so that we can
be effective in our patient and family care. Caring for
ourselves involves conscious attention to our health
and health practices. In addition, nurses have a
“responsibility to model health behaviors” (Leonard,
2014, p. 17). Do we eat a balanced diet, get
appropriate exercise, and get enough sleep? Do we
have strategies to manage stress appropriately, and do
we have adequate social support?

One approach to improving your health is to set goals
and to keep track of your progress. As part of a
concepts of health course, students are asked to
develop a personal health plan and journal periodically
during the semester about their ability to stick to the
plan. Here is an example of a simple plan: “I will
increase my intake of fruit and vegetables and walk
outside for 30 minutes at least 3 times per week.” As
the students reflect on their ability to stick to the plan in
the journal, caring for self is brought into conscious
awareness. This simple self-reflective practice may be
just the boost that is needed for a nurse to commit to
self-awareness and self-care on a long-term basis
(Figure 25-2). The following website gives information
on well-being and a self-assessment tool, as well as
tips on setting goals:
www.takingcharge.csh.umn.edu/enhance-wellbeing

(University of Minnesota, Center for Spirituality &
Healing, 2013).

Figure 25-2 Reminder: Take Care of Yourself

One additional strategy that we share with students is a
breathing/meditative exercise from Tai Chi, Qi Gong,
called the five-element breathing sequence. This
meditative exercise, which can be performed in less
than 10 minutes and can be very energizing and stress
reducing, is described in Box 25-1.

The simplest and perhaps most effective strategy we
can use to help us be fully present to our patients is to
pause to take a few deep breaths to calm ourselves
and clear the clutter from our minds before we address
each patient. It also helps to repeat the patient’s name
silently a time or two before we enter the room. This
practice, known as centering, enables the nurse to “be
available with the whole self and be open to the
personal and care needs of the patient” (Penque &

Snyder, 2014, p. 31). When we are with a patient, we
need to be certain that our mind is fully engaged in the
interaction with this patient for the moment. We must
be fully attentive to the patient, be both physically and
mentally present, meet the patient where he or she is
emotionally, listen actively to what the patient is saying,
focus on the nonverbal cues the patient is projecting,
touch the patient gently and reassuringly, and
demonstrate acceptance (Penque & Snyder, 2014;
Zerwekh, 2006). Being present can be used in any
situation where the nurse is addressing the wants and
needs of the patient. It is important not to force the
encounter on the patient for the benefit of the nurse’s
agenda (Penque & Snyder, 2014).

BOX 25-1 TAI CHI, QI GONG FIVE-

ELEMENT BREATHING SEQUENCE

1. Stand with your feet shoulder-width apart.
Relax your arms and shoulders.

2. Inhale slowly as you straighten and then
move both arms slightly back and then up
with palms facing up (as though you are
gathering a giant ball of energy). Stretch
to your full height as you inhale.

3. Exhale slowly as you press both palms
down in front of you with hands slightly
cupped and thumbs and index fingers

nearly touching. Bend your knees slightly
to sink down as you exhale.

4. Turn your hands over (palms up) just
below the waist, and inhale slowly as you
raise your hands in front of you, to chest
height. Straighten your legs as you inhale.
(Imagine lifting a ball of energy.)

5. Exhale slowly and extend the arms
directly in front of you, chest high, and fan
your hands open to release the energy in
front of your chest. Bend the knees
slightly to sink down as you exhale.

6. Inhale slowly, with palms facing you, to
gather the energy back toward your
chest. Straighten your legs as you inhale.

7. Press both arms straight out at shoulder
height as you exhale. Pretend you are
pushing on walls located on either side of
you. Continue the exhalation as you bring
your arms in front of you. Bend your
knees slightly to sink down as you exhale.

8. Inhale slowly as you gather the energy to
your chest. Straighten your legs as you
inhale and stretch to your full height.

9. Exhale slowly as you raise your arms
above your head to set the energy free.
Bend your knees slightly to sink down as
you exhale.

10. Transition your hands to the beginning to
repeat the sequence by inhaling as you

bring your hands halfway down and
exhaling the rest of the way. (You can
also end here by bringing your palms
together in closure, first inhaling and then
exhaling as you slowly move your hands
down in front of you.)

Nurses may feel they do not have time to focus on
caring presence. Caring opportunities are replaced by
the time it takes to input all the information into the
EHR and complete the measurable outcomes that are
expected of nurses. The elimination of face-to-face
interaction with the use of telephones, home
monitoring, and other forms of telemedicine makes
utilizing a caring presence more challenging. The
theory of nursing as caring describes caring “as the
end, rather than the means, of nursing, and that caring
is the intention of nursing, rather than merely its
instrument” (Boykin & Schoenhofer, 2015, p. 342).

A related and similar concept for practicing presence,
caring between, is described in the nursing as caring
theory (Boykin & Schonhofer, 2015). Consider, for
example, that a nurse experienced in caring for elders
with congestive heart failure will have expectations and
preconceived ideas about what he or she will find in a
patient situation. These expectations may not allow us
to really “see” the whole patient and his experience of
the illness. Caring between “is a loving relation into

which nurse and nursed enter and which they cocreate
by living the intention to care” (p. 344). The nurse
needs to enter the situation knowing the person as a
caring person. This knowledge will create an
acceptance confirming the person as caring. The
nurse’s responsibility is not in determining what is
wrong or needed in another, but to be present in the
situation to know the person as caring and to foster a
patient-specific caring environment. We need to come
to know our patients both intuitively and scientifically.
Our technologies provide an objective view of the
patient, and the nurse synthesizes this view with his or
her own perspective (wisdom) that is based on the
nurse’s experience, education, and intuition as applied
to the patient’s situation. This is the essence of caring.
One of the first skills we were taught in our basic
nursing education programs was active listening. We
were taught to get down to the same level of the
patient, make eye contact, touch gently (if culturally
acceptable), listen attentively and nod appropriately,
restate and clarify what we heard, ask questions to
seek additional information, listen for feelings that are
not being explicitly stated, and use silence to
encourage the patient to think and provide additional
information to us (Watanuki, Tracy, & Lindquist,
2014; Zerwekh, 2006). These communication skills are
fundamental to caring. When was the last time you sat
in a chair at a patient’s bedside to get to the same level
as the patient? Even a brief sit at the bedside can
communicate volumes about your availability and

willingness to listen, and it certainly feels good to get
off of your feet for a moment. Have you ever
experienced a patient who became emotional because
you looked at them instead of your computer? We
need to think carefully about the potential barriers to
active listening that technology might present. Consider
telephone encounters and e-health: Are you truly
listening and present to a patient you cannot see?
What are some of the ways that these caring presence
skills could be adapted for use in a telehealth
encounter? What are the challenges of communicating
at a distance, yet being fully present for the patient?

We conclude our discussion of caring presence with a
definition of the art of nursing provided by Finfgeld-
Connett (2008):

The art of nursing is the expert use and
adaptation of empirical and meta-physical
knowledge and values. It is relationship-
centered and involves sensitively
adapting care to meet the needs of
individual patients. In the face of
uncertainty, creativity is employed in a
discretionary manner. Artful nursing
promotes beneficent practice and results
in enhanced mental and physical well-
being among patients. It also results in
professional satisfaction and personal
growth among nurses. (p. 528)

Let us all strive for beneficent practice that atones for
the potential disruptions to the therapeutic nurse–
patient relationship that our use of technology
produces.

Reflective Practice
As professionals, we should be constantly mindful of
the need for practice improvement. Zande, Baart, and
Vosman (2014) discussed ethical sensitivity as a type
of practical wisdom. Ethical sensitivity is integral to high
quality care and clinical decision making. They
advocated for reflection on practice:

Taking daily practice of care as point of
entry for reflection is a way to discern
both explicit moral knowledge and tacit
moral knowing. Nurses and other
professionals can contribute to
improvement on quality of care by
creating opportunities to reflect on daily
ethical concerns in an inter-professional
team. (p. 75)

Liberati et al. (2015) also advocated for the use of
reflection to help professionals “observe their work
from a different perspective. . . . Such an exploration
may help providers to generate insights on how

healthcare services, processes, and facilities could be
modified to better respond to patients’ needs” (p. 49).

One way to focus more specifically on our practice is to
engage in reflective journaling (refer to Figure 25-3). In
the concepts of health course, we ask students to
complete a reflective practice assignment over a 6-
week period. Students are directed to review concepts
of caring presence and active listening and to commit
to consciously using a strategy for 6 weeks. At 3 and 6
weeks, they are asked to complete the following
reflective journal entry:

Figure 25-3 Reflective Practice

Attributed to Peter Drucker (1909-2005)

1. Write a brief description of the presence and
therapeutic communication approaches you tried
in your practice for the last 3 weeks. Provide
specific examples of patient situations in which
you tried the approach.

2. Reflect on the following:
* What did you do well?

* Which behaviors and skills do you need to
improve?

* How did you feel about the experience as it
was happening? Did you plan thoroughly?

* Did you achieve your objectives?

* Which aspects of planning do you need to
improve?

* How will this experience affect your future
practice?

3. Which personal professional development needs
have you identified after reflecting on your
performance? Which strategies will you use to
address these needs?

Our students frequently report that they enjoy this
experience and that the exercise helps to remind them
why they were originally attracted to nursing. They
describe experiences where they felt an authentic
connection to the patient. They also report that after 6

weeks of consciously practicing the strategy, it
becomes a part of their daily practice. Centering is the
most frequent strategy that the students choose to
practice.

Summary
Nursing practice relies on information and
communication technologies that receive inputs from
the nurses as well as all of the patient care
technologies. Computers, handheld devices, monitors,
and other healthcare technologies are essential tools
for nurses. Therefore, the nurse must have the ability
to implement, monitor, and evaluate all of this
equipment based on its inputs and outputs. The
increased demands on the nurse make it easy to lose
sight of the patient amid all of these technologies.
Nurses must look at monitors, devices, and other
gadgets to receive information; oftentimes, it is easy to
forget the patient is at the core of our care.

We hope that this brief overview of caring presence
prompts you to be more mindful of your practice and
that you, too, will commit to employing strategies that
enhance your caring presence in all patient
encounters. We do not want our patients to feel that we
are more focused on the machines that they are
connected to or the workstations that we bring with us
to the patient encounter. Yes, technology is great and it
does help us collect meaningful data and generate

knowledge about our patient situations, but equally
important is the need to collect the human-to-human
data that become available only when we step away
from the technology and interact authentically with our
patients.

When you save a person’s life—they call
you a hero

When you blend science with caring—
they call you an expert

When you share your compassion—they
call you a friend

When you do all three—they call you a
nurse

—Author Unknown

THOUGHT-PROVOKING QUESTIONS

1. Examine each of the 10 caritas processes
developed by Watson. Describe an
example of a patient encounter that
demonstrates the use of each caritas
process.

2. Reflect on your personal health. Are you
a role model for your patients? Which
aspects of your personal health do you

need to improve? Which strategies will
you adopt to improve your health?

3. Choose a caring presence strategy to
implement in your practice and use the
reflective journal template provided in the
chapter to reflect on your practice.

References
Boykin, A., & Schoenhofer, S. O. (2015).

Anne Boykin and Savina O.
Schoenhofer’s nursing as caring
theory. In M. Smith & M. Parker (Eds.),
Nursing theories and nursing practice
(4th ed., pp. 341–356.). Philadelphia,
PA : F. A. Davis.

Finfgeld-Connett, D. (2008). Qualitative
convergence of three nursing
concepts: Art of nursing, presence and
caring. Journal of Advanced Nursing,
63(5), 527–534. doi: 10.1111/j.1365-
2648.2008.04622.x

Kleiman, S. (2010). Josephine Paterson
and Loretta Zderad’s humanistic
nursing theory. In M. Parker & M.

Smith (Eds.), Nursing theories and
nursing practice (3rd ed., pp. 337–
350). Philadelphia, PA : F. A. Davis.

Leonard, B. (2014). Complementary
therapies: Nurse’s self-care. In M.
Snyder, R. Lindquist, & M. Tracy
(Eds.), Complementary and alternative
therapies in nursing (7th ed., pp. 17–
26). New York, NY : Springer.

Liberati, E. G., Gorli, M., Moja, L.,
Galuppo, L., Ripamonti, S., & Scaratti,
G. (2015, May). Exploring the practice
of patient centered care: The role of
ethnography and reflexivity. Social
Science & Medicine, 13345–13352.
doi:10.1016/j.socscimed.2015.03.050

O’Keefe-McCarthy, S. (2009).
Technologically-mediated nursing care:
The impact on moral agency. Nursing
Ethics, 16(6), 786–796.

Penque, S., & Snyder, M. (2014).
Presence. In M. Snyder R. Lindquist &
Tracy, M (Eds.), Complementary and

alternative therapies in nursing (7th
ed., pp. 27–37). New York, NY :
Springer.

University of Minnesota, Center for
Spirituality & Healing (2013). Taking
charge of your health and wellbeing.
Retrieved from
http://www.takingcharge.csh.umn.edu/enhance-
wellbeing

Watanuki, S., Tracy, M. F., & Lindquist, R.
(2014). Therapeutic listening. In M.
Snyder, R. Lindquist, & M. Tracy
(Eds.), Complementary and alternative
therapies in nursing (7th ed., pp. 39–
53) New York, NY : Springer.

Watson, J. (2015). Jean Watson’s theory
of human caring. In M. Smith & M.
Parker (Eds.), Nursing theories and
nursing practice (4th ed., pp. 321–
339). Philadelphia, PA : F. A. Davis.

Zande, M., Baart, A., & Vosman, F. (2014).
Ethical sensitivity in practice: finding
tacit moral knowing. Journal of

Advanced Nursing, 70(1), 68–76.
doi:10.1111/jan.12154

Zerwekh, J. (2006). Connecting and
caring presence. In Nursing care at the
end of life: Palliative care for patients
and families (pp. 113–130).
Philadelphia, PA : F. A. Davis
Company.

CHAPTER 26: Nursing
Informatics and the
Foundation of
Knowledge

Dee McGonigle and Kathleen Mastrian

Objectives
1. Explore the contribution of nursing

informatics to the foundation of
knowledge and to organizational learning
and knowledge.

2. Explore organizational knowledge
management processes and knowledge
co-creation.

3. Identify the characteristics of a learning
healthcare organization.

Key Terms
» Codify

» Data

» Data-centric

» Information

» Information technology (IT)

» Knowledge

» Knowledge acquisition

» Knowledge-centric

» Knowledge dissemination

» Knowledge domain process (KDP)

» Knowledge generation

» Knowledge management systems
(KMSs)

» Knowledge repositories

» Knowledge workers

» Nursing informatics (NI)

Introduction

Throughout this text, the reader has learned about the
many facets of nursing informatics (NI) and the
interfacing of nurse knowledge workers and
technology. The Foundation of Knowledge model
(Figure 26-1) has provided a framework for examining
the dynamic interrelationships among data,
information, and knowledge used to meet the needs
of healthcare delivery systems, organizations, patients,
and nurses. The importance of knowledge
management in nursing and health care is emphasized
by taking this one last opportunity to ensure that the
reader understands and appreciates the value of
knowledge management in the nursing profession and
the role that technology has in supporting knowledge
acquisition, knowledge generation, knowledge
dissemination, and knowledge processing. We will also
look at the characteristics of a learning healthcare
organization and how information technology is integral
to promoting and supporting learning organizations.

Figure 26-1 Foundation of Knowledge Model

Designed by Alicia Mastrian.

Foundation of Knowledge
Revisited
A review of the Foundation of Knowledge model that
provides a framework for the development of this text is
useful. At its base, the model has bits, bytes (computer
terms for chunks of information), data, and information
in a random representation. Growing out of the base
are separate cones of light that expand as they reflect
upward and represent knowledge acquisition,
knowledge generation, and knowledge
dissemination. At the intersection of the cones and
forming a new cone is knowledge processing.

Encircling and cutting through the knowledge cones is
feedback, which acts on and may transform any or all
aspects of knowledge represented by the cones.

Now, imagine the model as a dynamic figure with the
cones of light and the feedback rotating and interacting
rather than remaining static. Knowledge acquisition,
knowledge generation, knowledge dissemination,
knowledge processing, and feedback are constantly
evolving for nurse scientists. The transparent effect of
the cones is deliberate and is intended to suggest that
as knowledge grows and expands, its use becomes
more transparent; that is, the user is not even
consciously aware of which aspect of knowledge he or
she is using at any given moment during her or his
practice.

If you are an experienced nurse, think back to when
you were a novice. Did you feel like all you had in your
head were bits of data and information that did not form
any type of cohesive whole? As the model depicts, the
processing of knowledge as an individual in
professional practice begins a bit later (imagine a
timeline applied vertically), with early experiences on
the bottom and expertise growing as the processing of
knowledge kicks in. Early on in nursing education,
conscious attention is focused mainly on knowledge
acquisition, and learners depend on their instructors
and others to process, generate, and disseminate
knowledge. As learners become more comfortable with

the science of nursing, they begin to take over some of
the other knowledge functions. However, to keep up
with the explosion of information in nursing and health
care, one must continue to rely on the knowledge
generation and dissemination of others. In this sense,
nurses are committed to lifelong learning and the use
of knowledge in the practice of nursing science.

Knowledge management and transfer in healthcare
organizations are likely to be studied in greater depth
as our understanding of professional knowledge
increases and processes to capture and codify it
improve. The Foundation of Knowledge model is not
perfect, and others have developed models of
knowledge that are more complex. For example,
Evans and Alleyne (2009) constructed the
knowledge domain process (KDP) model to
represent knowledge construction and dissemination in
an organization. Yet, they caution:

[T]he KDP model, like all models, is an
abstraction aimed at making complex
systems more easily understood. While
the model presents knowledge processes
in a structured and simplified form, the
nature and structure of the processes
themselves may be open to debate. (p.
148)

As we will learn later in the chapter, getting the
knowledge to the user and creating a culture where
new knowledge is seamlessly integrated into health
care remains a challenge. Mason (2016) offered this
insight:

Simply put, knowledge management
undertakes to identify what is in essence
a human asset buried in the minds and
hard drives of individuals working in an
organization. Knowledge management
also requires a system that will allow the
creation of new knowledge, a
dissemination system that will reach
every employee, with the ability to
package knowledge as value-added in
products, services and systems. (para. 1)

Figure 26-2 depicts knowledge management in an
organization. Note the informatics tools that are integral
to KM, particularly in the knowledge dissemination,
knowledge development, and knowledge processing
aspects of KM.

Figure 26-2 The Knowledge Management Lifecycle

For nurse knowledge workers, information is their
primary resource, and when one deals with information
it is done in overlapping phases. That is, the nurse is
continually acquiring, processing or assimilating,
retaining, and using this information to generate and
disseminate knowledge. However, it is not a sequential
phasing; instead, there is a constant gleaning of data
and information from the environment, with the data

and information massaged into knowledge bases so
that they can be applied and shared (disseminated).

The Nature of Knowledge
Knowledge may be thought of as either explicit or tacit.
Explicit knowledge is the knowledge that one can
convey in letters, words, and numbers. It can be
exchanged or shared in the form of data, manuals,
product specifications, principles, policies, theories,
and the like. Nurses can disseminate and share this
knowledge publicly or on the record and scientifically or
methodically. A nursing model or theory that is well
developed and easily explained and understood is an
example of explicit knowledge. Tacit knowledge, in
contrast, is individualized and highly personal or
private, including one’s values or emotions. Knowing
intuitively when and how to care is an example of tacit
knowledge. This type of knowledge is difficult to
convey, transmit, or share with others because it
consists of one’s own insights or slant on things,
perceptions, intuitions, sense, hunches, or gut feelings.
Tacit knowledge reflects skills and beliefs, which is why
it is difficult to explain or communicate it to others.
Lake (2005) stated:

From close examination of and reflection
on the literature it is possible to infer
nursing prioritization of the patient need
for care as it is initially taught to nursing

students and is then developed in
practice and influenced by practice
setting. The process of nursing
prioritization of the patient need for care
involves discretionary judgment and
ongoing assessment throughout and
between unfolding patient situations. It is
best understood from studies addressing
clinical decision-making in nursing
through the interpretive paradigm and in
the plain language descriptions of nurse
decision-making. The principles of such
decision-making are discussed only in
very general terms and the rationale
remains the tacit knowledge of nursing.
(p. 152)

More recently, Farr and Cressy (2015) used grounded
theory methodology to study how professionals
perceive the quality of their performance and found that
intangible, tacit knowledge was just as important to the
perception of quality of performance as more
standardized rational measures of quality based on
organizational policy.

This paper illuminates the importance of
the tacit, intangible and relational
dimensions of quality in actual practice.
Staff values and personal and

professional standards are core to
understanding how quality is co-produced
in service interactions. Professional
experience, tacit clinical knowledge,
personal standards and values, and
conversations with patients and families
all contributed to how staff understood
and assessed the quality of their work in
everyday practice. (p. 8)

Along these same lines, references to co-creation of
knowledge are beginning to surface in the literature.
Bagayogo, Lapointe, Ramaprasad, and Vedel (2014)
suggested that knowledge co-creation is increasingly
important to innovation in organizations, and that
knowledge is co-created as individuals collaborate on a
shared task and share their experiences and
perceptions. They reported on the use of social media
support for breast and prostate cancer patients:
“Individuals work together and co-create knowledge
through a process that evolves temporally and is
embedded in a web of interactions. Both temporal and
interactional dimensions have been considered in the
study of knowledge co-creation” (p. 627).

How nursing students and practicing nurses learn is
directly affected by their practice experiences within
their own personal frame of reference. The quality of
clinical decision making is directly related to experience

and knowledge. Knowledge is situational. Explicit and
tacit knowledge are used to conduct assessments,
diagnoses, intervention implementation, and evaluation
of nursing actions for each individual patient.
Knowledge management systems (KMSs) must
blend these knowledge needs and provide knowledge
bases and decision support systems to inform clinical
decision making. Each person processes and
assimilates knowledge in a unique way influenced by
his or her unique perspective. What is needed is an
explicit way of surfacing these nuggets of knowledge
so that they can be shared among practitioners.

Knowledge Use in Practice
One way to capture and codify tacit knowledge is to
engage in reflection and reflective practice. Schutz
(2007) believed that

reflection is both a way of learning about
practice and a basis for changing
practice. One must engage in reflective
practice because this approach can
enable a practitioner to find a means in
which to put this personal or experiential
knowledge into words and to find a way
of considering why the situation turned
out as it did and whether future practice
might be different. (p. 27)

Some healthcare organizations are encouraging
reflective practice to codify tacit knowledge and thus to
build an organization’s knowledge base. Sharing
experiences in a Nursing Practice Council is one
means to encourage collaboration and knowledge
sharing among professionals. Joining a LISTSERV,
creating a blog, or participating in a community of
practice (CoP; see Box 26-1 for more information) are
other examples of collaboration to build knowledge.
Watson (2007) described knowledge audits,
narratives, and storytelling as means of surfacing tacit
knowledge and assessing the knowledge resources of
personnel within an organization. He described the use
of information technology (IT) tools for knowledge
management in an organization, such as intranets,
extranets (shared intranets among several like
organizations), knowledge directories, blogs, and wikis.
Research suggests that organizations that embrace
and encourage knowledge transfer among workers not
only sustain and build professional competence and
organizational engagement, but also enhance the
quality of the work life for professionals (Leiter, Day,
Harvie, & Shaughnessy, 2007). Mason (2016)
suggested that, in order to facilitate knowledge co-
creation, organizations must put “mechanisms of
socialization, mentorships, apprenticeships, and
opportunities for face-to-face communication in place”
(para. 7). It is also clear that organizations must create
and support a knowledge culture and user-friendly
knowledge management infrastructure to offset the

potential resistance to using knowledge management
tools. Figure 26-3 depicts some of the issues
associated with knowledge management that create
knowledge management challenges.

Figure 26-3 Organizational Knowledge Management
Issues

Data from UBM Tech. (2016). Knowledge management for the support

center. Retrieved from http://www.thinkhdi.com/knowledge-

management

BOX 26-1 COMMUNITIES OF

PRACTICE

Glenn Johnson and Jeff Swain

Revised by Dee McGonigle and Kathy Mastrian

Developing and sustaining a community of
practice in the work environment is beyond the
main scope of this text. However, educators (in
particular) and nurses need to understand how

the effective collaboration skills that learners
acquire in learning communities during their
formal education may translate to and promote
the development of CoPs in their professional
lives. As the Web-based tools for collaboration
continue to evolve, they are supporting online
CoPs, also known as virtual communities of
practice. The following is a brief overview of this
important and emerging trend for work in the
knowledge era.

Wenger (2006) defined a CoP as follows:
“Communities of practice are groups of people
who share a concern or a passion for something
they do and learn how to do it better as they
interact regularly” (para. 3). He suggests that
CoPs have three important characteristics: (1)
the domain, (2) the community, and (3) the
practice. Wenger defines a domain as a shared
interest about which people are passionate and
for which they possess some related
competence. The community aspect relates to
the joint activities that are undertaken by the
group to build relationships and knowledge
about the domain. The practice aspect denotes
that the members of the community are
practitioners of something and through the CoP
develop and share resources, knowledge, and
solutions to problems. The recent improvement
of Internet-based communications technologies

has the potential to promote the global
expansion of CoPs.

Nursing is a profession that is particularly well-
suited to the development of CoPs, especially in
light of the new knowledge generated and
disseminated every day. The many nursing
LISTSERVs are evidence of the growing trend
toward sharing knowledge in a CoP. An early
informatics LISTSERV was utilized by Caring
(now ANIA), a nursing informatics organization.
Members posted questions to other members
and requested information and experiences
related to informatics. For example, a member
of the LISTSERV might ask others about their
experiences related to a specific issue in
implementing a bar-code medication
administration system or about training
procedures for implementing an electronic
health record. Other members posted replies to
the query. All members had the opportunity to
view the question and the responses. One of the
difficulties of using a LISTSERV as a CoP is that
the discussion is not moderated; many threads
could be running simultaneously.

Blogging is slowly replacing the LISTSERV as a
collaboration tool. An advantage of blogging is
that when one wants information, one seeks it
out directly rather than working through the
continuous feed to email that was common

when using a LISTSERV as a collaboration tool
(although it is also possible to subscribe to a
blog feed). An example of a well-organized and
global CoP is the Cochrane Collaboration
(www.cochrane.org), an international
organization that promotes and supports
collaboration among healthcare professionals to
develop evidence-based practice
recommendations for healthcare interventions. A
nursing practice council within a healthcare
organization is another example of a CoP. In the
future, it is hoped that the use of CoPs in
nursing will grow beyond knowledge sharing and
promote more knowledge discovery and sense
making.

REFERENCE

Wenger, E. (2006). Communities of
practice: A brief introduction.
Retrieved from
https://web.archive.org/web/20130704222806/http://www.ewenger.com/theory/communities_of_practice_intro.htm

Characteristics of Knowledge
Workers
According to Gent (2007), there are three types of
knowledge workers: (1) knowledge consumers, (2)

knowledge brokers, and (3) knowledge generators.
This breakdown of knowledge workers is not mutually
exclusive; instead, people transition between these
states as their situations and experience, education,
and knowledge change.

Knowledge consumers are mainly users of
knowledge who do not have the expertise to
provide the knowledge they need for themselves.
Novice nurses can be thought of as knowledge
consumers who use the knowledge of experienced
nurses or who search information systems for the
knowledge necessary to apply to their practice. As
responsible knowledge consumers, they must also
question and challenge what is known to help them
learn and understand. Their questioning and
challenging facilitate critical thinking and the
development of new knowledge.
Knowledge brokers know where to find information
and knowledge; they generate some knowledge but
are mainly known for their ability to find what is
needed. More experienced nurses and nursing
students become knowledge brokers out of
necessity, needing to know.
Knowledge generators are the “primary sources of
new knowledge” (para. 2). They include nursing
researchers and nursing experts—the people who
know. They are able to answer questions, craft
theories, find solutions to nursing problems or
concerns, and innovate as part of their practice.

Dixon (2012) blogged about knowledge work and
knowledge workers and provides these insights:

Knowledge workers need to acquire new
knowledge every 4–5 years or else they become
obsolete (para. 4).
Knowledge work is invisible, interdependent, and
constantly changing (para. 5).
Knowledge workers, whether they are scientists,
engineers, marketers, accountants, or
administrators, must continuously read the situation
in front of them and then, based on that
interpretation, determine the appropriate next action
to take (para. 5).
Knowledge workers view their knowledge as their
personal possession. The knowledge they possess
is in their minds so when they leave the
organization, the means of production leaves with
them (para. 6).

Nurses are knowledge workers, working with
information and generating information and knowledge
as a product. All of the various nursing roles—practice,
administration, education, research, informatics—
involve the science of nursing. They are knowledge
acquirers, providing convenient and efficient means of
capturing and storing knowledge. They are knowledge
users, individuals or groups who benefit from valuable,
viable knowledge. Nurses are also knowledge

engineers, designing, developing, implementing, and
maintaining knowledge. They are knowledge
managers, capturing and processing collective
expertise and distributing it where it can create the
largest benefit. They are knowledge developers or
generators, changing and evolving knowledge based
on the tasks at hand and information available.

The healthcare industry, the nursing profession, and
patients all benefit as nurses develop nursing
intelligence and intellectual capital by gaining insight
into nursing science and its enactment, practice. NI
applications of databases, knowledge management
systems, and repositories where this knowledge can be
analyzed and reused facilitate this process, enabling
knowledge to be disseminated and reused.

Knowledge Management in
Organizations
To be able to enhance the acquisition, processing,
generation, dissemination, and reuse of nursing
knowledge, nurses must codify or be able to articulate
knowledge structures so that they can be captured
within the KMSs. According to Markus (2001), an early
and prolific writer about organizational knowledge
management:

Synthesis of evidence from a wide variety
of sources suggests four distinct types of
knowledge reuse situations according to
the knowledge reuser and the purpose of
knowledge reuse. The types involve
shared work producers, who produce
knowledge they later reuse; shared work
practitioners, who reuse each other’s
knowledge contributions; expertise-
seeking novices; and secondary
knowledge miners. Each type of
knowledge reuser has different
requirements for knowledge repositories.
(para. 1)

Markus referred to knowledge repositories as
“organizational memory systems” (para. 1). These
memory systems gained popularity among help desk
personnel who could access and reuse the knowledge
of solutions when clients sought help for similar
problems. Health care is an arena in which KMSs or
knowledge repositories are clearly valuable. Hsia, Lin,
Wu, and Tsai (2006) recognize that nurses are
“knowledge-intensive” (para. 4) professionals who are
“required to take new nursing knowledge and
experience that can be acquired through various net-
enabled applications or the Internet. Nursing
professionals are being asked to do more with less in
such contexts, while their nursing care responsibilities

have increased” (para. 4). Today, information
technology capabilities are expanding to develop and
support a “knowledge-centric [boldface added] view
rather than simply a data-centric [boldface added]
view” (para. 4). Nurse knowledge workers must be able
to access, use, and share these new informatics tools
because “a well-designed IT-based knowledge
management system (KMS) has become an ever more
central force in improving the quality of care in
competitive e-health environments” (para. 4). Capturing
the explicit and tacit forms of knowledge is paramount
to truly harness nursing knowledge. As knowledge
repositories evolve to enhance sharing and
repurposing of knowledge, nurses will be able to easily
access, process, evaluate, reuse, generate, and
disseminate knowledge.

