TECHNOLOGY

NURSING INFORMATICS AND THE FOUNDATION OF KNOWLEDGE

THIRD EDITION

The Pedagogy

Nursing Informatics and the Foundation of Knowledge, Third 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:

NURSING INFORMATICS AND THE FOUNDATION OF KNOWLEDGE

THIRD EDITION

Dee McGonigle, PhD, RN, CNE, FAAN, ANEF Chair, Virtual Learning Environments and Professor, Graduate Programs

Chamberlain College of Nursing Member, Informatics and Technology Expert Panel (ITEP)

American Academy of Nursing Member, Serious Gaming and Virtual Environments Special Interest Group for the Society for Simulation in Healthcare (SSH)

Kathleen Mastrian, PhD, RN Associate Professor and Program Coordinator for Nursing

Pennsylvania State University, Shenango Sr. Managing Editor, Online Journal of Nursing Informatics (OJNI)

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Library of Congress Cataloging-in-Publication Data Nursing informatics and the foundation of knowledge / [edited by] Dee McGonigle, Kathleen Mastrian.—3e.

p. ; cm. Includes bibliographical references and index. ISBN 978-1-284-04158-3 (paperback) I. McGonigle, Dee, editor of compilation. II. Mastrian, Kathleen Garver, editor of compilation. [DNLM: 1. Nursing Informatics. 2. Knowledge. WY 26.5] RT50.5 651.5’04261—dc23

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Contents

Preface Acknowledgments Authors’ Note Contributors

SECTION I: BUILDING BLOCKS OF NURSING INFORMATICS

1 Nursing Science and the Foundation of Knowledge Kathleen Mastrian and Dee McGonigle

Introduction Quality and Safety Education for Nurses Summary References

2 Introduction to Information, Information Science, and Information Systems Dee McGonigle and Kathleen Mastrian

Introduction Information Information Science Information Processing Information Science and the Foundation of Knowledge Introduction to Information Systems Information Systems Summary References

3 Computer Science and the Foundation of Knowledge Model 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? What Is the Human–Technology Interface? Looking to the Future Summary Working Wisdom Application Scenario Internet and Software Resources References

4 Introduction to Cognitive Science and Cognitive Informatics Dee McGonigle and Kathleen Mastrian

Introduction Cognitive Science Sources of Knowledge Nature of Knowledge How Knowledge and Wisdom Are Used in Decision Making Cognitive Informatics CI and Nursing Practice What Is AI? Summary References

5 Ethical Applications of Informatics Kathleen Mastrian, Dee McGonigle, 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 Overview of Nursing Informatics Ramona Nelson and Nancy Staggers

Introduction Metastructures, Concepts, and Tools of NI The Future of NI Summary References

7 Informatics Roles and the Knowledge Work of Nursing Julie A. Kenney and Ida Androwich

Introduction The Nurse as a Knowledge Worker The Knowledge Needs and Competencies of Nurses What Is Nursing Informatics Specialty Practice? The Future of Nursing Informatics Summary References

8 Information and Knowledge Needs of Nurses in the 21st Century Lynn M. Nagle, Nicholas Hardiker, Kathleen Mastrian, and Dee McGonigle

Introduction Definition and Goal of Informatics Health Information Technologies Impacting Nursing Nurses Creating and Deriving New Knowledge Generating Nursing Knowledge Challenges in Getting There The Future Summary References

9 Legislative Aspects of Nursing Informatics: HITECH and HIPAA Kathleen M. Gialanella, Kathleen Mastrian, and Dee McGonigle

Introduction Overview of the HITECH Act How a National HIT Infrastructure Is Being Developed How the HITECH Act Changed HIPAA Implications for Nursing Practice Summary References

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

10 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

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

12 The Human–Technology Interface Judith A. Effken, Dee McGonigle, and Kathleen Mastrian 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

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

14 Nursing Informatics: Improving Workflow and Meaningful Use Denise Hammel-Jones, Dee McGonigle, and Kathleen Mastrian 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

15 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 Ownership of Electronic Health Records Flexibility and Expandability The Future Summary References

16 Informatics Tools to Promote Patient Safety and Clinical Outcomes Kathleen Mastrian and Dee McGonigle 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

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

18 Using Informatics to Promote Community/Population Health Margaret Ross Kraft, Ida Androwich, Kathleen Mastrian, and Dee McGonigle 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

19 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 History of Telehealth Nursing Aspects 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 A Day in the Life of a Home Telenurse The Patient’s Role in Telehealth Telehealth Research The Foundation of Knowledge Model and Home Telehealth Parting Thoughts for the Future and a View Toward What the Future Holds Summary References

SECTION V: EDUCATION APPLICATIONS OF NURSING INFORMATICS

20 Nursing Informatics and Nursing Education Heather E. McKinney, Sylvia DeSantis, Dee McGonigle, and Kathleen Mastrian Introduction: Nursing Education and the Foundation of Knowledge Model Knowledge Acquisition and Sharing Hardware and Software Considerations Delivery Modalities Technology Tools Internet Tools: Webcasts, Searching, Instant Messaging, Chats and Online Discussions, Electronic Mailing Lists, and Portals Promoting Active and Collaborative Learning

Knowledge Assessment Methods Knowledge Dissemination and Sharing The Future Exploring Information Fair Use and Copyright Restrictions Summary References

21 Simulation in Nursing Informatics Education Nickolaus Miehl Introduction Nursing Informatics Competencies in Nursing Education A Case for Simulation Incorporating EHRs into the Learning Environment Challenges and Opportunities What Does the Future Hold? Summary References

22 Games, Simulations, and Virtual Worlds for Educators Brett Bixler Introduction Case Scenario Educational Games Educational Simulations Virtual Worlds Choosing Among Educational Games, Simulations, and Virtual Worlds The Future of Games, Virtual Worlds, and Simulations Summary References

SECTION VI: NURSING INFORMATICS: RESEARCH APPLICATIONS

23 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

24 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 Ethics of Data Mining Summary References

25 Translational Research: Generating Evidence for Practice Jennifer Bredemeyer and Ida Androwich 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

26 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

27 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

28 Emerging Technologies and the Generation of Knowledge Peter J. Murray, W. Scott Erdley, Dee McGonigle, and Kathleen Mastrian Introduction Looking Back from the Future Historical Overview Some Technologies of Today Some Views of What Will Affect the Future Some Emerging Technologies and Other Issues That Will Impact Nursing and Health Care 491 Summary References

29 Nursing Informatics and the Foundation of Knowledge Dee McGonigle and Kathleen Mastrian Introduction Foundation of Knowledge Revisited Knowledge Use in Practice 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. 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 this, 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.

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 reexploring 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.

• The Building Blocks of Nursing Informatics section covers the building blocks of NI: nursing science, information science, computer science, cognitive science, and the ethical management of information.

• The Perspectives on Nursing Informatics section provides readers with a look at various viewpoints on NI and NI practice as described by experts in the field.

• The Nursing Informatics Administrative Applications: Precare and Care Support section covers important functions of administrative applications of NI.

• The Nursing Informatics Practice Applications: Care Delivery section covers healthcare delivery applications including electronic health records (EHRs), clinical information systems, telehealth, patient safety, patient and community education,

and care management. • The Education Applications of Nursing Informatics section presents subject matter on how informatics supports nursing

education. • The Nursing Informatics: Research Applications section covers informatics tools to support nursing research, including data

mining and bioinformatics. • The Imagining the Future of Nursing Informatics section focuses on the future of NI, emphasizes the need to preserve caring

functions in technology-laden environments, and summarizes the relationship of informatics to the Foundation of Knowledge model and 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. 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 and Becky Myrick. Both fielded our questions and concerns in a very professional and respectful manner.

Dee acknowledges the undying love, support, patience, and continued encouragement of her best friend and husband, Craig, and her son, Craig, who has also 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 Bob and Rosalie Garver. Kathy also acknowledges those friends who understand the importance of validation, especially Katie, Bobbie, Kathy, Anne, and Barbara.

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

Eric R. Doerfler, PhD, NP Pennsylvania State University School of Nursing Middletown, PA

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

William Scott Erdley, DNS, RN Niagara University Niagara University, NY

Nedra Farcus, MSN, RN 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 Pennsylvania State University Erie, PA

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

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

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 feedback on their new knowledge of the building blocks of NI.

Figure I-1 Foundation of Knowledge Model Source: Designed by Alicia Mastrian.

Chapter 1

Nursing Science and the Foundation of Knowledge Kathleen Mastrian and Dee McGonigle

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 is defined as the combination of nursing science, information science, and computer science. This chapter focuses on nursing science as one of the building blocks of nursing informatics, although in this text the traditional definition of nursing informatics is extended to include cognitive science as one of the building blocks. 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 (2003) defines nursing in this way: “Nursing is the protection, promotion, and optimization of health and abilities, prevention of illness and injury, alleviation of suffering through the diagnosis and treatment of human response, and advocacy in the care of individuals, families, communities, and populations” (p. 6). 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.

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 and 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 (an idea discussed further in the Introduction to Cognitive Science and Cognitive Informatics chapter). 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 reexplore 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 (computer terms for chunks of information), data, and information in a random representation (Figure 1-1). 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 they 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.

Figure 1-1 Foundation of Knowledge Model Source: Designed by Alicia Mastrian.

The Foundation of Knowledge model 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 in each section of the text 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 personal digital assistant (PDA) or that reside 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 and are covered in detail in the Nursing Informatics Administrative Applications: Precare and Care Support and Nursing Informatics Practice Applications: Care Delivery sections of this text. Technologies that support and inform nursing education and nursing research are covered in the Education Applications and Research Applications of Nursing Informatics sections respectively.

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 PDA or 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) suggests 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, Greenfield (2007) conducted research among nursing students to determine the effectiveness of PDA technology applied to medication administration. Her study makes a good case for incorporating such technology into nursing curricula. 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 makes 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 addresses 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 are promoting the inclusion of informatics content in nursing education programs. These initiatives include a proposal by the National League for Nursing (NLN, 2008); recommendations in the Quality and Safety Education for Nurses (Cronenwett et al., 2007) report; the Technology Informatics Guiding Education Reform (TIGER) Initiative (2007); and a plan by the American Association of Colleges of Nursing (AACN, 2008).

The NLN’s (2008) position statement, Preparing the Next Generation of Nurses to Practice in a Technology-Rich Environment: An Informatics Agenda, challenges nurse educators to prepare informatics-competent nurses who can practice safely in a technology- rich healthcare environment.

In the Quality and Safety Education for Nurses (2007) report, Cronenwett and colleagues identified several core competencies for nursing education. One competency specifically addressed nursing informatics: “Use information and technology to communicate, manage knowledge, mitigate error, and support decision-making” (p. 129). Another addressed the appropriate use of data and information in nursing practice to promote quality improvement: “Use data to monitor the outcomes and processes and use improvement methods to design and test changes to continuously improve the quality and safety of health care systems” (p. 127).

The TIGER (2007) initiative identifies 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 Quality and Safety Education for Nurses (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, n.d.b):

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

Appreciate the necessity for all health professionals to seek lifelong, continuous learning of information technology skills

processes of care

Identify essential information that must be available in a common database to support patient care

Contrast benefits and limitations of different communication technologies and their impact on safety and quality

Navigate the electronic health record

Document and plan patient care in an electronic health record

Employ communication technologies to coordinate care for patients

Value technologies that support clinical decision making, error prevention, and care coordination

Protect the 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 the outcomes of care processes

Value nurses’ involvement in design, selection, implementation, and evaluation of information technologies to support patient care

Use high-quality electronic sources of health-care information

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

Reprinted from Nursing Outlook, 55(3), Cronenwett, L., Sherwood, G., Barnsteiner J., Disch, J., Johnson, J., Mitchell, P., Sullivan, D., Warren, J., Quality and safety education for nurses, pages 122–131. copyright 2007, with permission from Elsevier.

Graduate-level informatics KSAs include the following (QSEN Institute, n.d.a):

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 the implementation and appropriate use of electronic health records

Assist team members to adopt information technology by piloting and evaluating proposed technologies

Value the use of information and communication technologies in patient care

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 and knowledge management systems

Access and evaluate high-quality electronic sources of healthcare information

Participate in the 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

Value the importance of standardized terminologies in conducting searches for patient information

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.

Reprinted from Nursing Outlook, 57(6), Cronenwett, L., Sherwood, G., Pohl, J., Barnsteiner, J., Moore, S., Sullivan, D., Ward, D., Warren, J.,

Quality and safety education for advanced nursing practice, pages 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.

Goossen (2000) believes 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 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, 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.

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.

http://www.aacn.nche.edu/education-resources/MastersEssentials11.pdf American Nurses Association. (2003). Nursing’s social policy statement (2nd ed.). Silver Spring, MD: Author. 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]. Greenfield, S. (2007). Medication error reduction and the use of PDA technology. Journal of Nursing Education, 46(3), 127–131. Retrieved from

Education Module database [document ID: 1227347171]. National League for Nursing (NLN). (2008). Preparing the next generation of nurses to practice in a technology rich environment: An informatics

agenda [Position statement]. http://www.nln.org/aboutnln/PositionStatements/informatics_052808.pdf QSEN Institute. (n.d.a). Graduate KSAs. http://qsen.org/competencies/graduate-ksas/ QSEN Institute. (n.d.b). Pre-licensure KSAs. http://qsen.org/competencies/Pre-licensure-ksas/Skiba, D. (2007). Faculty 2.0: Flipping the novice to expert

continuum. Nursing Education Per- spectives, 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

Economics, 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.

http://www.tigersummit.com/uploads/TIGERInitiative_Report2007_Color.pdf

Chapter 2

Introduction to Information, Information Science, and Information Systems Dee McGonigle and Kathleen Mastrian

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 officer Chief technical officer Chief technology officer Cloud computing Cognitive science Communication science Computer-based information system Computer science Consolidated Health Informatics Data Dissemination Document Electronic health record Federal Health Information Exchange Feedback Health information exchange Health Level Seven Indiana Health Information Exchange Information Information science Information system Information technology Input Interface Internet2 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 Stakeholder Summaries Synthesis Telecommunications

Introduction This chapter explores information, information systems (IS), and information science. The key word here, of course, is information. Healthcare professionals are knowledge workers, and they deal with information on a daily basis. Many concerns and issues arise with healthcare information, such as ownership, access, disclosure, exchange, security, privacy, disposal, and dissemination. With the gauntlet of developing electronic health records having been laid down, publicand private-sector stakeholders have been collaborating on a wide-ranging variety of healthcare information solutions. These initiatives include Health Level Seven (HL7), Consolidated Health Informatics’ (CHI’s) eGov initiative, 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). The most recent federal government initiative, the HITECH Act, has set 2014 as the deadline for implementing electronic health records (see the Legislative Aspects of Nursing Informatics: HITECH and HIPAA chapter).

