Healthcare Information Technology and Medical Surgical Nurses: The Emergence

of a New Care Partnership

A Thesis

Submitted to the Faculty

of

Drexel University

by

An'Nita C. Moore

in partial fulfillment of the

requirements for the degree

of

Doctor of Nursing Practice

May 2010

ii

Dedications

I would first like to dedicate this thesis to my parents for their relentless confidence and

support in my educational endeavors. They‟ve always been my largest supporters

throughout my academic matriculation and without a doubt, this success is just as much

theirs as it is mine. Congratulations! Secondly, I‟d like to dedicate this thesis to all of the

children in my life – Calvin, Kanell, KaNya, Kayla, Christian, Kirsten, Deja, Daria, &

Daliyah. Never doubt your ability to excel and succeed. It is possible to maintain a

balance between hard work and hard play! If you push yourself beyond the realm of

comfort, you‟ll be surprised at how much you can achieve. However, if you aren‟t able to

push yourself, don‟t worry; I don‟t mind giving you a healthy nudge. Lastly, I would like

to dedicate this thesis to my family, friends, colleagues, and associates who have a desire

to embark upon and/or complete academic pursuits but have been unable to do so. Know

that I carry the torch for you as well as myself as I recognize that I am not an isolated

being, but rather a representative of my community.

iii

Acknowledgements

There have been so many who have contributed to my degree completion in one way or

another I hope I am able to do justice in acknowledging their involvement. First and

foremost, I must thank God who is the head of my life. I know the terminology is very

cliché, but I mean it with all sincerity. So many times I‟ve asked “Father, why me? –

Why did you pick me at such a young age to achieve the successes I‟ve been able to

achieve? Why have you allowed me to progress in a season when so many others have

experienced set-backs? How have I been able to matriculate through ten years of college

without any student loans or debt? How did I manage to complete my degree

requirements early and be the first African-American to graduate from this program?”

While there are many things I do know, I don‟t have a sensible answer to any of these

questions so with meekness and sincerity all I can say is “Father, thank you!” I would be

remiss to if I did not acknowledge the guidance I received from my supervising

professor, Dr. Kathleen Fisher, as well as my other committee members, Dr. Fran

Cornelius, Dr. Prudence Dalrymple, and Dr. Jean Giddens. They served as a perfectly

blended group with unique contributions all aimed toward helping me succeed. I must

extend an additional note of gratitude to Dr. Fisher for her flexibility in working with me.

I appreciate you making yourself available to me and being sensitive to my proposed

timeline. To my classmates who were a part of the Drexel dozen, I must say I greatly

benefited from each of your unique perspectives, our collegial debates, and the healthy

competition experienced. Rita thank you again for opening your doors to me the times I

needed to stay in Philadelphia. It meant a great deal to me. Becky, Deanne, Stephanie,

and Lisa, you don‟t know how great it felt to have you share in my special day with me.

iv

The comradery shown was genuine and I was comforted by it. I must extend a very

special thank you to my other half Darnell. I‟m quite sure I metmorphosed into a

minimum of 12 personalities over the past three years - thank you for your patience!

LaKeisha, thank you for working with me as my focus group moderator. I know it wasn‟t

the easiest task to fit into your busy schedule but you found a way. Joy I appreciate the

opportunity to bounce information around with you regarding the use of data analysis

packages. That‟s not a topic most people want to talk about but you were just excited

about it as I. Tamika thank you for your genuine excitement and zeal for my success. Last

but not least, Pam thank you for your quiet support during this process. I know that many

times you extended latitude and understanding as I shifted priorities – you are

appreciated.

v

Table of Contents

LIST OF TABLES .......................................................................................................... vii

LIST OF FIGURES ........................................................................................................ viii

ABSTRACT ....................................................................................................................... ix

CHAPTER 1: INTRODUCTION AND OVERVIEW .................................................. 1

1.1. Introduction ........................................................................................................1

1.2. Background ........................................................................................................2