Consider the retirement of a healthcare professional
who has worked in a system for 40 years. What types
of uncaptured, uncodified, tacit knowledge walk out the
door on the day of the retirement? Can you appreciate
the value of well-constructed knowledge repository?
Interestingly, Dixon (2012) suggested that supervisors
need to first recognize and acknowledge the tacit
knowledge of seasoned professionals and find ways to
make them feel valued by the organization. Using
seasoned professionals as mentors to new
professionals is a good way to help them surface tacit
knowledge and share their wisdom. Nursing science is
dependent on knowledge generation, and NI should

facilitate all aspects of nursing, especially in the
generation of knowledge, and support translational
research, where we attempt to bridge the gap between
what we know (research) and what we do (practice).
Just like we emphasized earlier, Swan, Lang, and
McGinley (2004) described NI and a common nursing
language as important vehicles to access stores of
clinical information that can be used as the basis for
research and to help answer the question, “What do
nurses do?” “Embedding nursing language within
informatics structures is essential to make the work of
nurses visible and articulate evidence about the quality
and value of nursing in the care of patients, groups,
and populations” (para. 27). In this text, it has been
established that NI is a vital tool for evidence-based
clinical decision making, especially when one is able to
demonstrate how nurses structure and process
information. An important direction for the future is to
study the impact of NI on nursing science. As the
HITECH Act has been implemented, the use of
electronic health records (EHRs) has become more
commonplace in the United States. Such records must
be designed to enhance patient outcomes through
content enrichment and improved caregiver decision
making. As bioinformatics and computational biology
continue to evolve, their integration into the EHR is
inevitable. Nurse informaticists must facilitate the
inclusion of computational tools and algorithms to help
handle the collection, organization, analysis,
processing, presentation, and dissemination of

biological data to help address biological questions and
unravel biological mysteries. It is imperative that
current research strategies, such as those used to
search for biomarkers, and new pharmacologic
treatments be included in the EHR. In this
bioinformatics era, one must be able to delineate
biomarkers and have the necessary alerts, follow-ups,
and reminders built into the system to make all
caregivers aware of the bioinformatics information,
such as the analysis of genes causing hypertension,
cardiovascular disease, and diabetes. Bioinformatics
and computational biology will complement all of the
current methods and aid in the analysis of populations
and tracking of selected diseases’ progression.
Consequently, nurse informaticists must be proactive in
the development of policies and ethically based
solutions to safeguard the genetic data contained in
EHRs, manage the patient care implications of
bioinformatics, and wisely use computational biology in
this bioinformatics era. Visit www.nursingworld.org to
access a document co-authored by Greco, Tinley, and
Seibert (2011) for the ANA, Essential Genetic and
Genomic Competencies for Nurses with Graduate
Degrees.

NI can also be used to facilitate nursing administration
and managerial studies of the work of nursing.
Numerous opportunities for data mining in NI have
been described in this text. Some larger healthcare
systems store all of the clinical information from their

affiliated hospitals and clinics in a central data
warehouse. General data scans and analyses looking
for patterns may, for example, suggest a trend toward
better outcomes for patients with congestive heart
failure in one of the affiliate hospitals. This identification
of such a trend clearly begs for further analyses. A
nurse researcher or administrator could ask, “Which
factors contribute to these better outcomes and how
can they be put into practice across the system?” Other
research studies might focus on assessing the
effectiveness of strategic planning and organizational
goal setting or studying workflow, communication
processes, and interprofessional collaboration in an
organization.

Managing Knowledge Across
Disciplines
Interprofessional collaboration is emerging as a key to
better quality outcomes for patients. This collaboration
is supported by the EHR and other technologies that
facilitate communication among health professionals.
Stichler (2014), in a discussion of collaboration on the
design of healthcare facilities, describes
interprofessional collaboration as “magic at the
intersection”; that is, “true interprofessional practice
intersects and positive outcomes can be achieved as a
result of the synergy that occurs among different
professionals who come together with a common

purpose and goal” (p. 10). Her words can also be
applied to interprofessional collaboration in patient
situations. Consider the ways that NI tools and
technologies can help to ensure that the perspectives
of all professionals are heard and valued to create this
“magic at the intersection.”

Another way for professionals to share perspectives
and knowledge on patient situations is the HUDDLE
(Healthcare, Utilizing, Deliberate, Discussion, Linking,
Events) method, described in a review of the literature
by Glymph et al. (2015). As they describe:

The huddle is a team-building tool that
increases effective communication
among healthcare providers. It is a quick
meeting of healthcare members to share
information. This brief meeting or huddle
takes place at the start of the workday. It
is also a time where groups plan for
contingencies, express concerns,
address conflicts, or reassign resources.
(p. 184)

Can you think of ways that the HUDDLE could be
facilitated electronically in the future?

Research studies aimed at advancing the state of the
science of NI are becoming more commonplace as the

benefits of a robust NI system for managing knowledge
are recognized. We will explore a few here. Rochefort,
Buckenridge, and Forster (2015) explored the use of
an algorithm to mine the EHR for the detection of three
key adverse events (AEs): hospital-acquired
pneumonia, catheter-associated bloodstream
infections, and in-hospital falls. Prior to their work, the
hospitals used discharge diagnostic codes for adverse
event detection, which they believed resulted in both
under- and overestimation of AEs. Their algorithm was
designed to be more comprehensive and mine a
combination of various types of data in the EHR. “To
move this field forward, as well as to maximize the
accuracy of AE detection, there is a need for
comprehensive automated AE detection algorithms
that integrate the information from all the available data
sources (e.g., microbiology and laboratory results, free-
text radiology reports and progress notes and
electronic vital signs)” (para. 10). Evans, Yeung,
Markoulakis, and Guilcher (2014) studied the use of
an online CoP to promote the creation and sharing of
knowledge related to manual therapies among
physiotherapists. They demonstrated that the CoP
approach promoted a social learning environment with
a strong component of engagement, sharing, and co-
creation of knowledge applicable to practice. Brown
and colleagues (2013) demonstrated the use of a wiki
platform to promote international collaboration for
developing and maintaining evidence-based nutrition
guidelines for adults with head and neck cancers.

During the 4-month monitoring process, they reported
over 2,000 page views from 33 different countries. Key
to this process was the opportunity for international
stakeholder feedback that was used to modify and
update the practice guidelines. They conclude, “The
use of this technology is expected to continue to rise as
the advantages of maintaining a live current document
for optimal clinical practice are realized” (p. 189).

We invite you to search the scholarly nursing literature
for other examples of the use of information
technologies to generate, share, and manage
professional knowledge.

The Learning Healthcare
System
The Learning Healthcare System is a relatively new
concept that is being implemented in some of the
larger healthcare systems and is being developed in
collaborative partnerships among groups of hospital
systems. A learning healthcare system was defined in
the 2013 Institute of Medicine (IOM) report, Best Care
at Lower Cost: The Path to Continuously Learning
Health Care in America as follows:

The foundation for a learning health care
system is continuous knowledge
development, improvement, and

application. Although unprecedented
levels of information are available,
patients and clinicians often lack access
to guidance that is relevant, timely, and
useful for the circumstances at hand.
Overcoming this challenge will require
applying computing capabilities and
analytic approaches to develop real-time
insights from routine patient care,
disseminating knowledge using new
technological tools, and addressing the
regulatory challenges that can inhibit
progress. (p. 2)

Some literature also refers to this concept as a rapid-
learning healthcare system (Greene, Reid, & Larson,
2012): “The hallmarks of the rapid-learning health
system are the vital partnership between research and
clinical operations and a shared commitment to
leverage scientific knowledge and evaluation for rapid,
point-of-care improvements” (p. 209). These learning
healthcare systems take advantage of informatics
analytics concepts and processes for data mining the
rich clinical data in the EHRs. Using both structured
and unstructured data, these data are mined for new
clinical understandings that are rapidly implemented to
improve patient outcomes. The system depends on
data sharing, rather than data hoarding that was part of
the earlier competitive culture healthcare environment.

As Greene and colleagues explain, “By blending
research evidence with daily experiences of a frontline
workforce, a learning organization leverages evidence
about “what works” in the context of its own setting,
population, available resources, and organizational
culture” (p. 208). Figure 26-4 provides a schematic
overview of knowledge management in a learning
healthcare system.

Figure 26-4 The Learning Healthcare System

Data from Greene, S. M., Reid, R. J., & Larson, E. B. (2012).

Implementing the learning health system: From concept to action. Annals

of Internal Medicine, 157(3), 207.

The IOM (2013) report provides the following
description of the characteristics of a Learning
Healthcare System, which includes the use of science

and informatics, encourages patient–clinician
partnerships, provides incentives, and promotes a
culture shift to a continuous learning culture:

Real-time access to knowledge—A learning
healthcare system continuously and reliably
captures, curates, and delivers the best available
evidence to guide, support, tailor, and improve
clinical decision making and care safety and quality.
Digital capture of the care experience—A learning
healthcare system captures the care experience on
digital platforms for real-time generation and
application of knowledge for care improvement.
Engaged, empowered patients—A learning
healthcare system is anchored on patient needs
and perspectives and promotes the inclusion of
patients, families, and other caregivers as vital
members of the continuously learning care team.
Incentives aligned for value—A learning healthcare
system has incentives actively aligned to encourage
continuous improvement, identify and reduce
waste, and reward high-value care.
Full transparency—A learning healthcare system
systematically monitors the safety, quality,
processes, prices, costs, and outcomes of care,
and makes information available for care
improvement and informed choices and decision
making by clinicians, patients, and their families.
Leadership-instilled culture of learning—A learning
healthcare system is stewarded by leadership

committed to a culture of teamwork, collaboration,
and adaptability in support of continuous learning
as a core aim.
Supportive system competencies—A learning
healthcare system constantly refines complex care
operations and processes through ongoing team
training and skill building, systems analysis and
information development, and creation of the
feedback loops for continuous learning and system
improvement. (p. 18)

Technologies that provide support for the collection and
analysis of clinical data are also evolving. New
infrastructures will need to be deployed. For example,
Mandl et al. (2014) described the Scalable
Collaborative Infrastructure for a Learning Healthcare
System (SCILHS) architecture to support data
collection and analysis from a group of 10 healthcare
organizations. Similarly, Kaggal et al. (2016) described
an infrastructure for mining unstructured data (free text
entries) in the EHR using natural language processing
(NLP) tools.

As learning healthcare systems concepts are
implemented more widely, we will experience more
rapid knowledge dissemination than was previously
possible with more traditional forms of research,
especially the randomized clinical trial. Research
samples will no longer be limited by the researcher’s
access to subjects. Clearly, though, these new

research paradigms will also necessitate new ethics
considerations for the use of clinical data and the
protection of human subjects. For more information
about learning healthcare systems, track developments
at The Learning Healthcare Project
(www.learninghealthcareproject.org/index.php).

Summary
In the future, there will be many more attempts to
capture, represent, and explain knowledge processes
in professional practice. It is hoped that the reader is
convinced that for the nursing profession to evolve,
knowledge must be dynamically generated,
disseminated, and assimilated. This ever-changing
interplay means that as knowledge is generated,
disseminated, and assimilated, new questions about
the impact of NI that will help new knowledge to be
generated, assimilated, and so on will arise. The
assimilation of new knowledge in a profession is a
multifaceted approach of individual perception,
challenges, and collective thought applied to the
practice of nursing. Nurses challenge what is known
and want to acquire, process, generate, and
disseminate knowledge to improve patient outcomes.

As a result of reading this text, you should have a
deeper understanding of knowledge and informatics,
as well as the power they have to inform the science of
nursing. It is hoped that you also gained valuable

insights into the core principles of NI and the NI
practice specialty. We hope that we have motivated
you to continue to learn more and perhaps delve into
the science of NI in a nursing research role. Readers
are invited to become active participants in molding the
future of both nursing and informatics sciences.

THOUGHT-PROVOKING QUESTIONS

Become informatics savvy and ask yourself the
following questions:

1. How can I apply the knowledge I gain
from my practice setting to benefit my
patients and enhance my practice?

2. How can I help my colleagues and
patients embrace, understand, and use
technologies to manage health?

3. How can I use and communicate my
wisdom to help create the theories, tools,
and knowledge of the future?

References
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Abbreviations
3D

Three-dimensional

ABC
Alternative billing codes

ACLS
Advanced cardiac life support

ADT
Admission, discharge, and transfer system

AHRQ
Agency for Healthcare Research and Quality

AI
Artificial intelligence

ALA
American Library Association

Alt
Alternate key on the computer keyboard

ALU
Arithmetic logic unit

AMIA
American Medical Informatics Association

AMOLED
Active matrix organic light-emitting diode

ANA
American Nurses Association

ANGEL
A New Global Environment for Learning

ANIA
American Nursing Informatics Association

ANSI
American National Standards Institute

API
Application programming interface

APMs
Alternative Payment Models

ARG
Augmented-reality game

ARRA
American Recovery and Reinvestment Act

ATSDR
Agency for Toxic Substances and Disease Registry

b
Bit

B
Byte

BCMA
Bar Code Medication Administration

BI
Bioinformatics

BIOS
Basic input/output system

BMP
Bitmap image

bps
Bits per second

BRFSS
Behavioral Risk Factor Surveillance System

CAI
Computer-assisted instruction

CASE
Computer-aided software engineering

CBIS
Computer-based information system

CCC
Clinical care classification

CD
Compact disk

CD-R
Compact disk—recordable

CD-ROM
Compact disk—read-only memory

CD-RW
Compact disk—recordable and rewritable

CDC
Centers for Disease Control and Prevention

CDS/CDSS
Clinical decision support/clinical decision support
system

CHESS
Comprehensive Health Enhancement Support
System

CHF
Congestive heart failure

CHI
Consolidated health informatics

CHIP
Children’s Health Insurance Program

CI
Cognitive informatics

CINAHL
Cumulative Index to Nursing and Allied Health
Literature

CIO
Chief information officer

CIS
Clinical information systems

CMIS
Case management information system

CMP
Civil monetary penalties

CMS
Course management system; content management
system; Centers for Medicare and Medicaid
Services

CNPII
Committee for Nursing Practice Information
Infrastructure

COPD
Chronic obstructive pulmonary disease

CPGs
Clinical practice guidelines

CPOE
Computerized physician/provider order entry

CPU
Central processing unit

CRA
Community risk assessment

CRT

Cathode ray tube

CSS
Cascading style sheets

CTA
Cognitive task analysis

CTO
Chief technical officer; chief technology officer

Ctrl
Control key on the computer keyboard

CWA
Cognitive work analysis

DBMS
Database management system

DDR SDRAM
Double data rate synchronous dynamic random-
access memory

DHIS
Division of Health Informatics and Surveillance

DHR
Digital health record

DPI
Dots per inch

DRAM
Dynamic random-access memory

DSDM
Dynamic system development method

DSS
Decision support system

DVD
Digital versatile disk; digital video disk

DVD-R
Digital video disk—recordable

DVD-RW
Digital video disk—recordable and rewritable

DW
Data warehouse

EB
Exabyte

EBP
Evidence-based practice

EDI
Electronic data interchange

EEPROM
Electronically erasable programmable read-only
memory

EHR
Electronic health record

ELSI

Ethical, legal, and social issues

eMAR
Electronic mediation administration record

EMR
Electronic medical record

EPROM
Erasable programmable read-only memory

ERD
Entity–relationship diagram

ERIC
Education Resources Information Center

ESC
Escape key

ESLI
Ethical, social, and legal implications

F key
Function key on the computer keyboard

F/OSS or FOSS
Free/open source software

FHIE
Federal Health Information Exchange

FMEA
Failure modes and effects analysis

FPROM

Field programmable read-only memory

FPU
Floating-point unit

GAO
Government Accountability Office

GB
Gigabyte

GDC
Genomic Data Commons

GHz
Gigahertz

GLBA
Gramm-Leach-Bliley Act

GUI
Graphical user interface

HCI
Human–computer interaction

HCT
Human–computer technology

HDMI
High-definition multimedia interface

HGP
Human Genome Project

HHA

Home health agency

HIE
Health information exchange

HIPAA
Health Insurance Portability and Accountability Act

HIS
Hospital information system

HIT
Health information technology

HITECH
Health Information Technology for Economic and
Clinical Health Act

HL7
Health Level 7

HMIS
Health management information system

HMO
Health maintenance organization

HTI
Human–technology interaction

HTML
Hypertext Markup Language

IaaS
Infrastructure as a service

I/O
Input/output

ICNP
International Classification of Nursing Practice

IDE
Integrated drive electronics

IEEE
Institute of Electrical and Electronics Engineers

IHI
Institute for Healthcare Improvement

IHIE
Indiana Health Information Exchange

IM
Instant message

IN
Informatics nurse

INS
Informatics nurse specialist

IP
Internet Protocol

IPS LCD
In-plane switching liquid crystal display

IS
Information system

ISO
International Standards Organization or
International Organization for Standardization

IT
Information technology

KB
Kilobyte

KMS
Knowledge management system

LAN
Local area network

LCD
Liquid crystal display

LOINC
Logical Observation Identifiers Names and Codes

LOS
Length of stay

LTC
Long-term care

MACRA
Medicare Access and Summary CHIP
Reauthorization Act

MAN
Metropolitan area network

MB
Megabyte

MCIS
Managed care information system

MHDC
Massachusetts Health Data Consortium

MHz
Megahertz

MIPS
Millions of instructions per second; Merit-based
Incentive Payment System

MMIS
Medicaid management information systems

MMORPG
Massive multiplayer online role-playing game
(sometimes shortened to MMO)

Modem
Modulator–demodulator

MOO
Object-oriented multiuser dungeon

Moodle
Modular object-oriented dynamic learning
environment

MoSCoW
Must have, Should have, Could have, and Would

have

MP3
MPEG-1 Audio Layer-3

MPEG
Moving Picture Experts Group

MPI
Master patient index

MRI
Magnetic resonance imaging

MU
Meaningful use

MUD
Multiuser dungeon

MUSH
Multiuser shared hack, habitat, holodeck, or
hallucination

NANDA-I
NANDA International, Inc.

NCPHI
National Center for Public Health Informatics

NGC
National Guideline Clearinghouse

NGI
Next-generation Internet

NHANES
National Health and Nutrition Examination Survey

NHII
National Health Information Infrastructure

NHIN
National Health Information Network

NHQR
National Healthcare Quality Report

NI
Nursing informatics

NIC
Nursing Intervention Classification; network
interface card

NIDSEC
Nursing Information and Data Set Evaluation
Center

NIS
Nursing information system

NIST
National Institute of Standards and Technology

NLS
National language support

NMDS
Nursing Minimum Data Set

NMMDS
Nursing Management Minimum Data Set

NOC
Nursing outcome classification

NPC
Nonplayer character

NPI
National provider identifier

OASIS
Outcomes and Assessment Information Set

OCR
Office of Civil Rights

ONC
Office of the National Coordinator for Health
Information Technology

OS
Operating system

OSI
Open systems interconnection

OWL
Web ontology language

PaaS
Platform as a service

PACS

Picture archiving and communication system

PADS
Planned accelerated discharge protocols

PB
Petabyte

PBL
Problem-based learning

PC
Personal computer

PCA
Patient-controlled analgesia

PCI
Peripheral component interconnection

PCIS
Patient care information system

PDA
Personal data assistant; personal digital assistant

PEDA
Pre-brief/enactment/debrief/assessment

PERS
Personal emergency response system

PHI
Protected health information; public health
informatics

PHR
Personal health record

PNDS
Perioperative Nursing Data Set

POSIX
Portable Operating System Interface for UNIX

PPS
Prospective payment system

PROM
Programmable read-only memory

PrtSc or Prnt Scrn
Print screen key

PS/2
Personal System/2

PT/INR
Prothrombin time/international normalized ratio

QA
Quality assurance

QCDR
Qualified Clinical Data Registry

QPP
Quality Payment Program

QRPH
Quality, research, and public health

RAD
Rapid application development

RAM
Random-access memory

RATS
Readiness assessment tests

RCT
Randomized controlled trial

RDBMS
Relational database management system

RDF
Resource description framework

RFI
Radiofrequency identifier

RFID
Radio frequency identification

RHIO
Regional health information organization

RIS
Radiology information system

ROM
Read-only memory

RSS
Really simple syndication

RSVP
Rapid Syndromic Validation Project

RU
Research utilization

SaaS
Software as a service

SCSI
Small Computer System Interface

SDLC
Systems development life cycle

SDO
Standards developing organization

SDRAM
Synchronous dynamic random-access memory

SGML
Standard Generalized Markup Language

SNOMED CT
Systematic Nomenclature of Medical Clinical Terms

SOX
Sarbanes-Oxley Act

SPRC
Suicide Prevention Resource Center

SQL
Structured English Query Language

STEM
Science, technology, engineering, and math

TB
Terabyte

TCP
Transmission Control Protocol

TELOS
Technological and systems, economic, legal,
operational, and schedule feasibility

TPO
Treatment payment operations

URL
Uniform resource locator

USB
Universal serial bus

VNA
Visiting Nurse Association

VoIP
Voice-over-Internet Protocol

VR
Virtual reality

W3C
World Wide Web Consortium

WAN

Wide area network

WMC
Web-based medical chart

WWW
World Wide Web

XML
Extensible Markup Language

YB
Yottabyte

YRBSS
Youth Risk Behavior Surveillance System

ZB
Zettabyte

Glossary
A New Global Environment for Learning (ANGEL)

A course management system designed to support
classroom learning in academic settings.

Acceptable use
A corporate policy that defines the types of activities
that are acceptable on the corporate computer
network, identifies the activities that are not
acceptable, and specifies the consequences for
violations.

Access
To obtain or retrieve data in order to process it.

Accessibility
Ease of accessing the information and knowledge
needed to deliver care or manage a health service;
the extent to which a system is usable by as many
users as possible.

Acquisition
The act of acquiring; to locate and hold. We acquire
data and information.

Active listening
A therapeutic communication technique in which the
nurse employs conscious attention to what a patient

is saying, reflects back feelings and phrases, and
asks questions to clarify meaning.

Acuity systems
Systems that calculate the nursing care
requirements for individual patients based on
severity of illness, specialized equipment and
technology needed, and intensity of nursing
interventions; and determine the amount of daily
nursing care needed for each patient in a nursing
unit.

Administrative processes
The processes used by administration, such as the
electronic scheduling, billing, and claims
management systems including electronic
scheduling for inpatient and outpatient visits and
procedures, electronic insurance eligibility
validation, claim authorization and prior approval,
identification of possible research study
participants, and drug recall support.

Admission, discharge, and transfer (ADT) systems
Systems that provide the backbone structure for the
other types of clinical and business systems; they
contain the groundwork for the other types of
healthcare information systems because they
include the patient’s name, medical record number,
visit or account number, and demographic
information such as age, sex, home address, and
contact information. They are the central sources

for collecting this type of patient information and
communicating it to the other types of healthcare
information systems, including clinical and business
systems.

Advanced cardiac life support (ACLS)
Protocol for a set of knowledge, skills, and clinical
interventions for the immediate or initial treatment of
life-threatening medical emergencies such as
cardiac arrest or stroke.

Adverse events
Any undesirable experiences or outcomes in a
patient related to the use of a medical treatment or
product.

Advocate
Someone who represents another person’s
interests; to act in patients’ best interest; to act
and/or speak on patients’ behalf; to make the
healthcare delivery system responsive to patients’
needs.

Advocate/policy developer
A nurse informatics specialist who is key to
developing the infrastructure of health policy. Policy
development on the local, national, and
international levels is an integral part of this role.

Agency for Healthcare Research and Quality
(AHRQ)

An agency within the U.S. Department of Health
and Human Services that supports health services
research initiatives.

Agency for Toxic Substances and Disease Registry
(ATSDR)

A federal agency that acts as a repository for
research and data regarding hazardous materials
that serves the public by using the best science,
taking responsive public health actions, and
providing trusted health information to prevent
harmful exposures and diseases related to toxic
substances.

Aggregate data
Any types of data that can be referenced as a
single entity, but that also consist of more than one
piece of data; collected, gathered, and reported
data that are related and kept together in a way that
addresses their relationship. For example, the
population of a state is an aggregate of the
populations of its cities, counties, and regions.

Alarm fatigue
Multiple false alarms by smart technology that
cause workers to ignore or respond slowly to them.

Alert
Warning or additional information provided to
clinicians to help with decision making; the action of
the clinician or system triggers the generation of an
alert. For example, an alert could be generated if

the patient’s serum potassium level is high and he
is on potassium chloride; the system would alert the
nurse on the screen (soft copy alert) with or without
audio and/or by a printed (hard copy alert) warning.
Also known as a trigger.

Algorithms
Step-by-step procedures for problem solving or
calculating; sets of rules for problem solving. In data
mining, an algorithm defines the parameters of the
data mining model; it is the recipe or method with
which the data mining model is developed.

Alleles
Members of a pair or series of genes that occupy a
specific position on a specific chromosome.

Alternative payment models (APMs)
The Reauthorization Act of 2015 (MACRA)
reformed Medicare payments by making changes
that created a quality payment program (QPP) to
replace the hodgepodge system of Medicare
reporting programs. The MACRA QPP has two
paths—merit-based payment system (MIPS) or
alternative payment models (APMs)—that will be in
effect through 2021 and beyond. The APMs are not
just incentives, but fundamental changes in how we
pay for health care in the United States. It is these
models, particularly those dealing with total cost of
care, that have the potential to fundamentally alter
the value we receive from health care.

Alternatives
Choices between two or more options.

American Library Association
A U.S.-based organization that promotes libraries
and library education internationally.

American National Standards Institute (ANSI)
An organization dedicated to promoting consensus
on norms and guidelines related to the assessment
of health agencies.

American Recovery and Reinvestment Act (ARRA)
An economic stimulus package enacted in February
2009 that was intended to create jobs and promote
investment and consumer spending during the
recession. This act has also been referred to as the
Stimulus or Recovery Act. There was a push for
widespread adoption of health information
technology, and Title XIII of ARRA was given a
subtitle: Health Information Technology for
Economic and Clinical Health (HITECH) Act.
Through this act, healthcare organizations can
qualify for financial incentives based on the level of
meaningful use achieved; the HITECH Act
specifically incentivizes health organizations and
providers to become meaningful users.

AMOLED (active matrix organic light-emitting
diode)

Smartphone display with individual pixels being lit
separately (active matrix); the next generation

super AMOLED type includes touch sensors. With
the active matrix, you have crisp, vivid colors and
darker blacks.

Analysis
Separating a whole into its elements or component
parts; examination of a concept or phenomena, its
elements, and their relations.

Analytical model
A method, process, and structure for analyzing and
examining a dataset.

Antiprinciplism
Theory that emerged with the expansive
technological changes in recent years and the
tremendous rise in ethical dilemmas accompanying
these changes. Opponents of principlism include
those who claim that its principles do not represent
a theoretical approach and those who claim that its
principles are too far removed from the concrete
particularities of everyday human existence; the
principles are too conceptual, intangible, or
abstract; or the principles disregard or do not take
into account a person’s psychological factors,
personality, life history, sexual orientation, religious,
ethnic, and cultural background.

Antivirus software
A computer program that is designed to recognize
and neutralize computer viruses—that is, malicious
codes that replicate over and over and eventually

take over the computer’s memory and interfere with
its normal functioning.

Application
The implementation software of a computer system.
This software allows users to complete tasks such
as word processing, developing presentations, and
managing data.

Applications (apps)
Software used on a smartphone or other mobile
device.

Archetype
Broad or general, idealized model of an object or
concept from which similar instances are derived,
copied, patterned, or emulated; the original model
after which other similar things are patterned; the
first form from which varieties arise or imitations are
made.

Arithmetic logic units
Essential building blocks of the processor of a
computer that digitally perform arithmetic and
logical functions.

Art of nursing
The relationship-centered aspects of nursing care,
in which the focus is on communicating caring and
providing emotional support and comfort to the
patient.

Artificial intelligence

The field that deals with the conception,
development, and implementation of informatics
tools based on intelligent technologies. This field
attempts to capture the complex processes of
human thought and intelligence.

Assessment
The simulation stage in which student performance
is rated or graded. The student should be provided
with a detailed explanation of how they will be
assessed and graded that relates to the goal,
educational outcomes, and, if applicable,
course/program outcomes. Detailed rubrics are
recommended.

Asynchronous
That which is not synchronous; not in real time, or
does not occur or exist at the same time, having the
same period or time frame. Learning anywhere and
at any time using Internet and World Wide Web
software tools (e.g., course management systems,
e-mail, electronic bulletin boards, webpages) as the
principal delivery mechanisms for instruction.

Attribute
Quality or characteristic; field or element of an entity
in a database.

Audiopod
Traditional, audio-based podcast or utility to
download podcasts.

Augmented-reality games (ARGs)
Games in which a device, such as a smartphone, is
used to overlay on the real world and bring people
together physically and virtually to solve a series of
challenges.

Authentication
Processes to serve to authenticate or prove who is
accessing the system.

Autonomy
The right of an individual to choose for himself or
herself.

Avatar
Image on the Internet that represents the user in
virtual communities or other interactions on the
Internet; three-dimensional or two-dimensional
image representing one user on the Internet.

Bagging
The use of voting and averaging in predictive data
mining to synthesize the predictions from many
models or methods or for using the same type of a
model on different data; it deals with the
unpredictability of results when complex models are
used to data mine small datasets.

Baiting
Tricking a user to load an infected physical device
onto their computer by leaving it in a public area

such as a copy room. The user loads the device to
try to identify its owner.

Bar-code medication administration (BCMA)
A system using bar-code technology affixed to the
medication, the patient ID bracelet, and the nurse
ID badge to support the five rights of medication
administration.

Basic input/output system (BIOS)
Binary input/output system, basic integrated
operating system, or built-in operating system; a
system that resides or is embedded on a chip that
recognizes and controls a computer’s devices.

Behavioral Risk Factor Surveillance System
(BRFSS)

An assessment system initially designed to collect
information on the movement of mentally impaired
persons from state-operated facilities into
community settings. The assessments have since
been expanded to include other populations and
are designed to determine the effectiveness of
programs in meeting the healthcare needs of at-risk
populations.

Beneficence
Actions performed that contribute to the welfare of
others.

Big data

Voluminous amounts of datasets that are difficult to
process using typical data processing; huge
amounts of semistructured and unstructured data
that are unwieldy to manage within relational
databases. Unstructured big data residing in text
files represent more than 75% of an organization’s
data.

Binary system
System used by computers; a numeric system that
uses two symbols: 0 and 1.

Bioethics
The study and formulation of healthcare ethics.
Bioethics takes on relevant ethical problems
experienced by healthcare providers in the
provision of care to individuals and groups.

Bioinformatics
The application of computer science, information
science, and cognitive science principles to
biological systems, especially in the human genome
field of study; an interdisciplinary science that
applies computer and information sciences to solve
biological problems.

Biomedical informatics
Interdisciplinary science of acquiring, structuring,
analyzing, and providing access to biomedical data,
information, and knowledge to improve the
detection, prevention, and treatment of disease.

Biometrics
Study of processes or means to uniquely recognize
individual users (humans) based on one or more
intrinsic physical or behavioral attributes or
characteristics. Authentication devices that
recognize thumb prints, retinal patterns, or facial
patterns are available. Depending on the level of
security needed, organizations will commonly use a
combination of these types of authentication.

Bioterrorism
The use of pathogens or other potentially harmful
biological agents to sicken or kill members of a
targeted population. Informatics database
applications are used to track strategic indicators,
such as emergency room visits, disease case
reports, frequency and type of lab testing ordered
by physicians and/or nurse practitioners, missed
work, and over-the-counter medication purchases,
that may indicate an outbreak that can be attributed
to bioterrorism.

Bit
Unit of measurement that holds one binary digit, 0
or 1. The smallest possible chunk of data memory
used in computer processing, making up the binary
system of the computer.

Blended
An approach to education that combines traditional
face-to-face instruction with technology-based

(online) instruction. See also hybrid.

Blogs
Interactive, online weblogs. Typically a combination
of what is happening on the Web as well as what is
happening in the blogger’s or creator’s life. A blog is
as unique as the blogger or person creating it.
Thought of as a diary and guide.

Blogger
Someone who creates and maintains a blog; a
person who blogs.

Boosting
Increasing the power of models by weighting the
combinations of predictions from those models to
create a predicted classification; an iterative
process using voting or averaging to combine the
different classifiers.