It is quite evident from the previous brief listing that there is a need to remedy healthcare information technology 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 care possible 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 include 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 integrity and quality of the data, rather than the form, are what matter. Integrity refers to whole, complete, correct, and consistent data. 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. 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.

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 right 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, then 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 and 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. 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 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 some 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 information systems (IS). This extensive, interdisciplinary science integrates features from cognitive science, communication science, computer science, library science, and 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 information technology 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 focuses 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 Claude E. Shannon, who is considered the father of information theory (Horgan, 1990), thought of information processing as the conversion of latent information into manifest information. Latent information is that which is not yet realized or apparent, whereas manifest information is obvious or clearly apparent. According to O’Connor and Robertson (2005), “Shannon believed that information was no different than any other quantity and therefore could be manipulated by a machine” (para. 13).

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 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 cuttingedge, 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 information technology 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 information technology 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.

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), computer-based ISs “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 set of interrelated components that collect, manipulate, store and disseminate data and information and provide a feedback mechanism to meet an objective” (Stair & Reynolds, 2008, 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 (see the Systems Development Life Cycle: Nursing Informatics and Organizational Decision Making chapter). 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.

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 electronic health record (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 toprocess 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 hospitalenterprise. It should help to link financial and clinical outcomes.

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 and include 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. Reports are designed to inform and are 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. Documents represent information that can be printed, saved, e-mailed or otherwise shared, or displayed. Summaries are condensed versions of the original designed to highlight the major points. Alerts are warnings, feedback, or additional information necessary to assist the user in interacting with the system. Outcomes are the expected results 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 information technology (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.

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, hand-held, 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. http://www.infosci.cornell.edu/ Goldstein, D., Groen, P., Ponkshe, S., & Wine, M. (2007). Medical informatics 20/20. Sudbury, MA: Jones and Bartlett. Horgan, J. (1990). Claude E. Shannon: Unicyclist, juggler and father of information theory. Retrieved March 2008 from

http://www.ecs.umass.edu/ece/hill/ece221.dir/shannon.html HµREL Corporation. (2010). Human-relevant: HµREL. Technology overview. http://www.hurelcorp.com/overview.php Jessup, L., & Valacich, J. (2008). Information systems today (3rd ed.). Upper Saddle River, NJ: Pearson Prentice Hall. O’Connor, J., & Robertson, E. (2005). Claude Elwood Shannon. http://www.thocp.net/biographies/shannon_claude.htm Schupak, A. (2005). Technology: The bunny chip. http://members.forbes.com/forbes/2005/0815/053.html Stair, R., & Reynolds, G. (2008). Principles of information systems (8th ed.). Boston, MA: Thomson Course Technology. Web Dictionary of Cybernetics and Systems. (2007). Technological determinism. http://pespmc1.vub.ac.be/ASC/TECHNO_DETER.html

Chapter 3

Computer Science and the Foundation of Knowledge Model 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. Articulate how computers can support collaboration, networking, and information exchange.

Key Terms

Acquisition Applications Arithmetic logic unit (ALU) Basic input/output system (BIOS) Binary system Bit Bus Byte Cache memory Central processing unit (CPU) Communication software Compact disk read-only memory (CD-ROM) Compact disk-recordable (CD-R) Compact disk-rewritable (CD-RW) Compatibility Computer Computer science Conferencing software Creativity software Databases Degradation Desktop Digital video disk (DVD) Digital video disk-recordable (DVD-R) Digital video disk-rewritable (DVD-RW) Dissemination Dynamic random access memory (DRAM) E-mail E-mail client Electronically erasable programmable read-only memory (EEPROM) Exabyte (EB) Execute Extensibility FireWire Firmware Flash memory Gigabyte Gigahertz Graphical user interface Graphics card Hard disk Hard drive Hardware Information

Information Age Instant message (IM) Integrated drive electronics (IDE) Internet browser Keyboard Knowledge Laptop Main memory Mainframes Megabyte (MB) Megahertz (MHz) Memory Microprocessor Microsoft Surface Modem Monitor Motherboard Mouse MPEG-1 Audio Layer-3 (MP3) Networks Nonsynchronous Office suite Open source Operating system (OS) Palm computers Parallel port Peripheral component interconnection (PCI) Personal computer (PC) Personal digital assistant (PDA) Plug and play Port Portability Portable operating system interface for UNIX (POSIX) Power supply Presentation Processing Productivity software Professional development Programmable read-only memory (PROM) Publishing QWERTY Random-access memory (RAM) Read-only memory (ROM) Security Serial port Small Computer System Interface (SCSI) Software Sound card Spreadsheet Supercomputers Synchronous Synchronous dynamic random-access memory (SDRAM) Technology Terabyte (TB) Throughput Touch screen Universal serial bus (USB) User friendly User interface Video adapter card Virtual memory Wearable technology 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 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.

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 computing surfaces, an evolving technology.

According to Intel Corporation’s technology research team, the goal is “technology that just works.” “To conceal complexity, Intel Research is looking at a number of solutions by:

Relating user mental models with complex systems and technology to improve the use and adaptation of systems across devices and contexts.

Enabling devices to explore their environment to discover other devices and capabilities, and then form integrated ‘teams’ that self-organize for higher functionality and performance.

Better control of failure modes, graceful degradation, and self-healing across ensembles of devices. Zero-knowledge applications and interoperation.” (Intel Corporation, 2008, para. 2)

BOX 3-1 MICROSOFT SURFACE TENSION? iTABLE Dee McGonigle Do not get too attached to your mouse and keyboard, because they will be outdated soon if Microsoft and PQ Labs have their way. Microsoft has introduced the Microsoft Surface and PQ Labs is building custom iTables, according to Kumparak (2009). Have you ever thought of digital information you can touch and grab? Microsoft and PQ Labs are leading us into the next generation of computing, known as surface or table computing.

Surface or table computing consists of a multitouch, 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 such devices as a digital camera and personal digital assistant (PDA). This interface generally rests on top of a table and is so advanced that it can actually sense objects, touch, and gestures from many users (Microsoft, 2008).

Imagine entering a restaurant and interacting with the menu through the surface of the table where you sit. 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 PDA. You can set the PDA on the 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 certainly a different kind of eating experience—but one that will become commonplace for the next generation of users.

You might be wondering when this new age of computing will be touched by typical users. In fact, it is already used in Las Vegas, as well as in selected casinos, banks, restaurants, and hotels throughout the United States and Canada.

You should seek to explore this new interface, which will forever change how we interact and compute. Think of the ramifications for health care …

REFERENCES Kumparak, G. (2009). Look out, Microsoft Surface: The iTable might just trump you in every way. http://www.crunchgear.com/2009/01/10/look- out-microsoft-surface-the-itable-mightjust-trump-you-in-every-way/

Microsoft. (2008). Microsoft Surface: General questions. Retrieved May 2010 from http://www.microsoft.com/SURFACE/about_faqs/faqs.aspx

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 flat, horizontally 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 computers combine the casing in a flat rectangular casing that is attached to the hinged or foldable monitor. Palm computers and personal digital assistants also have a protective outer plastic and metal case with an embedded liquid crystal display screen.

Central Processing Unit

Sometimes conceptualized as the “brain” of the computer, the central processing unit (CPU) 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 CPU serves as the command center that directs the actions of all other computer components, and it manages both incoming and outgoing data that are processed across components. Common CPUs include the Pentium, K6, PowerPC, and Sparc models.

The CPU 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 CPU uses the cache to store inprocess data so that it can be quickly retrieved as needed. The CPU 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.

In the past, the speed and power of a CPU 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 CPU that operates at 4 GHz is 1,000 times faster than an older one that operates at 4 MHz. The more cycles a processor can complete per second, the faster computer programs can run.

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, which were traditionally made from off-the-shelf logic or from gate arrays, have been replaced by servers made using microprocessors. Mainframes have been almost replaced with multiprocessors consisting of small numbers of off-the-shelf microprocessors. Even high-end supercomputers are being built with collections of microprocessors” (Hennessy & Patterson, 2006, p. 3).

Motherboard

The motherboard has been called the “central nervous system” of the computer. It is 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, BIOS read-only memory (ROM), 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 240-V 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 W, with an average of 300 to 400 W. 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 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 the gigabytes or even terabytes 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, 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 CPU during write operations (puts them into storage) or read by the CPU 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) is “much faster than conventional (nonsynchronous) memory because it can synchronize itself with a microprocessor’s bus” (Null & Lobor, 2006, p. 8).

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 primarily stored 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 a 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, 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 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), or digital video disk (DVD) drive, and the floppy disk drive.

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. Both compact disk-recordable (CD-R) and compact disk-rewritable (CD-RW) drives are common. The same principle applies to 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 Drive

This portable memory device uses electronically erasable programmable ROM to provide fast permanent memory.

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 adaptors 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: connects to a printer Serial: 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) 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 CPU 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.

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. “End user performance is likely to be facilitated by user

friendliness of software packages” (Mahmood, 2003, p. 71). 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. 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.

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 (bit). 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; a 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.

The next advancements in computer capacity are moving into the range of terabytes (TB), petabytes (PB), exabytes (EB), zettabytes (ZB), and yottabytes (YB). These terms storage capacity are defined as follows:

TB 1,000 GB PB 1,000,000 GB EB 1,000 PB ZB 1,000 EB YB 1,000 ZB

To put all of this in perspective, Williams (n.d., para. 5) writes about the data powers of 10: 2 kilobytes: A typewritten page

2 megabytes: A high-resolution photograph 10 megabytes: A minute of high-fidelity sound or a digital chest X-ray 50 megabytes: A digital mammogram 1 gigabyte: A symphony in high-fidelity sound or a movie at TV quality 1 terabyte: All the X-ray films in a large technologically advanced hospital 2 petabytes: The contents of all U.S. academic research libraries 5 exabytes: All words ever spoken by human beings

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

REFERENCE Williams, R. (n.d.). Data powers of ten. http://ict.stmargaretsacademy.org.uk/computing/hardware/dataquan/d_p_ten2.html

Open Source Software

The open source movement began several years ago, but recently 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. Open Office and KOffice are both examples of open source productivity software.

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 operating systems include the Microsoft Windows family, Linux, Mac OS X, and UNIX. 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 instance, a user can work on a word processing document while listening for an “e-mail received” signal, have a Web 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])

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 (2004) described how the Windows OS has been designed in keeping with the following goals established by Microsoft:

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. Portable operating system interface for UNIX (POSIX) compliance: Applications designed to follow the POSIX (IEEE

1003.1) standard can be compiled to run on Windows without changing the source code. 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 office suites, is the type of software most commonly used both in the workplace and on personal computers. Several software companies produce these multiple-program software, which usually bundles together word processing, spreadsheets, databases, presentation, Web development, and e-mail 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 programs included in five of the most popular office suites: Microsoft Office, Open Office, KOffice, Corel WordPerfect Suite, and Apple iWork (for Macintosh computers). Of these five, Open Office (for Windows, Linux, Solaris, Mac OS X, FreeBSD, and HP-UX OSs) and KOffice (for Linux environments but also being developed for Windows and Mac OS X platforms) are open source, free software.

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).

Communication Software

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

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 WordPerfect 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,

Microsoft Power Point, Open Office Impress, KOffice KPresenter, Corel Show, Apple Keynote

graphs, media

Databases Database creation for text andnumbers

Microsoft Access (in elite packages), Open Office Base, KOffice Kexi, Corel Calculate, Corel Paradox

E-mail Integrated e-mail program to sendand receive electronic mail Microsoft Outlook, Corel WordPerfect Mail, Mozilla Thunderbird

Drawing Graphics and diagram drawing Open Office Draw, Corel Presentation Graphics,KOffice Kivio, Karbon, Krita

Math formulas Inserts math equations in wordprocessing and presentation work Open Office Math, KOffice KFormula

Desktop publishing Page layouts and publication-readydocuments Microsoft Publisher (in elite packages), Apple Pages

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 PhotoImpact, Corel Draw, Painter, and Paint Shop Pro, GIMP (open source), KOffice’s Krita (open source)

Vector graphics programs

Mathematically rendered, geometric modeling is applied through shapes, curves, lines, points and manipulated for shape, color, size. Ideal for printing and three-dimensional (3D) modeling

Adobe Flash, Freehand, and Illustrator, CorelDraw 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, brochures

Adobe InDesign, Corel PageMaker, 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, 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 QuickTime and FinalCut Studio, Corel VideoStudio, Ulead VideoStudio, Real Studio, CamStudio (open source), Audacity (open source)

TABLE 3-3 COMMUNICATION SOFTWARE FEATURES AND EXAMPLES

COMMUNICATI ON SOFTWARE E-mail client Resident programs

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

Microsoft Outlook and Outlook Express, Eudora, Pegasus, Mozilla Thunderbird, Lotus Notes Web-based programs Gmail, 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, hand-held devices Conferencing

MSN Instant Messenger, Microsoft Live Messenger, Yahoo Messenger, Apple iChat

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, screen shots 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; or other plug-and-play input devices, such as digital cameras, digital video recorders (camcorders), MP3 players, electronic musical instruments, and physiologic monitors (Figure 3-1). 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 two primary input devices on a computer are the keyboard and mouse.

Figure 3-1 Computer System

Keyboard

Computer keyboards are 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 101 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.

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.

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 are either 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 instance, 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).

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 quite good quality; 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.

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 just 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 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:

The computer-literate nurse will have knowledge, and as a result, power and influence. Society has accepted computers as standard elements, and as such, computers will continue to shape nurses’ psychological, social, economic, and political existence in innumerable ways. Nursing, in order to interface with other spheres of society, must be computer literate. In short, society has accepted computer technology as a means to enhance life; so must nursing. (Richards, 2001, p. 9)

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.