1.3. Purpose................................................................................................................3

1.4. Research Questions ............................................................................................3

1.5. Significance .........................................................................................................4

1.6. Limitations ..........................................................................................................5

1.7. Delimitations .......................................................................................................6

1.8. Summary .............................................................................................................6

CHAPTER 2: REVIEW OF THE LITERATURE........................................................ 8

2.1. Introduction ........................................................................................................8

2.2. Concept One: The Nurse-Technology Dyad ....................................................8

2.3. Concept Two: Healthcare Information Technology ..................................... 10

2.4. Concept Three: Clinical Decision Making ..................................................... 14

2.5. Summary ........................................................................................................... 17

CHAPTER 3: DESIGN AND METHODOLOGY....................................................... 19

3.1. Overall Approach and Rationale .................................................................... 19

3.2. Trustworthiness................................................................................................ 21

3.3. Methods ............................................................................................................. 22

3.4. Focus Groups .................................................................................................... 24

3.5. Site Selection ..................................................................................................... 26

3.6. Population Sample ........................................................................................... 28

3.7. Protection of Human Subjects ........................................................................ 29

3.8. Data Collection ................................................................................................. 30

3.9. Data Analysis .................................................................................................... 31

vi

3.10. Epoche ............................................................................................................... 33

CHAPTER 4: RESULTS ............................................................................................... 35

4.1. Introduction ...................................................................................................... 35

4.2. Overview of the Study ..................................................................................... 35

4.3. Subject Demographics ..................................................................................... 36

4.4. Themes .............................................................................................................. 38

4.5. Novice and Experienced Nurses: Perceptual Similarities and Differences 44

CHAPTER 5: SUMMARY & IMPLICATIONS FOR FUTURE RESEARCH ....... 54

5.1. Overview of Study ............................................................................................ 54

5.2. Conclusions ....................................................................................................... 54

5.3. Limitations of Study ........................................................................................ 62

5.4. Recommendations for Future Research ........................................................ 62

LIST OF REFERENCES ............................................................................................... 64

APPENDIX A: LIFEBRIDGE HEALTH IRB APPROVAL ...................................... 70

APPENDIX B DREXEL UNIVERSITY IRB APPROVAL ........................................ 71

APPENDIX C: INFORMED CONSENT DOCUMENT ............................................. 73

APPENDIX D: FOCUS GROUP INTERVIEW GUIDE ............................................. 83

APPENDIX E: DEMOGRAPHIC DATA COLLECTION FORM ............................ 84

APPENDIX F: CATEGORICAL ANALYSIS OF FINDINGS .................................. 88

APPENDIX G: VENN DIAGRAM COMPARISON OF DATA CATEGORIES ..... 92

APPENDIX H: DEMOGRAPHIC DATA SUMMARY .............................................. 93

VITA ............................................................................................................................ 94

vii

List of Tables

AH. Demographic Data Summary …………………………………………………...93

viii

List of Figures

1. Venn Diagram Comparison of Data Categories…………………………….92

ix

Abstract Healthcare Information Technology and Medical Surgical Nurses: The Emergence of a

New Care Partnership

An‟Nita C. Moore, DrNP

Kathleen Fisher, PhD – Supervising Professor

Currently, increasing numbers of hospitals and ambulatory care institutions in the United

States are experiencing expanding use and diffusion of healthcare information technology