Borrowed theory
Theories borrowed or made use of from other
disciplines. As nursing began to evolve, theories
from other disciplines (e.g., psychology, sociology)
were adopted to try to empirically describe, explain,
or predict nursing phenomena. As nursing theories
continue to be developed, nurses are now
questioning whether these borrowed theories were
sufficient or satisfactory in their relation to the
nursing phenomena they were used to describe,
explain, or predict.

Brain
The central information processing unit of humans.
An organ that controls the central nervous system,
it is responsible for cognition and the interpretation,
processing, and reaction to sensory input.

Browser
Software used to locate and display webpages.
Also known as a web browser or Internet browser.

Brushing
A technique whereby the user manually chooses
specific data points or observations or subsets of
data on an interactive data display; these data can
be visualized in two-dimensional or three-
dimensional surfaces as scatterplots. Also known
as graphical exploratory data analysis.

Brute force attack
A technique where software creates many possible
combinations of characters in an attempt to guess
passwords to gain access to an network or a
computer.

Building blocks
Basic elements or parts of nursing informatics such
as information science, computer science, cognitive
science, and nursing science.

Bus
Subsystem that transfers data between a
computer’s internal components or between

computers.

Byte
Unit of memory equal to eight bits or eight
informational storage units, which represents one
keystroke (e.g., any push of a key on a keyboard
such as pressing the space bar, a lowercase “a” or
an uppercase “T”). It is considered the best way to
indicate computer memory or storage capacity.

Cache memory
Smaller and faster memory storage used by a
computer’s processor to store copies of frequently
used data in main memory.

Call centers
Registered nurse–staffed facilities at which nurses
typically act as case managers for callers or
perform patient triage.

Care ethics
An ethical approach to solving moral dilemmas
encountered in health care that is based on
relationships and a caring attitude toward others.

Care plan
A set of guidelines that outline the course of
treatment and the recommended interventions that
will achieve optimal results.

Caring
The nontechnical aspects of nursing interventions
that communicate acceptance and concern for a

patient.

Caritas processes
Nursing interventions that communicate loving
concern for the unique humanity of every patient.

Case management information systems
Computer programs and information management
tools that interact to support and facilitate the
practice of case managers.

Case study
An account of a nursing informatics activity, event,
or problem containing some of the background and
complexities actually encountered by a nurse. The
case is used to enhance one’s learning about
nursing informatics principles, practices, and trends.
Each case describes a series of events that reflect
the nursing informatics episode as it actually
occurred.

Casuist approach
An approach to ethical decision making that grew
out of the concern for more concrete methods of
examining ethical dilemmas. Casuistry is a case-
based ethical reasoning method that analyzes the
facts of a case in a sound, logical, and ordered or
structured manner. The facts are compared to the
decisions arising out of consensus in previous
paradigmatic or model cases.

Centering

The act of taking a moment to clear one’s mind of
clutter and focus one’s attention exclusively on a
patient prior to engaging in a therapeutic encounter.

Centers for Disease Control and Prevention (CDC)
An agency of the U.S. Department of Health and
Human Services that works to protect public health
and safety related to disease control and
prevention.

Centers for Medicare and Medicaid Services
The largest health insurer in the United States,
particularly for home healthcare services, and for
the elderly, for healthcare services.

Central processing unit (CPU)
An old term for processors and microprocessors
that execute computer programs, thought of as the
brain controlling the functioning of the computer; the
computer component that actually executes,
calculates, and processes the binary computer
code instigated by the operating system and other
applications on the computer. It serves as the
command center that directs the actions of all other
components of the computer and manages both
incoming and outgoing data.

Central stations
Multifunctional telehealthcare platforms for
receiving, retrieving, and/or displaying patients’ vital
signs and other information transmitted from
telecommunications-ready medical devices.

Certification
System for validating that a nurse possesses
certain skills and knowledge or is competent to
complete a task. Competence and skill level are
determined by or based on an external review,
assessment, examination, or education.

Certified EHR technology
An electronic health record (EHR) that meets
specific governmental standards for the type of
record involved, either an ambulatory EHR used by
office-based healthcare practitioners or an inpatient
EHR used by hospitals. The specific standards to
be met are set forth in federal regulations.

Change
A transition to something different.

Chat
Real-time electronic communications; users type
what they want to say, and their messages are
displayed on the screens of all participants in the
same chat. Internet Relay Chat (IRC) is the Internet
protocol for chat.

Chief information officers
People involved with the information technology
infrastructure of an organization. This role is
sometimes called chief knowledge officer.

Chief technical officers
People focused on organizationally based scientific

and technical issues and responsible for
technological research and development as part of
the organization’s products and services.

Chief technology officers
Another name for chief technical officers.

Chronic disease
Long-term disease, such as congestive heart
failure, diabetes, and respiratory ailments.

Civil monetary penalties
Fines laid out by the Social Security Act, which the
Secretary of Health and Human Services can
assess for many types of noncompliant conduct.

Classification
The technique of dividing a dataset into mutually
exclusive groups.

Classification and regression trees (CART)
A decision tree method that is used for sorting or
classifying a dataset. A set of rules that can be
applied to a new dataset that has not been
classified; the set of rules is designed to predict
which records will have a specified outcome.

Clinical analytics
Process of analysis by which clinical data are used
to help make decisions and develop predictive
analytics.

Clinical databases

Collections of related patient records stored in a
computer system using software that permits a
person or program to query the data to extract
needed patient information.

Clinical decision support (CDS)
A computer-based program designed to assist
clinicians in making clinical decisions by filtering or
integrating vast amounts of information and
providing suggestions for clinical intervention. May
also be called a clinical decision support system
(CDSS).

Clinical documentation systems
Arrays or collections of applications and
functionality; amalgamations of systems, medical
equipment, and technologies working together that
are committed or dedicated to collecting, storing,
and manipulating healthcare data and information
and providing secure access to interdisciplinary
clinicians navigating the continuum of client care.
Designed to collect patient data in real time and to
enhance care by putting data at the clinician’s
fingertips and enabling decision making where it
needs to occur—at the bedside. Also known as
clinical information systems (CISs).

Clinical guidelines
Recommendations that serve as a guide to
decisions and provide criteria for specific practice
areas.

Clinical informatics
Application of informatics and information
technology to deliver healthcare services. It is also
referred to as applied clinical informatics or
operational informatics.

Clinical information systems
Arrays or collections of applications and
functionality; amalgamations of systems, medical
equipment, and technologies working together that
are committed or dedicated to collecting, storing,
and manipulating healthcare data and information
and providing secure access to interdisciplinary
clinicians navigating the continuum of client care.
Designed to collect patient data in real time and to
enhance care by putting data at the clinician’s
fingertips and enabling decision making where it
needs to occur—at the bedside. Also known as
clinical documentation systems.

Clinical outcomes
Patients’ results and consequences from clinical
interventions.

Clinical practice council
Group that uses the information generated by the
clinical information systems to design clinical
education programs. Also called nursing practice
council.

Clinical practice guidelines
Informal or formal rules or guiding principles that a

healthcare provider uses when determining
diagnostic tests and treatment strategies for
individual patients. In the electronic health record,
they are included in a variety of ways such as
prompts, pop-ups, and text messages.

Clinical research informatics
The use of informatics in the discovery and
management of new knowledge relating to health
and disease. It includes management of information
related to clinical trials and also involves informatics
related to secondary research use of clinical data.
Clinical research informatics and translational
bioinformatics are the primary domains related to
informatics activities to support translational
research,

Clinical transformation
The complete alteration of the clinical environment;
widespread change accompanies transformational
activities, and clinical transformation implies that the
manner in which work is carried out and the
outcomes achieved are completely different from
the prior state, which is not always true in the case
of simply implementing technology. Technology can
be used to launch or in conjunction with a clinical
transformation initiative; however, the
implementation of technology alone is not justifiably
transformational ability. Therefore, this term should
be used cautiously to describe redesign efforts.

Cloud computing
Web browser–based login-accessible data,
software, and hardware; could link systems
together and reduce costs.

Cloud storage
Data storage provided by networked online servers
that are typically outside of the institution whose
data are being housed.

Coded terminology
Nursing terminologies that are given a specific and
standardized designation so that they can be easily
entered into computerized nursing documentation
systems, searched for, and easily retrieved.

Codify
To classify, reduce to code, or articulate.

Cognitive
That which uses one’s capacity to think. The
process of cognition is important to generate
knowledge. Conscious intellectual or mental activity
such as thinking, reasoning, and remembering, it
includes imagination or the ability to imagine and
the ability to learn.

Cognitive activity
Any process or task (activity) that involves the
capacity to think, reason, imagine, and learn.

Cognitive informatics
Field of study made up of the disciplines of

neuroscience, linguistics, artificial intelligence, and
psychology. This multidisciplinary study of cognition
and information sciences investigates human
information-processing mechanisms and processes
and their engineering applications in computing.

Cognitive science
Interdisciplinary field that studies the mind,
intelligence, and behavior from an information
processing perspective.

Cognitive task analysis (CTA)
Examination of the nature of a task by breaking it
down into its component parts and identifying the
performers’ thought processes.

Cognitive walkthrough
A technique used to evaluate a computer interface
or a software program by breaking down and
explaining the steps that a user will take to
accomplish a task.

Cognitive work analysis (CWA)
A multifaceted analytic procedure developed
specifically for the analysis of complex, high-
technology work domains.

Collaboration
The sharing of ideas and experiences for the
purposes of mutual understanding and learning.

Columns
Fields or attributes of an entity in a database.

Communication science
Area of concentration or discipline that studies
human communication.

Communication software
Technology programs used to transmit messages
via e-mail, telephone, paging, broadcast (such as
MP3), and Internet (such as instant messaging,
Voice-over-Internet Protocol, or Listservs).

Communication systems
Collections of individual communications networks
and transmission systems. In health care, they
include call light systems, wireless phones, pagers,
e-mail, instant messaging, and any other devices or
networks that clinicians use to communicate with
patients, families, other professionals, and internal
and external resources.

Communications hub
A device that captures and assists in the
transmission of information from peripheral
equipment. A processor organizes the data,
appropriately encrypts the data to assure
confidentiality, and transmits the encrypted data to
appropriate decision makers. Data can be
transmitted via traditional phone lines, through the
Internet, or over wireless networks. Typically the
hub will be a small box, to which peripheral
equipment is connected.

Community risk assessment (CRA)
A comprehensive examination of a community to
identify factors that potentially affect the health of
the members of that community. Often used in
public health program planning.

Compact disk read-only memory (CD-ROM)
Disk that can hold approximately 700 megabytes of
data accessible by a computer.

Compact disk-recordable (CD-R)
Compact disk that can be used once for recording.

Compact disk-rewritable (CD-RW)
Compact disk that can be recorded onto many
times.

Compatibility
The ability to work with each other or other devices
or systems; for example, software that works with a
computer.

Competency
A statement or description of goals, skills, or
behaviors to be achieved.

Compliance
Conforming or performing in an acceptable manner;
correctly following the rules.

Comprehensive Health Enhancement Support
System (CHESS)

A computer-based system designed to help
underserved breast cancer patients manage their
disease.

Computational biology
The action complement of bioinformatics and,
therefore, biomedicine; it is the actual process of
analyzing and interpreting data.

Computer
A machine that stores and executes programs; a
machine with peripheral hardware and software to
carry out selected programming.

Computer-aided software engineering (CASE)
Systematic application of computer software tools
and techniques to facilitate engineering practice.

Computer-assisted instruction (CAI)
Any instruction that is aided by the use of a
computer.

Computer-based
That which uses the computer to interact; the
computer is the base tool.

Computer-based information systems
Combinations of hardware, software, and
telecommunications networks that people build and
use to collect, create, and distribute useful data,
typically in organizational settings.

Computer science

Branch of engineering (application of science) that
studies the theoretical foundations of information
and computation and their implementation and
application in computer systems. The study of
storage/memory, conversion and transformation,
and transfer or transmission of information in
machines— that is, computers—through both
algorithms and practical implementation problems.
Algorithms are detailed, unambiguous action
sequences in the design, efficiency, and application
of computer systems, whereas practical
implementation problems deal with the software
and hardware.

Computerized physician (provider) order entry
systems

Systems that automate the way that orders have
traditionally been initiated for patients. Clinicians
place orders within these systems instead of using
traditional handwritten transcription onto paper.
These systems provide major safeguards by
ensuring that physician orders are legible and
complete, thereby providing a level of patient safety
that was historically missing with paper-based
orders. They provide decision support and
automated alert functionality that was previously
unavailable with paper-based orders.

Computerized provider order entry (CPOE)
An electronic process or system that automates the
way that orders have traditionally been initiated for

patients. It allows a healthcare provider to enter
orders electronically and to also manage the results
of those orders.

Conceptual framework
Framework used in research to chart feasible
courses of action or to present a desired approach
to a study or analysis; built from a set of concepts
that are related to a proposed or existing system of
methods, behaviors, functions, relationships, and
objects. A relational model. A formal way of thinking
or conceptualizing about a phenomenon, process,
or system under study.

Conferencing software
Electronic communications system or software that
supports and facilitates two or more people meeting
for discussion. High-end systems offer telepresence
(a lifelike experience allowing people to feel as if
they were present in person—it would be as though
the nurse were physically there with the patient—so
people can work, learn, and play in person over the
Internet or have an effect at a remote location).

Confidentiality
The mandate that all personal information be
safeguarded by ensuring that access is limited to
only those who are authorized to view that
information.

Connectionism
A component of cognitive science that uses

computer modeling through artificial neural
networks to try to explain human intellectual
abilities.

Connectivity
Ability to hook up to the electronic resources
necessary to meet the user’s needs. The ability to
use computer networks to link to people and
resources. The unbiased transmission or transport
of Internet Protocol packets between two end
points.

Consequences
Outcomes or products resulting from one’s decision
choices.

Consolidated health informatics (CHI)
A collaborative effort to adopt health information
interoperability standards, particularly health
vocabulary and messaging standards, for
implementation in federal government systems.

Consultant
A person hired to provide expert advice, opinions,
and recommendations based on his or her area of
expertise.

Context of care
The setting, services, patient, environment, and
professional and social interactions surrounding the
delivery of patient interventions.

Continuing education

Coursework or training completed after
achievement of a baccalaureate degree, often for
the purpose of recertification.

Continuous learner
Person who gleans lessons or learns from success
as well as failures, or who constantly searches for
information to add to his or her knowledge base.

Copyright
A legal term used by many governments around the
world that gives the inventor or designer of an
original product sole or exclusive rights to that
product for a limited time; the same laws that cover
physical books, artwork, and other creative material
are still applicable in the digital world.

Core business systems
Systems that enhance administrative tasks within
healthcare organizations. Unlike clinical information
systems, whose aim is to provide direct patient
care, these systems support the management of
health care within an organization. They provide the
framework for reimbursement, support of best
practices, quality control, and resource allocation.
There are four common types of core business
systems: (1) admission, discharge, and transfer
(ADT); (2) financial; (3) acuity; and (4) scheduling
systems.

Core sciences
The branches of study and knowledge that form the

foundation of nursing informatics, including nursing,
computer, and information sciences. Some,
including the editors of this text, believe that
cognitive science should also be included in the list
of NI core sciences.

Courage
The strength to face difficulty.

Course management system (CMS)
Software system designed for both faculty and
students that supports educational episodes,
including tools for grading, learner assessment,
content presentation/interaction, and
communication. These systems provide for the
support of learning activities throughout course
delivery; proprietary examples include ANGEL,
Blackboard, WebCT, Learning Space, and
eCollege.

Covered entity
A healthcare provider that conducts certain
transactions in electronic form (a “covered
healthcare provider”), a healthcare clearinghouse,
or a health plan that electronically transmits any
health information in connection with transactions
(billing and payment for services or insurance
coverage) for which the U.S. Department of Health
and Human Services has adopted standards;
identified in the Administrative Simplification
regulations.

Creativity software
Programs that support and facilitate innovation and
creativity (an intellectual process relating to the
creation or generation of new ideas, concepts, or
new relationships between currently existing ideas
or concepts); they allow users to focus or
concentrate more on creating new things in today’s
digital age and less on the mechanics or workings
of how they are created or developed.

Crowdsourcing
Information generated by individuals on social
media.

Culture broker
Person who can translate between science and
clinical care and between science and the self-
caring citizen.

Cumulative Index to Nursing and Allied Health
Literature

A comprehensive nursing and allied health literature
database.

Data
Raw facts that lack meaning.

Data-centric
Data are the central focus.

Data dictionary
Software that contains a listing of tables and their
details, including field names, validation settings,

and data types.

Data file
A collection of related records.

Data gatherer
One involved in the direct procurement of raw facts
(data); raw facts (data) collector.

Data mart
Collection of data focusing on a specific topic or
organizational unit or department created to
facilitate management personnel making strategic
business decisions. Could be as small as one
database or larger, such as a compilation of
databases; generally smaller than a data
warehouse.

Data mining
A process of utilizing software to sort through data
so as to discover patterns and ascertain or
establish relationships. This process may help to
discover or uncover previously unidentified
relationships among the data in a database.

Data warehouse
An extremely large database or repository that
stores all of an organization’s or institution’s data
and makes this data available for data mining. A
combination of an institution’s many different
databases that provides management personnel
flexible access to the data.

Database
A collection of related records stored in a computer
system using software that permits a person or
program to query the data so as to extract needed
information; it may consist of one or more related
data files or tables.

Database management system (DBMS)
Software program/s and the hardware used to
create and manage data.

Datasets
Collections of interrelated data.

Debrief
The simulation stage comprised of a student-
centered discussion, during which the participants
and observers reflect on performance during the
scenario and make recommendations for future
practice.

Decision making
Output of cognition; outcome of our intellectual
processing.

Decision support
Recommendations for interventions based on
computerized care protocols. The decision support
recommendations may include such items as
additional screenings, medication interactions, or
drug and dosage monitoring.

Decision support/outcomes manager

Person charged with reviewing the effects of
interventions suggested by the computerized
decision support system.

Decision support system
Computer applications designed to facilitate human
decision-making processes. Usually are rule based,
using a specified knowledge base and a set of rules
to analyze data and information and provide
recommendations to users.

Decision tree
A set of decisions represented in a tree-shaped
pattern; the decisions produce the rules for the
classification of a dataset.

Degradation
Loss of quality; for example, in telecommunications,
it is the loss of quality in the electronic signal.

Desktop
Computer’s interface that resembles the top of a
desk, where the user keeps things he or she wants
to access quickly, such as paper clips, pens, and
paper. On the computer’s desktop, the user can
customize the look and feel to have easy access to
the programs, folders, and files on the hard drive
that the individual uses the most.

Digital divide
The gap between those who have and those who
do not have access to online information.

Digital health record (DHR)
An electronic record of patient assessments that
are collected over time, typically by a telemonitoring
device. For example, daily assessments of weight
and blood pressure can be captured electronically
and graphically displayed to allow for the detection
of subtle trends.

Digital pen
A writing implement that can also digitally capture
handwriting or drawings. This device is battery
operated and generally comes with a universal
serial bus (USB) cradle that permits uploading
captured materials to a desktop, laptop, or palmtop
computer. The user can use it as a ballpoint pen
and write on regular paper just as he or she would
with a normal pen or can capture the output digitally
after writing on digital paper.

Digital video disk/digital versatile disk (DVD)
Optical disk storage format that can generally hold
or store more than six times the amount of data that
a compact disk can.

Digital video disk–recordable (DVD-R)
Disk on which a user can record once.

Digital video disk–recordable and rewritable (DVD-
RW)

Disk on which a user can record many times.

Dimension

A collection of related attributes that provide
information about the data or the context of the
facts. In a multidimensional database, a set of
similar entities is known as a dimension; in a
relational database, each field is considered a
dimension.

Dissemination
A thoughtful, intentional, goal-oriented
communication of specific, useful information or
knowledge.

Distance education
Education provided from a remote location.

Document
To capture and save information for later use.

Documentation
Communication in the form of written or typed text,
audio, video, graphics, photographs, pictures, or
any blending of these means used to describe
some characteristics or elements of an object,
system, or practice. For example, nursing
documentation generates information about a
patient (individual, family, group, community,
populations) that describes the care and/or services
that have been provided and allows for the
communication necessary between nurses and
other healthcare providers.

Domain name

A series of alphanumeric characters that forms part
of the Internet address or URL (e.g., psu.edu
denotes Pennsylvania State University’s address).

Dots per inch (DPI) switch
An actual switch on a computer mouse that allows
you to adjust the mouse’s sensitivity to movement
to result in faster or slower mouse pointer speeds.
Slowing the speed can enhance precision while
speeding it up can facilitate large data transfers.

Double data rate synchronous dynamic random-
access memory (DDR SDRAM)

A chip that allows for greater bandwidth and twice
the transfers per the computer’s internal clock’s unit
of time; one of the transfers occurs at the start of
the new unit of time and the other transfer occurs at
the end of the unit of time.

Drill down
A means of viewing data warehouse information by
going down to lower levels of the database to focus
on information that is pertinent to the user’s needs
at the moment.

Duty
One’s feeling of being bound or obligated to carry
out specific tasks or roles based on one’s rank or
position.

Dynamic random-access memory (DRAM)

Type of RAM chip requiring less space to store the
same amount on a similar static RAM (SRAM) chip;
however, DRAM requires more power than SRAM
because DRAM needs to keep its charge by
constantly refreshing.

Dynamic system development method (DSDM)
An agile software development strategy based on
the rapid application development model, which is
iterative and used in the system development life
cycle and project management.

Dynamic webpage shells
Webpages that can be custom scripted to provide
realistic case scenarios during a simulation
experience.

E-brochure
Electronic brochure. Patient education material that
is typically tied to an agency website and may
include such information as descriptions of
diseases and their management, medication
information, or where to get assistance with a
healthcare issue.

E-health
Healthcare initiatives and practice supported by
electronic or digital media. The most typical use is
for patient and family education where information
is communicated electronically.

E-learning

Electronic learning or learning that is facilitated by
electronic means such as computers and the
Internet. E-learning, online, and Web-based
education has caused a significant shift in student–
teacher relationships in nursing education.

Email
Electronic mail. To compose, send, receive, and
store messages in electronic communication
systems.

Email client
Program that manages email functions.

E-portfolio
Personalized collections of evidence from
coursework, experiences outside of the classroom,
and reflective commentary related to this evidence
that can be shared with others electronically;
categorized electronic presentation of one’s skills,
education, and examples of work and/or career
achievements.

Earcons
Auditory tones that are combined to represent
relationships among data elements, such as the
relationship of systolic blood pressure to diastolic
blood pressure.

Educational Resources Information Center
A comprehensive educational resources database.
An international database of educational literature.

Educator
Sage, leader, and/or guide who assists in the
process or practice of learning.

Edutainment
Learning while having fun; an activity where the
learner is engaged and entertained while they learn;
a combination of “education” and “entertainment.”

eHealth Initiative
Initiative developed to address the growing need for
managing health information and to promote
technology as a means of improving health
information exchange, health literacy, and
healthcare delivery.

Electronic communication
Any exchange of information that is transmitted
electronically.

Electronic data interchange (EDI)
Specific set of standards for exchanging information
between or among computers (computer to
computer).

Electronic health records (EHRs)
Computer-based data warehouses or repositories
of information regarding the health status of a client,
which are replacing the former paper-based
medical records; they are the systematic
documentation of a client’s health status and health
care in a secured digital format, meaning that they

can be processed, stored, transmitted, and
accessed by authorized interdisciplinary
professionals for the purpose of supporting efficient,
high-quality health care across the client’s
healthcare continuum. Also known as electronic
medical records (EMRs).

Electronic mailing list
Automatic mailing list server such as LISTSERV
that sends an e-mail addressed to the list to
everyone who has subscribed to the list
automatically. Similar to an electronic bulletin board
or news forum.

Electronic medical records (EMRs)
See electronic health records (EHRs).

Electronic medication administration record
(eMAR)

A system that uses bar-coding technology in order
to submit and fill prescriptions. Typically, handheld
scanners read bar codes and transmit them to the
pharmacy.

Electronically erasable programmable read-only
memory (EEPROM)

A nonvolatile storage chip used in computers and
other devices to store small amounts of volatile data
(e.g., calibration tables or device configuration).

Embedded devices

Specialized devices that contain an operating
system designed to perform a dedicated function or
special purpose. Smart devices can connect to the
Internet, while dumb devices cannot. Embedded
devices have extensive applications in the
consumer, business, and healthcare marketplaces.
Examples of embedded devices are banking ATMs,
appliances such as dishwashers, security systems,
answering machines, vehicular navigation systems,
portable music players, cable TV boxes, routers,
glucometers, and portable EKG machines.

Emerging technologies
New technologies that are likely to impact health
care in a significant way, such as nanotechnology
or biotechnology.

Empiricism
Knowledge that is derived from our experiences or
senses.

Empowerment
Promotion of self-actualization; achievement of
power or control over one’s own life.

Enactment
The simulation stage in which a student enacts an
assigned role during the established timeframe in a
prepared simulation area.

End users

Target users or consumers of software and
computer technology. Software or computing
applications should be designed for the end user,
the person who will ultimately be using them.

Engage
To capture the attention of the student and motivate
or energize them to actively participate in the
educational activity.

Enterprise integration
Electronically linking healthcare providers, health
plans, government, and other interested parties to
facilitate electronic exchange and use of health
information among all stakeholders.

Entities
See covered entity.

Entity–relationship diagram (ERD)
Diagram that specifies the relationships among the
entities in the database. Sometimes the implied
relationships are apparent based on the entities’
definitions; however, all relationships should be
specified as to how items relate to one another.
There are typically three relationships: one to one,
one to many, and many to many.

Entrepreneur
Person who assumes the risks of beginning an
enterprise or business and accepts responsibility for
organizing and managing the organization.

Enumerative approach
Nursing terminology in which words or phrases are
represented in a list or a simple hierarchy; gives an
explicit and exhaustive listing of all the objects that
fall under the concept or term in question.

Epidemiology
The field of study identifying things that come upon
the people. Incidence, prevalence, and control of
disease. Case finding.

Epistemology
Study of the nature and origin of knowledge; what it
means to know.

Erasable programmable read-only memory
(EPROM)

Type of computer memory chip that retains its data
when its power supply is switched off and can be
erased with ultraviolet light.

Ergonomics
In the United States, this term is used to describe
the physical characteristics of equipment—for
example, the optimal fit of a scissors to a human
hand. In Europe, it is synonymous with human
factors—that is, the interaction of humans with
physical attributes of equipment or the interaction of
humans and the arrangement of equipment in the
work environment.

Ethical decision making

The process of making informed choices about
ethical dilemmas based on a set of standards
differentiating right from wrong. The decision
making reflects an understanding of the principles
and standards of ethical decision making, as well as
philosophical approaches to ethical decision
making. It requires a systematic framework for
addressing the complex and often controversial
moral questions.

Ethical dilemma
A difficult choice or issue that requires the
application of standards or principles to solve.
Issues that challenge us ethically.

Ethical, social, and legal implications
Consideration and understanding of the ethical,
social, or legal connections or aspects of an issue
that relate to a moral question of right and wrong.

Ethicists
Experts in the arbitrary, ambiguous, and
ungrounded judgments of other people. Ethicists
know that they make the best decision they can
based on the situation and stakeholders at hand.

Ethics
A process of systematically examining varying
viewpoints related to moral questions of right and
wrong.

Eudaemonistic

A system of ethical evaluation that involves
consideration of which actions lead to being an
excellent and happy person.

Events
Occurrences that might be significant to other
objects in a system or to external agents; for
example, creating a laboratory request is an
example of a healthcare event in a laboratory
application. An event is defined and could be a
triggering event for the task or workflow; a task or
workflow can have several triggering events.

Evidence
Artifacts, productions, attestations, or other
examples that demonstrate an individual’s
knowledge, skills, or valued attributes.

Evidence-based practice (EBP)
Nursing practice that is informed by research-
generated evidence of best practices.

Exabytes (EB)
Units of measure for computer memory equal to
one quintillion bytes of computer memory.

Executes
Carries out software’s or a program’s instructions.

Exome
The part of the genome formed by exons.

Exome sequencing

The reading of changes in the genes of the genome
to identify mutations relating to a trait or illness.

Exon
A section of a gene that is transcribed into RNA and
translated into protein.

Expert systems
Decision support systems that implement the
knowledge of one or more human experts.

Exploratory data analysis (EDA)
Approach or philosophy that uses mainly graphical
techniques to gain insight into a dataset. It identifies
the most important variables. Conducted during the
exploratory phase, EDA provides guidance into the
complexity or general nature of the various models
that should be considered for implementation during
pattern discovery.

Extensibility
System design feature that allows for future
expansion without the need for changes to the
basic infrastructure.

Extensible Markup Language (XML)
Computer language that began as a simplified
subset of Standard Generalized Markup Language
(SGML). Its major purpose is to facilitate the
exchange of structured data across different
information systems, especially via the Internet.
XML is considered an extensible language because

it permits its users to define their own elements,
allowing customization to enable purpose-specific
development.

Face-to-face
Most widely used teaching method among nurse
educators, where the teacher and the learners meet
together in one location at the same time.

Failure modes and effects analysis (FMEA)
A systematic evaluation of a process to determine
how and why it failed to produce the desired results.

Fair use
Doctrine that permits the limited use of original
works without the copyright holder’s permission; an
example would be quoting or citing an author in a
scholarly manuscript.

Federal Health Information Exchange (FHIE)
A federal information technology healthcare
initiative that enables the secure electronic one-way
exchange of patient medical information from the
Department of Defense’s legacy health information
system, the Composite Health Care System
(CHCS), for all separated service members to the
Veterans Affairs’ (VA) VistA Computerized Patient
Record System (CPRS). The point of care in
veterans affairs.

Feedback

Input in the form of opinions about or reactions to
something such as shared knowledge. In an
information system, feedback refers to information
from the system that is used to make modifications
in the input, processing actions, or outputs.

Fidelity
The extent to which a simulation mimics the
processes of a real environment; in the context of
ethics, the right to what has been promised.

Fields
Columns or attributes of an entity in a database.

Field study
Study in which end users evaluate a prototype in
the actual work setting prior to its general release.
Also called field test, alpha test, or beta test.

Financial systems
Systems used to manage the expenses and
revenues accrued while providing health care. The
finance, auditing, and accounting departments
within an organization most commonly use financial
systems. These systems determine the direction for
maintenance and growth for a given facility.
Financial systems often interface to share
information with materials management, staffing,
and billing systems to balance the financial impact
of these resources within an organization. These
systems report the fiscal outcomes so that these
outcomes can be tracked against the organizational

goals of an institution. Financial systems are one of
the major decision-making factors as healthcare
institutions prepare their fiscal budgets. They often
play a pivotal role in determining the strategic
direction for an organization.

Firewall
A tool commonly used by organizations to protect
their corporate networks when they are attached to
the Internet. A firewall can be either hardware or
software, or a combination of the two. It examines
all incoming messages or traffic to the network. The
firewall can be set up to allow only messages from
known senders into the corporate network; it can
also be set up to look at outgoing information from
the corporate network.

FireWire
Apple Computer’s version of a high-performance
serial bus used to connect devices to a computer.

Firmware
Hardware and software programs or data written
onto ROM, PROM, and EPROM.

Flash drives
Small, removable storage devices.

Flash memory
Special type of EEPROM that can be erased and
reprogrammed in blocks instead of one byte at a
time. Many modern PCs have their BIOS stored on

a flash memory chip so that it can easily be updated
if necessary.

Folksonomies
Organization and classification of online content by
users; derived from “folk” and “taxonomy.” Users
tag information with key words to make it easier to
index and search vast amounts of information.

Foundation of Knowledge model
Model proposing that humans are organic
information systems constantly acquiring,
processing, generating, and disseminating
information or knowledge in both their professional
and personal lives. The organizing framework of
this text.

Futurologist
Guru who is a forward thinker and looks to the
future.

Game
A structured activity undertaken for enjoyment.