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; or 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 in their infancy in most nursing work environments (and most nurses’ personal lives), but they are predicted to grow dramatically in the future:

As the Net generation grows in influence, the trend will be toward networks, not hierarchies; toward open collaboration rather than authority; toward consensus rather than arbitrary edict. The communication support provided by networks and information systems will also alter patterns of social interaction within a healthcare organization. This technology provides a medium for greater accessibility to shared information and support for rich interpersonal exchange and collaboration across departmental boundaries. (Richards, 2001, p. 10)

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:

Electronic media do more than just expand access to vast bodies of information. They also serve as a convenient vehicle for building virtual social networks for creating shared knowledge through collaborative learning and problem solving. Cross pollination of ideas through worldwide connectivity can boost creativity synergistically in the co-construction of knowledge. (Bandura, 2002, p. 4)

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; e-mail 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 often 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, 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, e-mail, social networking applications, and web conferencing logs. Box 3-3 provides information on Web 2.0, the latest iteration of the World Wide Web.

BOX 3-3 WEB 2.0 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, 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, 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 launch 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 video conferencing 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 Web conferencing. 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) warns 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 tools are providing a new cyber-playground that is limited only by users’ own imaginations and intelligence. We encourage you to explore these tools. Refer to this text’s companion website (http://go.jblearning.com/mcgonigle) for more information.

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

What Is the Human–Technology Interface? In the context of using a computer system, the human–technology interface is facilitated by the input and output devices discussed previously in this chapter. Specifically, the keyboard, mouse, monitor, laser pen, joystick, stylus, or game pads and controls, and other

USB or plug-and-play devices, such as MP3 players, digital cameras, digital camcorders, musical instruments, and hand-held smaller computers, such as personal digital assistants, are all viable devices for interfacing with a computer.

The GUI associated with the OS of a computer provides the on-screen environment for direct interaction between the user and the computer. The typical GUI provided by Windows or Mac OS X utilizes a user-friendly desktop metaphor interface that is made up of the input and output devices and icons that represent files, programs, actions, and processes. These interface icons can be activated by clicking the mouse buttons to perform various actions, such as provide information, execute functions, open and manipulate folders (directories), select options, and so forth.

Although these aspects of a computer system may be taken for granted, they are critical in facilitating a sense of comfort and competency in users of the system. This environment is particularly critical in nursing, when computers are used in the context of nursing care. One question that arises is, Do nurses control these information technology tools, or do the tools shape the activities, decisions, and attention of the nurses as users of technology? Both possibilities can be answered in the affirmative to some extent, but the former is the safest situation for nursing care. (See The Art of Caring in Technology-Laden Environments for an expanded discussion of this issue). If the nurse user needs to focus on the software or hardware because of difficult-to-use programs, confusing GUI schema, or sheer complexity in the programming, the nurse’s provision of client care will suffer. It is critical that any software and hardware used in the nursing milieu be expertly designed to facilitate nursing care in a user-friendly, intuitive way. This is one reason that informatics experts, called nurse informaticians, are being placed in positions of authority where they can facilitate the adoption of computer systems within nursing care environments. It is essential that the activities of the staff nurses are reflected well within the software that is used in the care setting. If nurses are knowledgeable about computers and related technologies, they will be able to provide meaningful data and information about how computer systems best work within their particular care areas.

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 coming trends toward wearable technology, smaller and faster hand-held 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.

In the future, computers will become more powerful yet more compact, which will contribute to the development of several technologic initiatives that are currently still in their infancy. 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, time-saving, and interactive capabilities emerging from information technology research, the field of nursing informatics will grow in similar proportions.

Voice-Activated Communicators

Voice-activated communicators are already being developed by a variety of companies, including Vocera Communications. These new technologies will permit nurses and other healthcare professionals to use wireless, hands-free devices to communicate with one another and to record data. This technology promises to become a user-friendly and cost-effective way to increase clinical productivity.

Game and Simulation Technology

Game and simulation technology promises to offer realistic, innovative ways to teach nursing content in general, including nursing informatics concepts and skills. The same technology that powers video games can be used to create dynamic educational interfaces to help student nurses learn about pathophysiology, care guidelines, medication usage, and a host of other topics. Such applications can also be very valuable for client education and health promotion materials. The “serious games” industry is just beginning to develop. Video game producers are now 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 (2006), is working on developing best practices to support innovation in healthcare training, messaging, and illness management.

Virtual Reality

Virtual reality is another technological breakthrough that will become common in nursing education and professional development in the future. 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 were 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 provides a sense of presence that is lacking in multimedia and other complex programs.

Mobile Devices

Mobile devices will be used more by nurses both at the point of care and in planning, documenting, interacting with the healthcare team, and research.

There are strong indicators that nursing is ready to move quickly to adopt this new technology and utilize it to its full potential at the point-of-care. We anticipate the rate of adoption for mobile information systems within nursing to be rapid, and it will ultimately equal and perhaps exceed that of physicians. Mobile Nursing Informatics will be at the core of nursing in the 21st century. Ready access to data and analytical tools will fundamentally change the way practitioners of the health sciences conduct research, and approach and solve problems. (Suszka-Hildebrandt, 2000, p. 3)

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 clients 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, 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 interdisciplinary team.

Consider this question: “How can you develop competency in using the various computer hardware and software not only to promote efficient 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 e-mail 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 a Pentium CPU system with 500 GB of storage and 4 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. 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 e-mail 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.

2. How could Dan afford to install software from all four groups on his new laptop? If Dan accessed some open source software (e.g., Open Office for his productivity software), he could save money to put toward creativity software.

Internet and Software Resources BBC Absolute Beginner’s Guide to Using Your Computer: A WebWise Guide. http://www.bbc.co.uk/webwise/abbeg/abbeg.shtml BBC’s Computer Tutor: The BBC’s Guide to Using a Computer. http://www.bbc.co.uk/webwise/topics/your-computer/

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 Bandura, A. (2002). Growing primacy of human agency in adaptation and change in the electronic era. European Psychologist, 7(1), 2–16. Evans, D. (2010). Introduction to computing: Explorations in language, logic, and machines. University of Virginia. http://www.computingbook.org Hennessy, J., & Patterson, D. (2006). Computer architecture: A quantitative approach (4th ed.). San Francisco, CA: Morgan Kaufmann. Intel Corporation. (2008). Concealing complexity. Technology and research. http://techresearch.intel.com/articles/Exploratory/1430.htm

Mahmood, M. (2003). Advanced topics in end user computing. Hershey, PA: Idea Group Inc. Null, L., & Lobor, J. (2006). The essentials of computer organization and architecture (2nd ed.). Sudbury, MA: Jones and Bartlett. Richards, J. A. (2001). Nursing in a digital age. Nursing Economic$, 19(1), 6–12. Robert Wood Johnson Foundation. (2006). Games for health. http://gamesforhealth.org/about/ Sarkar, N. (2006). Tools for teaching computer networking and hardware concepts. Hershey, PA: Idea Group. Silbershatz, A., Baer Galvin, P., & Gagne, G. (2004). Operating system concepts (7th ed.). Hoboken, NJ: John Wiley & Sons. Suszka-Hildebrandt, S. (2000). Mobile information technology at the point-of-care. PDA Cortex. http://www.rnpalm.com/mitatpoc.htm

Chapter 4

Introduction to Cognitive Science and Cognitive Informatics Dee McGonigle and Kathleen Mastrian

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 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. 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).

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. According to Wikipedia (2013), “The term cognitive science was coined by Christopher Longuet-Higgins in his 1973 commentary on the Lighthill report, which concerned the then-current state of artificial intelligence research” (para. 36). 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:

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. (2010, 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 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. Just as neurons form elaborate information processing networks, so artificial neural networks are unique computer programs that model or simulate their biologic analogs.

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. 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) describes 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 suggests 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; 2008, suggests the disciplines of neuroscience, linguistics, AI, and psychology constitute this field. It defines 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 explains 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)

CI 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 they 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 for nursing. 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” (Association for the Advancement of Artificial Intelligence [AAAI], 2007a, para. 1). According to the AAAI (2007b), AI is the “scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines” (para. 2).

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” (AAAI, 2007b, para. 4).

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” (AAAI, 2007b, para. 4).

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.

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 this important work?

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

References Association for the Advancement of Artificial Intelligence (AAAI). (2007a). AI overview. http://www.aaai.org/AITopics/html/overview.html Association for the Advancement of Artificial Intelligence (AAAI). (2007b). Cognitive science.

http://www.aaai.org/aitopics/pmwiki/pmwiki.php/AITopics/CognitiveScience Cognitive Science Society. (2005). CSJ archive. http://www.cogsci.rpi.edu/CSJarchive/1980v04/index.html Cohn, D. (2006). AI reaches the golden years. http://www.wired.com/news/technology/0,71389–0.html Encyclopedia Britannica. (2007). Epistemology. 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. Holt, T. (2006). Sources of knowledge. http://www.theoryofknowledge.info/sourcesofknowledge.html Lamont, I.(2007). The grill: Ray Kurzweil talks about “augmented reality” and the singularity. Retrieved October 2007 from

http://www.computerworld.com/action/article.do?command=viewArticleBasic&articleId=306176 Mastrian, K. (2008, February). Invited editorial: Cognitive informatics and nursing practice. Online Journal of Nursing Informatics, 12(1).

http://ojni.org/12_1/kathy.html Merriam-Webster Online Dictionary. (2007). Logic. http://www.merriam-webster.com/dictionary/logic Pacific Northwest National Laboratory, U.S. Department of Energy. (2008). Cognitive informatics. http://www.pnl.gov/coginformatics/ Shallcross, D. J., & Sisk, D. A. (1999). What is intuition? In T. Arnold (Ed.), Hyponoesis glossary: Intuition.

http://www.hyponoesis.org/Glossary/Definition/Intuition Sivananda, S. (2004). Four sources of knowledge. http://www.dlshq.org/messages/knowledge.htm Stanford Encyclopedia of Philosophy. (2010). Cognitive science. http://plato.stanford.edu/entries/cognitive-science/ 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. Wikipedia. (2013). Cognitive science. http://en.wikipedia.org/wiki/Cognitive_science

Chapter 5

Ethical Applications of Informatics Kathleen Mastrian, Dee McGonigle, 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 Application (app) 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 Ethicist 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 Standard 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 journeys into the brave new world of digital communications, 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 and knowledge development. 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. 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.

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) refer 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) emphasize 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 (also known simply as 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. A sensor attached to the patient’s mobile device 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. 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 are 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 (“White paper,” 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, and YouTube. Other widely used means of instantaneous communications include wikis, blogs, tweeting, Skype, and the “hangout” 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, including a 78% increase in use among the 50- to 64- year-old age group, and a 42% increase in use among persons older than 65 years over a time frame of a little more than 3 years. Facebook reported in June 2012 that it had 955 million active monthly users. Twitter’s influence on health care is suggested by the fact that more than 100 million pieces of healthcare information have been tweeted, with as many as 140 million tweets being recorded in a day’s time (Prasad, 2013, p. 492). Moreover, people spend more than 700 billion minutes per month actively engaged with the Facebook site (Miller, 2011, p. 307).

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. 1). Englund and colleagues (2012) note 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). The mobile device known as the smartphone has the capability to take still pictures as well as make live recordings; it has found its 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 laws. 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).

A white paper published by the National Council of State Boards of Nursing (NCSBN; White paper, 2011) provides a thorough discussion of the issues associated with nurses’ use of social media.

Ethical Dilemmas and Morals Ethical dilemmas arise 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.

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.

Source: 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).

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).

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/).

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 longterm 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 Nicomachean principles (Aristotle, 350 BC) 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 (Healthcare Ethics, 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 (n.d.) states that “Carol Gilligan’s In a Different Voice (1982) established care ethics as a major new perspective in contemporary moral and political discourse” (p. 2). 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 or 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.

Source: 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. Several more case studies presented for practice in implementing the ethical model for ethical decision making are available on the companion website for this text (http://nursing.jbpub.com/informatics).

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

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.

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. Healthcare professionals need to juggle all of these balls simultaneously, 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.

References Alpert, S. (2008). Privacy issues in clinical genomic medicine, or Marcus Welby, M.D., meets the $1000 genome. Cambridge Quarterly of Healthcare

Ethics, 17(4), 373–384. Retrieved from Health Module (Document ID: 1880623501). Anderson, K. (2012, September). Patient care and social media. Australian Nursing Journal, 22. http://go.galegroup.com.silk.library.umass.edu/ps/i.do?

id=GALE%CA301964363&v=2.1&u=mlin_w_umassamh&it=r&p+AONE&sw=w Angst, C. (2009). Protect my privacy or support the common-good? Ethical questions about electronic health information exchanges. Journal of

Business Ethics, 90(suppl), 169–178. Retrieved from ABI/INFORM Global (Document ID: 2051417481). Aristotle. (350 BC). Nichomachean ethics. Book I. (W. D. Ross, Trans.). Retrieved from http://www.constitution.org/ari/ethic_00.htm Beauchamp, T. L., & Childress, J. F. (1977). Principles of biomedical ethics. New York, NY: Oxford University Press. Beauchamp, T. L., & Childress, J. F. (1994). Principles of biomedical ethics (4th ed.). New York, NY: Oxford University Press. Benjamin, M., & Curtis, J. (1992). Ethics in nursing (3rd ed.). New York, NY: Oxford University Press. Derse, A., & Miller, T. (2008). Net effect: Professional and ethical challenges of medicine online. Cambridge Quarterly of Healthcare Ethics, 17(4),

453–464. Retrieved from Health Module (Document ID: 1540615461). eHealth code. (n.d.). http://www.ihealthcoalition.org/ehealth-code/ Englund, H., Chappy, S., Jambunathan, J., & Gohdes, E. (2012, November/December). Ethical reasoning and online social media. Nurse Educator, 37,

242–247. http://dx.doi.org/10.1097/NNE.0b013e31826f2c04 Engster, D. (n.d.). Can care ethics be institutionalized? Toward a caring natural law theory.

https://lmstest.manhattan.edu/pluginfile.php/39833/mod_resource/content/1/Engster%20Care%20and%20Political%20Theory.pdf Healthcare Ethics. (2007). Virtue ethics. http://www.ascensionhealth.org/ethics/public/issues/virtue.asp Howard, R. (Director). (1995). Apollo 13 [Motion picture]. Universal City, CA: MCA Universal Studios. Husted, G. L., & Husted, J. H. (1995). Ethical decision-making in nursing (2nd ed.). New York, NY: Mosby. International Council of Nurses (ICN). (2006). The ICN code of ethics for nurses. http://www.icn.ch/icncode.pdf Jonsen, A. R. (1991). Casuistry as methodology in clinical ethics. Theoretical Medicine, 12, 295–307. Lyons, R., & Reinisch, C. (2013). The legal and ethical implications of social media in the emergency department. Advanced Emergency Nursing

Journal, 35(1), 53–56. http://dx.doi.org/10.1097/TME.0b013e31827a4926 Mack, J. (2000). Patient empowerment, not economics, is driving e-health: Privacy and ethics issues need attention too! Frontiers of Health Services

Management, 17(1), 39–43; discussion 49–51. Retrieved from ABI/INFORM Global (Document ID: 59722384). Makus, R. (2001). Ethics and Internet healthcare: An ontological reflection. Cambridge Quarterly of Healthcare Ethics, 10(2), 127–136. Retrieved from

Health Module (Document ID: 1409693941). Martin, P. A. (1999). Bioethics and the whole: Pluralism, consensus, and the transmutation of bioethical methods into gold. Journal of Law, Medicine &

Ethics, 27(4), 316–327.