(HIT), including more expansion toward the electronic health record (EHR). Considering

nurses are responsible for documenting, interpreting, and acting upon the voluminous

amount of data maintained by information systems, it is imperative that they efficiently

utilize HIT by effectively analyzing the data it yields to aid in their clinical decision

making. A few studies have addressed the relationship between nurses and information

technology in practice, unfortunately the body of literature relative to the topic is narrow

and was primarily explored prior to the proliferate implementation of EHRs. This study

sought to explore two focal points with regards to the interaction between healthcare

information technology and nurses, the first being how medical surgical nurses are

utilizing HIT in their current clinical practice. The second aim was to examine the

influence of HIT on nurses‟ clinical decision making. Utilizing qualitative content

analysis, data from two homogeneous focus groups of novice and experienced nurses was

analyzed to evaluate the identified research questions. Findings from data collected from

both groups suggest that nurses‟ clinical decision making is not overtly influenced by the

use of healthcare information technology. Five themes emerged that described nurses‟

experiences with the information technology. The following were identified as theme

labels: (a) healthcare information technology as a care coordination partner, (b)

x

healthcare information technology as a change agent in the care delivery environment, (c)

healthcare information technology – unable to meet all the needs, of all the people, all the

time, (d) curiosity about healthcare information technology – what other bells and

whistles exist, and (e) big brother is watching. Nurses‟ use of new information

technology is more reliant on its‟ ability to organize and coordinate care for assigned

patient groups as opposed to guiding decision making. Results of this study suggests that

a new care partnership has emerged as the provision of nursing care is no longer supplied

by a single practitioner but rather by a paired team, consisting of nurses and technology.

1

CHAPTER 1: INTRODUCTION AND OVERVIEW

1.1. Introduction

Currently, increasing numbers of hospitals and ambulatory care institutions in the

United States are experiencing expanding use and diffusion of healthcare information

technology (HIT), including more expansion toward the electronic health record (EHR)

(Taylor, et al., 2005). Survey estimates suggest approximately 27% of acute care

hospitals and 12% of ambulatory care settings have adopted various forms of electronic

health records (Bower, 2005). This progressive shift toward electronic health records has

begun to augment the delivery of patient care thus resulting in a dramatic transformation

in the care giving paradigm. Representing the largest portion of direct caregivers,

registered nurses have been labeled the largest consumers of HIT (Deese & Stein, 2004).

Because of their continuously interdependent working relationship, healthcare technology

has become an integral component of contemporary workflow practices for nurses.

Despite the safety and efficacy benefits provided by HIT, it has not been clearly

substantiated that the presence of highly advanced healthcare information technology in

the workplace truly influences a nurse‟s clinical decision making, thus potentially

improving health outcomes (Weber, 2007).

Considering nurses are responsible for documenting, interpreting, and acting upon

the voluminous amount of data maintained by clinical information systems (CIS), it is

imperative that they efficiently utilize HIT by effectively analyzing the data it yields to

aid in their clinical decision making (Kleiman & Kleiman, 2007). The majority of clinical

information systems literature focuses on practitioners‟ acceptance and use, factors

influencing successful system implementation, workflow considerations, as well as

2

perceived and actual benefits (Davis, 1989; McGrath, 2008; Prince & Herrin, 2007;

Zuzelo, Gettis, Hansell, & Thomas, 2008). What remains to be further examined

however, is the interaction between nurses and technology since the infusion of more

technology in the nursing workplace is likely to continue. However, the expense of

purchasing, training, and updating healthcare technology is immense, and even more so

in a less than robust economic climate. A typical nurse‟s 24/7 use of technology to

support and deliver care must be maximized to be cost effective.

1.2. Background

The nursing literature has largely focused on the complexities experienced by

nurses in their increased roles and responsibilities to manage healthcare technologies

(Almerud, Alapack, Fridlund, & Ekebergh, 2008; Henderson & Henderson, 2006;

Zuzelo, Gettis, Hansell, & Thomas, 2008). Considering the necessity to manage clinical

and technical knowledge, it is not surprising that the consequences of the interaction

remain unknown. Research suggests that experienced nurses are better equipped to

optimally incorporate technology into their practice as opposed to their less-experienced

counterparts (Tabak, Bar-Tal, & Cohen-Mansfield, 1996). Experienced nurses have also

been found to possess refined clinical decision making skills thus enhancing their patient

care abilities (Banning, 2008). Clinical Decision Support Systems (CDSS) have been

introduced to aid in clinicians‟ decision making although questions have been raised

regarding its effect on health outcomes. In other words, is there really a true payoff or

benefit to the technology? A few studies have addressed the relationship between nurses

and technology in practice and have similarly concluded that the value of technology is

not determined by the technology itself, but rather by the user‟s appraisal of it (Holroyd,

3

et al., 2007; Weber, 2007). Unfortunately the body of literature relative to the topic is

narrow and was primarily explored prior to the proliferate implementation of EHRs.