Game mechanics
The rules, instructions, directions, and constructs
that the player or learner interacts with while playing
the game. It is imperative that the rules are clearly
stated in the instructions or directions so the player
knows what is expected of them and the game itself
has rules that it too must obey. The mechanics
determine how the players or learners interact with

the rules and how the game responds to the
player’s or learner’s moves or behaviors within the
game, thus connecting the player’s or learner’s
actions to the purpose of the game.

Gameplay
How the player or learner interacts with or plays the
game.

Genome
A body of genes. Hans Winkler is credited with
merging “genesis” and “soma” (genome) to create
this term.

Genomic data commons (GDC)
The data-sharing platform promoting precision
medicine in oncology.

Genomics
The study of the genome.

Gigabyte (GB)
Unit of measure used to express bytes of data
storage and capability in computer systems; 1
gigabyte equals 1,000 megabytes.

Gigahertz
Unit of measure used to express speed and power
of some components such as the microprocessor; 1
gigahertz equals 1,000 megahertz.

Good
Favorable outcome in ethics.

Google Glass
A wearable computer from Google that can take
pictures, play video, and display text messages
without anyone else knowing. Currently, it costs
approximately $1,500.

Government Accountability Office (GAO)
The highest audit institution of the federal
government that provides auditing, evaluation, and
investigative services for the U.S. Congress.

Gramm-Leach-Bliley Act
Federal legislation in the United States that controls
how financial institutions handle the private
information they collect from individuals.

Graphical user interface (GUI)
(pronounced “gooey”) Software that provides a
user-friendly desktop metaphor interface that is
made up of the input and output devices as well as
icons that represent files, programs, actions, and
processes.

Graphics card
A board that plugs into a personal computer to give
it display capabilities.

Gray gap
A term used to reflect the age disparities in
computer connectivity; there are fewer persons
older than age 65 who use computer technology
than members of younger age groups.

Gulf of evaluation
The gap between knowing one’s intention (goal)
and knowing the effects of one’s actions.

Gulf of execution
The gap between knowing what one wants to have
happen (the goal) and knowing what to do to bring it
about (the means to achieve the goal).

Hackers
Computer-savvy individuals most commonly
thought of as malicious people who hack, or break,
through security to steal or alter data and
information; can also be any of a group of computer
aficionados who band together in clubs and
organizations or who use their skills as a hobby.

Half-life of knowledge
The time span from when knowledge is gained to
when it becomes obsolete.

Handheld devices
Computers that are small enough to be used while
holding in one’s hand or easily carried in a pocket;
synonymous with PDA (personal digital assistant).

Haplotypes
Sets of closely linked alleles on a chromosome that
tends to be inherited together.

HapMap
Describes the common patterns of human DNA
sequence variation and is expected to be a key

resource for researchers to use to find genes
affecting health, disease, and responses to drugs
and environmental factors.

Haptic
Sense of touch; The science of applying tactile
sensation or touch to human-computer interactions
allowing for users to use special input/output
devices such as joysticks, data gloves, etc. to feel
or sense and manipulate or control a virtual, three-
dimensional object’s attributes of texture, shape,
surface, temperature, and/or weight.

Hard disk
Magnetic disk that stores electronic data.

Hard drive
Permanent data storage area that holds the data,
information, documents, and programs saved on
the computer, even when the computer is shut off.
The actual physical body of the computer and its
components.

Hardware
Physical or tangible parts of the computer.
Computer parts that one can touch and that are
involved in the performance or function of the
computer, such as the keyboard and monitor.

Harm
Physical or mental injury or damage. Unfavorable
outcome in ethics.

Health disparities
The health status differences between different
groups of people, especially minorities and
nonminorities; the gaps between the health status
of minorities and nonminorities in the United States
are ongoing even with the advances in technology
and healthcare practices.

Health information exchange (HIE)
Organization that prepares and organizes people
and resources to manage healthcare information
electronically across organizations within a
community or region.

Health Information Portability and Accountability
Act (HIPAA)

Law signed by President Bill Clinton in 1996
addressing the need for standards to regulate and
safeguard health information and making provisions
for health insurance coverage for employed
persons who change jobs.

Health information technology (HIT)
Hardware, software, integrated technologies or
related licenses, intellectual property, upgrades, or
packaged solutions sold as services that are
designed for or support the use by healthcare
entities or patients for the electronic creation,
maintenance, access, or exchange of health
information.

Health Information Technology for Economic and

Clinical Health (HITECH) Act
Title XIII of the American Recovery and
Reinvestment Act, which was enacted in February
2009. Under this act, healthcare organizations can
qualify for financial incentives based on the level of
meaningful use achieved; the HITECH Act
specifically incentivizes health organizations and
providers to become “meaningful users.”

Health Level 7
An accredited standards-developing organization
that is committed to developing standard
terminologies for information technology that
support interoperability of healthcare information
management systems.

Health literacy
The acquisition of knowledge that promotes the
ability to understand and to manage one’s health.

Health management information system (HMIS)
An information system that is specially intended to
support and help with the planning, resource
allocation, and management of health programming
to make healthcare more effective and efficient; an
information system that plans and manages health
programs, rather than the actual delivery of health
care.

Healthcare-associated infections
Infections that patients acquire while being treated
in a healthcare facility.

Healthcare information
Information that is related to health and well-being
of a person, especially information related to
therapeutic (care) interactions between people and
healthcare providers.

Healthcare provider
A qualified person delivering appropriate health
care professionally to an individual, group, family,
community, or population in need of healthcare
services; includes hospitals, skilled nursing
facilities, nursing homes, long-term care facilities,
home health agencies, hemodialysis centers,
clinics, community mental health centers,
ambulatory surgery centers, group practices,
pharmacies and pharmacists, laboratories,
physicians, and therapists.

HealthVault
Microsoft’s online personal health record system.

Heuristic evaluation
An evaluation in which a small number of
evaluators (often experts in relevant fields such as
human factors or cognitive engineering) evaluate
the degree to which an interface design complies
with recognized usability principles (the
“heuristics”).

High-definition multimedia interface (HDMI)

An adapter that has expanded connectivity and
transfer. HDMI is replacing analog video standards
as an audio/video interface that can transfer
compressed and uncompressed video and digital
audio data from any device that is HDMI compliant
to compatible monitors, televisions, video
projectors, and audio devices.

High-fidelity
A high level of realism generated by the equipment
used in simulations.

High-hazard drugs
Drugs known to cause significant adverse side
effects when administered inappropriately; drugs
subject to frequent administration errors.

Home health agency (HHA)
Organization that delivers part-time and intermittent
skilled services, including nursing and other
therapeutic services, in the patient’s home.

Home health care
An alternative site for healthcare services typically
focusing on post–hospital discharge patient needs.

Home telehealth care
Home healthcare clinical and educational services
provided via telecommunications-ready tools.

HONcode
One of the two most common symbols that power
users look for to identify trusted health sites.

Hospital information system (HIS)
An information system intended to manage the
clinical, financial, and administrative needs of the
hospital; refers to the paper-based as well as
computer-based information processing that
manages the functional aspects (administrative,
financial, and clinical) of a hospital.

Human factors engineering
Recognizing the limitations of human performance
and developing products to overcome these
limitations.

Human Genome Project (HGP)
A 13-year project designed to identify all of the
20,000–25,000 genes in human DNA; determine
the sequences of 3 billion chemical base pairs in
human DNA; create databases to store this
information; and address the resultant ethical, legal,
and social issues.

Human Mental Work Load (HMWL)
Mental processing or cognitive demands placed on
a person when he or she is interacting with
technology.

Human–computer interactions
How people use and interact with computers; the
study of how people use computers and software
applications and the ways that computers influence
people.

Human–computer interface
The hardware and software through which the user
interacts with the computer.

Human–technology interaction (HTI)
How users interact with technology. The study of
that interaction.

Human–technology interface
The hardware and software through which the user
interacts with any technology (e.g., computers,
patient monitors, telephone).

Hybrid
A descriptor for individual courses in which
instruction is delivered using multiple formats such
as online, face to face, print based, or audio or
videoconference (e.g., PicTel).

Hypertext
Clickable words that allow users to access another
document at a remote location.

Indiana Health Information Exchange
A collaborative effort among institutions in Indiana
to provide high-quality patient care and enhance the
safety and efficiency of health care.

Industrial Age
Late 18th and early 19th centuries, when major
changes occurred in manufacturing, farming, and
transportation; inventions and innovations led these
changes.

Informaticists
People with specialized training or certification in
informatics; specialists in using technology to
manage health data and information.

Informatics
A field that integrates a specialty’s science,
computer science, cognitive science, and
information science to manage and communicate
data, information, knowledge, and wisdom in a
specialty’s practice.

Informatics innovator
One who makes enhancements or improvements
and creative, novel, and inventive solutions in the
informatics specialty.

Informatics nurse
A nurse with specialized skills, knowledge, and
competencies in informatics. A registered nurse
with an interest or experience working in an
informatics field. A generalist in the field of
informatics in nursing.

Informatics nurse specialist
A registered nurse with formal, graduate education
in the field of informatics or a related field, who is
considered a specialist in the field of nursing
informatics.

Informatics solution
A generic term used to describe the product that an

informatics nurse specialist recommends after
identifying and analyzing an issue. Informatics
solutions may encompass technology and
nontechnology products such as information
systems, new applications, nursing vocabulary, or
informatics curricula.

Information
Data that are interpreted, organized, or structured.
Data processed using knowledge or data made
functional through the application of knowledge.

Information Age
Period at the end of the 20th century, when
information was easily accessible using computers,
networks, and the Internet.

Information literacy
Recognizing when information is needed and
having the ability to locate, evaluate, and effectively
use the needed information. An intellectual
framework for finding, understanding, evaluating,
and using information.

Information mediator
A new nursing role arising out of the need for
technology to support immediate access to up-to-
date knowledge anywhere and anytime.

Information science
The science of information, studying the application
and usage of information and knowledge in

organizations and the interfacings or interaction
between people, organizations, and information
systems. An extensive, interdisciplinary science that
integrates features from cognitive science,
communication science, computer science, library
science, and social sciences.

Information systems
The manual and/or automated components of
system of users or people, recorded data, and
actions used to process the data into information for
a user, group of users, or an organization.

Information technology (IT)
Use of hardware, software, services, and
supporting infrastructure to manage and deliver
information using voice, data, and video, or the use
of technologies from computing, electronics, and
telecommunications to process and distribute
information in digital and other forms. Anything
related to computing technology, such as
networking, hardware, software, the Internet, or the
people who work with these technologies. Many
hospitals have IT departments for managing the
computers, networks, and other technical areas of
the healthcare industry.

Information user
The person who accesses and makes use of
information made available to her/him.

Informatique

French term referring to the computer milieu.

Infrastructure
Structural elements that provide the framework
supporting a system. In the case of information
technology, infrastructure refers to the architecture
of the computer system, its operating system, and
various other systems that are fundamental to its
operation.

Infrastructure as a service (IaaS)
Cloud-based services that provide a rentable
backbone to companies enabling the scalable, on-
demand infrastructure they need to support their
dynamic workloads; the user pays what they use
and they do not have to invest in hardware,
including networks, storage, and data center space.

Input
Data and information entered into a computer
system.

Input devices
Hardware and software used to enter data and
information into a computer.

Input/output system (I/O)
(Pronounced “eye-oh.”) Any program, operation, or
device that transfers data to or from a computer and
to or from a peripheral device.

Instant message (IM)
Form of real-time communication between two or

more people based on typed text conveyed via
computers connected over a network.

Integrated drive electronics (IDE)
Technology where the drive controller is located on
the drive itself instead of being a separate controller
connected to the motherboard of a computer.

Integration
Assimilating or combining to make whole; in
computer terminology, the process through which
different technologies—software and hardware
components—are synchronized and combined to
make a functional and structural system.

Integrity
Quality and accuracy. Employees need to have
confidence that the information they are provided is,
in fact, true. To accomplish this, organizations need
clear policies to clarify how data are actually input,
to determine who has the authorization to change
such data, and to track how and when data are
changed.

Intelligence
Mental ability to think logically, reason, prepare,
ideate, assess alternative solutions to problems,
problem solve by choosing a proposed solution,
think abstractly, comprehend and grasp ideas,
understand and use language, and learn.

Interactions

Interfacing with users commonly using tasks or
notifications.

Interactive technologies
Technologies that promote or support user
communication with other persons (e.g., e-mail) or
technologies that depend on a user response (e.g.,
games).

Interdisciplinary knowledge team
A team composed of members of various
disciplines in a healthcare organization, each of
whom contributes unique knowledge to the team in
problem-solving or management situations.

Interfaces
Mechanisms or systems used by separate things to
interact. For example, if one wants to change a CD
in a CD player, one could use a remote; the human
user is not related to the CD player but can interact
with it using the remote control. Therefore, the
remote control becomes the interface that enables
that person to tell the CD player which CD to play.

International Organization for Standardization (ISO)
An international network supporting collaboration
among the standards-developing agencies of
numerous countries for the development of
consistent standards in a multitude of industries to
support a global economy. ISO is best known in the
technology industries for the ISO 9000 standards.
See International Standards Organization.

International Standards Organization
A nongovernmental group that connects and
bridges the public and private sectors to develop
and publish international standards that assimilate
the latest expert knowledge, with the goal being to
provide practical tools for tracking economic,
environmental, and societal challenges. Also known
as International Organization for Standardization.

Internet
A global system of computer networks whose
connectivity promotes worldwide communications
via computers.

Internet2
A nonprofit consortium that develops and deploys
advanced network applications and technologies,
for education and high-speed data transfer
purposes. Led by 212 universities, it is also known
as University Corporation for Advanced Internet
Development.

Internet browser
Software used to locate and display webpages.
Also known as web browser or browser.

Internet of Things (IoT)
Electronic devices that connect with each other to
provide real-time data and interpretation of data
without human intervention

Interoperability

Ability of various systems and organizations to work
together to exchange information.

Intranet
A computer network that is contained within an
enterprise and that has restricted access; it has the
look and feel of the Internet and often provides links
to the Internet. The purpose of an intranet varies
but can include provision of employee and
departmental directories, policies and procedures,
internal and external resources, schedules, and
updates on programs and business. The benefits
are browsing capabilities and the ability to maintain
contact information and phone numbers in a central
location, with easy dissemination.

Introns
The sections of a gene that are transcribed but are
removed before being translated into protein.

Intrusion detection devices
Both hardware and software that allow an
organization to monitor who is using its network and
which files that user has accessed.

Intrusion detection system
Method of security that uses both hardware and
software detection devices as a system that can be
set up to monitor a single computer or an entire
network. Corporations must diligently monitor for
unauthorized access of their networks.

Intuition
A way of acquiring knowledge that cannot be
obtained by inference, deduction, observation,
reason, analysis, or experience.

Iowa model
A model that facilitates the translation of research
evidence into clinical practice. Also known as the
Iowa model of evidence-based practice.

iPod
The name given to a family of portable MP3 players
from Apple Computer.

IPS LCD (in-plane switching liquid crystal display)
Smartphone display using polarized light passing
through a color filter and all of the pixels are backlit.
The liquid crystals control the brightness and which
pixels are on or off. With the active matrix, you have
crisp, vivid colors and darker blacks.

Iteration
Replication and refinement of a method until it
meets a goal or provides the desired result; each
repetition is referred to as an iteration.

Jump drives
Small, removable storage devices.

Just culture
An atmosphere of trust. In a just culture, everyone
understands what is acceptable and unacceptable

behavior and they are urged and rewarded for
supplying vital safety-related information.

Justice
Fairness. Treatment of everyone in the same way.

Key field
Within each database record, one of the fields
identified as the primary key. It contains a code,
name, number, or other bit of information that acts
as a unique identifier for that record. In a healthcare
system, for example, a patient is assigned a patient
number or ID that is unique for that patient.

Keyboard
Set of keys resembling an actual typewriter that
permits the user to input data into a computer.

Know–do gap
Situation that exists because solutions to global
health problems are available but are not
implemented in a timely fashion because of the lack
of access to important health information. The
Internet connections in developing countries are
widely scattered, for example, and may not be
efficient or sufficient for viewing healthcare
information.

Knowledge
The awareness and understanding of a set of
information and ways that information can be made
useful to support a specific task or arrive at a

decision; abounds with others’ thoughts and
information. Information that is synthesized so that
relationships are identified and formalized.
Understanding that comes through a process of
interaction or experience with the world around us.
Information that has judgment applied to it or
meaning extracted from it. Processed information
that helps to clarify or explain some portion of our
environment or world that we can use as a basis for
action or upon which we can act. Internal process of
thinking or cognition. External process of testing,
senses, observation, and interacting.

Knowledge acquisition
The act of getting knowledge.

Knowledge brokers
People who know where to find information and
knowledge. They generate some knowledge but are
mainly known for their ability to find what is needed.
More experienced nurses and nursing students
become knowledge brokers out of necessity—
needing to know.

Knowledge builder
Person who examines, interprets, and compares
clinical data and trends with an eye toward
improving clinical practice based on the available
evidence.

Knowledge-centric
Knowledge is the central focus.

Knowledge consumers
Users of knowledge who do not have the expertise
to provide the knowledge they need for themselves.

Knowledge dissemination
Distribution and sharing of knowledge.

Knowledge domain process (KDP) model
Model that represents knowledge construction and
dissemination in an organization.

Knowledge exchange
The product of collaboration when sharing an
understanding of information promotes learning to
make better decisions in the future.

Knowledge generation
The creation of new knowledge by changing and
evolving knowledge based on one’s experience,
education, and input from others.

Knowledge generators
Nursing researchers and nursing experts—the
people who know; they are able to answer
questions, craft theories, find solutions to nursing
problems or concerns, and innovate practice.

Knowledge management systems (KMSs)
Repositories of information that contain the latest
collective expertise based on experience and
research. The knowledge is typically stored in a

computerized system that promotes easy access
for use.

Knowledge processing
The activity or process of gathering or collecting,
perceiving, analyzing, synthesizing, saving or
storing, manipulating, conveying, and transmitting
knowledge.

Knowledge repositories
Collections of information made available to an
organization’s workers to support and inform their
work.

Knowledge user
Individual or group who benefits from valuable,
viable knowledge.

Knowledge workers
Those who work with information and generate
information and knowledge as a product.

Lab-on-a-chip device
A nanotechnology device designed to perform blood
analyses.

Laboratory information systems
Systems that report on blood, body fluid, and tissue
samples along with biological specimens that are
collected at the bedside and received in a central
laboratory. These systems provide clinicians with
reference ranges for tests indicating high, low, or
normal values so that they can make care

decisions. Often the laboratory system provides
result information directing clinicians toward the
next course of action within a treatment regimen.

Laptop
Portable battery-powered computer that the user
can take with him or her. Also known as a
notebook.

Latex-based simulation
Simulation using manikins and/or other training
devices made of latex.

Legacy system
Old computer systems or programs that are not
replaced because the institution does not want to
expend the resources; they can cause problems,
especially in interfacing with newer systems.

Liberty
The independence from controlling influences.

Library science
An interdisciplinary science that integrates law,
applied science, and the humanities to study issues
and topics related to libraries (collection,
organization, preservation, archiving, and
dissemination of information resources).

Local area network (LAN)
Organizationally based network; joined together
locally.

Logic
A system of thinking that uses principles of
inference and reasoned ideas to govern action.

Logical Observation Identifiers Names and Codes
(TLOINC)

A database, universal standards, structured names,
and coding system for identifying medical laboratory
tests, measurements, and observations. Created
and maintained by the Regenstrief Institute, a U.S.
nonprofit medical research organization.

Long-term care facility
A healthcare institution designed to support the
needs of those who need ongoing care, especially
the aged.

Longevity
Usability beyond the immediate clinical encounter.
Long-term value.

Machine learning
A subset of artificial intelligence that permits
computers to learn either inductively or deductively.
Inductive machine learning is the process of
reasoning and making generalizations or extracting
patterns and rules from huge datasets—that is,
reasoning from a large number of examples to a
general rule. Deductive machine learning moves
from premises that are assumed true to conclusions
that must be true if the premises are true.

Main memory
A computer’s internal memory.

Mainframes
Extremely high-performance computers that are
smaller than a supercomputer, used for high-
volume, processor-intensive computing. Computers
used by some large businesses and/or for scientific
processing purposes.

Malicious code
Software that includes spyware, viruses, worms,
and Trojan horses.

Malicious insiders
Insiders or employees who sabotage or add
malicious code or hacks into systems to cause
damage or to steal data and information.

Malware
Malicious software; an evil, malicious program that
infects a device and is intended to steal information,
take control of, irritate, damage, or destroy data,
information, or the device.

Managed care information systems
Information systems that cross organizational
boundaries so that data can be obtained at any and
all of the patient areas; these information systems
make it possible for nurses and physicians to make
clinical decisions while being mindful of their
financial ramifications.

Mapping
How environmental facts (e.g., the order of light
switches or variables in a physiologic monitoring
display) are accurately depicted by the information
presentation.

Mask
Method that a proxy server uses to protect the
identity of a corporation’s employees while they are
surfing the World Wide Web. The proxy server
keeps track of which employees are using which
masks and directs the traffic appropriately.

Massachusetts Health Data Consortium
A consortium of regional healthcare organizations
that collects data, publishes comparative
information, supports and promotes electronic
standards, educates, and researches.

Massive multiplayer online role-playing games
Games using the Internet to provide a shared,
simultaneous experience for dozens or even
hundreds of players.

Master patient index
A tool that identifies, compares, removes duplicate
entries, combines, and cleans patient records so
that they can be added to a master index; it
provides a comprehensive and single view of a
patient via that person’s record while establishing a
master index of all patients.

Meaningful use
The American Recovery and Reinvestment Act of
2009 specifies three main components of
meaningful use: (1) the use of a certified electronic
health record (EHR) in a meaningful manner, such
as e-prescribing; (2) the use of certified EHR
technology for electronic exchange of health
information to improve quality of health care; and
(3) the use of certified EHR technology to submit
clinical quality and other measures. The criteria for
meaningful use will be staged in three steps. Stage
1 (2011–2012) set the baseline for electronic data
capture and information sharing. Stage 2 (2013)
and Stage 3 (expected to be implemented in 2015)
continue to expand on this baseline and be
developed through future rule making.

Medicaid management information system (MMIS)
An integrated group of procedures and computer
processing operations (subsystems) developed at
the general design level to meet Medicaid’s
principal objectives of control and administrative
costs; service to recipients, providers, and inquiries;
operations of claims control and computer
capabilities; and management reporting for planning
and control.

Medical home/health information exchange
An information technology platform that enables the
seamless exchange of important patient information
among many providers in a healthcare system.

Typically the primary care physician (medical home)
initiates the collection of patient data, coordinates
the care of the patient, and helps to maintain the
accuracy of such data. Other care providers access
the information and add to it as they provide
services to patients.

Medical informatics
A specialty that integrates medical science,
computer science, cognitive science, and
information science to manage and communicate
data, information, knowledge, and wisdom in
medical practice.

Medicare Access and Summary CHIP
Reauthorization Act of 2015 (MACRA)

An act that reformed Medicare payment by making
changes that created a quality payment program
(QPP) to replace the hodgepodge system of
Medicare reporting programs.

Medication management devices
Range of telecommunications-ready medication
devices to remind or otherwise alert patients to
medication compliance needs.

MEDLINE
A database that contains more than 22 million
records, maintained and produced by the National
Library of Medicine.

Megabyte (MB)

Unit of measure used to express the amount of data
storage and capability in computer systems; 1
megabyte equals 1,000 kilobytes.

Megahertz
Unit of measure used to express the speed and
power of some components such as the
microprocessor.

Memory
Data stored in digital format; generally refers to
random-access memory (RAM).

Merit-Based Incentive Payment System (MIPS)
The Reauthorization Act of 2015 (MACRA)
reformed Medicare payments by making changes
that created a quality payment program (QPP) to
replace the hodgepodge system of Medicare
reporting programs. The MACRA QPP has two
paths—Merit-based Payment System (MIPS) or
Alternative Payment Models (APMs)—that will be in
effect through 2021 and beyond. As a consolidation
and refinement of various incentive programs, MIPS
is an important program, but it neither aspires to nor
will drive change in the value of health care at
anywhere near the levels of change that the
retirement of the baby boomer generation will force
upon Medicare and society.

Meta-analysis
A form of systematic review that uses statistical
methods to combine the results of several research

studies.

Meta-learning
Learning that combines the predictions from several
data mining models with the goal of synthesizing
these predicted classifications to generate a final
best predicted classification; also known as
stacking.

Metadata
Data about data; in data mining, data contained in
the data mining model that describes other data.
For example, metadata would describe the
patterns, trends, and relationships of the mined
data.

Metrics
Measurements or a set of measurements to
quantify performance; they provide understanding
about the performance of a process or function.
Typically, within clinical technology projects, one
identifies and collects specific metrics about the
performance of the technology or metrics that
capture the level of participation or adoption.
Equally important is the need for process
performance metrics. Process metrics are collected
at the initial stage of a project or problem
identification. Current-state metrics are then
benchmarked against internal indicators. When
there are no internal indicators to benchmark
against, a suitable course of action is to benchmark

against an external source, such as a similar
business practice within a different industry.

Microprocessor
Chip that integrates the processor onto one circuit,
incorporating the functions of the computer’s central
processing unit or processor. Microprocessors
continue to evolve in terms of their processing
capacity.

Microsoft Surface
Windows-based tablet computers featuring touch
screens and interactive whiteboards.

Milestones
Predetermined planned occurrences that indicate
the completion or achievement of a deliverable.

Millions of instructions per second (MIPS)
The number of machine instructions that a
computer can execute in one second; in this case,
millions per second.

Mind
The brain’s conscious processing; encompasses
thought processes, memory, imagination and
creativity, emotions, perceptions, and inner drive or
will.

Mobile devices
Handheld computers, such as smartphones or
tablets.

Mobile e-health (mobile health, m-health)
Health-related uses of mobile technologies
including mobile phones (and increasingly, Internet-
enabled, wireless-connected smartphones),
personal digital assistants, tablet computers and
subnotebook microcomputers, remote diagnostic
and monitoring devices, and global positioning
system (GPS)/geographic information system
mapping equipment.

Model of terminology use
A domain content model that is optimized for the
management of particular entities within an
informational and/or operational context.

Modem
Hardware that allows a user to send and receive
information over the phone or cable lines, for
example, with a computer. It enables Internet
connectivity via a telephone line or cable
connection through network adaptors situated
within the computer apparatus.

Monitor
Computer display that allows the user to view text
and graphic images.

Moral dilemmas
Situations for which there is no clear evidence that
one of several alternatives is morally right or wrong.

Moral rights

Ethical privileges.

Morals
Social conventions about right and wrong human
conduct that are socially constructed and tacitly
agreed upon as good or right.

MoSCoW
Must have, Should have, Could have, and Would
have; an approach where a team works with
stakeholders to develop a prioritized requirements
list and a development plan.

Motherboard
A key foundational computer component. All other
components are connected to it in some way (either
via local sockets, attached directly to it, or
connected via cables). The essential structures of
the motherboard include the major chipset, super
I/O chip, BIOS, read-only memory, bus
communications pathways, and a variety of sockets
that allow components to plug into it.

Mouse
A small device that one can roll along or scroll to
control the movement of the pointer or cursor on a
display and click to search for and/or execute
features.

MP3 aggregator
A program that can facilitate the process of finding,
subscribing to, and downloading podcasts. A

commonly known aggregator is Apple Computer’s
iTunes, which is a free program available as a
download from apple.com. Using a program such
as iTunes gives the user the ability to search for
podcasts based on many criteria, including
category, author, or title. iTunes provides access to
audio downloads, which may be either songs or
podcasts.

MPEG-1 Audio Layer-3 (MP3)
Digital or electronic audio programming format.

Multidimensional databases
Databases that combine data from numerous data
sources and are optimized for online analytical
processing applications; they use multidimensional
structures to organize the data, and each data
attribute is considered as a separate dimension.

Multimedia
A computer-based technology that incorporates
traditional forms of communication to create a
seamless and interactive learning environment.

Multispatial
Relating to the need for educators in the age of
technology to account for both physical and virtual
spaces and their relationship to the learning
process.

Multiuser dungeon

A computer program, usually running over the
Internet, that allows multiple users to participate in
virtual-reality role-playing games.

Multiuser shared hack, habitat, holodeck, or
hallucination (MUSH)

A computer program that allows the user to extend
a virtual-reality “world” by adding new rooms,
objects, and features.

NANDA International, Inc. (NANDA-I)
A standardized nursing terminology consisting of a
taxonomy of nursing diagnoses.

Nanotechnology
Microscopic technology on the order of one billionth
of a meter.

National Center for Public Health Informatics
(NCPHI)

Center created in 2005 by the Centers for Disease
Control and Prevention to provide leadership in the
field of public health informatics.

National Guideline Clearinghouse (NGC)
A comprehensive database of clinical practice
guidelines developed as a result of research. The
NGC website allows users to browse for clinical
guidelines, view abstracts and full-text links,
download full-text clinical guidelines to personal
digital assistive devices, obtain technical reports,
and compare guidelines.

National Health and Nutrition Examination Survey
(NHANES)

A survey sponsored by the Centers for Disease
Control and Prevention that combines both
questionnaires and physical examinations to collect
data on the health and nutritional status of adults
and children in the United States.

National Health Information Infrastructure
An initiative intended to improve the effectiveness,
efficiency, and overall quality of health and health
care in the United States. A comprehensive
knowledge-based network of interoperable systems
of clinical, public health, and personal health
information that would improve decision making by
making health information available when and
where it is needed. The set of technologies,
standards, applications, systems, values, and laws
that support all facets of individual health, health
care, and public health. The NHII is voluntary and
not a centralized database of medical records or a
government regulation.

Nationwide Health Information Network (NHIN)
An agency of the U.S. Department of Health and
Human Services charged with the development of a
safe, secure, interoperable health information
infrastructure.

National Healthcare Quality Report (NHQR)

A report that explores the quality of health care in
the United States; it has been issued by the Agency
for Healthcare Research and Quality every year
since 2003.

National Institute of Standards and Technology
A nonregulatory federal agency within the U.S.
Department of Commerce that was founded in
1901; its mission is to promote U.S. innovation and
industrial competitiveness by advancing
measurement science, standards, and technology
in ways that enhance economic security and
improve the quality of life. From automated teller
machines and atomic clocks to mammograms and
semiconductors, innumerable products and
services rely in some way on technology,
measurement, and standards provided by NIST.

National provider identifier (NPI)
A standard 10-position unique identifier (code)
mandated by HIPAA legislation and designed to
replace previous provider identifiers.

Negligence
A departure from the standard of due care—
prudent, reasonable care—toward others, including
intentionally posing risks that are unreasonable as
well as unintentionally, but carelessly, imposing
risks.

Negligent insider
A well-meaning, but careless employee who

unintentionally exposes a network to security
vulnerabilities by ignoring or forgetting about proper
security procedures

Net generation
Students used to surfing the Web and interacting
online.

Networks
Connections of computers that can be local and/or
organizationally based, joined together into a local
area network, on a wider area scope (such as a city
or district) using a metropolitan area network, or
from an even greater distance (e.g., a whole
country or continent or the Internet in general) using
a wide area network configuration.

Network accessibility
The ability of the network to be accessed by the
right user to obtain what that person needs when he
or she needs it.

Network availability
The state in which network information is accessible
when needed.

Network security
The specific precautions taken to ensure that the
integrity of a network is safe from unauthorized
entry and that the data and information stored on
the network are accessible only by authorized
users.

Neural network
A nonlinear predictive model. Such models learn by
training and resembling the structure of biological
neural networks. Neural networks model the neural
behavior of the human brain and are a way to
bridge the gap between computers and humans.

Neuroscience
The study of the nervous system.

Never events
Events that should never occur, such as wrong-site
surgeries and retained surgical objects. While rare,
over 4,000 patients per year have the wrong site
operated on or have retained surgical objects.