McGonigle, D. (2000). The ethical model for ethical decision making. Inside Case Management, 7(8), 1–5. Miller, L. A. (2011). Social media: Friend and foe. Journal of Perinatal and Neonatal Nursing, 307–309.

http://dx.doi.org/10.1097/JPN.0b013e31823506e9 Pellegrino, E. D. (1993). The metamorphosis of medical ethics: A thirty-year retrospective. Journal of the American Medical Association, 269, 1158–

1162. Pellegrino, E., & Thomasma, D. (1993). The virtues in medical practice. New York, NY: Oxford University Press. Prasad, B. (2013). Social media, health care, and social networking. Gastrointestinal Endoscopy, 77, 492–495. Resnik, D. (2001). Patient access to medical information in the computer age: Ethical concerns and issues. Cambridge Quarterly of Healthcare Ethics,

10(2), 147–154; discussion 154–156. Retrieved from Health Module (Document ID: 1409693961). Scott, A. (2002). Plato’s Meno. http://www.angelfire.com/md2/timewarp/plato.html Spector, N., & Kappel, D. M. (2012). Guidelines for using electronic and social media. Online Journal of Nursing, 17.

http://www.medscape.com/viewarticle/780050 Stern, J. (2013). Google Glass: What you can and can’t do with Google’s wearable computer. http://abcnews.go.com/Technology/google-glass-googles-

wearable-gadget/story?id=19091948 Swartz, M. K. (2011, November/December). The potential for social media. Journal of Pediatric Health Care, 25, 345. Velasquez, M., Andre, C., Shanks, T., & Myer, M. (for the Markkula Center for Applied Ethics). (1987). What is ethics?

http://www.scu.edu/SCU/Centers/Ethics/practicing/decision/whatisethics.shtml White paper: A nurse’s guide to the use of social media. (2011). www.ncsbn.org

Section II

Perspectives on Nursing Informatics

Chapter 6 Overview of Nursing Informatics Chapter 7 Informatics Roles and the Knowledge Work of Nursing Chapter 8 Information and Knowledge Needs of Nurses in the 21st Century Chapter 9 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 Overview of Nursing Informatics chapter begins this exploration. In the Informatics Roles and the Knowledge Work of Nursing chapter, the reader learns about NI roles, competencies, and skills. The Information and Knowledge Needs of Nurses in the 21st Century chapter considers the evolving NI needs of nurses and the development of standardized terminologies in NI. The Legislative Aspects of Nursing Informatics: HITECH and HIPAA chapter follows.

In the Overview 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 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 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.

The Informatics Roles and the Knowledge Work of Nursing 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. 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.

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. 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 Information and Knowledge Needs of Nurses in the 21st Century chapter notes 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 information technology–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 information technology 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.

Equally important in informatics practice is a thorough understanding of current legislation and regulations that shape 21st century practice. 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. 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 Source: 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

overview of nursing informatics Ramona Nelson and Nancy Staggers

OBJECTIVES

1. Define nursing informatics and key terminology. 2. Explore nursing informatics metastructures, concepts, and tools. 3. Analyze the sciences underpinning nursing informatics and their relationship to nursing informatics practice. 4. Describe phenomena of nursing.

Key Terms

Data Decision support system Ergonomics Expert system Human–computer interaction Informatics nurse Informatics nurse specialist Informatics solution Information Knowledge Nanotechnology Nursing informatics Usability Wisdom

Introduction Nurses in all settings and areas of practice are considered knowledge workers. The foundations of nursing informatics (NI) conceptualize the process of knowledge generation in nursing. The conceptual framework underpinning the science and practice of NI centers on the concepts of data, information, knowledge, and wisdom. These salient concepts are described in this chapter.

The following quote was crafted by a panel of NI experts as they revised the metastructures portion of the American Nurses Association’s (ANA) Scope and Standards for Nursing Informatics Practice:

Nursing informatics (NI) is a specialty that integrates nursing science, computer science, and information science to manage and communicate data, information, knowledge and wisdom in nursing practice. NI supports consumers, patients, nurses, and other providers in their decision-making in all roles and settings. This support is accomplished through the use of information structures, information processes, and information technology.

The goal of NI is to improve the health of populations, communities, families, and individuals by optimizing information management and communication. These activities include the design and use of informatics solutions, and/or technology to support all areas of nursing, including, but not limited to, the direct provision of care, establishing effective administrative systems, designing useful decision support systems, managing and delivering educational experiences, enhancing life-long learning, and supporting nursing research. (ANA, 2008, p. 1) (Source: © 2008 American Nurses Association. Reprinted with permission. All Rights Reserved.)

Within the scope and standards document, the term “individuals refer[s] to patients, healthcare consumers and any other recipient of nursing care or informatics solutions. The term patient refers to consumers in both a wellness and illness model” (ANA, 2008, p. 1). The authors thank Paulette Fraser, MS, RN, BC, for her work as coleader of the metastructures section of the ANA’s 2007 revision of the Scope and Standards for Nursing Informatics Practice.

The following passage is reprinted with permission of the ANA. Boldface type has been applied to key terms, and figure and table

numbers have been changed to correspond to this chapter.

The conceptual framework for NI is based on work by Graves and Corcoran (1989), who provided the initial definition and description of data, information, and knowledge as these terms apply to the science and practice of NI. Nelson (Nelson, 2002; Nelson & Joos, 1989) and Joos (Joos, Nelson, & Smith, 2010) added the concept of wisdom and reconceptualized how these concepts interrelate. In addition, the discussion of the definition and goal of nursing presented in the Scope and Standards of Practice evolved from work by Staggers and Thompson (2002). NI is one example of a discipline-specific informatics practice within the broader category of health informatics. NI has become well established within nursing since its recognition as a specialty for registered nurses by the ANA in 1992. It focuses on the representation of nursing data, information, knowledge, and wisdom and the management and communication of nursing information within the broader context of health informatics. NI (1) provides a nursing perspective, (2) illuminates nursing values and beliefs, (3) denotes a practice base for nurses in NI, (4) produces unique knowledge, (5) distinguishes groups of practitioners, (6) focuses on the phenomena of interest for nursing, and (7) provides needed nursing language and word context to health informatics (Brennan, 2003).

Metastructures, Concepts, and Tools of NI To understand the foundations of NI, one must begin by exploring its metastructures, sciences, concepts, and tools. Metastructures are overarching concepts used in theory and science. Also of interest are the sciences underpinning NI, concepts and tools from information science and computer science, human–computer interaction (HCI) and ergonomics concepts, and the phenomena of nursing.

Metastructures: Data, Information, Knowledge, and Wisdom

In the mid-1980s, Blum (1986) introduced the concepts of data, information, and knowledge as a framework for understanding clinical information systems and their impact on health care. He did this by classifying the then-current clinical information systems by the three types of objects that these systems processed: data, information, and knowledge. He noted that the classification was artificial with no clear boundaries; however, increasing complexity between the concepts existed.

In 1989, Graves and Corcoran built on this work when they published their seminal work describing the study of NI using the concepts of data, information, and knowledge. The article contributed two broad principles to NI that are acknowledged here: a definition of NI that has been widely accepted in the field; and an information model that identified data, information, and knowledge as key components of NI practice. The Graves model is presented in Figure 6-1.

Graves and Corcoran (1989) drew from Blum (1986) to define the three concepts as follows: (1) data are discrete entities described objectively without interpretation; (2) information is data that are interpreted, organized, or structured; and (3) knowledge is information that is synthesized so that relationships are identified and formalized. Drawing on this work, Nelson (2002; Nelson & Joos, 1989) defined wisdom as the appropriate application of knowledge to the management and solution of human problems.

Data, which are processed to create information and then knowledge, may be obtained from individuals, families, communities, and populations and the environment in which they exist. Data, information, knowledge, and wisdom are of concern to nurses in all areas of practice. For example, data derived from direct care of an individual may then be compiled across persons and aggregated for decision making by nurses, nurse administrators, or other health professionals. Further aggregation may address communities and populations. Nurse educators may create case studies using these data, and nurse researchers may access aggregated data for systematic study.

Figure 6-1 Conceptual framework for the study of nursing knowledge Source: American Nurses Association (ANA). (2008). Nursing informatics: Scope & standards of practice. Springfield, MD: nursebooks.org.

As an example, an instance of vital signs for an individual’s heart rate, respiration, temperature, and blood pressure can be considered a set of data elements. A serial set of vital signs taken over time, placed into a context, and used for longitudinal comparisons is considered information. That is, a dropping blood pressure and increasing heart rate, respiratory rate, and fever in an elderly, catheterized person are recognized as being abnormal for this person. The recognition that the person may be septic and, therefore, may need certain nursing interventions reflects information synthesis (knowledge) based on nursing knowledge and experience.

Figure 6-2 builds on the work of Graves and Corcoran (1989) by adding the concept of wisdom and reconfiguring the interrelationships between and among the concepts. As data are transformed into information and information into knowledge, each level increases in complexity and requires greater application of human intellect. The x-axis in (Figure 6-2) represents interactions within and between the concepts as one moves from data to wisdom; the y-axis represents the increasing complexity of the concepts’

increasing interrelationships. Wisdom is knowing when and how to apply knowledge to deal with complex problems or specific human need (Nelson, 2002;

Nelson & Joos, 1989). Although knowledge focuses on what is known, wisdom focuses on the appropriate application of that knowledge. For example, a knowledge base may include several options for managing an anxious family, whereas wisdom would guide the decisions about which of these options are most appropriate within a specific family. As this example demonstrates, the scope of NI is based on the scope of nursing practice and nursing science with a concentration on data, information, knowledge, and wisdom. It is not limited by current technology. If the study of NI was limited to what the computer can process, the study of informatics could not fully appreciate or support the full scope and complexity of nursing practice. NI must consider how nurses impact technology and how technology impacts nursing. An understanding of this interaction makes it possible to understand how nurses create knowledge and how they make use of that knowledge in their practices.

Figure 6-2 The relationship of data, information, knowledge, and wisdom Source: Copyright Ramona Nelson. Used with the permission of Ramona Nelson, President Ramona Nelson Consulting at ramonanelson@verizon.net. All rights reserved.

The appropriate use of knowledge involves the integration of empirical, ethical, personal, and aesthetic knowledge in the process of implementing actions. The individual must apply a high level of empirical knowledge in understanding the current situation, apply a professional value system in considering possible actions, be able to predict the potential outcome of these actions with a high level of accuracy, and then have the willpower to carry out the selected action in the current environment. An example of applied wisdom demonstrating this integration in NI is the appropriate use of information management and technological tools to support effective nursing practice.

The addition of wisdom raises new and important research questions. This addition challenges the discipline to develop tools and processes for classifying, measuring, and coding wisdom as it relates to nursing, NI, and informatics education. These research avenues help clarify the relationships between wisdom and the intuitive thinking of expert nurses. Such research is invaluable in building information systems to support expert healthcare practitioners and to support the decision process of more novice nurses.

Two interrelated forces have encouraged expansion of the NI model to include wisdom. First, the initial work was limited to the types of objects processed by automated systems in the mid-1980s. However, NI is now concerned with the use of information technology to improve the access and quality of health care that is delivered to individuals, families, and communities. Addition of the concept of wisdom expands the focus of the model from the technology and the processing of objects to include interaction of the human with the technology and resultant outcomes.

The previous ANA Scope and Standards of Practice (2001) had considered the inclusion of the concept of wisdom as too controversial. However, with the recognition of this concept in the 2008 ANA Scope and Standards of Practice, nurses are now demonstrating the practical application of the concept to the practice of NI. For example, Schleyer and Beaudry (2009) described how the data-to-wisdom continuum applies to informatics in telephone triage nursing practice. Another example from acute care is a statement by Troy Seagondollar posted on the NI Listserv ni-wg on November 19, 2010, at 11:27 am:

Content removed due to copyright restrictions.

More formally, the philosophical underpinnings and validity of the concept of wisdom in the data–information–knowledge– wisdom framework are discussed in more detail by Matney, Brewster, Sward, Cloyes, and Staggers (2011). Essentially, two perspectives in philosophy, postpositivism and hermeneutics, together support the addition of wisdom in the framework for NI.

Sciences Underpinning NI

A significant contribution of Graves and Corcoran (1989) was a description and definition of NI that was widely accepted in the field in the 1990s. It stated that NI is a combination of nursing science, information science, and computer science to manage and process nursing data, information, and knowledge to facilitate the delivery of health care. The central notion was that the application of these three core sciences was what made NI unique and differentiated it from other informatics specialties.