However, literature does provide descriptive templates for institutional administrators

implementing CDSS. Considerations include obtaining early user participation by

allowing end-users an opportunity to engage in needs assessments prior to the selection

of a system, allowing clinical staff an opportunity to test applications in a simulation or

pilot setting prior to widespread use, extending invitations to nurse experts to work with

system designers in individualizing system settings to reflect practical clinical scenarios,

and increasing the availability of resource staff when new CIS‟s are first introduced.

Despite the presence of suggested integration strategies to optimize acceptance and

success, institutions have liberty in determining what elements they choose to include in

implementation tactics.

1.3. Purpose

The objective of this study was to address the gap in current literature relative to

the relationship between nurses and technology in practice. Thus, the primary intent of

this project was to explore nurses‟ experiences with HIT and to better discern if the new

clinical decision support systems enhanced nurse‟s clinical decision making (CDM). The

long term goal of this project was to establish a foundation for programs that can be

developed to help novice nurses effectively and appropriately integrate HIT into their

practice.

1.4. Research Questions

The specific questions of this study were to evaluate:

1.4.1. Question One

4

How are medical surgical nurses utilizing healthcare information technology in their

current clinical practice?

1.4.2. Question Two

Is nurse‟s clinical decision making influenced by healthcare information technology?

1.5. Significance

As the prevalence of HIT continues to rise, it will be critical to ensure that nurses

continue to develop and maintain the cognitive skills necessary to practice as efficient

clinicians. Unfortunately, cognitive competence in the area of clinical decision making is

potentially compromised when clinicians excessively rely on external forms of support

such as clinical decision support systems. This study is paramount in examining how

nurses currently interact with HIT so that as healthcare environments continue to flourish

with advanced forms of technology, appropriate consideration is also given to the

development of nurses responsible for the effective and efficient use of clinical

information systems.

Additionally, it is essential that those involved in CIS implementation efforts

evaluate and address practical integration in addition to logistical considerations. The

American Association of Colleges of Nurses recently deemed the management and

application of information and patient care technology an essential element to be taught

to baccalaureate nursing students (2009). Effective integration for the nurse clinician

necessitates the development and maintenance of well-developed clinical decision

making skills to prioritize the role of HIT in patient care. As the largest consumers of

healthcare information technology, the nursing profession is best suited to lead an

evaluation of how nurses are integrating HIT into their practice. This work facilitates a

5

better understanding of how nurses are using CIS and its impact on CDM. The resulting

knowledge will help structure HIT implementation and evaluation efforts to ensure

optimal benefits for patients, nurses, and society.

1.6. Limitations

Limitations of the study were relative to recruitment strategies, investigator

influence, data collection method, and applicability to other settings. The participants

were recruited through purposive sampling which does not allow for the adequate

probability that the sample will be representative of the population as a whole.

Additionally, the nurse researcher worked in the research setting with direct interaction

with most members of the targeted population and as such may have influenced

participant responses. Although open-ended questions were asked, the presence of the

nurse investigator as the interviewer could have persuaded participants to respond in a

manner they perceived as favored versus truthful. Therefore, a facilitator conducted the

focus groups to avoid undue influence. Literature has reported that one of the downfalls

of group interviews is that one to two members generally dominate the discussion which

may interfere with the participation of more passive members (Stewart & Shamdasani,

1990a). Lastly, the researches applicability to other settings is of concern. Qualitative

research is often critiqued regarding the usefulness of its‟ findings beyond the sample

population of interest. The cooperating facility has its own set of cultures and norms that

may influence user interactions which may not be shared with other healthcare

institutions.