New England Health EDI Network
An example of an implementation model for building
regional health information organizations that are
functional, sustainable, and growing while reducing
administrative costs.

Next-Generation Internet
A government project to develop new, faster
technologies to enhance research and
communication.

Nicomachean
An approach to ethical thinking based on the work
of Aristotle.

Nonmaleficence
Doing no harm.

Nonplayer character (NPC)
An individual in a simulation, virtual world, or game
that is controlled by the program, not another
person.

Nonsynchronous
That which is not in real time or does not occur or
exist at the same time, having the same period or
time frame. Occurring anywhere and anytime using
Internet and World Wide Web software tools (e.g.,
course management systems, e-mail, electronic
bulletin boards, webpages) as the principal delivery
mechanisms.

Nursing informatics (NI)
Traditional definition: A specialty that integrates
nursing science, computer science, and information
science to manage and communicate data,
information, knowledge, and wisdom in nursing
practice. Our definition: The synthesis of nursing
science, information science, computer science,
and cognitive science for the purpose of managing,
disseminating, and enhancing healthcare data,
information, knowledge, and wisdom to improve
collaboration and decision making; provide high
quality patient care; and advance the profession of
nursing. NI is the specialty that integrates nursing
science with multiple information management and
analytical sciences to identify, define, manage, and
communicate data, information, knowledge, and

wisdom in nursing practice. NI supports nurses,
consumers, patients, the interprofessional
healthcare team, and other stakeholders in their
decision making in all roles and settings to achieve
desired outcomes. This support is accomplished
through the use of information structures,
information processes, and information technology.

Nursing informatics competencies
A set of essential skills related to informatics
deemed appropriate for various levels of nursing
practice.

Nursing interventions classifications (NIC)
A comprehensive, standardized classification of
interventions that nurses perform. It is research-
based and useful for clinical documentation and
communicating care provided across settings and
integrating data across systems and various
practice settings. These classifications aid in
conducting effectiveness research, measuring
productivity, and evaluating competencies. The NIC
is also used for reimbursement as well as aiding in
designing curriculums.

Nursing knowledge
A body of facts accumulated over time from
experience, education, and research that are used
to make nursing decisions.

Nursing outcomes classifications (NOC)
A comprehensive, standardized classification of

measurable patient outcomes that was developed
for use in all settings and with all patient
populations. Standardized outcomes are used in
information systems and electronic health records
and are critical to the advancement of nursing
knowledge and the practice of nursing education.

Nursing science
The ethical application of knowledge acquired
through education, research, and practice to
provide services and interventions to patients so as
to maintain, enhance, or restore their health; to
advocate for health; and to acquire, process,
generate, and disseminate nursing knowledge to
advance the nursing profession.

Nursing terminology
Body of the terms used in nursing.

Nursing theory
Concepts, propositions, and definitions that
represent a methodical viewpoint and provide a
framework for organizing and standardizing nursing
actions.

Object-oriented multiuser dungeon
Similar to a multiuser dungeon—a computer
program, usually running over the Internet, that
allows multiple users to participate in virtual-reality
role-playing games—but with more advanced
programming features.

Office of Civil Rights
Part of the U.S. Department of Health and Human
Services and responsible for enforcing the Health
Insurance Portability and Accountability Act. It
provides significant information and guidance to
clinicians who must comply with the Privacy and
Security Rules. It has been tracking complaints and
investigating violations since 2003.

Office of the National Coordinator (ONC) for Health
Information Technology

An office within the U.S. Department of Health and
Human Services that was established through the
HITECH Act. The ONC is headed by the national
coordinator, who is responsible for overseeing the
development of a nationwide health information
technology infrastructure that supports the use and
exchange of information.

Office suite
Software that is generally distributed together with a
consistent user interface that is designed for
knowledge workers and clerical personnel. These
software packages can interact with each other to
enhance productivity and ease of use.

Online
Something accomplished while connected to or
using a computer.

Online analytic processing (OLAP)
A fast analysis of shared data stored in a

multidimensional database that allows the user to
easily and selectively extract and view data from
different points of view. OLAP and data mining
complement each other even though they are quite
different.

Online chats
Synchronous interactions with another person
facilitated by an Internet connection technology.

Ontological approach
Theory that considers ontology development
(domain analysis) and its mapping to object models
(specification of infrastructure). Based on
enumerating all concepts used in a domain and in
providing their formal definitions according to
suitable formalisms (usually logic based).

Ontology
Study of that which is compositional in nature and a
partial representation of the entities within a domain
and the relationships that hold between them. An
explicit specification of a conceptualization.

Open Access Initiative
A worldwide movement to make a library of
knowledge available to anyone with Internet
access.

Open source
Computer software where the source code is made
available for use and/or modification without

charge. The developers share code in the hopes
that the software will evolve as others modify and
improve upon the base.

Open source software
Software that enables users to freely copy and
reuse or repurpose the software by providing
access to the source code; free and open use of
software source code.

Open Systems Interconnection (OSI)
A model of standardization for communications in a
network developed to ensure that various programs
would work efficiently with one another.

Operating system (OS)
The most important software on any computer. It is
the very first program to load on computer start-up
and is fundamental for the operation of all other
software as well as the computer’s hardware.

Order entry management
A program that allows a clinician to enter
medication and other care orders directly into a
computer, including orders for laboratory,
microbiology, pathology, radiology, nursing, and
medicine; supply orders; ancillary services; and
consults.

Order entry systems
Systems that automate the way that orders are
initiated for patients. Clinicians place orders within

these systems instead of using traditional
handwritten transcription onto paper. Such systems
provide major safeguards by ensuring that
physician orders are legible and complete, thereby
providing a level of patient safety that was
historically missing with paper-based orders. They
also provide decision support and automated alert
functionality that was previously unavailable with
paper-based orders.

Outcome
Changes, results, and/or impacts from inputting and
processing.

Output
Changes that exit a system and that can activate or
modify processing.

Palm computers
Miniature or small computers that fit in the palm of
the hand.

Parallel port
Interface for connecting an external device that is
capable of receiving more than one bit at a time.

Password
A code established by the user to identify himself or
herself when the user enters the system. Most
organizations today enforce a strong password
policy. Strong password policies include using
combinations of letters, numbers, and special

characters such as plus (+) signs and ampersands
(&). Policies typically include the enforcement of
changing passwords every 30 or 60 days.

Patient care information system (PCIS)
Patient-centered information systems focused on
collecting data and disseminating information
related to direct care. Several of these systems
have become mainstream types of systems used in
health care. The four types of systems most
commonly found in healthcare organizations include
(1) clinical documentation systems, (2) pharmacy
information systems, (3) laboratory information
systems, and (4) radiology information systems.

Patient care support system
System of components that make up each of the
specialty disciplines within health care and their
associated patient care information systems. The
four types of systems most commonly found in
healthcare organizations include (1) clinical
documentation systems, (2) pharmacy information
systems, (3) laboratory information systems, and
(4) radiology information systems.

Patient-centered
Focused on the patient/person (rather than on the
illness/healthcare professional), with patients
becoming active participants in their own healthcare
initiatives. Patients as active participants receive
services designed to meet their individual needs

and preferences, under the guidance and counsel
of their healthcare professionals. Data,
observations, interventions, and outcomes focused
on direct patient care.

Patient-centered care
Care that is responsive to and cognizant of patient
preferences, values, and needs.

Patient informed consent
A document that a patient signs to agree to
treatment. A document that a home healthcare
patient signs to agree to receive telehealthcare
services in addition to conventional home health
care.

Patient outcomes
Measurable effects resulting from best practice
treatment interventions that improve or stabilize the
course of health over time.

Patient support
The total array of tools and software that can be
used to provide information and assistance to help
meet the healthcare needs of consumers.

Payer organization
An organization that contracts with healthcare
agencies and service providers to attempt to
manage healthcare costs.

PEDA
Pre-brief, enactment, debrief, and assessment: the

four major components of simulations; see
individual term definitions.

Perception
The process of acquiring knowledge about the
environment or situation by obtaining, interpreting,
selecting, and organizing sensory information from
seeing, hearing, touching, tasting, and smelling.
Sensory experience foundational to formulating
knowledge.

Performance improvement
Enhancement of performance. A quality indicator.

Performance improvement analyst
Person who analyzes performance improvement
initiatives. Person who is intimately involved in the
design of the system used by nursing.

Peripheral biometric (medical) devices
A variety of telecommunications-ready
measurement devices, such as blood pressure
cuffs and blood glucose meters, that typically use
the household telephone jack to transmit patient
data to a central server location.

Peripheral component interconnection (PCI)
Mechanism for attaching peripheral devices to a
motherboard via computer bus, expansion slots, or
integrated circuits.

Peripheral devices
Devices with a digital readout typically used in

home telehealth and whose output is capable of
being captured by computer. Generally this
equipment is self-administrated by the patient or
family caregiver. Examples of commonly used
peripheral devices include a weight scale, blood
pressure monitor, pulse oximeter, thermometer,
glucometer, spirometer, prothrombin/International
Normalized Ratio meter, digital camera (to capture
images of wounds), and a personal digital
assistant–based or telephonic self-reporting device.

Personal computer (PC)
Computer made for individual use or directly used
by an end user.

Personal digital assistant (PDA)
A handheld device, miniature or small computer, or
palmtop that uses a pen for inputting data instead of
a keyboard. Also called a handheld computer. Also
known as personal digital assistive.

Personal emergency response systems
Signaling devices that enable patients to access
emergency and other care needs.

Petabytes (PB)
Units of information or computer storage equal to 1
quadrillion bytes, or 1,000 terabytes.

Pharmacy information systems
Information systems that facilitate the ordering,
managing, and dispensing of medications for a

facility. They also commonly incorporate allergy and
height/weight information for effective medication
management; they streamline the order entry,
dispensing, verification, and authorization process
for medication administration while often interfacing
with clinical documentation and order entry systems
so that clinicians can order and document the
administration of medications and prescriptions to
patients while having the benefits of decision
support alerting and interaction checking.

Phishing
An attempt to steal information by manipulating the
recipient of an e-mail or phone call to provide
passwords or other private information.

Picture archiving and communication system
(PACS)

System that is designed to collect, store, and
distribute medical images such as computed
tomography (CT) scans, magnetic resonance
images, and X-rays; it replaces traditional hard copy
films with digital media that are easy to store,
retrieve, and present to clinicians. This system may
be a stand-alone system, separate from the main
radiology system, or it can be integrated with a
radiology information system and a computer
information system. The benefit of PACSs is their
ability to assist in diagnosis and to store vital patient
care support data.

Platform as a service (PaaS)
Cloud computing service that provides everything
needed to support the cloud application’s building
and delivering lifecycle, enabling users to develop
and launch custom Web applications rapidly to the
cloud.

Plug and play
The ability to add new devices to a computer easily
without having to manually install and reconfigure
the computer to accept the device.

Podcast
A digital media file or collection of related files that
are distributed over the Internet using syndication or
subscription feeds for playback on portable media
players such as MP3 players, laptops, and personal
computers; the subscription relies on RSS feeds.
Online media delivery. Enhanced podcasts contain
slides and pictures; vodcasts contain videos.

Policies
Basic principles that guide behavior and
performance and are enforced. For example, in a
corporation, corporate policy would be enforced by
corporate administration; the U.S. government
enforces public policy.

Population health management
A term adopted by healthcare management
companies to express their goal of achieving
optimal health outcomes at a reasonable cost. The

management process involves data collection and
trend analyses that are used to predict clinical
outcomes in a group of people.

Port
Interface between a computer and other devices or
other computers.

Portability
Ability to be transported easily. For example, users
can easily take handheld computers wherever they
go.

Portable Operating System Interface for UNIX
(POSIX)

A uniform set of standards adopted by the Institute
of Electrical and Electronics Engineers and the
International Standards Organization that define an
interface between programs and operating systems.
The standardization ensures that software can be
easily ported to other POSIX-compliant operating
systems.

Portals
Tools for organizing information from webpages into
simple menus on one’s desktop. Also,
multifunctional telehealthcare platforms for
receiving, retrieving, and/or displaying patients’ vital
signs and other information transmitted from
telecommunications-ready medical devices.

Portfolio

A collection of evidence used to demonstrate
knowledge and skill achievement. A nursing
portfolio provides the opportunity for a student to
document a variety of sometimes unquantifiable
skills, such as creativity, communication, and critical
thinking.

Power supply
A device that supplies electrical energy or power;
the device that provides the electrical energy or
power to the computer. A battery can be a source of
energy or power.

Pre-brief
The simulation stage in which the student receives
the simulation information: goal, educational
outcomes, and related course/program outcomes.
The simulation is explained and focused for the
student. He or she should know how to prepare for
the activity; told what is expected of him or her;
provided with the background necessary to be able
to fully enact his or her role in the activity; and given
specifics about how he or she will be assessed. The
student must also be provided with the timeframe
within which the simulation must be completed.

Precision medicine
An evolving approach for disease treatment and
prevention that considers individual variability in
genes, environment, and lifestyle for each patient.

Presence

The act of being fully there and being fully with
patients; exclusively focusing on patients and their
unique needs.

Presentation
Act of presenting or showing; typically uses
presentation software in a slide show format. The
most commonly used presentation software in the
United States is Microsoft PowerPoint.

Primary key
A field within a record (also known as the key field)
that contains a code, name, number, or other bit of
information that acts as a unique identifier for that
record. In a healthcare system, for example, a
patient is assigned a patient number or ID that is
unique for that patient.

Principlism
A foundation for ethical decision making. Principles
are expansive enough to be shared by all rational
individuals, regardless of their background and
individual beliefs.

Privacy
An important issue related to personal information,
about the owner or about other individuals, that
focuses on sharing this information with others
electronically and the mechanisms that restrict
access to this personal information.

Private cloud

Cloud space operated for a single organization with
the infrastructure being managed and/or hosted
internally or outsourced to a third party; it provides
added control and avoids multi-tenancy.

Problem-based
Typically refers to a type of student-centered
instructional strategy where students collaboratively
solve problems and reflect on their experiences.

Problem solving
Cognitive process of critically thinking through a
problem or issue to determine a course of action.

Process analysis
Breaking down the work process into a sequential
series of steps that can be examined and assessed
to improve effectiveness and efficiency; explains
how work takes place, gets done, or how it can be
done.

Process map
A visual depiction of the output of workflow analysis
process.

Process owners
Those persons who directly engage in the workflow
to be analyzed and redesigned and have the
ultimate responsibility for the performance of the
process. These individuals can speak about the
intricacy of the process, including process
variations from the normal. When constructing a

team, it is important to include individuals who are
able to contribute information about the exact
current-state workflow and offer suggestions for
future-state improvements.

Processing
Acting on something by taking it through
established procedures so as to convert it from one
form to another. Examples include the processing of
information into data and the processing of a credit
application to get a loan.

Processor
Newer term for central processing unit (CPU); the
component that executes computer programs,
thought of as the brain controlling the functioning of
the computer; the computer component that
actually executes, calculates, and processes the
binary computer code instigated by the operating
system and other applications on the computer. It
serves as the command center that directs the
actions of all other components of the computer and
manages both incoming and outgoing data.

Product developer
One who designs, creates, and builds a product,
such as a computer program, network, and/or
system. One who employs productivity software to
create a product.

Productivity software
Programs or software that help us compose, create,

or develop. An example is the Microsoft Office suite
of productivity tools, which offers word processing,
spreadsheet, database, presentation, and Web
tools to help us complete both professional and
personal tasks.

Professional development
Acquisition of skills required for maintaining a
specific career path or general skills offered through
continuing education, including the more general
skills area of personal development. It can be seen
as training to keep current with changing
technology and practices in a profession or as part
of the concept of lifelong learning.

Professional networking
Connecting with other professionals in a field with a
predetermined and focused purpose as well as an
identified target audience in mind.

Programmable read-only memory (PROM)
Form of digital memory where the setting of each bit
is locked on a chip by a fuse or antifuse. PROM is
used to store programs permanently, so it is useful
in applications where the programming needs to be
permanent. The device cannot be erased, so it
must be replaced if changes are deemed necessary
in the system.

Project manager
Person responsible for the success of a project,
who manages the planning and enactment of the

project.

Protected health information
Any and all information about a person’s health that
is tied to any type of personal identification.

Prototype
Original mockup or first model; original form that is
studied, tested, and processed before duplication.

Proxy server
Hardware security tool to help protect an
organization against security breaches.

Psychology
The field that studies the mind and behavior.

PsycINFO
A comprehensive database in the field of education
and psychology.

Public cloud
Cloud space owned and operated by companies
offering public access to computing resources. It is
believed to be more affordable and economically
sound than private clouds because the user does
not need to purchase or maintain the hardware,
software, or supporting infrastructure, as these are
managed and owned by the cloud provider.

Public health
The science of protecting the well-being of
communities and the population through education,

research, intervention, and prevention.

Public health informatics (PHI)
An aspect of informatics focused on the promotion
of health and disease prevention in populations and
communities.

Public health interventions
Actions taken to promote and secure the well-being
of a population or a community.

Publishing
The process of production and dissemination of
information.

Qualified Clinical Data Registries (QCDRs)
Introduced for the Physician Quality Reporting
System (PQRS) beginning in 2014, a QCDR will
complete the collection and submission of PQRS
quality measures data on behalf of individual
eligible professionals (EPs) and PQRS group
practices. For 2016, a QCDR is a Centers for
Medicare and Medicaid Services–approved entity
that collects medical and/or clinical data for the
purpose of patient and disease tracking to foster
improvement in the quality of care provided to
patients.

Qualified electronic health record
An electronic record containing health-related
information on an individual, which consists of the
individual’s demographic and clinical health

information, including medical history and a list of
health problems, and supports entry of physician
orders. A qualified electronic health record can
capture and query information relevant to
healthcare quality and exchange electronic health
information with and assimilate such information
from other sources to provide support for clinical
decision making.

Qualitative studies
Types of research design that focus on the human
experience of a phenomenon using words,
concepts, language, and meanings rather than
numbers to capture the essence of the subject
under study. Subjective studies.

Quality
A level or grade of excellence; relative merit; a
distinct or essential characteristic, attribute, or
property.

Quality assurance (QA)
The systematic process of assessing and testing to
verify that a product or service being developed or
used is meeting its specified requirements; focuses
on discovering and correcting defects before they
become part of the final product.

Quantitative studies
Research that looks at the what, where, and when
to provide understanding of phenomena based on
quantifying data and using statistical measures;

depending on the research, they may ascertain
cause-and-effect relationships. Objective studies.

Quantum bits (qubits)
Three-dimensional arrays of atoms in quantum
states.

Quantum computer
A proposed machine that is not based on the binary
system, but instead performs calculations based on
the behavior of subatomic particles or qubits. It is
estimated that if quantum computing is ever
realized, we will be able to execute millions of
instructions per second (MIPS) due to the qubits
existing in more than one state at a time or having
the ability to simultaneously execute and process.

Quantum computing
Using a quantum computer.

Query
A form of questioning. A request for information; an
example would be a database query.

QWERTY
Name given to the typical computer keyboard
layout, derived from the six letters in the first row
below the numeric or number row.

Radio frequency identification (RFID) chip
An identification chip that stores information for
retrieval.

Radio frequency identifier (RFI)
A reprogrammable chip that communicates with a
reader to aid in identifying an object.

Radiology information system (RIS)
Information system designed to schedule, report,
and store information as it relates to diagnostic
radiology procedures. One common feature found
in most radiology systems is a picture archiving and
communication system (PACS). The benefit of RISs
and PACSs is their ability to assist in diagnosing
complex cases and storing vital patient care support
data.

Random-access memory (RAM)
Volatile, temporary storage system that allows a
computer’s processor to access program codes and
data while working on a task. RAM is lost once the
system is rebooted, shut off, or loses power.

Randomized controlled trial (RCT)
A study design that randomly assigns participants
into an experimental group or a control group. As
the study is conducted, the only expected difference
between the control and experimental groups in an
RCT is the outcome variable being studied.

Ransomware
A specific type of malware or malicious code that
cripples the computer network until a ransom is
paid by the organization whose network was
compromised.

Rapid application development (RAD)
A method using prototyping and reiteration to
develop products faster and of superior quality.

Rapid Syndromic Validation Project
System where local healthcare professionals report
cases such as influenza. Data are analyzed
centrally, and the resulting information is shared
with appropriate local authorities in an attempt to
identify outbreaks early and prevent the spread of
contagious diseases.

Rationalism
An ethical position that contends knowledge is
derived from deductive reasoning and not from the
senses.

RDF site summary
Resource description framework site summary. See
Really simple syndication (RSS).

Read-only memory (ROM)
Essential permanent or semipermanent, nonvolatile
memory that stores saved data and is critical in the
working of the computer’s operating system and
other activities. ROM is primarily stored in the
motherboard but may also be available through the
graphics card, other expansion cards, and
peripherals.

Real environment data
Patient data collected in the home during telehealth

monitoring. These data are typically more reflective
of the true patient situation because they are
collected in the real environment and not the
artificial environment of a healthcare agency.

Real time
Human time; occurs live, with users or learners
interacting at the same time.

Real-time telehealth
Live interactions between two or more clinicians,
usually performed with videoconferencing
equipment.

Really simple syndication (RSS)
A form of web feed used to publish frequently
updated content in podcasts, blog entries, or even
news headlines. Subscribers receive update notices
whenever new content is added or a site is
updated. Also known as RDF site summary (RSS
1.0 and RSS 0.90) and rich site summary (RSS
0.91).

Reasoning
Way of thinking, calculating, interpreting, or
introspectively rethinking or critically thinking
through an issue; reflective thought to analyze or
think through one’s ideas and alternatives.

Records
Rows in a relational database representing
individual patients, for example; also called tuples.

Groups of related fields in a database. Captures
audio and video using specific devices.

Reflective commentary
Narrative comments that focus on why an individual
thinks specific evidence is important, the ways in
which the individual values what he or she has
learned, or why the individual thinks the evidence is
important for his or her profession.

Regional health information exchanges
See regional health information organization.

Regional health information organization (RHIO)
A regional network of healthcare organizations and
providers who exchange information related to the
health of the population. The goal is to work
together without duplication to provide cost-effective
health care and promote community well-being.

Relational database
A database that can store and retrieve data very
rapidly. “Relational” refers to how the data are
stored in the database and how they are organized.

Relational database management system (RDBMS)
A system that manages data using the relational
model. A relational database could link a patient’s
table to a treatment table, for example, by a
common field such as the patient ID number field.

Reporting
The act of using of documents or information

system outputs to convey information to
stakeholders.

Reporting and population health management
The data collection tools to support public and
private reporting requirements, including data
represented in a standardized terminology and
machine-readable format.

Report
Document that contains data or information based
on a query or investigation designed to yield
customized content in relation to a situation and a
user, group of users, or an organization. Designed
to inform, reports may include recommendations or
suggestions based on programming and other
embedded parameters.

Repository
Central place where data are collected, stored, and
maintained. Central location for multiple databases
or files that can be distributed over a network or
directly accessible to the user. Location for files and
databases so that the data can be reused,
analyzed, explored, or repurposed.

Research utilization
The process of moving new understandings
generated in research into practice.

Research validity

A conclusion that can be drawn about the conduct
of research based on an analysis of the research
design and methods (internal validity) and the
applicability of the findings to the general population
(external validity).

Researcher
A person who performs systematic inquiries of a
topic in order to develop knowledge on that topic; a
person who does research.

Resource description framework (RDF)
A structure of consistent semantics adopted by the
World Wide Web Consortium (W3C) to promote
encoding, exchange, and reuse of metadata.

Results management
An approach to evaluating the outcomes of a
process to determine whether that process was
useful or valuable.

Reusability
The extent to which software or other work-related
artifacts can be used in more than one computing
program or software system.

Rights
Privileges; include the right to privacy,
confidentiality, and so on.

Risk assessment
Determination of risk or danger, such as assessing
for risk factors related to heart disease.

Robotics
The design, development, and implementation of
robots or machines to carry out tasks typically
performed by people.

Role playing
Situation that allows students to try on real-life
scenarios by filling either pre-scripted or ad-libbed
roles (e.g., doctor, nurse, patient, clinician) without
the fear or pressure of putting another’s life at risk
while trying to determine the best course of action
or find a solution to a fictitious patient’s health
issue.

Root-cause analysis
Similar to failure modes and events analysis;
analysis to discover why a process is faulty or
produces an undesired result.

Rows
Records in a database; also known as tuples.

Safety culture
An organizational commitment to patient safety and
the prevention of medical errors.

Sarbanes-Oxley Act
Legislation that was put in place to protect
shareholders as well as the public from deceptive
accounting practices in organizations.

Scaffolding

Adding initial support for a task and then gradually
removing that support over time.

Scareware
An e-mail designed to scare the user into believing
that their computer has been infected. The hacker
seeks to gain remote access to the computer to “fix”
it.

Scenario
Mock description of a situation or series of events.

Scheduling systems
Systems designed to track resources within a
facility while managing the frequency and
distribution of those resources. For example,
resource scheduling systems provide information
about operating room utilization, or availability of
intensive care unit beds and regular nursing unit
beds.

Scoring
The data mining process of applying a model to
new data.

Second Life
A proprietary virtual reality tool that allows users to
create virtual communities.

Secure information
Information that is protected from error,
unauthorized access, and other threats that can
compromise its integrity and safety.

Security
Protection from danger or loss. In informatics, one
must protect against unauthorized access,
malicious damage, and incidental and accidental
damage and enforce secure behavior and maintain
security of computing, data, applications,
information, and networks.

Security breaches
Any security violations.

Self-control
Self-discipline. Strength of will.

Sensor and activity monitoring systems
Systems for tracking activities of daily living of
seniors and other at-risk individuals in their places
of residence. For example, applications use
sensors to detect anomalies or problems such as
faucets and stoves left turned on.

Serial port
An interface for connecting an external device that
is capable of receiving only one bit at a time, such
as a mouse, a modem, and some printers.

Serious game
A game that has as its main purpose something
other than entertainment; for example, an
educational game, designed for learning, that is a
subset of both education and fun.

Server
A computer or a group of computers that link
computers together or provide services to a group
of computers.

Shoulder surfing
Watching over someone’s back as he or she is
working on a computer. This is still a major way that
confidentiality is compromised.

Simulated documentation
A replicated documentation system that nursing
students can use to learn how to access electronic
health records and document nursing care.

Simulation scenario
A case or situation developed in a simulation setting
to mimic an actual practice situation.

Simulations
Imitations of real-life events or circumstances; in
nursing education, replications of clinical scenarios
developed to provide an opportunity for practice in a
mock situation. Simulations can be web-based,
latex-based, or virtual in a virtual world.

Simulator
A mechanical or electronic device that provides an
environment in which a simulation can occur. Some
of these may be quite large.

Situational awareness
The ability to detect, integrate, and understand

critical information that leads to an overall
understanding of a problem or situation.

Six Sigma/Lean
Business management tactic that seeks to improve
the quality of process outputs by identifying and
removing the causes of imperfections (errors) and
reducing inconsistency and variability in processes;
Lean and Six Sigma are a complementary
combination of activities that focus on doing the
right steps and actions (Lean) and doing them right
the first time (Six Sigma).

Small Computer System Interface (SCSI)
Set of standards for physically connecting and
transferring data between computers and peripheral
devices. The SCSI standards define commands,
protocols, and electrical and optical interfaces.
Standardization among commercial products helps
to ensure that devices will interface with many
different systems.

Smart pump
Machine used to infuse medication that includes
dose-checking technology and safeguards
designed to help avert medication errors.

Smart rooms
Patient rooms that are equipped with technologies
to increase patient safety and improve patient care.

Smartphone

A cell phone that has limited personal digital
assistant capabilities. Smartphones have limited
personal computer functionality; they have an
operating system and facilitate the use of e-mail
and other applications.

SNOMED CT
One of a suite of designated standards for use in
U.S. Federal Government systems for the electronic
exchange of clinical health information; a required
standard in interoperability specifications of the U.S.
Healthcare Information Technology Standards
Panel. The clinical terminology is owned and
maintained by the International Health Terminology
Standards Development Organisation (IHTSDO), a
not-for-profit association.

Social bookmarking
Saving bookmarks or Internet URLs to a public
website instead of on the user’s private computer.
The purpose is to share and grow the list of
websites related to a specific topic. As users add
bookmarks, they also typically add keyword tags
that aid in search and organization processes.

Social engineering
The manipulation of a relationship based on one’s
position in an organization. For example, someone
attempting to access a network may pretend to be
an employee from the corporate information
technology office, who then simply asks for an

employee’s digital ID and password. Another
example of social engineering is a hacker
impersonating a federal government agent. After
talking an employee into revealing network
information, the hacker basically has an open door
to enter the corporate network.

Social media
Communication tools such as Twitter and Facebook
that promote real-time information exchange.

Social networking
Subscribing to and utilizing Web-based applications
for the purpose of sharing personal information with
others.

Social sciences
Collection of academic/scientific fields or disciplines
concerned with the study of the human aspects of
our world/environment.

Software
Anything that can be stored electronically. Software
is divided into two types: system software (includes
the operating system and other software necessary
for the computer to function) and application
software (allows users to complete specific tasks,
such as word processors, spreadsheet software,
presentation software, database managers, and
media players).

Software as a service (SaaS)

Cloud-based applications with the following
benefits: the ability to quickly start using innovative
or specific business apps that are scalable to your
needs, any connected computer can access the
apps and data, and data are not lost if your hard
drive crashes because the data are stored in the
cloud.

Sound card
A computer expansion card that facilitates the input
and output of audio signals to and from a computer
under control of computer programs. Also known as
an audio card.

Spear phishing
A targeting phishing scheme that takes advantage
of specific information provided in an organization’s
directory, thus allowing for a personalized scam e-
mail.

Spreadsheet
Text and numbers located in cells on a grid and the
software necessary to process formulas and other
computations such as creating graphs and charts.

Spyware
A program that may contain malicious code that
may attack or attempt to “take over” a computer.
Spyware may also be nonmalicious in intent and
monitor the user’s behavior in an attempt to gain
information about the user for targeted advertising.

Stacking
The process of synthesizing the predictions from
several models.

Staff development
The process of providing opportunities for
professional growth and skills development.
Computer information systems are frequently used
to assist with the ongoing education and
development of nursing staff members, as this
medium can embed prompts, information, and
related questions in the nursing documentation
system with a link to an appropriate clinical
protocol.

Stakeholders
Individuals or groups with the responsibility for
completing a project and influencing the overall
design, and those who are most impacted by
success or failure of the system implementation.

Standard Generalized Markup Language (SGML)
Metalanguage; markup language for documents.
Extensible Markup Language (XML) began as a
simplified subset of SGML.

Standardized nursing terminology
A body of terms used in nursing that is in some
ways approved by an appropriate authority or by
general consent.

Standardized plan of care

A plan that presents clinicians with treatment
protocols to maximize their outcomes and support
best practices.

Standards
Benchmarks. Criteria. Rules. Norms. Principles.

Standards-developing organizations
Organizations that create guidelines, standards,
and rules to help healthcare entities collect, store,
manipulate, dispose of, and exchange secure
protected health information.

Static medium
Something that cannot be updated; for example, a
print-based brochure may be outdated almost as
soon as it is printed.

STEM (science, technology, engineering, and math)
A curriculum based on an interdisciplinary and
applied approach to educating students in science,
technology, engineering, and mathematics. STEM
integrates these subjects and learning occurs
through authentic or real-world applications.

Store-and-forward telehealth transmission
An application of telehealth care in which images
and other clinical data are captured and transmitted
to specialist clinicians.

Structured English Query Language (SQL)
(pronounced “sequel”) A database querying
language, rather than a programming language.

SQL is a standard language for accessing and
manipulating databases. It simplifies the process of
retrieving information from a database in a
functional or usable form while facilitating the
reorganization of data within the database.