In addition to these three core sciences, other sciences may be required to solve informatics issues. James Turley (1996) expanded the model of NI to include cognitive science. Certainly, the cognitive aspect of humans is a critical piece for the informatics nurse specialist (INS) and the informatics nurse (IN) to understand. However, other sciences may be equally as critical, depending on the issue at hand. For example, if the INS is dealing with a systems implementation in an institution, an understanding of organizational theory may be germane to successful implementation (Staggers & Thompson, 2002). As science evolves, it may be necessary to include other core sciences in future models.

Although the core sciences are foundational to the work of NI, the practice of the specialty is considered an applied science rather than a basic science. The combination of sciences creates a unique blend that is greater than the sum of its parts, a unique combination that creates the definitive specialty of NI. Further, informatics realizes its full potential within health care when it is grounded within a discipline; in this case, the discipline is nursing. Computer and information science applied in isolation have less impact than if applied within a disciplinary framework. Through application, the science of informatics can solve critical healthcare issues of concern to a particular discipline.

Structured Language as a Tool for NI

Many of the tools used by the IN and INS are based on metastructures and concepts that incorporate knowledge from nursing and other health and information sciences. Nursing knowledge is gained by the ability to extract data that specifically defines nursing phenomena. Many different languages and ways of organizing data, information, and knowledge exist based on different concepts.

The creation of nursing taxonomies and nomenclatures has occurred over the past years, allowing these iterations to occur. The ANA has formalized the recognition of these languages and vocabularies through a review process of the Committee on Nursing Practice Information Infrastructure (CNPII). Box 6-1 lists the ANA-approved nursing languages (as of August 2012) and provides a website for each approved language (http://www.nursingworld.org/MainMenuCategories/ThePracticeofProfessionalNursing/NursingStandards/Recognized-Nursing- Practice-Terminologies.aspx).

At a higher level of structure, several resources have been developed to facilitate interoperability among different systems of concepts and nomenclature. For instance, the Systemized Nomenclature of Medicine (SNOMED CT) is considered a universal healthcare terminology and messaging structure. In nursing, SNOMED enables terminology from one system to be mapped to concepts from another system, such as the North American Nursing Diagnosis Association (NANDA) terminology, Nursing Intervention Classification (NIC), and Nursing Outcome Classification (NOC). On a larger scale, the Unified Medical Language System of the National Library of Medicine (UMLS; http://www.nlm.nih.gov/research/umls) incorporates the work of more than 100 vocabularies, including SNOMED (http://www.nlm.nih.gov/research/umls/knowledge_sources/metathesaurus/). The INS must be aware of these tools and may be called on to understand the concepts of one or more languages, the relationships between related concepts, and integration into existing vocabularies for a given organization.

BOX 6-1 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:

www.nursing.uiowa.edu/excellence/nursing_knowledge/clinical_effectiveness/index.htm (NIC/NOC can be obtained from the same source)

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: www.nursing.uiowa.edu/excellence/nursing_knowledge/clinical_effectiveness/index.htm (NIC/NOC can be obtained from the same source)

6. Nursing Management Minimum Data Set (NMMDS), 1998 Website: http://www.nursing.umn.edu/icnp/usa-nmds 7. PeriOperative Nursing Data Set (PNDS) 1999

Website: www.aorn.org or http://www.aorn.org/workarea/DownloadAsset.aspx?id=21663 8. SNOMED CT, 1999

Website: www.ihtsdo.org/snomed-ct/ 9. Nursing Minimum Data Set (NMDS), 1999

Website: http://www.nursing.umn.edu/icnp/usa-nmds/ 10. International Classification for Nursing Practice (ICNP), 2000 Website: http://www.icn.ch/icnp.htm 11. ABC Codes, 2000

Website: www.abccodes.com Prepared from information located at http://www.nursingworld.org/MainMenuCategories/ThePracticeofProfessionalNursing/NursingStandards/Recognized-Nursing-Practice- Terminologies.aspx

12. Logical Observation Identifiers Names and Codes (LOINC), 2002 Website: http://loinc.org 13. Retired Data Sets

Patient Care Data Set (PCDS), 1998

The importance of languages and vocabularies cannot be overstated. The INS must seek a broader picture of the implications of his or her work and the uses and outcomes of languages and vocabularies for end users. For instance, nurses working in mapping a home care vocabulary with an intervention vocabulary must see beyond the technical aspect of the work. They must understand that there

may be a case manager for a multisystem health organization or a home care agency that is developing knowledge of nursing acuity and case mix based on the differing vocabularies that they have integrated. The INS must envision the differing functions that may be used with the data, information, and knowledge that have been created. See the Informatics Roles and the Knowledge Work of Nursing chapter for a more thorough discussion of terminologies.

Concepts and Tools from Information Science and Computer Science

Computer science focuses on the study of the theoretical foundations of computation processes and of practical techniques for their application in computer systems. Information science is an interdisciplinary science concerned with the collection, classification, manipulation, storage, retrieval, and dissemination of information.

Informatics tools and methods from computer and information sciences are considered fundamental elements of NI, including information technology, information structures, information management, and information communication.

Information technology includes computer hardware, software, communication, and network technologies, derived primarily from computer science. The other three elements are derived primarily from information science. Information structures organize data, information, and knowledge for processing by computers. Information management is an elemental process within informatics in which one is able to file, store, and manipulate data for various uses. Information communication processes enable systems to send data and to present information in a format that improves understanding. The use of information technology distinguishes informatics from more traditional methods of information management. Thus, NI incorporates the four previously mentioned additional elements from computer and information science. Underlying all of these are HCI concepts, discussed next.

HCI and Related Concepts

HCI, usability, and ergonomics concepts are of fundamental interest to the INS. Essentially, HCI deals with people, software applications, computer technology, and the ways they influence each other (Dix, Finlay, Abowd, & Beale, 2004). Elements of HCI are rooted in psychology, social psychology, and cognitive science. However, the design, development, implementation, and evaluation of applications derive from applied work in computer science, the specific discipline at hand (in this case, nursing), and information science. For example, an INS assesses an application before purchase to determine whether the application design complements the way nurses cognitively process medication orders.

A related concept is “usability,” which deals with specific issues of human performance during computer interactions for specific tasks within a particular context (Dix et al., 2004). Usability issues address the efficiency and effectiveness of an application. For example, an INS might study the ease of learning an application, the ease of using an application, or the speed of task completion and errors that occurred during application use when determining which system or application would be best used on a nursing unit.

The term ergonomics typically is used in the United States to describe the design and implementation of equipment, tools, and machines related to human safety, comfort, and convenience. Commonly, the term ergonomics refers to attributes of physical equipment or to principles of arrangement of equipment in the work environment. For instance, an INS may have a role in ensuring that good ergonomics principles are used in an intensive care unit to select and arrange various devices to support workflow for cross- disciplinary providers and patients’ families.

HCI, usability, and ergonomics are related concepts that are typically subsumed under the rubric of human factors, or how humans and technology relate to each other. The overall goal is better design for software, devices, and equipment to promote optimal task completion in various contexts or environments. Optimal task completion includes the concepts of efficiency and effectiveness, including considerations about the safety of the user. It is essential that the INS understand these concepts to be able to develop effective strategies to select, implement, and evaluate information structures and informatics solutions.

The importance of human factors in health care was elevated with the Institute of Medicine’s 2001 report. Before this, HCI and usability assessments and methods were being incorporated into health care at a glacial speed. In the past 5 years, the number of HCI and usability publications in health care has increased substantially. Vendors have installed usability laboratories and incorporated usability testing of their products into their systems life cycles. The Food and Drug Administration (FDA) has mandated usability testing as part of its approval process for any new devices (Medical Devices Today, 2007). Thus HCI and usability are critical concepts for INs and INSs to understand. Numerous usability methods and tools are available (e.g., heuristics [rules of thumb], naturalistic observation, and think-aloud protocols). Readers are referred to HCI references and The Human–Technology Interface chapter to learn more about these methods.

Phenomena of Nursing

The metaparadigm of nursing comprises four key concepts: (1) nurse, (2) person, (3) health, and (4) environment. Nursing actions are based on interrelationships between the concepts and are related to the values nurses hold relative to them. Nurses make decisions about interventions from their unique perspectives. Decision making is the process of choosing among alternatives. The decisions that nurses make can be characterized by both the quality of decisions and the impact of the actions resulting from those decisions. As knowledge workers, nurses make numerous decisions that affect the life and well-being of individuals, families, and communities. The process of decision making in nursing is guided by the concept of critical thinking. Critical thinking is the intellectually disciplined process of actively and skillfully using knowledge to conceptualize, apply, analyze, synthesize, or evaluate data and information as a guide to belief and action (Scriven & Paul, 1997).

Clinical wisdom is the ability of the nurse to add experience and intuition to a situation involving the care of a person (Benner, Hooper-Kyriadkidis, & Stannard, 1999). Wisdom is demonstrated in informatics by the ability of the INS to evaluate the documentation drawn from a health information system (HIS) and the ability to adapt or change the system settings or parameters to improve the workflow of the clinical nurse.

Nurses’ decision making is described as an array of decisions that include specific behaviors and cognitive processes surrounding a

cluster of issues. For example, nurses use data transformed into information to determine interventions for persons, families, and communities. Nurses make decisions about potential problems presented by an individual and about appropriate recommendations for addressing those problems. They also make decisions in collaboration with other healthcare professionals, such as physicians, pharmacists, or social workers. Decisions also may occur within specific environments, such as executive offices, classrooms, and research laboratories.

An information system collects and processes data and information. Decision support systems are computer applications designed to facilitate human decision-making processes. Decision support systems are typically rule based, using a specified knowledge base and a set of rules to analyze data and information and provide recommendations. Other decision support systems are based on knowledge models induced directly from data, regression, or classification models that predict characteristics or outcomes. Recommendations take the form of alerts (i.e., calling user attention to abnormal laboratory results or potential adverse drug events) or suggestions (e.g., appropriate medications, therapies, or other actions) (Haug, Gardner, & Evans, 1999).

An expert system is a type of decision support system that implements the knowledge of one or more human experts 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. Whereas control systems implement decisions without involvement of a user, decision support systems merely provide recommendations and rely on the wisdom of the user for appropriate application of these provided recommendations. Within informatics, there is always a tension between which decisions should be automated and which decisions require human intervention. The relationships among these concepts and information, decision support, and expert systems are depicted in Figure 6-3.

An INS must be able to navigate the complexity of the relationships between the following elements and understand how they facilitate decision making:

Data, information, knowledge, and wisdom Nursing science, information science, computer science, and other sciences of interest to the issue at hand (e.g., cognitive

science) Nurse, person, health, and environment Information structures, information technology, managing and communicating information

Figure 6-3 Levels and types of automated systems Source: Modified from Englebardt, S. & Nelson, R. (2002). Health care informatics: An Interdisciplinary approach. St. Louis, MO: Mosby. Used with the permission of Ramona Nelson, President Ramona Nelson Consulting at ramonanelson@verizon.net. All rights reserved.

The Future of NI The future of NI will impact and be impacted by several driving trends. These include (1) changes in society, such as the aging population and the increased use of participatory and mobile technology; (2) changes in healthcare delivery, including the changing and expanding role of nursing within healthcare delivery; and (3) changes in technology, such as nanotechnology, which promises to redefine the composition of nearly every human-made material and drastically alter biomedical applications (Alivisatos, 2001).

All of these changes will drive increased saturation of informatics concepts and solutions into mainstream nursing and healthcare practices. As informatics solutions become as common a tool as the stethoscope, every nurse, to be safe and effective, will need to incorporate informatics concepts into all aspects of practice. One example is the increased recognition of the concept of wisdom as a key concept for NI. Its more detailed definition and measurement will be a part of the future practice of all nursing.

Summary This chapter outlined the foundations of NI. The following definition for NI is offered: NI is a specialty that integrates nursing science, computer science, and information science to manage and communicate data, information, knowledge, and wisdom in nursing practice. As part of this chapter’s consideration of NI, interrelationships among major NI concepts were discussed. As data are transformed into information and information into knowledge, and knowledge is applied through wisdom to ensure appropriate, effective, and compassionate nursing care, increasing complexity and interrelationships ensue. The boundaries between concepts can become blurred and feedback loops from one concept level to another emerge. These major concepts can be related to various types of systems, including information, expert, and decision support systems. The following sciences are intimately intertwined with NI: nursing, computer, and information science. Other sciences are used as required by the issue at hand.

Critical elements for NI include structured languages and HCI concepts. Taxonomies and other current structured languages for nursing were listed within this chapter. HCI concepts were briefly defined and discussed because they are critical to the success of

informatics solutions. In an ideal world, the authors would like to see the following:

Patients who are truly active participants in managing their own health. The use of technology, such as personal health records and automated monitoring devices, along with the implementation of participatory medicine, will make that possible.

Safe care, where more than 100,000 patients do not die each year from medical errors. Improved use of technology, such as decision support systems and alerts, will make that possible.

Health care that can be afforded by all. Increased use of prevention strategies and efficiencies gained from technology will make that possible.

A working environment for all nurses where data, information, and knowledge are effectively managed to ensure wisdom guides all nursing decisions.

THOUGHT-PROVOKING QUESTIONS

1. How is the concept of wisdom in NI like or unlike professional nursing judgment? 2. Can you create examples of how expert systems (not decision support systems but true expert systems) can be used to support nursing practice? 3. How would you incorporate the data-to-wisdom continuum into a job description for an NI specialist? 4. Can any aspect of nursing wisdom be automated? 5. The chapter states that research will be invaluable in building information systems to support expert healthcare practitioners and support the

decision-making processes of more novice nurses. What is the significance of this statement to the study of HCI in NI?

References Alivisatos, A. P. (2001). Less is more in medicine: Sophisticated forms of nanotechnology will find some of the first real-world applications in

biomedical research, disease diagnosis and possibly therapy. Scientific American, 285(3), 66–73. American Nurses Association (ANA). (2008). Nursing informatics: Scope and standards of practice. Springfield, MD: Nursesbooks.org Benner, P., Hooper-Kyriadkidis, P., & Stannard, D. (1999). Clinical wisdom and interventions in critical care: A thinking-in-action approach.