Suicide prevention community assessment tool
Risk assessment method that addresses general
community information, prevention networks, and
the demographics of the target population as well
as community assets and risk factors.

Summaries
Condensed versions of the original designed to
highlight its major points.

Supercomputers
The fastest computers; designed to run special
applications that require numerous calculations.

Surveillance
The act of watching for trends in health-related data
for early detection of health threats.

Surveillance data system
A networked computer system designed to use
health-related data trends to predict the probability
of an outbreak of a contagious or infectious disease
or to detect morbidity and mortality trends in a
geographic area as a precursor to public health
planning or response.

Synchronous

Real time or occurring at the same time; having the
same period or time frame. Learning anywhere and
anytime in real time using delivery modalities such
as traditional face-to-face, Internet, and World Wide
Web software tools (e.g., course management
systems, chat, e-mail, electronic bulletin boards,
audio– video communication tools).

Synchronous dynamic random-access memory
(SDRAM)

The most common type of dynamic random-access
memory found in personal computers.

Syndromic surveillance
A specialized system of data collection that seeks to
detect trends in the incidence and severity of a
specific disease or health-related syndrome and
plan the public health response.

Synthesis
Combining parts of existing material or ideas into a
new entity or concept.

Systems development life cycle (SDLC)
Stages involved in the life of a system, typically an
information system; a model used in the project
management of a system’s development effort,
spanning from feasibility to its demise.

Systems engineering
An approach where technology manufacturers
partner with organizations to identify risks to patient

safety and promote safe technology integration.

Table
A collection of related records in a database.

Tags/tag clouds
A collection of keywords (tags) that describe the
contents of websites related to a topic of interest,
which are then organized by importance using
differing colors and font sizes and styles (cloud).
Many tag clouds are navigable; that is, the tags are
hyperlinks to webpages.

Task analysis
Analytic technique that focuses on how a task must
be accomplished, including detailed descriptions of
task-related activities, task characteristics and
complexity, and the environmental conditions
required for a person to perform a given task.

Tasks
Actions that are value added and necessary. For
example, some tasks come about because of
workarounds or for other unsubstantiated reasons.
Tasks that are considered non–value added and are
not necessary for the purpose of compliance or
regulatory reasons should be eliminated from the
future-state process.

Technologist
Person skilled in the use of technology.

Technology

Method by which people use knowledge and tools.
Knowledge used to solve problems, control and
adapt to our environment, and extend human
potential. Generally people use technology to refer
to machines or devices such as computers and the
infrastructure that supports them. For example, cell
phones and planes are technologies that are
tangible—one can see and touch them—but cannot
see and touch the vast infrastructures supporting
them, such as the wireless communications
between the device (cell phone) and the cell towers,
and the electronic guidance used by the device
(plane) to navigate the skies.

Telecommunications
Broadcasting or transmitting signals over a distance
from one person to another person or from one
location to another location for the purpose of
communication.

Telehealth
Telecommunication technologies used to deliver
health-related services or to connect patients and
healthcare providers to maximize patients’ health
status. A relatively new term in the medical/nursing
vocabulary, referring to a wide range of health
services that are delivered by telecommunications-
ready tools such as the telephone, videophone, and
computer.

Telehealth care

Health services delivered by telecommunications-
ready tools, usually supervised by a nurse or other
clinician.

Telehealth hardware
Equipment that captures objective vital signs data.
Some systems use interactive self-reporting
devices to capture subjective information on how a
patient feels as well. The values obtained from the
patient are then collected and transmitted by a
communication hub. Peripheral devices used in
home telehealth can include any item with a digital
readout. Generally this equipment is self-
administered by the patient or family caregiver.

Telehealth software
Computer programs designed to collect and
interpret health data gathered remotely via a
telehealth communications system.

Telemedicine
Health services delivered by telecommunications-
ready tools, supervised or directed by a physician.

Telemonitoring
Remote measurement of patients’ vital signs and
other necessary data.

Telenursing
Health services delivered by telecommunications-
ready tools, supervised or directed by a nurse.

Telepathology

Use of telecommunications technology to facilitate
the transmission and transfer of pathology data for
the purposes of diagnosis, education, and research.
Transmission and exchange of image-rich
pathology data between remote locations.

Telephony
Telephone monitoring of patients at their residences
by off-site telenurses.

Teleradiology
Use of telecommunications technology to
electronically transmit and exchange radiographic
patient images with the consultative text or
radiologist reports from one location to another.

TELOS strategy
An approach that provides a clear picture of the
feasibility of a project; TELOS stands for
“technologic and systems, economic, legal,
operational, and schedule feasibility.”

Terabytes (TB)
Units of measurement for data storage capacity.
One terabyte equals 1,024 gigabytes.

Term
At its simplest level, a word or phrase used to
describe something concrete (e.g., leg) or abstract
(e.g., plan).

Terminology
Vocabulary of technical terms used in a particular

field, subject, science, or art; concerned with the
collection, description, processing, and presentation
of terms belonging to specialized areas of usage of
one or more languages; nomenclature.

Thick (fat) client
A computer connected to a network designed
primarily for data processing and not
communications or storage.

Thin client
A computer that conveys input and output from the
user to the server and back, but does no
processing.

Three-dimensional (3D)
A geometric model of the physical universe in which
we live; the three dimensions are typically length,
width, and depth (or height), although any three
directions can be chosen, as long as they do not lie
in the same plane.

Three-dimensional (3D) computer graphics
Graphics that use three-dimensional
representations of geometric data stored in the
computer for the purposes of performing
calculations and rendering images. These images
may be stored for later viewing or displayed in real
time.

Throughput

The amount of work a computer can do in a given
time period; a measure of computer performance
that can be used for system comparison.

Thumb drives
Small, removable storage devices.

TIGER initiative
The work of the Technology Informatics Guiding
Education Reform team. This team of nursing
leaders developed a vision for utilizing information
technology to transform nursing practice.

Touch pad
An alternative to using a mouse. A device that
senses the pressure of the user’s finger along with
the movement of the finger on the touch pad to
control input positioning.

Touch screen
A display used as an input device for interacting
with or relating to the display’s materials or content.
The user can touch or press on the designated
display area to respond, execute, or request
information or output.

Transistor
Solid-state semiconductors that resulted in the
second generation of computers. Digital devices
much smaller and faster than analog computers.

Translational bioinformatics
The development of storage, analytic, and

interpretive methods to optimize the transformation
of increasingly voluminous biomedical and genomic
data into proactive, predictive, preventive, and
participatory information.

Translational informatics
The application of research informatics to
translational research in order to close the gap from
research to the bedside to improve the health of
patients and the community.

Translational research
Research that is conducted with a vision toward
transforming clinical nursing practice (translating
the results into practice).

Transparent
Done without conscious thought.

Transparent technology
Technology that is not visible or recognizable by the
user, therefore allowing the user to focus on the
function or output and not the challenges of the
technology itself.

Transparent wisdom
Applying knowledge in a practical way or translating
knowledge into actions without conscious thought.

Transput
Input and output activities, collectively.

Treatment/payment/operations

The treatment of patients, the payment for services,
or the operations of the entity. Providers and other
covered entities were not originally required to
include in the accounting any disclosures that were
made to facilitate the treatment of patients, the
payment for services, or the operations of the entity
(the “TPO exception”); this exception ended in
January 2011 for providers that recently
implemented electronic health record (EHR)
systems. For those providers with EHR systems
that were implemented before passage of the
HITECH Act, the TPO exception ended in January
2014. It is easy to understand why this exception
ended: Because all providers must implement
comprehensive EHR systems, it will be very easy to
generate an electronic record with an accounting of
anyone who accessed a patient’s record.

Trend
General movement; a line of development. The
process of getting others to emulate one’s actions.

Trending
The process of collecting patient data and analyzing
those data collected over time via telehealth
technology. Trending analysis provides a more
accurate picture of health status than the analysis
of episodic data collected during an agency visit.

Triage

The process of assessing patients who are ill or
injured and determining the need for intervention
based on the severity of the health issue. Some
software programs used in telehealth monitoring
systems provide this function by comparing actual
data with a preset standard and then alerting
clinicians that an intervention is necessary.

Trojan horses
Malicious code, capable of replicating within a
computer, that is hidden in data or a program that
appears to be safe.

Trust-e
One of the two most common symbols that power
users look for to identify trusted health sites.

Truth
Fact. Certainty. Sincere action, character, and
fidelity.

Tuples
Records in a database; also known as rows.

Tutorial
Learning materials available to the learner, who
must then be self-directed to study the specific
topical area presented.

U-healt
See ubiquitous health.

U-nursing

Based on the concept of ubiquitous computing, the
concept that nurses will provide care to anyone,
anytime, anywhere using emerging transparent
(ubiquitous) technologies and devices that support
nursing care and practice.

Ubiquitous
Existing or being everywhere at the same time;
widespread.

Ubiquitous health
The concept of health care that is so present in
one’s daily life that it seems invisible or in the
background. Based on the concept of ubiquitous
computing, wherein technologies become
increasingly invisible as they are incorporated into
everyday use—so much so that they are not even
thought of while being used.

Ubiquity
State of being everywhere at once (or seeming to
be everywhere at once). Presence in many places
especially simultaneously. With changing models of
healthcare delivery, information and knowledge
should be available anywhere.

Uncertainty
Ambiguity. Insecurity. Vagueness.

Universal serial bus (USB)
A means of connecting a myriad of plug-in devices,
such as portable flash drives, digital cameras, MP3

players, graphics tablets, light pens, and so on,
using a plug and play connection without rebooting
the computer.

Unstructured data
Data that are not contained in a database; data
residing in text files, which can represent more than
75% of an organization’s data; data that are not
organized or that lack structure.

Usability
The ease with which people can use an interface to
achieve a particular goal. Issues of human
performance during computer interactions for
specific tasks within a particular context.

USB flash drive
A portable memory device that uses electronically
erasable programmable ROM to provide fast
permanent memory. The USB flash drive is typically
a removable and rewritable device that includes
flash memory and an integrated universal serial bus
(USB) interface. They are portable, due to their
small size; durable; dependable; and obtain their
power from the device they are connected to via the
USB port.

User friendly
Programs and peripherals that make it easy to
interact or use computers. Design of a program to
enhance the ease with which the user can utilize

and maximize the productivity from computer
programs.

User interface
Mechanisms or systems used by users to interact
with programs.

Value
Relative worth of an object or action, such as
aesthetic beauty or ethical value.

Values
Important and lasting beliefs that provide principles
and guidance for behaviors and beliefs.

Veracity
Right to truth.

Video adapter card
A board or card that is inserted or plugged into a
computer to provide display capabilities.

Videopod
A podcast that provides video in addition to audio
functionality; self-contained system with a video
transmitter.

Virtual memory
The use of hard disk space on a temporary basis
when the user is running many programs
simultaneously. This temporary use frees up RAM
to allow programs to run simultaneously and
seamlessly.

Virtual peers
Virtual populations of individuals who are
genetically and behaviorally alike.

Virtual reality
Technology that simulates reality in a virtual
medium.

Virtual simulation
Simulation using a three-dimensional virtual world
or environment resembling the real-world setting
and activities being simulated.

Virtual world
A world that exists in cyberspace where people can
establish avatars, purchase land, and interact with
others. Emerging virtual worlds such as Second Life
are changing the meaning of social networking. It is
a live, online, interactive three-dimensional
environment in which users interact using speech or
text via a personalized avatar. Access requires a
modern computer and Internet connection.

Virtue
A certain ideal toward which we should strive that
provides for the full development of our humanity.
Attitude or character trait that enables us to be and
to act in ways that develop our highest potential;
examples are honesty, courage, compassion,
generosity, fidelity, integrity, fairness, self-control,
and prudence. Like habits, virtues become

characteristics of a person. The virtuous person is
the ethical person.

Virtue ethics
Theory that suggests individuals use power to bring
about human benefit. One must consider the needs
of others and the responsibility to meet those
needs.

Viruses
Malicious codes that attach to an existing program
and execute its harmful script when opened.

Visiting Nurse Association (VNA)
A nonprofit home healthcare agency.

Voice recognition
A type of software that allows the user to input data
or to navigate the Web using voice commands.
Voice interactivity should help to reduce the
disparity associated with those who have limited
keyboard or mousing skills.

Waterfall model
An early systems development life cycle model that
is linear in nature; when one phase ends, you move
onto the next phase and do not go back, unlike in
its modern counterparts that stress iterative
development.

Wearable computing
Devices that a person can don or put on like other
articles of clothing or watches, jewelry, and other

accessories. Wearable devices are being used to
provide remote monitoring of physiologic
parameters in care settings, including patients’ own
homes.

Wearable technology
The study or practice of inventing, designing,
building, or using miniature body-borne
computational and sensory devices. Wearable
computers may be worn under, over, or in clothing,
or may actually be the clothes themselves.

Web 2.0
Developing tools for social networking. The
implications of the social networking technologies
that are major elements of Web 2.0 will have
significant impacts on the amount of information
and knowledge that are generated and the ways in
which they are used.

Web publishing
The design and development of webpages that
include links to digital files that are uploaded to web
servers, thereby making these files accessible to
others via web browsers.

Web quests
Searches of the World Wide Web for information.

Web servers
Multifunctional telehealthcare platforms for
receiving, retrieving, and/or displaying patients’ vital

signs and other information transmitted from
telecommunications-ready medical devices.

Web-based
Originating from the World Wide Web.

Web-based simulation
Simulation using the Internet or Web to resemble
the real-world setting and activities being simulated.

Web-enhanced
That which uses the World Wide Web to enhance
or promote functions or tasks such as effective
learning and skill acquisition.

Webcast
Media distributed over the Internet as a broadcast,
which relies on streaming media technology to
facilitate downloading and participation. Such
broadcasts could be distributed in real time, live, or
recorded for asynchronous interaction.

Webinar
Web-based seminar. Web conferencing that allows
a presenter to share his or her computer
screen/files and collaborate with the audience;
attendance is controlled by an access code.

Weblog
A website that contains the contributions of single or
multiple users about a particular topic or issue.
Similar in nature to a threaded discussion board or
a personal diary, weblogs (also known as blogs)

can provide insight into the perceptions of the
contributors about the topic.

Wetware
Direct body–brain interfaces. A reference to the
human mind or central nervous system when
interfaced with a computer; derived from computer
terminology such as “software” and “hardware.”

Wi-Fi
A wireless technology brand owned by Wi-Fi
Alliance, which is used to improve the
interoperability of wireless networking devices.

Wiki
Server software that allows users to create, edit,
and link webpage content from any web browser.
Server software that supports hyperlinks. The
simplest online database; used to develop
collaborative websites.

Wisdom
Knowledge applied in a practical way or translated
into actions; the use of knowledge and experience
to heighten common sense and insight so as to
exercise sound judgment in practical matters.
Sometimes thought of as the highest form of
common sense, resulting from accumulated
knowledge or erudition (deep, thorough learning) or
enlightenment (education that results in
understanding and the dissemination of
knowledge). Wisdom is the ability to apply valuable

and viable knowledge, experience, understanding,
and insight while being prudent and sensible. It is
focused on our own minds; it is the synthesis of our
experience, insight, understanding, and knowledge.
Wisdom is the appropriate use of knowledge to
solve human problems. It is knowing when and how
to apply knowledge.

Word processing
Creating documents using a word processing
software package such as Microsoft Word.

Work process
See workflow.

Workarounds
Ways invented by users to bypass the system to
accomplish a task; usually indicate a poor fit of the
system or technology to the workflow or user.
Devised methods to beat a system that does not
function appropriately or is not suited to the task it
was developed to assist with. For example, a nurse
might remove the armband from the patient and
attach it to the bed if the bar-code reader fails to
interpret bar codes when the bracelet curves tightly
around a small arm.

Workflow
A progression of steps (tasks, events, and
interactions) that constitute a work process; involve
two or more persons; and create or add value to the
organization’s activities. In a sequential workflow,

each step depends on the occurrence of the
previous step; in a parallel workflow, two or more
steps can occur concurrently. The term “workflow”
is sometimes used interchangeably with “process”
or “process flow,” particularly in the context of
implementations. A sequence of connected steps in
the work of a person or team of people—that is, the
process or flow of work within an organization; a
virtual illustration of the “real” work or steps (flow)
that workers enact to complete their tasks (work).
The purpose of examining and redesigning
workflow is to streamline the work process by
removing any unnecessary steps that do not add
value or might even hinder the flow of work.

Workflow analysis
Not an optional part of clinical implementations, but
rather a necessity for safe patient care fostered by
technology. The ultimate goal of workflow analysis
is not to “pave the cow path,” but rather to create a
future-state solution that maximizes the use of
technology and eliminates non–value-added
activities. Although many tools and methods can be
used to accomplish workflow redesign (e.g., Six
Sigma, Lean), the best method is the one that
complements the organization and supports the
work of clinicians.

World Wide Web (WWW)
An international network of computers and servers
that offers access to stored documents written in

HTML code, and access to graphics, audio, and
video files.

Worms
Forms of malicious code. Self-replicating computer
programs that use a network to send multiple
copies of itself to other computers, subsequently
tying up bandwidth and incapacitating networks.

Yottabytes (YB)
Units of information or computer storage equal to 1
septillion bytes.

Youth Risk Behavior Surveillance System (YRBSS)
An epidemiologic survey conducted by the Centers
for Disease Control and Protection to identify and
track the most common health risk behaviors that
lead to illnesses and mortality among youth.

Zero day attack
A technique where a hacker searches for and
exploits software vulnerabilities before the vendor is
able to release a patch or a fix.

Zettabyte (ZB)
Unit of information or computer storage equal to 1
sextillion bytes.

Index
Note: Page numbers followed by b, f and t indicate
material in boxes, figures and tables respectively.

A
AAACN. See American Academy of Ambulatory
Care Nursing
AAAI. See Association for the Advancement of
Artificial Intelligence
AACN. See Association of Colleges of Nursing
Academic Center for Evidence-Based Practice
(ACE), 502t
Academic Competencies, 267
access, 160, 472
accessibility, 24, 113b
Accountable Care Organizations (ACOs), 285
accurate information, 24
ACE Star model, 504t
ACOs. See Accountable Care Organizations
acquisition, 35. See also knowledge acquisition
action games, 448–449
active listening, 527f, 532
Active Matrix Organic Light-Emitting Diode
(AMOLED), 53
activity-monitoring systems, 377

actual users, surveys of, 219
acuity systems, 193
administrative information systems

aggregating patient and organizational data,
197–202
case management information systems, 190
communication systems, 190–191
core business systems, 191–193
department collaboration and exchange of
knowledge and information, 202–203
healthcare organization information systems,
types of, 190
interoperability, 195–196
order entry systems, 193–194
patient care support systems, 194–195

administrative processes, 272
admission, discharge, and transfer (ADT) systems,
192
ADT systems. See admission, discharge, and
transfer systems
Advanced Audio Coding (AAC), 418b
advanced cardiac life support (ACLS), 434
adventure games, 449
adverse events, 294
advocates, 422

policy developer, 131

adware software, 234, 238
Affordable Care Act, 385. See also Patient

Protection and Affordable Care Act
Agency for Healthcare Research and Quality
(AHRQ), 150, 153, 234, 251, 274, 294, 332, 384,
501

role of informatics, 502t
safety culture, 295
strategies for developing safety culture, 296

Agency for Healthcare Research and Quality
Patient Safety Network, 193
Agency for Toxic Substances and Disease Registry
(ATSDR), 345, 349
AHIMA. See American Health Information
Management Association
AHRQ. See Agency for Healthcare Research and
Quality
AI. See artificial intelligence
alarm fatigue, 297
alert, 31
algorithms, 486
alleles, 515
Alliance for Nursing Informatics (ANI), 139, 140b
Alliance for Patient Safety, 294
Allison, 91–92, 93

alternatives, 92

alphabetic data, 22
alphanumeric data, 22
Alternative Payment Models (APMs), 247
alternatives, 92

Amazon’s S3, 284b
American Academy of Ambulatory Care Nursing
(AAACN), 380
American Association for Justice, 245
American Association of Colleges of Nursing
(AACN), 405
American Association of Critical-Care Nurses
(AACN), 372
American Association of Health Plans, 501
American Health Information Management
Association (AHIMA), 140b, 267
American Library Association (ALA), 463
American Medical Association, 501
American Medical Informatics Association (AMIA),
107, 134, 138–139, 140b, 497
American National Standards Institute (ANSI),
157b, 201b
American Nurses Association (ANA), 8, 107, 108,
380, 436

Code of Ethics for Nurses, 162
definition of nursing informatics, 108–109
Nursing Informatics: Scope and Standards of
Practice, 128, 251
recognized terminologies supporting nursing
practice, 116b
standardized terminologies, use of, 279

American Nurses Credentialing Center (ANCC),
133, 426
American Nursing Association of Occupational

Health Nurses, 424
American Nursing Informatics Association (ANIA),
139, 140b, 424
American Psychological Association (APA), 427,
466
American Recovery and Reinvestment Act (ARRA),
149, 246, 268, 284
American Telemedicine Association (ATA), 366
American Well, 385
AMIA. See American Medical Informatics
Association
AMOLED. See Active Matrix Organic Light-
Emitting Diode
ANA. See American Nurses Association
analysis, 30
ANCC. See American Nurses Credentialing
Center
Androwich, Ida, 331–332b
anesthesia machines, 221
ANI. See Alliance for Nursing Informatics
ANIA. See American Nursing Informatics
Association
ANSI. See American National Standards
Institute
antiprinciplism, 84
antivirus software, 237, 238
APMs. See Alternative Payment Models
Apple iPod, 416
applications, 39, 79, 306
apps. See applications

ARGs. See augmented-reality games
Aristotle, 68
arithmetic logic units, 39
ARRA. See American Recovery and
Reinvestment Act
Array-Express, 516
art of nursing, 532
artificial intelligence (AI), 65, 67

in future, 73
meaning of, 72–73

artificial neural networks, 67
Association for the Advancement of Artificial
Intelligence (AAAI), 72
Association of College and Research Libraries, 464
Association of Colleges of Nursing (AACN), 380
asynchronous, 403
ATSDR. See Agency for Toxic Substances and
Disease Registry
Attachment Special Interest Group, 157b
attribute, 198
audio data, 22
audiopods, 419
augmented-reality games (ARGs), 452
authentication of users, 231–232

ways to, 231f

Autodesk, 259
autonomy, 84
availability, 230

avatar, 446

B
bagging, 482
baiting, 236
bar-code medication administration (BCMA), 246,
282, 303, 307
bar-code medication labeling, 306
Barack, Obama, 325
basic input/output system (BIOS), 42
BCMA. See bar-code medication administration
behavioral risk factor surveillance system, 347
beneficence, 84
BI. See bioinformatics
big data, 477–480

phase, 478–479
exploration of data, 479
knowledge deployment, 479–480
pattern discovery, 479
problem identification, 479

unstructured, 477

binary system, 44
bioethics, 79

consensus-based approach to, 86

bioinformatics (BI), 87
definition, 511–514
future of, 516–518

importance of, 514–516

biology computational. See computational biology
biomedical informatics, 511–514
Biomedical Information Science and Technology
Initiative Consortium, 514
biomedicine, 513
biometrics, 232
BIOS. See basic input/output system
biosense, 348
bioterrorism, 347
bit, 44
blended hybrid, 404
blogs, 330, 404
BMJ Clinical Evidence, 502t, 504
boosting, 482
borrowed theory, 8
Brailer, David, 285
brain, 65
Brewer, Steven L., Jr., 483–484b
bring your own device (BYOD) policy, 156
broadcast, 417b
brushing, 486
brute force attack, 233
building blocks, 22f

of nursing informatics, 7, 7f, 36f

building games, 449
bus, 41
Bush, George W., 107, 268

BYOD policy. See bring your own device policy
byte, 44

C
cache memory, 39
CAI. See computer-assisted instruction
call centers, 371
Cancer Game, 330
Cancer Genome Atlas Project, 514, 516
Capital Area Roundtable on Informatics in Nursing
(CARING), 139, 140b
capturing, 112–117
care ethics, 85–86
care plan, 190
CARING. See Capital Area Roundtable on
Informatics in Nursing
caring

strategies for, 530–533
theories, 526–529

caritas processes, 526–527
central to, 528

CART. See classification and regression trees
CASE. See computer-aided software
engineering
case analysis demonstration, 91–95

alternative, 92, 93
arguments for, 93

detailed analysis of, 94t
ethical dilemma and examine outcomes, 94–95
examine ethical dilemma, 91–92
hypothesize ethical arguments, 92–93

case management information systems, 190
case scenarios, 406–407
case study

home telehealth nurse, 360
home telemonitoring of multiple illnesses, 381
workflow analysis, 251

casual games, 449
casuist approach, 85
CBISs. See computer-based information
systems
CD-R. See compact disc-recordable
CD-ROM. See compact disc read-only memory
CD-RW. See compact disc-rewritable
CD/DVD burners, 233
CDS. See clinical decision support
CE. See continuing education
Cedars-Sinai Medical Center, 211
Center for Connected Health Policy, 367
Center for Evidence-Based Practices (CEBP), 502t
Center for Excellence in Public Health Informatics,
350
centering, 531

Centers for Disease Control and Prevention (CDC),
326, 329, 335, 343, 364

current initiatives, 348
Emergency Operations Center (EOC), 342
health literacy and health initiatives, 324–325
integrated surveillance system plan, 348
National Electronic Telecommunications System
for Surveillance, 348
patient education, 308
surveillance criteria, 342
Wide-ranging Online Data for Epidemiologic
Research, 348

Centers for Medicare and Medicaid Services
(CMS), 151, 195, 268, 310–311
central nervous system, 40
central processing unit (CPU), 39
central stations, 375
Centre for Evidence-Based Medicine, 502t
Cerner Corporation, 444–445
certification, 133
Certification Commission for Healthcare Information
Technology, 269
certified EHR technology, 145

definition of, 149

certified pediatric nurse (CPN), 426
CHAID. See chi square automatic interaction
detection
Chalmers, Iain, 498

change management, 257f
chats, 415–416
CHI. See Consolidated Health Informatics
chi square automatic interaction detection (CHAID),
483
chief information officers (CIOs), 29–30, 176
Chief Nursing Officers (CNOs), 280
chief technical officers (CTOs), 29–30
chief technology officers. See chief technical
officers
Children’s Nutrition Research Center, 330
chronic diseases

and conditions, 364
telehealth patient populations, 373

CI. See cognitive informatics
CIN: Computers, Informatics, Nursing, 140b
CINAHL. See Cumulative Index to Nursing and
Allied Health Literature
CIOs. See chief information officers
CISs. See clinical information systems
civil monetary penalties (CMP), 160
classification, 484
classification and regression trees (CART), 481,
483
classroom education, 333
climate symphony, 210
clinical analyst/system specialist, 131
Clinical and Translational Science Award (CTSA),
501

clinical databases, 9
clinical decision support (CDS), 123, 303, 309

features based on screen captures, 310

clinical documentation systems, 194
clinical informatics, 497
clinical information systems (CISs), 12, 29b, 123,
191, 194, 436, 445

electronic health records as
as clinical information system, 276b
clinical outcomes, 276–277b
EBP, 277b
as staff development tool, 277–278b

informational elements of, 120
as staff development tool, 277–278b

clinical practice guidelines, 9
clinical research informatics, 497
clinical transformation, 249
cloud computing, 32, 57–59, 57f, 240–241
cloud storage, 58
cloudy electronic health records, 284b
CMP. See civil monetary penalties
CMS. See Centers for Medicare and Medicaid
Services
CNPII. See Committee for Nursing Practice
Information Infrastructure
Cochrane, Archie, 498
Cochrane Collaboration, 498, 502t

Cochrane Qualitative Research Methods Group
(CQRMG), 499
codifying, 112–117, 545
cognitive activity, 117
cognitive informatics (CI), 65, 70–71

and nursing practice, 71–72
to usable systems, 71f

cognitive science, 26, 65–68
Cognitive Science Journal, 66
Cognitive Science Society, 66
cognitive task analysis, 215
cognitive walkthrough, 219
cognitive work analysis (CWA), 215–216
cohort research, 472
collaboration, 202–203, 402

TIGER vision for, 14

collaborative fieldwork model, 421
collaborative learning

elements for, 421
promoting active and, 420–423

commercial software, 46
Committee for Nursing Practice Information
Infrastructure (CNPII), 114b
communication(s), 380

electronic communication and connectivity, 272
telecommunications, 30
TIGER vision for, 14

tools to support, 350–351

communication science, 26
communication software, 48

features and examples, 51t

communication systems, 190–191
communities of practice (CoP), 542–543b
community health risk assessment, 345–347
community risk assessment (CRA), 347
community/population health

informatics to promote, 341–343
community health risk assessment, 345–347
core public health functions, 343–345
feedback to improve responses and promote
readiness, 351–353
knowledge to health disaster planning and
preparation, 349–350
processing knowledge and information,
347–349
tools to support communication and
dissemination, 350–351

compact disc read-only memory (CD-ROM), 42,
399
compact disc-recordable (CD-R), 43
compact disc-rewritable (CD-RW), 43
compatibility, 48
competency, 137

-based learning, 405

complete information, 24
compliance, 156
CompTIA. See Computing Technology Industry
Association
computational biology, 511–514
computer

in areas of research, 500
components, 38–45, 40f
computer science and, 53–54
input components, 49–52
output components, 53
supporting collaboration and information
exchange, 54–55
throughput/processing components, 52–53
as tool for managing information and generating
knowledge, 36–38

computer-aided software engineering (CASE), 184
computer-assisted instruction (CAI), 398–399
computer-based information systems (CBISs), 30
computer-based technology, 419
computer science, 26, 35, 66

knowledge and, 53–54

computer-supported learning, 399
computer vision syndrome, prevention of, 214
computerized physician order entry (CPOE), 193,
303

benefits of, 305

computerized provider order entry (CPOE), 193,
211, 246
Computing Technology Industry Association
(CompTIA), 233
conceptual framework, 8
conditional knowledge, 407
conferences, 425
conferencing software, 48, 51t
confidentiality, 77, 162, 230
connected health, 324
ConnectED program, 325
connection ports, 43–44
connectionism, 66–67, 67f
connectivity, 272
consensus-based approach, 86
consequences, 85, 145
Consolidated Health Informatics (CHI), 21
construction games, 449
consultant, 130
consumer demand, for information, 324–325
contact information, 24
context of care, 498
continuing education (CE), 419
Continuous Care Model, 372
control task analysis, 215–216
CoP. See communities of practice
copyright, 427, 468

restrictions, 426–427

core business systems, 191–193
cost–benefit analysis of health information
technology, 274
Council of Economic Advisers, 325
courage, 85
covered entity, 155
CPOE. See computerized physician order entry;
computer-based provider order entry
CPU. See central processing unit
CQRMG. See Cochrane Qualitative Research
Methods Group
creative software, 48

features and examples, 50t

CRISP-DM. See Cross-Industry Standard
Process for Data Mining
Cronbach’s alpha values, 137
Cross-Industry Standard Process for Data Mining
(CRISP-DM), 489
Crossing the Quality Chasm report, 294
crowdsourcing, 352
CTOs. See chief technical officers
CTSA. See Clinical and Translational Science
Award
culture, TIGER vision for, 14
Cumulative Index to Nursing and Allied Health
Literature (CINAHL), 466, 500, 502t
Current Procedural Terminology (CPT), 280b
CVS’s MinuteClinics, 385, 386
CWA. See cognitive work analysis