Philadelphia, PA: W. B. Saunders. Blum, B. (1986). Clinical information systems. New York, NY: Springer-Verlag. Brennan, R. (2003). One size doesn’t fit all: Pedagogy in the online environment: Vol. 1. Adelaide, Australia: National Centre for Vocational Education

Research. http://www.ncver.edu.au/research/proj/nr0F05e.htm Dix, A., Finlay, J., Abowd, G., & Beale, R. (2004). Human–computer interaction. Harlow, UK: Pearson, Prentice Hall. Graves, J., & Corcoran, S. (1989). The study of nursing informatics. Image, 21(4), 227–230. Haug, P., Gardner, R., & Evans, S. (1999). Hospital-based decision support. In E. S. Berner (Ed.), Clinical decision support systems: Theory and

practice (pp. 77–104). New York, NY: Springer-Verlag. Institute of Medicine. (2001). Crossing the quality chasm: A new health system for the 21st century. Washington, DC: National Academies Press. Joos, I., Nelson, R., & Smith, M. (2010). Introduction to computers for healthcare professionals (5th ed.). Sudbury, MA: Jones and Bartlett. Matney, S., Brewster, P., Sward, K., Cloyes, K., & Staggers, N. (2011, March). Philosophical approaches to the data–information–knowledge–wisdom

framework. Advances in Nursing Science, 34(1) 6–18. Medical Devices Today. (2007). New usability standard aims to help firms institute human factors programs.

http://www.medicaldevicestoday.com/2007/04/new_usability_s.html Nelson, R. (2002). Major theories supporting health care informatics. In S. Englebardt & R. Nelson (Eds.), Health care informatics: An interdisciplinary

approach (pp. 3–27). St. Louis, MO: Mosby-Year Book. Nelson, R., & Joos, I. (1989, Fall). On language in nursing: From data to wisdom. Pennsylvania League for Nursing PLN Vision (p. 6). Schleyer, R., & Beaudry, S. (2009). Data to wisdom: Informatics in telephone triage nursing practice. AAACN Viewpoint, 31(5), 1, 10–13. Scriven, M., & Paul, R. (1997). A working definition of critical thinking. Retrieved March 2008 from http://lonestar.texas.net/~mseifert/crit2.html Staggers, N., & Thompson, C. B. (2002). The evolution of definitions for nursing informatics: A critical analysis and revised definition. Journal of the

American Medical Informatics Association, 33(1), 75–81. Turley, J. (1996). Toward a model for nursing informatics. Image: Journal of Nursing Scholarship, 28(4), 309–313.

Chapter 7

Informatics Roles and the Knowledge Work of Nursing Julie A. Kenney and Ida Androwich

OBJECTIVES

1. Explore the concept of nurses as knowledge workers. 2. Discuss the evolving roles and competencies of nursing informatics practice.

Key Terms

Advocate/policy developer Certification Cognitive activity Consultant Continuous learner Data Data gatherer Decision support/outcomes manager Educator Entrepreneur Industrial Age Informatics Informatics innovator Informatics nurse specialist Information Information Age Information user Interdisciplinary knowledge team Knowledge Knowledge builder Knowledge user Knowledge worker Medical informatics Nursing informatics competencies Product developer Project manager Researcher Technologist TIGER initiative

Introduction The world has witnessed an unprecedented number of technological advances during the last 100 years. The early 20th century saw the invention of the car and the airplane; both modes of transportation drastically changed how people work and play. The entertainment world was dramatically altered by the invention of radio and television. The introduction of the computer altered the way data and information are viewed and used and changed the way business is conducted. The computer is now changing nursing and health care.

Nurses have historically gathered and interpreted data. Florence Nightingale is 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).

Today, nurses are able to access information much more quickly and easily than their predecessors. Accessing information via the Internet or the electronic health record (EHR) allows the nurse to provide the best possible patient care. Genomic health care and the interaction between genetic factors and the environment require new understanding of the various types of information needed to make decisions—a vast array of data characterized as a “data tsunami” (Bakken, Stone, & Larson, 2008).

Nursing recognized early on that computers would change health care and became actively involved in shaping how computers

were used in health care. The American Nurses Association (ANA) first recognized nursing informatics (NI) as a specialty in 1992 (ANA, 2008; Saba & McCormick, 2006). The introduction of this specialty has spurred the development of many informatics jobs, organizations, and publications. Nurses now have the ability to further their education by attending informatics conferences, reading journals, obtaining certificates and advanced degrees, and participating in numerous hospital-based and national and international informatics committees and groups.

The Nurse as a Knowledge Worker As described in the Overview of Nursing Informatics chapter, 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? This section focuses on the definition of a knowledge worker, the history of the term, and the ways in which it is used in health care and business. This chapter as a whole examines how nursing relates to the term knowledge worker and the effect a knowledge worker has on health care.

Definitions

Knowledge can be defined as “the distillation of information that has been collected, classified, organized, integrated, abstracted, and value added” (HIMSS, 2006, p. 49). A worker is “one that works especially at manual or industrial labor or with a particular material” (Merriam-Webster Online, 2011). 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, evidenced-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.

Knowledge Worker Concept

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 between 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.

Knowledge Workers and Health Care

The healthcare industry is firmly rooted in the Industrial Age. This long-standing tradition has resulted in an industry that is not

conducive to support the knowledge workers who represent most of the workforce (Sorrells-Jones & Weaver, 1999a; Wickramasinghe & Ginzberg, 2001). Sorrells-Jones and Weaver (1999a) state that “healthcare institutions are among the most rigidly bureaucratic and hierarchical, discipline-fragmented organizations in the U.S.” (p. 16). This organizational arrangement is evidenced by the multiple administrative levels that manage a single-function unit. Corporate values within health care reflect the desire for employees to be loyal and compliant, to avoid risk, and to see failure as negative instead of positive. Senior leadership keeps information tightly controlled and fails to see the need to bring in external intelligence and influence. Rewards are based on individual rather than team performance, and a significant pay difference exists between those at the top and those who produce the product (Weaver & Sorrells- Jones, 1999).

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).

Currently, there is a healthcare management trend toward adoption of flatter management styles with fewer layers of administration. Organizations are beginning to switch to a clinical product or service line format. This format is typically designed with the physician serving as the content expert and the nurse serving as the patient care expert. Unfortunately, this approach does not represent a significant change from the way things are currently done (Weaver & Sorrells-Jones, 1999).

In the future, management needs to understand and support the knowledge work and nonknowledge work that are performed daily in health care, as both types of work are integral to caring for patients safely. Organizations must switch from measuring the number of tasks completed to measuring the outcomes obtained by knowledge workers (Sorrells-Jones & Weaver, 1999b). This trend is becoming more evident with the posting of hospital report cards that demonstrate how effectively the hospital is caring for certain types of patients.

Nurses as Knowledge Workers

The question to ask is, “Are nurses knowledge workers?” As shown in Table 7-1, when nursing characteristics are compared to the characteristics of a knowledge worker, the nurse does meet the criteria for a knowledge worker. 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).

TABLE 7-1 A COMPARISON OF KNOWLEDGE WORKER CHARACTERISTICS AND NURSING CHARACTERISTICS

Knowledge Worker Characteristics Nursing Characteristics

Advanced formal education • All nurses have college degrees ranging from AD/AS to PhD.

Able to apply theoretical and analytical knowledge

• Nurses are educated on nursing theory and how to apply it in patient situations.

Continuous learner • Obtain advanced degrees. • Attend seminars. • Earn contact hours.

Specialized • Nursing specialties are as numerous as medical specialties.

Innovator • Nurses become innovative when they do not have proper equipment to care for the patients or

they feel that current products are inadequate.

Team member • Have been a member of the interdisciplinary team for a significant amount of time.

Snyder-Halpern et al. (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 et al. (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). The knowledge needs of nurses will continue to evolve as the systems improve.

The Challenge of Nurses as Knowledge Workers

For nurses to be treated as knowledge workers, they must first be recognized as knowledge workers (Snyder-Halpern et al., 2001). Nurses have been part of the interdisciplinary team for years, but are they ready to become part of the interdisciplinary knowledge team? Nursing may be ready to take that step, but are other members of the healthcare team ready to acknowledge nurses as respected members of the team (Sorrells-Jones & Weaver, 1999a)? One reason that acceptance may be difficult to achieve is the fact that nurses tend to be the least educated members of the interdisciplinary knowledge team, although this situation is slowly changing. Another reason is that nurses, historically, have had a difficult time being active members of the interdisciplinary team (Sorrells-Jones & Weaver, 1999b). Nursing still has a long way to go before nurses are fully accepted as equal participants in the interdisciplinary knowledge team. For nurses to reach this goal, a major attitude change toward nursing needs to take place. In addition, nurses must become better educated and more involved in the interdisciplinary knowledge team.

The Knowledge Needs and Competencies of Nurses In the early days of medicine, the entire body of medical knowledge could fit into a single volume. Today, the amount of information available is vast and expanding exponentially, a fact that makes the healthcare industry the world’s most knowledge-intense environment (Snyder-Halpern et al., 2001). Computers, technology, and the informatics fields are assisting healthcare workers in dealing with this information explosion.

Knowledge Needs

Nurses deal with a vast amount of information and knowledge every day, which they use to care for their patients. Nurses rely on an extensive amount of clinical information and specialized knowledge to evaluate the processes they have implemented and to measure the corresponding outcomes (Snyder-Halpern et al., 2001). Although nurses rely on their own knowledge, sometimes this knowledge base is not adequate; on such occasions, they must access information to provide safe patient care. In a national survey, consulting a peer was reported to be the most frequent way that information was obtained. The same survey also found that most of those surveyed did not use information resources to gather practice information, and that only approximately 25% had been trained on how to use an electronic database (Barton, 2005). If a peer does not have the information the nurse is seeking, the nurse is likely to turn to a hospital policy, a journal, a textbook, a drug book, an online resource, the EHR, or many other possible sources to find the needed information. New technology tools are likely to change these behaviors so that the best and most current information is readily available and regularly used.

For this information to be beneficial to the nurse and the patient, it must be reliable and credible. The resource must be easily accessible and packaged in such a way that the nurse is able to find the necessary information quickly and with a minimal amount of difficulty. One way this can be accomplished is by implementing a DSS, which is designed to support nurses in their decision-making activities. DSSs are increasingly being incorporated into the EHR.

Nursing Informatics Competencies

One challenge that health care is currently facing relates to the vast differences in computer literacy and information management skills that healthcare workers possess (McNeil, Elfrink, Beyea, Pierce, & Bickford, 2006). Barton (2005) believes 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) advocate 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 et al. (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 (INS), and (4) informatics innovator. Each of these skill levels needed to be defined before Staggers et al. (2001) could determine which level was the most appropriate for that skill set. Table 7-2 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.

Staggers, Gassert, and Curran (2002) conducted 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 stress 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. To access the entire list of competencies by skill level, visit http://www.nursingconsult.com/nursing/journals/0029-6465/full-text/PDF/s0029646508000546.pdf?issn=0029- 6465&full_text=pdf&pdfName=s0029646508000546.pdf&spid=21480607&article_id=666314. Table 7-3 provides a modified version of the list.

TABLE 7-2 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

Source: Republished with permission of SLACK Incorporated, from Journal of Nursing Education, Staggers, N., Gassert, C., & Curran, C. Staggers, N 40(7), 2001; 303–316; permission conveyed through Copyright Clearance Center, Inc.

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 (TIGER Initiative, 2006). 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.tigersummit.com/.

What Is Nursing Informatics Specialty Practice? NI is an established, yet ever-evolving profession that began when computers were introduced into health care. Those choosing NI as a career find it full of numerous and varied opportunities. Until recently, 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. This section of the chapter explores 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 IS 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 informaticians 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.

Scopes and Standards

NI is important to nursing and health care because it focuses on representing nursing data, information, and knowledge. NI meets the following needs for health informatics (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 includes the most recent INS standards of practice and the INS standards of professional performance. There are 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.

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 15% of their days with their patients and as much as 50% of their day documenting (HIMSS Nursing Informatics Awareness Task Force, 2007). Assisting nurses to incorporate this new technology into their daily workflow is one of many challenges that the INS may tackle.

BOX 7-1 INFORMATICS NURSE SPECIALIST STANDARDS OF PRACTICE AND PERFORMANCE Standards of Practice Standard 1: Assessment Standard 2: Problem 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 and Education Standard 5C: Consultation Standard 6: Evaluation

Standards of Professional Performance Standard 7: Education Standard 8: Professional Practice Evaluation Standard 9: Quality of Practice Standard 10: Collegiality Standard 11: Collaboration Standard 12: Ethics Standard 13: Research Standard 14: Resource Utilization Standard 15: Advocacy Standard 16: Leadership

Source: American Nurses Association (ANA). (2008). Nursing informatics: Scope and standards of practice. Silver Spring, MD: Nursesbooks.org. © 2008 American Nurses Association. Reprinted with permission. All Rights Reserved.

The INS may take on numerous roles. For example, one position that nurses fill quite well is the role of the project manager, as a result of their ability to manage multiple complex situations at one time (HIMSS Nursing Informatics Awareness Task Force, 2007). 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, 2008; Thede, 2003).

Project Manager. In the project manager role, the INS is responsible for the planning and implementing of an informatics project. The INS uses communication, change management, process analysis, risk assessment, scope definition, and team building. This role acts as the liaison between clinicians, management, IS, 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 educational 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 a key to 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 analyze nursing information needs and develop and market 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 also exist. The informatics nurse has a bachelor of science degree in nursing and additional knowledge and expertise in the informatics field (ANA, 2008). 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 Duke University: http://nursing.duke.edu/modules/son_academic/index.php?id=101 Excelsior College: http://www.excelsior.edu/nursing-masters-informatics-faq Loyola University Chicago: http://www.luc.edu/nursing/graduate_hsm.shtml New York University: http://www.nyu.edu/nursing/academicprograms/masters/programs/informatics.html Northeastern University: http://www.healthinformatics.neu.edu/ University of Alabama at Birmingham: Retrieved September 2010 from http://main.uab.edu/shrp/default.aspx?pid=77369 University of Colorado at Denver: http://www.ucdenver.edu/academics/colleges/nursing/programs-admissions/masters-programs/ms-

program/specialties/healthcareinformatics/Pages/default.aspx University of Iowa: http://www.nursing.uiowa.edu/center-for-nursing-classification-and-clinical-effectiveness University of Kansas: http://nursing.kumc.edu/academics/master-of-science/nursing-informatics.html University of Maryland: http://nursing.umaryland.edu/academic-programs/grad/masters-degree/ms-academicprogram/nursing-informatics University of North Carolina at Chapel Hill: https://nursing.unc.edu/academics/master-of-science-in-nursing/health-care-systems-msn/ University of Pittsburgh: http://www.unmc.edu/nursing/programs.html University of Utah: http://nursing.utah.edu/programs/msnursinginformatics.php University of Washington: http://www.son.washington.edu/portals/cipct/ Vanderbilt University: http://www.nursing.vanderbilt.edu/msn/ni.html

Certificate Programs Chamberlain College of Nursing: http://www.chamberlain.edu/admissions/graduate/graduate-certificate-programs Indiana University: http://nursing.iupui.edu/continuing/informatics.shtml Loyola University Chicago: http://www.luc.edu/media/lucedu/nursing/pdfs/Informatics%20Certificate.pdf Northeastern University: http://www.healthinformatics.neu.edu/ Penn State University: http://www.worldcampus.psu.edu/degrees-and-certificates/nursing-informatics-certificate/overview University of Iowa: http://informatics.grad.uiowa.edu/health-informatics/curriculum

Nurses who choose to specialize in NI have two certifications available to them. The first is obtained through the American Nurses Credentialing Center. The Center’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 http://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.