Cybersecurity Survey, 237

D
Dan P., 62
data, 8, 22, 107, 110, 111f, 128, 271, 537. See also
information

acquisition, 49–52
informatics tools for collecting, 469–471
moving from data silos to integrated data, 197f
nursing and health, 470
processing of, 52–53
quantitative, 470

data access, 380
data aggregation, 197–202
data analysis, 471–473

qualitative, 472–473, 473f
quantitative, 471–472, 473f

data-centric view, 545
data dictionary, 199
data files, 198
data gatherer, 119
data integrity, 23, 23f

threats to, 24f

data mart, 200
data mining, 13, 200, 477–480

concepts, 482–483

and electronic health records, 490–491
ethics of, 491
models, 486–489
techniques, 483–486

data warehouse (DW), 197
database, 48, 198, 441

construction, 198–199
example, 201

database management systems, 199, 470
datasets, 480, 514
Davies Award (HIMSS), 275
DDR SDRAM. See double data rate synchronous
dynamic random-access memory
decision making, 70, 78. See also ethical
applications of informatics

ethical. See ethical decision making
Husted bioethical, 85
knowledge and wisdom in, 69–70
organizational, 175–176

decision support, 190, 272
tools, 87

decision support systems (DSSs), 29b, 119–120
decision support/outcomes manager, 130
decision tree, 483

analysis, 483–485b, 486f

define, measure, analyze, improve, and control
(DMAIC), 488
delivery modalities, of nursing education, 400–405

competency-based learning, 405
face-to-face delivery, 401–402
hybrid/blended delivery, 404–405
online delivery, 402–404

Department of Health and Human Services
(USDHHS), 233, 268, 269, 285
descriptive statistics, importance of, 471f
design team, building, 252–253
desktop, 38

publishing, 48

digital books (eBooks), 414
digital divide, 325
digital versatile disc/digital video disc (DVD), 399
digital video disc (DVD), 42
digital video disc-recordable (DVD-R), 43
digital video disc-rewritable (DVD-RW), 43
DIKW paradigm, 109–112
discount usability evaluation, 219
dissemination, 31, 53, 55

tools to support, 350–351

distance education, 404
DMAIC steps, for Six Sigma, 488
Doctor on Demand, 385
document, 31

domain name, 332
dose–response assessment, 346
dots per inch (DPI) switch, 51
double data rate synchronous dynamic random-
access memory (DDR SDRAM), 42
DRAM. See dynamic random access memory
drill down analysis, 200, 482
Drucker, Peter, 117
Drummond Group, 269
DSDM. See dynamic system development
method
DSSs. See decision support systems
duty, 83
DVD. See digital video disc
DVD-R. See digital video disc-recordable
DVD-RW. See digital video disc-rewritable
DVD/CD drive, 43
DW. See data warehouse
dynamic random access memory (DRAM), 42
dynamic system development method (DSDM),
181–184, 182f
dynamic webpage shells, 441

E
e-brochure, 328
e-Health Code of Ethics, 83
e-health programs, 330
e-learning, 402, 425–426
email, 48, 51t, 416

scanning, 237–238

e-portfolios
description of, 408b
in higher education, 409b
process, 410–413b
for professional development, 409b
reason for creating, 408–409b

earcons, 218
EB. See exabytes
Ebola, 341
Eckes, George, 253
economic feasibility, 178
economics, 365–366
EDA. See exploratory data analysis
educated consumers, 364–365
education. See also nursing education

TIGER vision for, 14

educational games, 451–452
game mechanics and, 448–449

Educational Resources Information Center (ERIC),
466
educator, 130
edutainment, 434
EEPROM. See electronically erasable
programmable read-only memory
eHealth initiative, 326

EHRs. See electronic health records
electronic communication, 272
electronic health records (EHRs), 12, 21, 113, 149,
194, 249, 433, 446, 546

Accountable Care Organizations and, 285
administrative and reference terminologies,
280b
advantages of, 274–278
certification criteria, 270–271b
change management plan, 282
as clinical information system, 276–278b
cloudy, 284b
components of, 269–274
data mining and, 490–491
expandability of, 283–285
flexibility of, 283–285
functions and communication capabilities, 273f
future of, 285–287
implementation of, 280–283, 349
incorporating into learning environment,
441–445
ownership of, 280–283
pre-live strategies, 282
setting stage, 268–269
standardized terminology and, 278–280
support accountable care, 286f
training, 282
vendor selection process, 281

Electronic Health Records Competency Model, 267

electronic library catalogs, 467–468
electronic mailing lists, 416
electronic medication administration system
(eMAR), 307
electronic portfolios, 408b
electronic protected health information (EPHI),
238–239
electronic security

authentication of users, 231–232
offsite use of portable devices, 238–241
securing network information, 229–231
security tools security, 237–238
threats to, 232–237

electronically erasable programmable read-only
memory (EEPROM), 42
eMAR. See electronic medication administration
system
embedded devices, 39
eMedonline, 309
empiricism, 68
empowerment, 324
end-users, 182

adoption of EHR, 282

engage, 440
enterprise integration, 149
entity, 146, 198
entity relationship diagram (ERD), 198, 199f
entrepreneur, 131

Entrez PubMed, 502t
enumerative approach, 115b
Environmental Protection Agency (EPA), 346
Epidemic Information Exchange, 348
epidemiology, 69, 345, 347–349
equanimity, practice of, 526
erasable read-only memory, 42
ERD. See entity relationship diagram
ergonomics, 212, 213f
ERIC. See Educational Resources Information
Center
Essentials of Baccalaureate Education for
Professional Nursing Practice (AACN), 14, 15
ethernet, 44
ethical applications of informatics

applying ethics to informatics, 86–88
bioethics, 79
case analysis demonstration. See case
analysis demonstration
ethical decision making, 82–83
ethical dilemmas and morals, 81–82
ethical issues

new frontiers in, 95–96
and social media, 80–81

ethics. See ethics
healthcare ethics, theoretical approaches to,
83–86

ethical decision making, 82–83

casuist approach to, 85
ethical model for, 89–91b

ethical dilemmas
case analysis demonstration, 91–92
and examine outcomes in reflecting on ethical
decision, 94–95
and morals, 81–82

ethical issues
ESLI, 516, 517b, 518f
new frontiers in, 95–96
and social media, 80–81

ethical, social, and legal implications, 88
ethical, social, and legal issues (ESLI), 516, 517b,
518f
ethicists, 78
ethics

applying to informatics, 86–88
bioethics, 79
care, 85–86
of data mining, 491
in health care, 78f
telehealth, 381–382
virtue, 85, 93

eudaemonistic principles– 85
European Bioinformatics Institute, 516
evidence, 12, 408b, 498–499

evidence-based nursing, world views on, 503t
evidence-based practice (EBP), 496f

barriers to and facilitators of, 500
bridging gap between research and, 499–500
CIS, 276–278b
clarification of, 496
comparison of model approaches to, 504t
future of, 505–506
guidelines, 503–504
history of, 498
online resources for, 502–503t

exabytes (EB), 45
Excel, 472
executes, 39
executive support system, 29b
expandability, of electronic health record, 283–285
experienced nurses, 10, 134, 135t, 136t, 434
expert systems, 122
explicit knowledge, 539
exploration, of data mining, 479
exploratory data analysis (EDA), 482
exposure assessment, 346
extensibility, 48
Extensible Markup Language (XML), 157
Extreme Health, 386

F
face-to-face delivery, 401–402

Facebook, 329
failure modes and effects analysis (FMEA), 295
fair use, 426, 469

of information, 426–427, 468–469

Family Web project, 330
FDA. See Food and Drug Administration
feasibility, 178
Federal Health Information Exchange (FHIE), 21
Federal HIT Strategic Plan, 154
feedback, 31–32, 412b, 439

to improve responses and promote readiness,
351–353
in nursing science, 9

FHIE. See Federal Health Information Exchange
fidelity, 84, 437
field study, 220
fields (columns), 198
financial systems, 193
firewalls, 238
FireWire, 44
firmware, 42
fit between individuals, tasks, and technology
(FITT) model, 221
FITT model. See fit between individuals, tasks,
and technology model
five-element breathing sequence, 530, 531b
5 Million Lives campaign, 294
flash drives, 43, 233

flash memory, 42
flexibility, of electronic health record, 283–285
flexible information, 24
FLOSS. See Free/Libre Open Source Software
FMEA. See failure modes and effects analysis
focus groups, 219
Food and Drug Administration (FDA), 165,
296–297, 306
formal networks, 424
formal usability test, 220
Foundation of Knowledge Model, 10, 11f, 102f,
173f, 265f, 413, 461f, 463, 523f, 537, 538f

and home telehealth, 359–361
information science and, 27–28
nursing education, 397
revisited, 537–539

foundational interoperability, 196
free nursing podcast, 417b
Free/Libre Open Source Software (FLOSS), 185
free/open source software, 184–185
full presence, 529
functional model iteration, 183
future-state process maps, 256

G
game and simulation technology, 60
game mechanics, 434, 448–449

and virtual world simulation, 446–448

gameplay, 434
games, 434

augmented-reality games, 452
choosing among simulations, educational
games, and virtual worlds, 451–452
educational, 448–449, 451–452
future of, 452–453
serious games, 453
types of, 448–449

GAO. See Government Accountability Office
GB. See gigabytes
Gene Expression Omnibus, 516
genome, 514
genomic data, 497
genomics, 514
Geographic Information System (GIS), 29b
gigabytes (GB), 44
gigahertz, 39
GIS. See Geographic Information System
GLBA. See Gramm-Leach-Bliley Act
good action, 78
Google Glass, 79
Government Accountability Office (GAO), 301
Gramm-Leach-Bliley Act (GLBA), 158
graphical user interface (GUI), 47
graphics cards, 42, 44
gray gap, 328
great games, 448
GUI. See graphical user interface

gulf of evaluation, 216
gulf of execution, 216

H
hackers, 234
handheld devices and, 470
haplotypes, 514
HapMap. See International HapMap Project.
haptic technology, 37
hard disk, 41
hard drive, 41
Hardiker, Nicholas, 113–115b
hardware, 38–45
harm, 81
hazard identification, 346
Health Alert Network, 348
health care, 283, 375

ethics in, 78f

health disaster, 349–350
health disparities, 152
health education, Internet for, 330–335
health informatics, regulations, 146f
health information, 271
Health Information and Management Systems
Society, 140b, 185
health information exchange (HIE), 21, 260
health information organizations (HIOs), 348
health information technology (HIT), 145, 149, 246

definition of, 150
HIT Policy Committee, 154
HIT Standards Committee, 154
improving patient safety, 297
national infrastructure, 153–154
Office of National Coordinator for, 294

Health Information Technology for Economic and
Clinical Health (HITECH) Act, 113b, 145, 268, 284b,
546

definitions, 149–150
HIPAA changes, 154–161
HIPAA enhancements, 156–161
overview of, 148–153
purposes, 150–153

health initiatives, health literacy and, 325–327
Health Insurance Portability and Accountability Act
(HIPAA), 145–148, 284

HITECH Act changes, 154–161
HITECH Act enhancements, 156–161
organizations assisting, 157–158b
Privacy Rules, 154–156
Security Rules, 154–156

Health Level Seven (HL7), 21, 157b
health literacy, 327f

and health initiatives, 325–327
promoting in school-aged children, 329–330

Health Literacy: A Prescription to End Confusion,
326
health management information system, 176
Health on the Net (HON) Foundation, 332
Health Professions Network and the Employment
and Training Administration, 267
Health Resources Services Administration, 366
healthcare-associated infections, 151
healthcare informatics, nursing contributions to, 127
healthcare information, 21
Healthcare Information and Management Systems
Society (HIMSS), 130, 133, 138, 185, 196, 233,
246, 268, 314–315, 405

Cybersecurity Survey, 237
Davies Award, 275
Informatics Nurse Impact Survey, 314
Nursing Informatics Impact survey, 257
Stage 7 Awards, 274

Healthcare information exchange and
interoperability (HIEI), 285
healthcare organization information systems, types
of, 190
Healthcare organizations (HCOs), 327–329
healthcare provider, 149
healthcare worker shortages, 364
HealthIT, 349
Healthy People 2010, 325
Healthy People 2020, 325
heuristic evaluation, 219–220

HGP. See Human Genome Project
HIE. See health information exchange
HIEI. See Healthcare information exchange and
interoperability
high definition multimedia interface (HDMI), 43–44
high-hazard drugs, 307
high-quality data, 23
higher education, 399
HIMSS. See Healthcare Information and
Management Systems Society
HIPAA. See Health Insurance Portability and
Accountability Act
HIS. See hospital information system
HIT. See health information technology
HIT Policy Committee, 154
HIT Standards Committee, 154
HITECH Act. See Health Information Technology
for Economic and Clinical Health Act
home care, applications of telenursing in, 370–372
home health care, 371
home telehealth care, 359–361, 370

Foundation of Knowledge Model and, 359–361
managing, 379f
nurse, role of, 360
practice and protocols, 380–381
software, 378

communications, 380
data access and information sharing, 380
trending, 379
triage, 379–380

tools of
central stations, web servers, and portals,
375
medication management devices, 378
monitoring, 376f
peripheral biometric (medical) devices, 376
personal emergency response systems, 377
sensor and activity-monitoring systems, 377
special needs telecommunications-ready
devices, 378
telephones, 376
videocameras and videophones, 376–377

home telemonitoring, 362, 363
concerned patients and families, 374
hospitalized patients, 374
isolated patients, 373
of multiple illnesses, 381

HONcode, 332
hospital information system (HIS), 29b, 177
Hospital National Patient Safety Goals, 298
Hospital Survey on Patient Safety Culture, 296
HUDDLE (Healthcare, Utilizing, Deliberate,
Discussion, Linking, Events) method, 547
human error, 233
human factors, 212, 213f

engineering, 296

Human Genome Project (HGP), 515–516
ESLI questions, 517b

Human Mental Workload (MWL), 70, 71f
human–computer interactions, 214
humanistic nursing theory, 528–529
human–technology interface, 207–208

description of, 208–211
framework for evaluation, 221
future of, 221–223
improving, 212–221
problem, 211–212
and task completion, 222f

hybrid, 404
hybrid/blended delivery, 404–405
hypertext, 406
hypothesize ethical arguments, 92–93
HμREL Corporation, 30–31

I
IA technology. See intelligent agent technology
IaaS. See infrastructure as a service
ICNP version 2, 115b
IDE. See integrated drive electronics
identification (ID) card, 232
iHealth record, 21
IHIE. See Indiana Health Information Exchange
IM. See instant message

image data, 22
IMIA. See International Medical Informatics
Association
IMing. See instant messaging
impaired physical mobility, 113b
in-depth interviews, 472
In-Plane Switching Liquid Crystal Display (IPS
LCD), 53
Indiana Health Information Exchange (IHIE), 21
Industrial Age, 117
Industry-Sector Technical Competencies, 267
Industry-Wide Technical Competencies, 267
infection-control nurse, 200
infections, healthcare-associated, 151
informaticists, 514
informatics, 127. See also nursing informatics

applying ethics to, 86–88
as change agent, 256–258
ethical applications of. See ethical applications
of informatics
and healthcare technologies, 15
KSAs, 16–17
practice, workflow analysis and, 251–256
to promote community/population health,
341–343

community health risk assessment, 345–347
core public health functions, 343–345
feedback to improve responses and promote
readiness, 351–353
knowledge to health disaster planning and

preparation, 349–350
processing knowledge and information,
347–349
tools to support communication and
dissemination, 350–351

role of, 500–502
technologies for patient safety, 301–313
tools for collecting data and storage of
information, 469–471

informatics design, TIGER vision for, 14
informatics innovator, 134, 135t, 136t
Informatics Nurse Impact Survey, 314
informatics nurse specialist (INS), 128–129, 134,
135t, 136t

standards of practice and professional
performance for, 129b

Information & Resources for Nurses Worldwide,
503t
information, 8, 9, 21, 22–25, 26, 35, 107, 110, 111f,
128, 202–203, 537. See also data; knowledge

acquisition, 49–52
computer as tool for managing, 36–38
consumer demand for, 324–325
processing knowledge and, 347–349
processing of, 52–53
storage of, 469–471
user, 119

Information Age, 36, 117
information exchanges (HIE), 349
information literacy, 397, 464, 465f
Information Literacy Competency Standards for
Higher Education, 463
information processing, 21, 26–27
information science, 25–26

and Foundation of Knowledge model, 27–28

information sharing, 380
information systems (ISs), 189, 246

examples of, 29b
introduction to, 28–32

information technology (IT), 21, 176, 194, 503, 543
for patient safety, 301–313
TIGER vision for, 14

infrastructure as a service (IaaS), 58, 58f
innovative electronic data collection, 470
INP/APNN. See International Nurse
Practitioner/Advanced Practice Nursing
Network
InPen, 309
input, 25

devices, 49–52

instant message (IM), 48, 51t, 415
instant messaging (IMing), 415
instinct, 68

Institute for Health and Social Care Research, 406
Institute for Healthcare Improvement (IHI), 294, 296

smart pump technology, 308

Institute of Medicine (IOM), 276b
Committee on the Quality of Health Care, 151
Crossing the Quality Chasm, 294
definition of EHRs, 269
To Err Is Human, 294
health literacy, 326
Learning Healthcare System, 548
safety problems, 211

Institute of Translational Health Sciences, 501
institutional review board (IRB), 470
integrated drive electronics (IDE), 42
integration, 179
integrity, 230. See also data integrity
intelligence, 65, 73
intelligent agent (IA) technology, 298
interactions, 249
interactive technologies, 330
interfaces, 23

immersion, Microsoft, and PQ labs, 37b

International Classification for Nursing Practice
(ICNP), 112, 280
International Classification of Diseases, Version 10
(ICD-10), 279, 280b
International HapMap Project, 514–516

International Journal of Medical Informatics, 140b
International Medical Informatics Association
(IMIA), 134, 140b, 312
International Nurse Practitioner/Advanced Practice
Nursing Network (INP/APNN), 424
International Organization for Standardization
(ISO), 201b
International Radio Medical Center, 362
International Standards Organization (ISO), 157b
Internet, 334, 424

-based tools, 413–420
audiopods, 419
chats and online discussions (blogs),
415–416
digital books (ebooks), 414
electronic mailing lists, 416
instant messaging, 415
multimedia, 419–420
podcasts, 416–417, 417–418b
portals, 416
searching, 414–415
videopods, 419
webcasts and webinars, 414

browsers, 46, 51t
evidence-based online resources, 502–503t
for health education, 330–335
knowledge acquisition through, 466–468
Voice over Internet Protocol, 298

Internet Healthcare Coalition, 83
Internet of Everything (IoE), 428
Internet of Things (IoT), 32
Internet2, 21
interoperability, 185–186, 186f, 195–196, 284
Interprofessional collaboration, 547
Interstate Medical Licensure Compact (IMLC), 382
InTouch Health, 373
intranets, 543
intrusion detection devices, 235
intrusion detection system, 238
intuition, 68
IOM. See Institute of Medicine
IoT. See Internet of Things
Iowa model, 499, 504t

evidence-based practice, 503t

iPod, 417b
IPS LCD. See In-Plane Switching Liquid Crystal
Display
iScrub, 306
ISO. See International Standards Organization
IT. See information technology
iteration, 177
iTunes, 417–418b

J
James, John T., 293
Joanna Briggs Institute, 503t

Johns Hopkins Bloomberg School of Public Health,
503t
Johnson, Glenn, 162–163b, 408–412b, 542–543b
Joint Commission, 294, 296, 298, 301
Journal of AHIMA & Perspectives in Health
Information Management (online), 140b
Journal of Healthcare Information Management,
The, 138, 140b
Journal of Patient Safety, 293
Journal of the American Medical Association, 83
Journal of the American Medical Informatics
Association (JAMIA), The, 138–139, 140b
jump drives, 233
just culture, 295
justice, 84, 85

K
k-nearest neighbor, 486
KDD. See knowledge discovery and data mining
KDP model. See knowledge domain process
model
Kennedy, John F., 362
Kenney, Julie A., 331–332b
key field, 198
keyboard, 49–50
KMSs. See knowledge management systems
know–do gap, 325
knowledge, 8, 9, 12, 25, 26–27, 107, 110–111, 111f,
128, 537

communities of practice, 542–543b
computer as tool for generating, 36–38
in decision making, 69–70
definition of, 69
generation of, 504–505
to health disaster planning and preparation,
349–350
and information, 347–349
nature of, 65, 69, 539–541
sources of, 68
tools for acquiring, 345–347
transforming raw data into, 479f
use in practice, 541–543

knowledge acquisition, 9, 26, 69, 360, 537
through Internet and library holdings, 466–468
and sharing, 398

knowledge brokers, 544
knowledge builder, 119
knowledge-centric view, 545
knowledge consumers, 544
knowledge deployment, 479–480
knowledge discovery, 477–480
knowledge discovery and data mining (KDD), 480

benefits of, 489
case study, 482
and research, 481

knowledge discovery in data, 480

knowledge discovery in databases, 480
knowledge dissemination, 9, 361, 537

and sharing, 423–426

knowledge domain process (KDP) model, 539
knowledge exchange, 202–203
knowledge generation, 9, 360–361, 537

through nursing research, 464–466

knowledge generators, 544
knowledge management

across disciplines, 547–548
lifecycle, 540f
organizational issues, 543f
in organizations, 545–547
and transfer in healthcare organizations, 538

knowledge management systems (KMSs), 541, 545
knowledge processing, 9, 360
knowledge repositories, 545
knowledge, skills, and attitudes (KSAs), 16–17
knowledge user, 119
knowledge viability, 12
knowledge work, 117
knowledge worker, 10, 21, 141

characteristics of, 544–545
nurse as, 117–122

KSAs. See knowledge, skills, and attitudes

L
laboratory information systems, 194–195
Landmarks of Tomorrow (Drucker), 117
language, standardized, 112
laptop, 38
latex-based simulation, 433, 434f
leadership, 550

TIGER vision for, 14

Lean, 251
learner–interface interaction, 398
learning

active, 418–423
blended learning model, 404–405
collaborative, 418–423
competency-based, 403
e-learning, 402
face-to-face, 401–402
incorporating EHRs into, 391–393
online, 402–404
problem-based, 402
web-enhanced learning, 404

Learning Healthcare System, 548–550, 549f
learning management systems (LMSs), 405

evolution of, 398–400

learning-to-be skills, 437
learning-to-do skills, 437

learning-to-know skills, 437
legal feasibility, 178–179
legislation, 149, 268

and nursing practice, 165
privacy and data regulations, 158b

length of stay (LOS), 489
liberty, 84
library catalogs, electronic, 467–468
library science, 26
LISTSERV, 541
literacy. See health literacy
LMSs. See learning management systems
logic, 68
Logical Observation Identifier Names and Codes
(LOINC), 279–280, 280b
longevity, 113b
Longuet-Higgins, Christopher, 65–66
LOS. See length of stay
loving kindness, practice of, 526
lower-CASE tools, 184
loyalty, 118

M
machine learning, 482
MACRA. See Medicare Access and CHIP
Reauthorization Act of 2015
Magnet hospitals, 426
Mahan, Wendy, 55–56b

main memory, 41–42
mainframes, 39
malicious code, 234
malicious insiders, 234, 237
malware, 240
managed care information systems, 195
Management Competencies, 267
Management Information Systems (MIS), 29b
management, TIGER vision for, 14
mapping, 216
mask, 238
Massachusett s Health Data Consortium (MHDC),
21
massive multiplayer online role-playing games, 449
Maya, 259
MB. See megabytes
MDs. See medical devices
ME-PI Toolkit, 246
meaningful information, 24
meaningful use (MU), 145, 246, 268

definition of, 154
of electronic health records, 149

Medicaid, 145, 149
medical devices (MDs), 230
medical errors, 294
medical home models, 260
medical informatics, 141
Medical Product Safety Network, 297
medical simulations, 439. See also simulations

Medicare, 145, 149, 294, 386
Medicare Access and CHIP Reauthorization Act of
2015 (MACRA), 165, 247, 247f
Medicare Chronic Care Initiative, 387
Medicare Patient Advisory Commission (MEdpAC),
382
medication administration, 304–309

BCMA, 246, 302
after discharge, 309
rights of, 303
smart pump technologies for, 307–308
technologies to support, 304–309

medication errors, 303
medication management devices, 378
MEDLINE, 466
MedlinePlus, 332, 335
megabytes (MB), 44
megahertz, 39
memory, 38, 66
mentors, 422
Merit-Based Incentive Payment System (MIPS),
247
Merriam-Webster Online Dictionary, 250
meta-analysis, 384, 499

documentation search strategy, 505
and generation of knowledge, 504–505
steps, 505

meta-learning, 482–483

methicillin-resistant Staphylococcus aureus
(MRSA), 275
metrics, 258–259, 258t
MHDC. See Massachusett s Health Data
Consortium
mHealth, 369
MHHWQ. See Modified Home Healthcare Worker
Questionnaire
microfluidic biochip, 31
microprocessor, 39
Microsoft Surface, 37b
milestones, 181
Millennial Generation, 405
millions of instructions per second (MIPS), 60
mind, 65, 67
mini-games. See casual games
Minnesota Health Information Exchange, 284
MIPS. See Merit-Based Incentive Payment
System; millions of instructions per second
MIS. See Management Information Systems
mobile devices, 39, 61
mobile transaction, 40
modeling, 487
modem, 43
Modified Home Healthcare Worker Questionnaire
(MHHWQ), 449
monetary incentives, 154
monitor, 52–53
monitoring patients. See patient monitoring;
telemonitoring

moral dilemmas, 81
moral rights, 92
morals, 81–82
Morgan Stanley Children’s Hospital of New York,
406
MoSCoW approach, 182–183
motherboard, 40–41
mouse, 51–52
MP3. See MPEG-1 Audio Layer-3
MPEG-1 Audio Layer-3 (MP3), 43, 417b

aggregator, 417b

MU. See meaningful use
multidimensional databases, 486
multimedia, 419–420
multiprocessor support, 48
multiuser dungeon, 451
multiuser shared hallucination, 451
MWL. See Human Mental Workload

N
NANDA International (NANDA-I), 107, 115b, 279
NASA. See National Aeronautics and Space
Administration
National Aeronautics and Space Administration
(NASA), 362
National Center for Biotechnology Information
(NCBI), 511, 516

National Center for Cognitive Informatics and
Decision Making in Healthcare (NCCD), 70
National Center for Public Health Informatics
(NCPHI), 348
national coordinator, 154
National Council of State Boards of Nursing
(NCSBN), 163, 433
National eHealth Collaborative Technical Expert
Panel, The, 209
National Electronic Disease Surveillance System,
348
National Guideline Clearinghouse (NGC), 501–502
National Health and Nutrition Examination Survey,
347
National Health Information Center, 335
National Health Information Infrastructure (NHII), 21
National Health Information Network (NHIN), 21,
352
National Health Service, 336, 498
National Healthcare Disparities Report, 153
national healthcare quality report (NHQR), 150–151
National Human Genome Research Institute
(NHGRI), 513, 516
National Institute of Standards and Technology
(NIST), 154, 269
National Institutes of Health (NIH), 326, 335, 500

Biomedical Information Science and Technology
Initiative Consortium, 514
CTSA, 501
Human Genome Project, 515

National Institutes of Mental Health, 362
National League for Nursing (NLN), 13
National Library of Medicine, 279, 330, 466
National Network Libraries of Medicine, 326
National Patient Safety Foundation, 303
National Patient Safety Goals, 294
National Pharmaceutical Council, 378
National Quality Forum, 294
National Retail Data Monitor (NRDM), 347–348
NCBI. See National Center for Biotechnology
Information
NCCD. See National Center for Cognitive
Informatics and Decision Making in Healthcare
NCSBN National Simulation Study, 440
nearest neighbor analysis, 486
negligence, 84
negligent insider, 233
NEHEN. See New England Health EDI Network
Nelson, Ramona, 111
Net Generation, 405, 415
network, 54, 229
network accessibility, 241
network availability, 241
network information security, 229–231
network security, 241
network security policies, 234
networking, 423–424

social, 54, 162–163

neural networks, 66–67, 483
neuroscience, 66
never events, 294
New England Health EDI Network (NEHEN), 21
Next Generation Digital Learning Environment
(NGDLE), 400
Next-Generation Internet (NGI), 21
NGDLE. See Next Generation Digital Learning
Environment
NGI. See Next-Generation Internet
NHGRI. See National Human Genome Research
Institute
NHII. See National Health Information
Infrastructure
NHIN. See National Health Information Network
NHQR. See national healthcare quality report
NI. See nursing informatics
NIC. See Nursing Interventions Classification
NICA. See Nursing Informatics Competency
Assessment
NICA L3/L4 self-assessment instrument, 137
nicomachean, 85
Nightingale, Florence, 106, 344
Nightingale Tracker System, 470
NIHSeniorHealth, 335
NIST. See National Institute of Standards and
Technology
NLN. See National League for Nursing
NMDS. See Nursing Minimum Data Set
NMMDS. See Nursing Management Minimum

Data Set
“no pay for errors” initiative, 294
NOC. See Nursing Outcomes Classification
non-value added activities/step, 253–255
nonknowledge work, 119
nonmaleficence, 84
nonplayer character (NPC), 447
nonsteroidal anti-inflammatory drugs (NSAIDs), 304
NPC. See nonplayer character
NRDM. See National Retail Data Monitor
NSAIDs. See nonsteroidal anti-inflammatory
drugs
numeric data, 22
nurse informaticist, role of, 313
Nurse Licensure Compact (NLC), 382
nurse–patient interaction framework, 219f
nurses

as knowledge worker, 117–122
quality and safety education for, 16–18

nursing
ANA’s definition of, 8
capturing and codifying the work of, 112–117
contributions to healthcare informatics, 127–128
and healthcare worker shortages, 364

nursing education, 445–446
delivery modalities, 400–405

competency-based learning, 405
face-to-face delivery, 401–402

hybrid/blended delivery, 404–405
online delivery, 402–404

exploring information fair use and copyright
restrictions, 426–427
and Foundation of Knowledge Model, 397
future of, 427
game mechanics and virtual world simulation
for, 446–448
Internet-based tools, 413–420

audiopods, 419
chats and online discussions (blogs),
415–416
digital books (ebooks), 414
electronic mailing lists, 416
instant messaging, 415
multimedia, 419–420
podcasts, 416–417, 417–418b
portals, 416
searching, 414–415
videopods, 419
webcasts and webinars, 414

knowledge acquisition and sharing, 398
knowledge dissemination and sharing, 423–426

continuing education and recertification,
425–426
networking, 423–424
presenting and publishing, 424–425

learning management systems, evolution of,
398–400

nursing informatics competencies, 436–437
promoting active and collaborative learning,
420–423
simulations, games, and virtual worlds, 452–453
smartphones and smart devices in, 420b
technology tools, 405–413

case scenarios, 406–407
e-portfolios, 408–412b
electronic portfolios, 408b
portfolios, 407
simulations, 407
tutorials, 406
virtual reality, 413

virtual worlds in, 450–451

nursing graduates, 14–15
nursing informatics (NI), 7, 128–129, 464, 537

building blocks of, 7, 7f, 22f, 36f, 66f
capturing and codifying the work of nursing,
112–117
case study, 122
cognitive science, impact on, 65–68
competencies, 133–137, 136t, 141

in nursing education, 436–437
definition of, 106
DIKW paradigm, 109–112
education, simulation in, 434–436

case for, 437–441
formal educational programs, 132b

future of, 123, 139–141, 473
meaning of, 108–109
nurse as knowledge worker, 117–122
and organizational decision making, 175–176
and organizational decision making
organizations and journals, 138–139
practice, rewards of, 138
roles, 129–131, 131f
as specialty, 127
specialty education and certification, 131–133
specialty, evolution of, 106–108
websites and corresponding journals, 140b

Nursing Informatics Awareness Task Force, 130
Nursing Informatics Competency Assessment
(NICA), 436
Nursing Informatics Deep Dive, 13
Nursing Informatics: Scope and Standards of
Practice (Nelson), 108, 111, 128, 251

Second Edition, 436

Nursing Interventions Classification (NIC), 107, 279
nursing knowledge, 121
Nursing Management Minimum Data Set
(NMMDS), 114b
Nursing Minimum Data Set (NMDS), 114b
Nursing Outcomes Classification (NOC), 107, 279
nursing practice

definitions of four levels of, 135t
implications for, 161–165

standardized terminologies to support,
113–116b

Nursing Practice Council, 541
nursing research

case study, 464
and Foundation of Knowledge Model, 463
knowledge generation through, 464–466

nursing science, 7
nursing theory, 8
NVivo, 472

O
object-oriented multiuser dungeon, 451
object-oriented systems development (OOSD), 181
objective information, 25
OCR. See Office of Civil Rights
Office for Civil Rights (OCR), 146, 155, 233
Office of Minority Health and Health Disparities, 153
Office of the National Coordinator for Health
Information Technology (ONC), 150, 196, 269
office suite software, 48, 49t
office systems, 29b
Ohio State University Medical Center, 513
OHSU. See Oregon Health & Science University
OLAP. See online analytic processing
omics, 512–513b

ONC. See Office of the National Coordinator for
Health Information Technology
100,000 Lives campaign, 294
one-on-one education, 333
online analytic processing (OLAP), 486
online browser–based game, 449
online chats, 398
online delivery, 402–404
online discussions (blogs), 415–416
Online Journal of Nursing Informatics, The, 138,
140b
online learning, 402. See Internet
ontological approach, 115b
OOSD. See object-oriented systems
development
open access, 505
Open Access Initiative, 505
Open Data Pledge, 294
open source software (OSS), 46, 47f, 184–185
Open Systems Interconnection (OSI), 157b
operating system (OS), 39, 46–48
operational feasibility, 179
optimization, 250–251
order entry management, 272
order entry systems, 193–194
Oregon Health & Science University (OHSU), 513
organizational culture, 497
OS. See operating system
OSI. See Open Systems Interconnection
OSS. See open source software

outcome, 31
output, 31
OWL. See Web ontology language

P
PaaS. See platform as a service
Pacific Northwest National Laboratory (PNNL), 70
PACS. See picture archiving and
communication system
paper-based education, 334
parallel port, 43
password, 231–232, 232b
patient care support systems, 194–195
patient-centered care (PCC), 150, 194, 528
patient confidentiality. See confidentiality
patient education

choosing strategy, 332f
clinician’s view on, 333–334b
considerations for, 331–332b

patient engagement, 324
future directions for, 335–337

patient informed consent, 381
patient management, 310
patient monitoring

activity-monitoring systems, 377
home telemonitoring. See home
telemonitoring

remote monitoring (telemonitoring), 369
sample protocol, 380–381
telephone monitoring (telephony), 369

patient populations, telehealth, 372–375
assisted living and subacute patients, 375
at-risk populations, 373
chronic diseases, 373
concerned patients and families, 374
emergency response situations, 374
employers and wellness programs, 375
hospitalized patients, 374
incarcerated patients, 374
isolated patients, 373

patient privacy, 284
Patient Protection and Affordable Care Act (2010),
195. See also Affordable Care Act
patient safety

additional technologies for, 310–313
informatics technologies for, 301–313
websites, 316t

Patient Safety and Quality Improvement Act, 294,
295
Patient Safety Manual, 306
Patient Safety Movement Foundation, 294
Patient Safety Network, 295
patient support, 272
pattern discovery, of data mining, 479

Pawlenty, Tim, 284
PB. See petabytes
PC. See personal computer
PCC. See patient-centered care
PCI. See peripheral component interconnection
PEDA. See pre-brief, enactment, debrief, and
assessment
Pediatric Nursing and Certification Board, 426
pediatric programs, 181
Penn State College of Nursing, 404
Penn State University, 364
Pennsylvania Homecare Association, 364
perception, 68
peripheral biometric (medical) devices, 376
peripheral component interconnection (PCI), 43
personal computer (PC), 46
Personal Effectiveness Competencies, 267
personal emergency response systems, 377
petabytes (PB), 45
Pew Internet and American Life Project Health
Online survey report, 324
pharmacy information systems, 194
PHI. See protected health information
phishing, 236
phishing scam email, 236b
physical presence, 529
picture archiving and communication system
(PACS), 195
PillDrill, 309
platform as a service (PaaS), 58, 58f

plug and play, 38
PNNL. See Pacific Northwest National
Laboratory
podcasts, 416–417, 417–418b
Pokemon Targets Hospital, 240b
policies, 149

TIGER vision for, 14

population health management, 272–274
port, 38
portability, 48
portable devices, offsite use of, 238–241
Portable operating system interface for Unix
(POSIX), 48
portals, 375, 416
portfolios, 407
postproject phase, 183–184
potential, surveys of, 219
power supply, 41
PowerChart application, 445
PowerPoint presentation, 425
practice, rewards of, 138
pre-brief, enactment, debrief, and assessment
(PEDA), 437, 437–438t
preceptors, 422
precision medicine, 287
preproject phase, 182–183
presence, 529

strategies for, 530–533
types of, 529

presentation, 48, 424–425
primary key, 198
principlism, 84
printers, 53
privacy, 77, 149
Privacy Rules, 154–156
private cloud, 57
private health information (PHI), 491

vulnerability of, 159f

problem-based learning, 402
problem identification, of data mining, 479
problem solving, 72
process analysis, 252
process map, 249
process mining, 491
process owners, 252
processing, 30

data, 471–473
knowledge, 347–349

processor, 39
product developer, 130
productivity software, 48
professional associations, 424
professional development, 35
professional networking, 409b
professional online databases, 466
programmable read-only memory (PROM), 42

programs, 181
project life cycle phase, 183
project manager, 130
PROM. See programmable read-only memory
ProModel, 259
protected health information (PHI), 146–147, 147f,
155
Proteus smart pills, 309
prototype, 180
proxy servers, 238
psychology, 66
PsycInfo, 466
public cloud, 57
public health, 343

core functions, 343–345
improving, 152
preparedness in, 347

public health informatics (PHI), 344f
abbreviations used in, 354t
draft of competencies, 351
scope of, 345
sites, 353t

Public Health Information Network, 348
public health interventions, 349
publishing, 48, 424–425
PubMed Central, 503t
PulseNet USA, 348

Q
QCDRs. See Qualified Clinical Data Registries
QPP. See quality payment program
QRPH. See quality, research, and public health
QSEN. See Quality and Safety Education for
Nurses
Qualified Clinical Data Registries (QCDRs), 247
qualified electronic health record, 150
qualitative data analysis, 472–473, 473f
qualitative studies, 505
quality, 16–18, 248
Quality and Safety Education for Nurses (QSEN),
13, 16, 405, 501
quality payment program (QPP), 247
quality, research, and public health (QRPH), 345
quantitative data analysis, 471–472, 473f
quantitative studies, 505
quantum bits (qubits), 59
quantum computer, 59–60
quantum computing, 59–60
query, 200
QWERTY keyboard, 49

R
RAD. See rapid application development
radio frequency badges, 258
radio frequency identification (RFID), 232, 307, 311
radiology information system (RIS), 195

RAM. See random-access memory
random-access memory (RAM), 41–42
randomized controlled trial (RCT), 498–499
ransomware, 234
rapid application development (RAD), 180–181,
180f
rapid prototyping, 180–181, 180f
Rapid Syndromic Validation Project (RSVP), 21
Rational Rose, 184
rationalism, 68
RDF. See resource description framework
RDMS. See relational database management
system
read-only memory (ROM), 42
readiness, 351–353
Real-time Outbreak and Disease Surveillance
Laboratory (RODS), 347
real-time/interactive telehealth, 367–369
really simple syndication (RSS), 417
reason, 68
reasoning, 68
recertification, 425–426
records (rows), 198
reflective commentary, 409b
reflective practice, 533, 534f
RefWorks, 500
regional health information exchanges, 352
relational database, 13
relational database management system (RDMS),
199, 201b

relevant information, 24
reliable information, 24
remote access, managing, 239–240
remote monitoring, 369
remote patient monitoring, 369
Remote Presence Robot (RP-7), 373
removable storage device, 233, 234f
report, 31
reporting, 272–274
repository, 184, 200
reproducibility, 25
research. See nursing research
research utilization, 496–497
research validity, 499
researcher, 130
resource description framework (RDF), 417
Responsive (Reactive) Care Model, 372
results management, 272
return on investment (ROI), 489
reusability, 113b
RFID. See radio frequency identification
rights, 155
RIS. See radiology information system
risk assessment, 345

community health, 345–347
process, steps for, 346f

risk characterization, 346
Ritz Carlton hotels, 258
Ritzko, Jackie, 417–418b

Robert Wood Johnson Foundation (RWJF), 269
robotics technologies, 312
ROI. See return on investment
role playing, 402

games, 449

ROM. See read-only memory
root-cause analysis, 295
RSS. See really simple syndication
RSVP. See Rapid Syndromic Validation Project
RxNorm, 280b

S
SaaS. See software as a service
safety culture, 295

Agency for Healthcare Research and Quality,
295
description of, 294–295
strategies for developing, 296–301
user–technology–patient safety scheme, 298f

safety education, 16–18
Sample, Explore, Modify, Model, Access (SEMMA),
488–489
Sarbanes-Oxley Act (SOX), 158
scaffolding, 439
Scalable Collaborative Infrastructure for a Learning
Healthcare System (SCILHS), 550
scareware, 236

scenario, 406
schedule feasibility, 179
Scheduled Care Model, 372
scheduling systems, 193
Scholarly Talk About Research Series (STARS),
422
school-aged children, promoting health literacy in,
329–330
SCILHS. See Scalable Collaborative
Infrastructure for a Learning Healthcare System
scoring, 480
SCSI. See Small Computer System Interface
SDLC. See systems development life cycle
SDOs. See standards-developing organizations
Seaman’s Church Institute of New York, 362
search engines, 467
searching, 414–415
“seasoned nurses.” See experienced nurses
Second Life, virtual world of, 451
secure information, 239
security, 149, 48, 92. See also electronic security
security breaches, 233
Security Rules, 154–156
SEEDS. See Simulated E-hEalth Delivery
System
self-control, 85
semantic interoperability, 196
SEMMA. See Sample, Explore, Modify, Model,
Access
sensor, 377

and activity-monitoring systems, 377

SEQUEL. See Structured English Query
Language
serial port, 43
serious games, 448, 453
server, 441
severe acute respiratory syndrome (SARS), 341
sharing

knowledge acquisition and, 398
knowledge dissemination and, 423–426

shoulder surfing, 230
“shrink wrap” license, 468
SIMpill Medication Adherence System, 309
simulated documentation, 441, 442f
Simulated E-hEalth Delivery System (SEEDS), 443,
444–445
simulation game, 449–450
Simulation Learning System (Elsevier), 444
simulation scenario, 444
simulations, 407, 433

challenges and opportunities, 445
choosing among simulations, educational
games, and virtual worlds, 451–452
future of, 445–446, 452–453
goal of, 439
in nursing informatics education, 434–436
virtual world, 446–448

simulator, 439
situational awareness, 218
Six Sigma, 251
Six Sigma/Lean, 487–488
Small Computer System Interface (SCSI), 43
smart classrooms, 404
smart pump, 303

technologies, 307–308

smart rooms, 311
smartphones, 79, 416, 420b, 452
SNOMED CT. See Systematized Nomenclature
of Medicine
Snow, John, 344
social communication software, 54
social engineering, 235
social media, 164, 329, 352, 403, 404f

ethical issues and, 80–81

social networks, 54
use of, 162–163

social sciences, 26
Social Security numbers, 239
social–organizational analysis, 216
software, 46–48, 378

commercial, 46
communication, 48, 51t
creative, 48, 50t
home telehealth

communications, 380
data access and information sharing, 380
trending, 379
triage, 379–380

office suite, 49t
open source, 46, 47f
OS, 46–48
productivity, 48

software as a service (SaaS), 58, 58f
sound card, 44
sources of knowledge, 68
SOX. See Sarbanes-Oxley Act
speakers, 53
spear phishing, 236
special needs telecommunications-ready devices,
378
specialty, evolution of, 106–108
spreadsheets, 48, 439
SPSS. See Statistical Package for Social
Sciences
spyware, 234
SQL. See Structured Query Language
Squires Quest, 330
stacking, 483
staff development tool, 277–278b
Stage 7 Awards (HIMSS), 274
stakeholders, 26, 202
standardized language, 112

standardized nursing terminology, 114b
standardized plan of care, 190
standards, 77, 149
standards-developing organizations (SDOs), 157b
Stanford Encyclopedia of Philosophy (2010), 66
static dynamic random-access memory, 42
static medium, 327
Statistical Package for Social Sciences (SPSS),
472
stethoscope, 283
Stetler model, 498, 504t
“Stimulus” law. See American Recovery and
Reinvestment Act
storage capacities, 44–45b
store-and-forward telehealth transmission, 367
strategies analysis, 216
strategy games, 449
StratWorld, 446–448
structural interoperability, 196
Structured English Query Language (SEQUEL),
201b
Structured Query Language (SQL), 200, 201–202b
suicide prevention community assessment tool, 347
summaries, 31
supercomputers, 40
Surveillance, 342
surveillance data systems, 349
Swain, Jeff, 162–163b, 408–412b, 542–543b
swim-lane technique, 253

examples of, 254f

Synchronous dynamic random-access memory
(SDRAM), 42
syndromic surveillance systems, 342, 342f
synthesis, 30
Systematized Nomenclature of Medicine
(SNOMED), 107

—Clinical Terms (SNOMED CT), 279–280, 280b

systems development life cycle (SDLC), 175
analysis phase, 179
case scenario, 176–178
computer-aided software engineering tools, 184
design phase, 179
dynamic system development method, 181–184
implement phase, 179
interoperability, 185–186
maintenance phase, 179
object-oriented systems development, 181
open source software and free/open source
software, 184–185
rapid prototyping or rapid application
development, 180–181, 180f
test phase, 179
waterfall model, 178–180, 178f

systems engineering, 296
systems feasibility, 178

T
tables, 198
tacit knowledge, 539–540
TANIC. See TIGER-based Assessment of
Nursing Informatics Competencies
task analysis, 215
tasks, 249
task–technology fit model, 221
TB. See terabytes
teams

multidisciplinary team, 118
workflow redesign team, 252–253

technological feasibility, 178
technologist, 117
technology, 246

art of caring, 525–526
for baccalaureate nursing graduates, 14–15
certified EHR technology, 145, 149
computer, 36
game and simulation technology, 60
haptic, 37
human interfaces. See human–technology
interface
informatics, for patient safety, 301–313
radio frequency identifier, 307
robotics, 312
smart pump, 307–308
telehealth technology, 209

wearable, 311, 337
workflow and, 249–251

technology acceptance model, 221
Technology Informatics Guiding Education Reform
(TIGER), 13, 14, 134, 287, 405, 445
Teladoc, 385
Tele-ICU, 372, 382
telecommunications, 30
teleconsultations, 368–369
telehealth, 129, 359

clinical uses of, 366–367
description of, 366
driving forces

chronic diseases and conditions, 364
demographics, 363–364
economics, 365–366
educated consumers, 364–365
nursing and healthcare worker shortages,
364

evolving models, 385–386
future of, 386–387
history of, 362–363
home telehealth. See home telehealth
legal, ethical, and regulatory issues, 381–382
mHealth, 369
nursing aspects of, 361
patient populations, 372–375

assisted living and subacute patients, 375

at-risk populations, 373
chronic diseases, 373
concerned patients and families, 374
emergency response situations, 374
employers and wellness programs, 375
hospitalized patients, 374
incarcerated patients, 374
isolated patients, 373

patient’s role in, 382–383
physician-to-physician consult using, 368f
real-time (or interactive), 367–369
remote monitoring, 369
research, 383–384
research and information centers, 385b
store-and-forward, 367
technologies, nonclinical uses of, 369–370
telehealth care. See telehealth care
telenursing. See telenursing
telephony, 369
transmission formats and clinical applications,
367

telehealth care, 366–370
clinical uses of, 366–367
nonclinical uses of, 369–370
transmission formats and clinical applications of

mHealth, 369
real-time/interactive telehealth, 367–369
remote monitoring, 369

store-and-forward telehealth, 367
telephony, 369

telehealth devices, 369
Telehealth Resource Center, 382
telehealth technology, 209
telehome care, 368
telehospice, 369
TeleICU Model of Success, 372
TeleICU Nursing Practice Guidelines, 372
Telemed Tablet, 386
telemedicine, 362, 366, 373
telemental health, 368
Telemetry Charge Nurse, 298
telemonitoring, 362, 369

applications of. See home telehealth care
at-risk populations, 373
home. See home telemonitoring

telenursing, 370–372
telepalliative care, 369
telepathology, 362
telephones, 376
telephony, 369
teleradiology, 362
telerehabilitation, 368
TELOS strategy, 178
terabytes (TB), 44
terminology, 114b

administrative and reference, 280b

ANA-recognized terminologies, 279
standardized, 278–280

Theory of Human Caring, 526
three-dimensional (3D) view, 446
three dimensional virtual world, 451
throughput/processing components, 52–53
thumb drives, 233
tiering, 197
TIGER. See Technology Informatics Guiding
Education Reform
TIGER-based Assessment of Nursing Informatics
Competencies (TANIC), 46, 135

self-assessment instrument, 137

timeboxing, 183
timely information, 24
To Err Is Human, 152, 294
touch pad, 52
touch screen, 52
TPO exception, 160
TPS. See Transaction Processing System
Transaction Processing System (TPS), 29b
transcendent presence, 529
Translating Research into Practice Initiative (TRIP),
501
translational bioinformatics, 497
translational informatics, 501
translational research, 497, 497f
transparency, 25

transparent wisdom, 8
treatment/payment/operations, 160
trending, 379
triage, 197, 379–380
TRIP. See Translating Research into Practice
Initiative
Trip database, 503t
Trojan horses, 234
Trust-e, 332
truth, 84
Tuesdays with Morrie (Albom), 529
tuples, 201b
tutorials, 406
Tyler, Denise D., 276–278b, 333–334b

U
ubiquity, 113b
uncertainty, 81
Unified Medical Language System (UMLS), 280b
universal serial bus (USB), 40, 43–44

flash drive, 43, 236

University of Texas Medical Branch School of
Nursing, 422
unstructured data, 477
upper-CASE tools, 184
U.S. Copyright Law, 426
U.S. Department of Energy, 70

U.S. Department of Health and Human Services
(USDHHS), 146, 156, 239, 335, 387
U.S. Department of Veteran’s Affairs National
Center for Patient Safety, 295
U.S. National Library of Medicine, 332
usability, 218

consideration of, 383

USB. See universal serial bus
USDHHS. See U.S. Department of Health and
Human Services
user-centered design, 214
user-friendly aspects, 37
user interface, 47
utility, 25

V
value-added activities/steps, 253–255
value added vs. non–value added activities/step,
253–255
values, 77
variation, 255
veracity, 92
verifiable information, 25
video adapter cards, 44
video data, 22
videocameras, 376–377
videophones, 376–377
videopods, 419

Virginia Mason University Medical Center, 251
virtual memory, 42
virtual private networks (VPNs), 239
virtual reality, 60–61, 413, 427
virtual simulation, 433, 435f
virtual worlds

case scenario, 446–448
choosing among simulations, educational
games, and virtual worlds, 451–452
in education, 450–451
future of, 452–453
simulation, game mechanics and, 446–448

virtue, 85
ethics, 85, 93

viruses, 234
Visible Analyst, 184
voice-activated communicators, 60
Voice over Internet Protocol, 298
voice recognition software, 335
Von Neumann, John, 38
VPNs. See virtual private networks

W
W3C. See World Wide Web Consortium
Walgreens’ Healthcare Clinics, 385
Walt Disney Company, 258
Walter Reed Army Research Institute, 106

Washington Post, 211
waste, 255
waterfall model, 178–180
Watson, Jean, 526
wearable technology, 59, 311, 337
WEB 2.0, 55–56b
Web-based courses, 398, 403

types of interactions in, 398f

Web-based education, 402
Web-based medical chart (WMC), 441
Web-based simulation, 441
Web-based survey, 314
Web-based technology, 309
Web-enhanced courses, 398
Web-enhanced learning, 404
Web logs, 416
Web ontology language (OWL), 115b
Web publishing, 408b
Web quests, 323
Web search, 417b
Web servers, 375
webcasts, 414
webinars, 414
weblog, 330
WebMD, 416
websites

for ANA-approved nursing languages, 116b
dynamic webpage shells, 441
health-related, 83

for patient education, 332b
patient safety, 316t
standards for ethical development of, 83
user surveys for design, 236

well-baby care, 181
Well-Intentioned Providers, 298

case scenario, 300

Wellness Alliance, 176–177, 181
Wellness Program Coordinator, 176
Werley, Harriet, 106
WHO. See World Health Organization
Wide-ranging Online Data for Epidemiologic
Research, 348
Wi-Fi, 53
wiki, 414
Wikipedia, 414
Wired for Health Care Quality Act (2005), 303
wisdom, 35, 108, 110–111, 111f

as cardinal virtue, 85
in decision making, 69–70
definition of, 69
knowledge and, 12
transparent, 8
working, 61

WISH Patient Safety Forum, 297
WMC. See web-based medical chart
word processing, 48

work domain analysis, 215
work process, 249
workarounds, 211, 295
worker competencies analysis, 216
workflow

definition of, 249
paper-based, 251
and technology, 249–251
transitioning to future state, 255–256
variation in, 255

workflow analysis, 249
case study, 251
future directions, 259–260
and informatics practice, 251–256
optimization, 250–251
purpose, 245–248
value added vs. non–value added activities/step,
253–255

workflow redesign, 260
team building for, 252–253

working wisdom, 61
Workplace Competencies, 267
workspace security discipline, 233
World Health Organization (WHO), 341

Alliance for Patient Safety, 294

World Views on Evidence-Based Nursing, 503t

World Wide Web (WWW), 54
World Wide Web Consortium (W3C), 115b
worms, 234
written documents, 470
WWW. See World Wide Web

X
XML. See Extensible Markup Language

Y
YB. See yottabytes
yottabytes (YB), 45
Youth Risk Behavior Surveillance System, 347

Z
ZB. See zettabytes
zero day attack, 233
zettabytes (ZB), 45
Zika virus, 342

  • Cover Page
  • Title Page
  • Copyright Page
  • Contents
  • Preface
  • Acknowledgments
  • Contributors
  • Section I: Building Blocks of Nursing Informatics
    • 1 Nursing Science and the Foundation of Knowledge
      • Introduction
      • Quality and Safety Education for Nurses
      • Summary
      • References
    • 2 Introduction to Information, Information Science, and Information Systems
      • Introduction
      • Information
      • Information Science
      • Information Processing
      • Information Science and the Foundation of Knowledge
      • Introduction to Information Systems
      • Summary
      • References
    • 3 Computer Science and the Foundation of Knowledge Model
      • Introduction
      • The Computer as a Tool for Managing Information and Generating Knowledge
      • Components
      • What Is the Relationship of Computer Science to Knowledge?
      • How Does the Computer Support Collaboration and Information Exchange?
      • Cloud Computing
      • Looking to the Future
      • Summary
      • Working Wisdom
      • Application Scenario
      • References
    • 4 Introduction to Cognitive Science and Cognitive Informatics
      • Introduction
      • Cognitive Science
      • Sources of Knowledge
      • Nature of Knowledge
      • How Knowledge and Wisdom Are Used in Decision Making
      • Cognitive Informatics
      • Cognitive Informatics and Nursing Practice
      • What Is AI?
      • Summary
      • References
    • 5 Ethical Applications of Informatics
      • Introduction
      • Ethics
      • Bioethics
      • Ethical Issues and Social Media
      • Ethical Dilemmas and Morals
      • Ethical Decision Making
      • Theoretical Approaches to Healthcare Ethics
      • Applying Ethics to Informatics
      • Case Analysis Demonstration
      • New Frontiers in Ethical Issues
      • Summary
      • References
  • Section II: Perspectives on Nursing Informatics
    • 6 History and Evolution of Nursing Informatics
      • Introduction
      • The Evolution of a Specialty
      • What Is Nursing Informatics?
      • The DIKW Paradigm
      • Capturing and Codifying the Work of Nursing
      • The Nurse as a Knowledge Worker
      • The Future
      • Summary
      • References
    • 7 Nursing Informatics as a Specialty
      • Introduction
      • Nursing Contributions to Healthcare Informatics
      • Scope and Standards
      • Nursing Informatics Roles
      • Specialty Education and Certification
      • Nursing Informatics Competencies
      • Rewards of NI Practice
      • NI Organizations and Journals
      • The Future of Nursing Informatics
      • Summary
      • References
    • 8 Legislative Aspects of Nursing Informatics: HITECH and HIPAA
      • Introduction
      • HIPAA Came First
      • Overview of the HITECH Act
      • How a National HIT Infrastructure Is Being Developed
      • How the HITECH Act Changed HIPAA
      • Implications for Nursing Practice
      • Future Regulations
      • Summary
      • References
  • Section III: Nursing Informatics Administrative Applications: Precare and Care Support
    • 9 Systems Development Life Cycle: Nursing Informatics and Organizational Decision Making
      • Introduction
      • Waterfall Model
      • Rapid Prototyping or Rapid Application Development
      • Object-Oriented Systems Development
      • Dynamic System Development Method
      • Computer-Aided Software Engineering Tools
      • Open Source Software and Free/Open Source Software
      • Interoperability
      • Summary
      • References
    • 10 Administrative Information Systems
      • Introduction
      • Types of Healthcare Organization Information Systems
      • Communication Systems
      • Core Business Systems
      • Order Entry Systems
      • Patient Care Support Systems
      • Interoperability
      • Aggregating Patient and Organizational Data
      • Department Collaboration and Exchange of Knowledge and Information
      • Summary
      • References
    • 11 The Human–Technology Interface
      • Introduction
      • The Human–Technology Interface
      • The Human–Technology Interface Problem
      • Improving the Human–Technology Interface
      • A Framework for Evaluation
      • Future of the Human–Technology Interface
      • Summary
      • References
    • 12 Electronic Security
      • Introduction
      • Securing Network Information
      • Authentication of Users
      • Threats to Security
      • Security Tools
      • Offsite Use of Portable Devices
      • Summary
      • References
    • 13 Workflow and Beyond Meaningful Use
      • Introduction
      • Workflow Analysis Purpose
      • Workflow and Technology
      • Workflow Analysis and Informatics Practice
      • Informatics as a Change Agent
      • Measuring the Results
      • Future Directions
      • Summary
      • References
  • Section IV: Nursing Informatics Practice Applications: Care Delivery
    • 14 The Electronic Health Record and Clinical Informatics
      • Introduction
      • Setting the Stage
      • Components of Electronic Health Records
      • Advantages of Electronic Health Records
      • Standardized Terminology and the EHR
      • Ownership of Electronic Health Records
      • Flexibility and Expandability
      • Accountable Care Organizations and the EHR
      • The Future
      • Summary
      • References
    • 15 Informatics Tools to Promote Patient Safety and Quality Outcomes
      • Introduction
      • What Is a Culture of Safety?
      • Strategies for Developing a Safety Culture
      • Informatics Technologies for Patient Safety
      • Role of the Nurse Informaticist
      • Summary
      • References
    • 16 Patient Engagement and Connected Health
      • Introduction
      • Consumer Demand for Information
      • Health Literacy and Health Initiatives
      • Healthcare Organization Approaches to Engagement
      • Promoting Health Literacy in School-Aged Children
      • Supporting Use of the Internet for Health Education
      • Future Directions for Engaging Patients
      • Summary
      • References
    • 17 Using Informatics to Promote Community/Population Health
      • Introduction
      • Core Public Health Functions
      • Community Health Risk Assessment: Tools for Acquiring Knowledge
      • Processing Knowledge and Information to Support Epidemiology and Monitoring Disease Outbreaks
      • Applying Knowledge to Health Disaster Planning and Preparation
      • Informatics Tools to Support Communication and Dissemination
      • Using Feedback to Improve Responses and Promote Readiness
      • Summary
      • References
    • 18 Telenursing and Remote Access Telehealth
      • Introduction
      • The Foundation of Knowledge Model and Home Telehealth
      • Nursing Aspects of Telehealth
      • History of Telehealth
      • Driving Forces for Telehealth
      • Telehealth Care
      • Telenursing
      • Telehealth Patient Populations
      • Tools of Home Telehealth
      • Home Telehealth Software
      • Home Telehealth Practice and Protocols
      • Legal, Ethical, and Regulatory Issues
      • The Patient’s Role in Telehealth
      • Telehealth Research
      • Evolving Telehealth Models
      • Parting Thoughts for the Future and a View Toward What the Future Holds
      • Summary
      • References
  • Section V: Education Applications of Nursing Informatics
    • 19 Nursing Informatics and Nursing Education
      • Introduction: Nursing Education and the Foundation of Knowledge Model
      • Knowledge Acquisition and Sharing
      • Evolution of Learning Management Systems
      • Delivery Modalities
      • Technology Tools Supporting Education
      • Internet-Based Tools
      • Promoting Active and Collaborative Learning
      • Knowledge Dissemination and Sharing
      • Exploring Information Fair Use and Copyright Restrictions
      • The Future
      • Summary
      • References
    • 20 Simulation, Game Mechanics, and Virtual Worlds in Nursing Education
      • Introduction
      • Simulation in Nursing Informatics Education
      • Nursing Informatics Competencies in Nursing Education
      • A Case for Simulation in Nursing Informatics Education and Nursing Education
      • Incorporating EHRs into the Learning Environment
      • Challenges and Opportunities
      • The Future of Simulation in Nursing Informatics Education
      • Game Mechanics and Virtual World Simulation for Nursing Education
      • Game Mechanics and Educational Games
      • Virtual Worlds in Education
      • Choosing Among Simulations, Educational Games, and Virtual Worlds
      • The Future of Simulations, Games, and Virtual Worlds in Nursing Education
      • Summary
      • References
  • Section VI: Research Applications of Nursing Informatics
    • 21 Nursing Research: Data Collection, Processing, and Analysis
      • Introduction: Nursing Research and the Foundation of Knowledge Model
      • Knowledge Generation Through Nursing Research
      • Acquiring Previously Gained Knowledge Through Internet and Library Holdings
      • Fair Use of Information and Sharing
      • Informatics Tools for Collecting Data and Storage of Information
      • Tools for Processing Data and Data Analysis
      • The Future
      • Summary
      • References
    • 22 Data Mining as a Research Tool
      • Introduction: Big Data, Data Mining, and Knowledge Discovery
      • KDD and Research
      • Data Mining Concepts
      • Data Mining Techniques
      • Data Mining Models
      • Benefits of KDD
      • Data Mining and Electronic Health Records
      • Ethics of Data Mining
      • Summary
      • References
    • 23 Translational Research: Generating Evidence for Practice
      • Introduction
      • Clarification of Terms
      • History of Evidence-Based Practice
      • Evidence
      • Bridging the Gap Between Research and Practice
      • Barriers to and Facilitators of Evidence-Based Practice
      • The Role of Informatics
      • Developing EBP Guidelines
      • Meta-Analysis and Generation of Knowledge
      • The Future
      • Summary
      • References
    • 24 Bioinformatics, Biomedical Informatics, and Computational Biology
      • Introduction
      • Bioinformatics, Biomedical Informatics, and Computational Biology Defined
      • Why Are Bioinformatics and Biomedical Informatics So Important?
      • What Does the Future Hold?
      • Summary
      • References
  • Section VII: Imagining the Future of Nursing Informatics
    • 25 The Art of Caring in Technology-Laden Environments
      • Introduction
      • Caring Theories
      • Presence
      • Strategies for Enhancing Caring Presence
      • Reflective Practice
      • Summary
      • References
    • 26 Nursing Informatics and the Foundation of Knowledge
      • Introduction
      • Foundation of Knowledge Revisited
      • The Nature of Knowledge
      • Knowledge Use in Practice
      • Characteristics of Knowledge Workers
      • Knowledge Management in Organizations
      • Managing Knowledge Across Disciplines
      • The Learning Healthcare System
      • Summary
      • References
  • Abbreviations
  • Glossary
  • Index

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