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 the Healthcare Information and Management Systems Society. HIMSS, which celebrated its 50th year in 2011, was launched in 1961 and now has offices throughout the United States and Europe. HIMSS currently represents 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 a scholarly journal, The Journal of Healthcare Information Management. 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. To find out more about HIMSS, visit its homepage at http://www.himss.org/ASP/index.asp (HIMSS, 2013). HIMSS also periodically conducts NI workforce surveys; see http://www.himss.org/ResourceLibrary/ResourceDetail.aspx?ItemNumber=11587 for the 2011 results.

The American Medical Informatics Association (AMIA) was founded in 1990 when 3 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. To view this information and to see other AMIA offerings, visit http://www.amia.org (AMIA, 2013).

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, and 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 e-mail 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

To view this information and learn more about ANIA, visit https://www.ania.org/ (ANIA, 2013). The Alliance of 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. To view this information and learn more about ANI, visit http://www.allianceni.org (Alliance of Nursing Informatics, 2013).

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: http://www.amia.org/mbrcenter/wg/ni

American Nursing Informatics Association (includes Capital Area Roundtable on Informatics in Nursing [CARING]) Website: www.ania.org Resources link: http://www.ania.org/Resources.htm Journal: CIN: Computers, Informatics, Nursing

Health Information and Management Systems Society Website: www.himss.org Chapter websites: http://www.himss.org/ASP/chaptersHome.asp Journal: The Journal of Healthcare Information Management NI website: http://www.himss.org/asp/topics_nursingInformatics.asp

International Medical Informatics Association Website: www.imia.org Journal: International Journal of Medical Informatics NI website: http://www.imia.org/ni

Online Journal of Nursing Informatics Website: http://www.ojni.org

These groups have been instrumental in establishing the informatics community. Many other informatics groups that have not been covered here also exist. Box 7-3 lists some of these organizations and their publications.

The Future of Nursing Informatics NI is 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. Overall, the INS’s future looks very promising and rewarding.

In the future, all healthcare providers will likely receive education on informatics. All healthcare providers 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 literacy. 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 (Bakken et al., 2008).

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 an emerging nursing specialty that combines nursing science, information science, and computer science. 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. As a consequence of this trend, healthcare administrators now realize that they must begin to change the way that they view 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 will discover that they have happier employees and find that patient care has become safer and more efficient.

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. NI is a recognized specialty, but it affects all nurses. Nursing informatics competencies have been developed to ensure that all entry-level nurses are ready to enter the more technologically advanced field of nursing. 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. It will be interesting to see where technology takes health care in the future.

THOUGHT-PROVOKING QUESTIONS

1. A hospital is seeking to implement an 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. This chapter discusses the fact that nurses are knowledge workers. How does nursing move from measuring the tasks completed to measuring the final outcome of the patient?

References Alliance of Nursing Informatics. (2013). Homepage. http://www.allianceni.org American Medical Informatics Association. (2013). Homepage.

http://www.amia.org American Nurses Association (ANA). (2008). Nursing informatics: Scope and standard of practice. Silver Spring, MD: Nursesbooks.org. American Nursing Informatics Association (ANIA). (2013). Homepage. http://www.ania.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. 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. http://www.himss.org HIMSS Nursing Informatics Awareness Task Force. (2007). An emerging giant: Nursing informatics. Nursing Management, 13(10), 38–42. McCormick, J. (2009, May 14). Preparing for the future of knowledge work: A day in the life of the knowledge worker. Infomanagment Direct Online.

http://www.information-management.com/infodirect/2009_121/knowledge_worker_information_management_ecm_content_management- 10015405-1.html?pg=1

McNeil, B. J., Elfrink, V., Beyea, S. C., Pierce, S., & Bickford, C. J. (2006). Computer literacy study: Report of qualitative findings. Professional Nursing, 22(1), 52–59.

Merriam-Webster Online. (2011). http://mw1.merriam-webster.com/dictionary/worker O’Connor, J. J., & Robertson, E. F. (2003). Florence Nightingale biography. http://www-history.mcs.st-

andrews.ac.uk/history/Printonly/Nightingale.html Saba, V. K., & McCormick, K. A. (Eds.). (2006). Essentials of nursing informatics (4th ed.). New York, NY: McGraw-Hill. Snyder-Halpern, R., Corcoran-Perry, S., & Narayan, S. (2001). Developing clinical practice environments supporting the knowledge work of nurses.

Computers in Nursing, 19(1), 17–26. Sorrells-Jones, J., & Weaver, D. (1999a). Knowledge workers and knowledge-intense organizations, Part 1: A promising framework for nursing and

healthcare. Journal of Nursing Administration, 29(7/8), 12–18. Sorrells-Jones, J., & Weaver, D. (1999b). Knowledge workers and knowledge-intense organizations, Part 3: Implications for preparing healthcare

professionals. Journal of Nursing Administration, 29(10), 14–21. Staggers, N., Gassert, C., & Curran, C. (2001). Informatics competencies for nurses at four levels of practice. Journal of Nursing Education, 40(7), 303–

316. Staggers, N., Gassert, C., & Curran, C. (2002). A Delphi study to determine informatics competencies for nurses at four levels of practice. Nursing

Research, 51(6), 383–390. Thede, L. Q. (2003). Informatics and nursing: Opportunities and challenges (2nd ed.). Philadelphia, PA: Lippincott Williams & Wilkins. TIGER Initiative. (2006). Welcome to TIGER! http://www.tigersummit.com Weaver, D., & Sorrells-Jones, J. (1999). Knowledge workers and knowledge-intense organizations, Part 2: Designing and managing for productivity.

Journal of Nursing Administration, 29(9), 19–25. Wickramasinghe, N., & Ginzberg, M. J. (2001). Integrating knowledge workers and the organization: Role of IT. International Journal of Health Care

Quality Assurance, 14(6), 245–253.

Chapter 8

Information and Knowledge Needs of Nurses in the 21st Century Lynn M. Nagle, Nicholas Hardiker, Kathleen Mastrian, and Dee McGonigle

OBJECTIVES

1. Describe the goal of nursing informatics. 2. Explore the need for consistent terminology in nursing. 3. Describe the different approaches to terminology development. 4. Describe how clinical information technologies are impacting and will impact nursing practice. 5. Explore how nurses can create and derive clinical knowledge from information systems. 6. Speculate on the future of nursing in the context of health informatics.

Key Terms

Accessibility Clinical decision support Clinical information system Enumerative approach Evidence-based practice International Classification of Nursing Practice Nursing informatics Nursing knowledge Ontological approach Ontology Reusability Standardized nursing terminology Term Terminology Ubiquity

Introduction The information and knowledge informing the 21st century of healthcare delivery have been growing at an unprecedented pace in recent years. 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 information, 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.

This chapter defines and addresses the goal of informatics as it relates to nursing. More specifically, benefits to be derived from 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 goal, 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.

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.

Definition and Goal of Informatics Recall the definition of nursing informatics (NI) presented in the Overview of Nursing Informatics chapter (Staggers & Thompson, 2002):

A specialty that integrates nursing science, computer science, and information science to manage and communicate data, information, and knowledge in nursing practice. NI facilitates the integration of data, information, and knowledge to support patients, nurses, and other providers in their decision-making in all roles, and settings. This support is accomplished through the use of information structures, information processes, and information technology. (p. 260)

Nurses in identified informatics roles typically focus their efforts on articulating meaningful clinical nursing data and information structures that can be codified and processed; identifying the information processes associated with nurses’ work; and determining ways in which information and communication technologies can be most effectively used to support the capture, retrieval, and use of data, information, and knowledge. For nurses in other roles, however, the term “informatics” remains substantively obscure and misunderstood, if understood at all, as do the relevance and importance of the associated work.

More timely access to data and information—both clinical and financial—has been identified as a necessity in the climate of healthcare delivery in the 21st century (Hannah, 1995). Health service organizations, societies, and governments throughout the industrialized world are obsessed with 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, the goals of informatics need to include the use of technologies to empower citizens to manage their own health and wellness more effectively.

A current challenge within the nursing profession is the pending human resources crisis and dire projections of imminent nurse shortages. Consequently, nursing’s focus on information technology (IT) has been elevated as a central means by which nurses can be sufficiently supported in their work environments. Most importantly, IT has the potential to reduce the waste of valuable nursing resources by reducing the time spent in the “care and feeding” of patient records. Having more time for direct client care that is supported by ready access to information and knowledge translates into the provision of safer, higher quality care. Nurses need to be appropriately equipped with the tools to manage data, information, and knowledge effectively and efficiently. The work of nurse informaticists has become germane to the future of all nurses’ work.

Health Information Technologies Impacting Nursing As established in the Informatics Roles and the Knowledge Work of Nursing chapter, nurses are classified as knowledge workers. Studies have identified that, depending on the setting, nurses spend between 25% and 50% of their day managing and recording clinical information and seeking knowledge to inform their practice (Gugerty et al., 2007). 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 are then forever lost unless manually extracted for research purposes.

As evidence to support nursing practice continues to be uncovered by researchers and integrated into healthcare delivery, attention must be given to the tools that afford ready and easy access to this evidence. It could be suggested that as knowledge workers, nurses are also, albeit unwittingly, informaticians to a large extent. 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.

The impact of CISs on the practice of nursing is just beginning to be explicated because the opportunities to study wholly computerized clinical environments have been limited to date. As yet, the evidence that CISs actually improve nursing efficiency has been inconclusive. Poissant, Pereira, Tamblyn, and Kawasumi (2005) found that bedside terminals and central station desktops resulted in a 24% reduction in the time nurses spent on documentation activities. However, surveys of nurses’ perceptions and attitudes toward CISs have suggested that although the quality of documentation may improve, the amount of time associated with completing computer-related tasks increases (DesRoches, Donelan, Buerhaus, & Zhonghe, 2008; Kossman & Scheidenhelm, 2008). Others have

not found a significant time savings for nurses using specific CIS applications (Asaro & Boxerman, 2008; Franklin, O’Grady, Donyai, Jacklin, & Barber, 2007; Hakes & Whittington, 2008). A 2005 Health Information Management Systems Society survey of nurses (n = 1,760) revealed that most nurses believe that CISs improve patient safety (86%) and facilitate interdisciplinary collaboration (69%) and independent decision making (72%) (Dykes et al., 2005).

A 2011 study by Hripcsak, Vawdrey, Fred, and Bostwick used clinical log data to track various members of the healthcare team and their time spent generating and reading clinical notes. Nurses spent between 21.4 and 38.2 minutes per day authoring notes and between 9.0 and 16.9 minutes per day viewing notes. This study did not track minutes per day spent on documenting items on flow sheets reflecting the plan of care, which most likely accounts for the bulk of nursing documentation time. Perhaps the most interesting finding of this study is the low rate at which members of the team actually read the notes generated by members of the team.

These findings are reflective of what promises to be a growing trend in clinical settings as the sophistication and functionality of CISs continue to advance. However, more research is needed to understand the full extent of the impact of the current and future CISs on nursing practice.

Nurses Creating and Deriving New Knowledge Nursing Data Standards There are major efforts under way—internationally through the International Council of Nurses’ (2010) 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 CISs, because the capacity to 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 CIS 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 CISs 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).

Although significant progress has been made in this standardization work, it is still in its early days. Box 8-1 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 8-1 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 electronic health records are used in a meaningful way; achieving this goal will be problematic without consistent terminology (see the Legislative Aspects of Nursing Informatics: HITECH and HIPAA chapter for more information on the HITECH Act). 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 American Nurses Association (ANA, 2007), which operates a process of de jure standardization through its Committee for Nursing Practice Information Infrastructure (CNPII; http://www.nursingworld.org/MainMenuCategories/Policy-

Advocacy/Positions-and-Resolutions/ANAPositionStatements/Position-Statements-Alphabetically/PrivacyandConfidentiality.html). The ANA- approved list of nursing languages was presented in the Overview of Nursing Informatics chapter.

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. 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.

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]. http://ec.europa.eu/enterprise/ict/policy/doc/2007-ict-std-full-rep.pdf Werley, H. H., & Lang, N. M. (Eds.). (1988). Identification of the Nursing Minimum Data Set. New York, NY: Springer.

Integrated Decision Support Tools

CDS tools have evolved beyond the previously prevailing notion of these tools as accessible reference texts and written resource materials, such as policies and procedures. In the world of clinical computing, the capability to link various information sources and present a clinician with immediate guidance and support has begun to net benefits for safer care and improved clinical outcomes. Osheroff and colleagues (2007) defined CDS as tools that “provide clinicians, staff, patients, or other individuals with knowledge and person-specific information, intelligently filtered or presented at appropriate times, to enhance health and health care” (p. 141).

Most available CDS tools for nursing practice, although promising, are simplistic and in early development. Typically, CDS 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.

Nursing Knowledge in Evolution

Many renowned nurse authors have described the knowledge used by nurses (Benner, 1983; Carper, 1978; Schultz & Meleis, 1988). According to Carper (1978), “nursing … depends on the scientific knowledge of human behavior in health and in illness, the esthetic perception of significant human experiences, a personal understanding of the unique individuality of the self and the capacity to make choices within concrete situations involving particular moral judgments” (p. 22).

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 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.

Generating Nursing Knowledge 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. Of particular importance to the future design of CIS is the adoption of clinical data standards. Although this research is beyond the scope of this chapter, at least two decades of work effort 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, and recent work suggests that significant strides have been achieved (Bickford & Hunter, 2006; Delaney, 2006; Hannah et al., 2009). 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.

Challenges in Getting There Leadership The number of nurse leaders in health informatics has grown to a marked extent in the past two decades. Nevertheless, a significant knowledge gap remains to be addressed within the nursing leadership community. Many nurse leaders need to acquire a new set of skills and knowledge to understand and advance the adoption of information tools and technologies to support the delivery of clinical care. For several years, nurse informaticians have advocated for the need for all nursing leaders to become knowledgeable and engaged in setting the direction for informatics in the profession (Nagle, 2005; Pringle & Nagle, 2009; Simpson, 2000). Strategies for achieving this goal include the following: (1) identify the informatics education needs of nurse leaders, (2) develop mentorship programs for the

acquisition of informatics leadership skills, and (3) ensure enrollment of nurse leaders as sponsors for electronic health record (EHR) initiatives.

Clinical Practice

Despite valiant efforts to implement comprehensive CIS throughout North American healthcare settings, there are still many provider organizations with limited online functionality available to nurses. As indicated by numerous studies and reports on the state of IT adoption, many providers remain in the early phases of CIS acquisition and implementation (Eggert & Protti, 2006). In an unexpected twist, this lag is probably good news for nursing; it means there is an opportunity for nurses to immerse themselves in the developmental work of IT solutions to support practice.

Over the years, nurses have frequently been on the receiving end of systems that either did not add value to their work or, by virtue of their poor design, created additional work. Now nurses have the opportunity to head off future installations of IT solutions that do nothing to benefit and support the clinical practice of nurses and healthcare teams. It behooves nurses to become engaged in the acquisition, design, implementation, and evaluation of CIS to ensure that they realize the benefits of these systems for clinical care and outcomes.

It is equally important to consider that because of the average age of most practicing nurses, many have yet to develop a comfort level with the use of computers in their work settings. To minimize the anxiety associated with expected IT use, particular attention needs to be given to the issue of computer literacy. If nurses lack a solid footing in computer use, expectations for integration of informatics will prove difficult to realize. Strategies for nurses include the following: (1) seek encouragement and support to participate in the acquisition, design, implementation, and evaluation phases of CIS; (2) demand the adoption of IT solutions that support the delivery of safe, quality care; and (3) obtain the material and people resources needed to support their acquisition of informatics competencies.

Education

Over the years, numerous efforts have been undertaken to identify the core informatics competencies needed by nurses. These efforts have encompassed attempts to articulate core competencies for all nurses, from novice to expert (Hebert, 2000) and competencies for informatics experts (Hersh, 2006). In recognizing NI as a specialty, the American Nurses Association (2008) has articulated scope and standards of NI practice. What remains clear is that although progress has been made in the preparation of NI experts, much work remains to be done at the grassroots level of nursing education.

Studies of schools of nursing indicate that few basic nursing education programs have embedded the concepts and processes associated with informatics within the core curricula (Carty & Rosenfeld, 1998; Nagle & Clarke, 2004). Nevertheless, informatics content is now being slowly integrated into curricula. The primary obstacles to realizing curricula with embedded informatics concepts include a lack of faculty capacity, constraints of clinical practice environments (e.g., lack of student access to CISs), and limited funding. These barriers need to be addressed to ensure that graduates of the future are prepared to work in settings using information technology to support clinical care.

The core concepts and competencies of informatics are particularly well suited to a model of interprofessional education. Ideally, when emulating clinical settings, informatics knowledge should be integrated with the processes of interprofessional teamwork and decision making. Because simulation laboratories are becoming increasingly common fixtures in the delivery of health professional education, they provide a perfect opportunity to incorporate EHR applications, including access to CDS. The learning laboratory will then more closely approximate the IT-enabled clinical settings that are emerging in the real world.

An assumption is often made that future graduates will be more computer literate than the nurses currently in practice. Although this is likely true, computer comfort does not equate to an understanding of the facilitative and transformative role that IT will have in the future. It is essential that the future curricula of basic nursing programs incorporate the concepts related to the role of information technology in supporting clinical care delivery. Strategies to address the educational issues related to CIS include the following: (1) share prototypes of informatics integration among schools of nursing, (2) consider interprofessional education opportunities in addressing informatics concepts and competencies, (3) obligate nursing faculty to attain basic informatics competencies and support them as they do so, (4) seek and allocate funding for the development of innovative curricular models and associated technological support, and (5) incorporate accreditation criteria that necessitate an integration of informatics core concepts and competencies in all basic nursing programs.

In an Ideal World

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 wellbeing of citizens will be highly respected and parallel, if not exceed, the preeminence granted physicians.

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. 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. 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 CIS and CDS to achieve the global aspiration of safer, quality care for all citizens.

Summary 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 and competencies 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. What are the possibilities to accelerate the generation and uptake of new nursing knowledge? 2. What should be the areas of priority for the advancement of informatics in nursing? 3. How can a single agreed-upon model of terminology use (with linkages to a single terminology) help to integrate knowledge into routine clinical

practice?

References American Nurses Association (ANA). (2008). Scope and standards of nursing informatics practice. Washington, DC: Author. Asaro, P.V., & Boxerman, S. B. (2008). Effects of computerized provider order entry and nursing documentation on workflow. Journal of the American

Medical Informatics Association, 14(4), 415–423. Benner, P. (1983). Uncovering the knowledge embedded in clinical practice. Image: The Journal of Nursing Scholarship, 15(2), 36–41. Bickford, C. J., & Hunter, K. M. (2006). Theories, models, and frameworks. In V. K. Saba & K. A. McCormick (Eds.), Essentials of nursing informatics

(4th ed., pp. 265–278). New York, NY: McGraw-Hill. Carper, B. A. (1978). Fundamental patterns of knowing in nursing. Advances in Nursing Science, 1(1), 13–23. Carty, B., & Rosenfeld, P. (1998). From computer technology to information technology: Findings from a national study of nursing education.

Computers in Nursing, 16(5), 259–265. Delaney, C. W. (2006). Nursing minimum data set systems. In V. K. Saba & K. A. McCormick (Eds.), Essentials of nursing informatics (4th ed., pp.

249–261). New York, NY: McGraw-Hill. DesRoches, C. K., Donelan, P., Buerhaus, P., & Zhonghe, L. (2008). Registered nurses’ use of electronic health records: Findings from a national

survey. Medscape Journal of Medicine, 10(7), 164–173. Dykes, P., Cashen, M., Foster, M., Gallagher, J., Kennedy, M., MacCallum, R., … Whetstone, S. (2005). Surveying acute care providers in the U.S. to

explore the impact of HIT on the role of nurses and the interdisciplinary communication in acute care settings. Journal of Healthcare Information Management, 20(2), 36–44.

Eggert, C., & Protti, D. (2006). Clinical electronic communications: A new paradigm that is here to stay? Electronic Healthcare, 5(2), 88–96. Franklin, B. D., O’Grady, K., Donyai, P., Jacklin, A., & Barber, N. (2007). The impact of a closedloop electronic prescribing and administration system

on prescribing errors, administration errors, and staff time: A before and after study. Quality and Safety in Health Care, 16(4), 279–284. Graves, J. R., & Corcoran, S. (1989). The study of nursing informatics. Image: The Journal of Nursing Scholarship, 21(4), 227–231. Gugerty, B., Maranda, M. J., Beachley, M., Navarro, V. B., Newbold, S., Hawk, W., … Wilhelm, D. (2007). Challenges and opportunities in

documentation of the nursing care of patients. Baltimore, MD: Documentation Work Group, Maryland Nursing Workforce Commission. http://www.mbon.org/commission2/documentation_challenges.pdf

Hakes, B., & Whittington, J. (2008). Assessing the impact of an electronic medical record on nurse documentation time. Computers Informatics Nursing, 26(4), 234–241.

Hannah, K. J. (1995). Transforming information: Data management support of healthcare reorganization. Journal of the American Medical Informatics Association, 2(3), 147–155.

Hannah, K. J., White, P., Nagle, L. M., & Pringle, D. M. (2009). Standardizing nursing information in Canada for inclusion in electronic health records: C-HOBIC. Journal of the American Medical Informatics Association, 16(4), 524–530.

Hardiker, N. (2011). Developing standardized terminologies to support nursing practice. In D. McGonigle & K. Mastrian (Eds.), Nursing informatics and the foundation of knowledge (2nd ed., pp. 11–119). Sudbury, MA: Jones & Bartlett Learning.

Hersh, W. (2006). Who are the informaticians? What we know and should know. Journal of the American Medical Informatics Association, 13(2), 166– 170.

Hripcsak, G., Vawdrey, D., Fred, M., & Bostwick, S. (2011). Use of electronic clinical documentation: Time spent and team interactions. Journal of the American Medical Informatics Association, 18, 112–117.

International Council of Nurses. (2010). ICNP version 2.0. http://www.icn.ch/pillarsprograms/international-classification-for-nursing-practicer/ Kossman, S. P., & Scheidenhelm, S. L. (2008). Nurses’ perceptions of the impact of electronic health records on work and patient outcomes. Computers

Informatics Nursing, 26(2), 69–77. Nagle, L. M. (2005). Dr. Lynn Nagle and the case for nursing informatics. Canadian Journal of Nursing Leadership, 18(1), 16–18. Nagle, L. M., & Clarke, H. F. (2004). Assessing informatics in Canadian schools of nursing. Proceedings 11th World Congress on Medical Informatics

[CD]. San Francisco, CA. Nagle, L. M., White, P., & Pringle, D. (2010). Realizing the benefits of standardized measures of clinical outcomes. Electronic Healthcare, 9(2), e3–e9. O’Neal, P. V., Grap, M. J., Thompson, C., & Dudley, W. (2001). Level of dyspnea experienced in mechanically ventilated adults with and without saline

instillation prior to endotracheal suctioning. Intensive Critical Care Nursing, 17(6), 356–363. Osheroff, J. A., Teich, J. M., Middleton, B., Steen, E. B., Wright, A., & Detmer, D. E. (2007). A roadmap for national action on clinical decision

support. Journal of the American Medical Informatics Association, 14(2), 141–145. Poissant, L. J., Pereira, R., Tamblyn, R., & Kawasumi, Y. (2005). The impact of electronic health records on time efficiency of physicians and nurses: A

systematic review. Journal of the American Medical Informatics Association, 12(5), 505–516. Pringle, D., & Nagle, L. M. (2009). Leadership for the information age: The time for action is now. Canadian Journal of Nursing Leadership, 22(1), 1–

6. Schultz, P. R., & Meleis, A. I. (1988). Nursing epistemology: Traditions, insights, questions. Image: The Journal of Nursing Scholarship, 20(4), 217–

221. Simpson, R. L. (2000). Need to know: Essential survival skills for the information age. Nursing Administration Quarterly, 25(1), 142–147. Staggers, N., & Thompson, C. B. (2002). The evolution of definitions for nursing informatics: A critical analysis and revised definition. Journal of the

American Medical Informatics Association, 9(3), 255–261.

Chapter 9

Legislative Aspects of Nursing Informatics: HITECH and HIPAA Kathleen M. Gialanella, Kathleen Mastrian, and Dee McGonigle

OBJECTIVES

1. Describe the purposes of the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009. 2. Explore how the HITECH Act is enhancing the security and privacy protections of the Health Insurance Portability and Accountability Act

(HIPAA) of 1996. 3. Determine how the HITECH Act and its impact on HIPAA apply to nursing practice.

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 record Enterprise integration Entity Gramm-Leach-Bliley Act Health disparities Health information technology Health Insurance Portability and Accountability Act Health Level 7 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 Policy Privacy Protected health information Qualified electronic health record Rights Sarbanes-Oxley Act Security Standard Standards-developing organizations Treatment/payment/operations

Introduction 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 addresses Medicare and Medicaid HIT and provides significant financial incentives to healthcare professionals and hospitals that adopt and engage in the “meaningful use” of electronic health record (EHR) technology.

This chapter presents an overview of the HITECH Act, including the Medicare and Medicaid 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 EHR age. The concepts of “meaningful use” and “certified EHR technology” also are explored in this chapter.

Overview of the HITECH Act 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 seeks to change that situation by providing each person in the United States with an EHR. In addition, a nationwide HIT infrastructure will 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.

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 U.S. Department of Health and Human Services (HHS). 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 HHS, has been releasing a national healthcare quality report (NHQR) every year since 2003, and the current report, not unlike previous reports, finds the quality of health care in this country to be “suboptimal” (p. 2). The NHQR has also discussed 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 H1N1 flu pandemic 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 (2010), “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. Its current report, 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 (Box 9-1). The specific changes are discussed in greater detail later in this chapter.

BOX 9-1 OVERVIEW OF THE HEALTH INSURANCE PORTABILITY AND ACCOUNTABILITY ACT OF 1996 Dee McGonigle, Kathleen Mastrian, and Nedra Farcus 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 Department of Health and Human Services (HHS) has 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. (See the Statement of Delegation of Authority to the Office for Civil Rights, as published in the Federal Register on December 28, 2000. (U.S. Department of Health and Human Services, 2006, para. 1)

The need and means to guarantee the security and privacy of health information have been 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 U.S. Department of Health and Human Services 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).

One of the biggest stumbling blocks to implementation of comprehensive standards for privacy was the associated cost. The administrative simplification portion of HIPAA calling for standardized forms for claims, medical records, laboratory reports, insurance forms, and so forth was expected to save as much as $250 billion after the initial conversion costs. HHS projected that compliance with the proposed security and privacy rules would cost $6.7 billion. Not everyone agreed with the HHS estimate, however; a study conducted by Blue Cross/Blue Shield and reported by Egger (2000) suggested that the costs would be closer to $43 billion over 5 years. An overview of the proposed standards helps to illustrate why implementation was estimated to be so costly.

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).

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