6

1.7. Delimitations

Several measures were taken to mitigate the study‟s limitations and increase

trustworthiness of the work. To eliminate investigator influence of participant responses,

a moderator was utilized to conduct the focus group sessions. The moderator has

experience with leading focus groups as she has previously functioned in that capacity as

part of a multi-site National Institute of Mental Health funded study. Additionally the

moderator‟s direction of questions to participants helped to facilitate a balanced group

interview and allowed both introvert and extrovert participants an opportunity to share

their experiences. Albeit that qualitative research is criticized for the applicability of

generated knowledge to other settings, generalizability is not a primary goal of qualitative

research. It is important however that consumers of the work gain knowledge that is

useable and transferable into practice. The methods of the research process for this study

have been meticulously described so that based upon the design and sample population

consumers can adequately appraise the usefulness of research findings to their current

practice environment.

1.8. Summary

Nurses providing patient care in current technologically enhanced environments face

a level of complexity not previously encountered by veteran clinicians. HIT literature has

demonstrated the efficacy of its‟ systems relative to clinician workflow, improved

efficiency in care delivery, as well as enhancing patient safety. Despite possible benefits,

researchers have demonstrated that successful outcomes cannot be attained without early

end-user involvement, thoughtful system integration, and seamless organizational and

process considerations. The progressive emergence of healthcare information technology

7

has expanded the role of nurses from care coordinators to also functioning as information

processors. Effectively blending responsibilities requires knowledgeable professionals

who are well prepared to balance care demands with technology influences.

Although existing literature has evaluated the mitigating effects of technology on

workflow, medical errors, and patient outcomes, a very narrow body of literature has

raised concern with nurses‟ integration of technology into their practice in an effort to

achieve proposed beneficial outcomes. Considering contraindication exists regarding the

benefits of clinician use of HIT, additional exploration is indicated. Existing literature has

taken into consideration user interactions with Healthcare Information Systems which are

influenced by factors such as perceived ease of use, perceived usefulness, and prior

exposure to technology (Davis, 1989). Further investigation is necessary centered upon

the narrow focus of how clinicians integrate the components of HIT into their practice

that aid in cognitive performance, such as clinical decision making, without

compromising the development of analytical and logical thought processes that are

essential for nursing functions. The nurse educator and scholar have an opportunity to fill

the gap in HIT literature relative to technology use, thus impacting HIT implementation

considerations.

8

CHAPTER 2: REVIEW OF THE LITERATURE

2.1. Introduction

The progression of healthcare delivery has been augmented not only by changes

in practice but also by assistive resources utilized for the enhancement of patient care,

resulting in a dramatic change in the care giving paradigm. Similar to other professions,

the healthcare industry has incorporated the use of varying forms of technology to help

streamline care delivery, secure patient confidentiality, and improve patient safety as well

as health outcomes (Almerud, et al., 2008; Ammenwerth, Iller, & Mahler, 2006; Barnard,

1999; Barnard & Sandelowski, 2001; Henderson & Henderson, 2006; Simpson, 2004;

Summers, 2007). Accordingly, nurses as care providers are challenged with balancing

artful care delivery with technology navigation while maintaining a positive nurse-patient

relationship. The introduction of HIT and clinical information systems has expanded the

realm of nursing to integrate technology as an element as important in nursing practice as

the patient or population being served (Huffman & Sandelowski, 1997).

2.2. Concept One: The Nurse-Technology Dyad

Many nurses have embraced technology as a part of their care delivery model. As

a result, the provision of nursing care is no longer supplied by a single practitioner but

rather by a paired team, consisting of nurses and technology, working collaboratively in

an interdependent relationship to achieve established goals. A combination of two

separate terms, the concept of the nurse-technology dyad may be further understood by

defining its components. As depicted in the Miriam-Webster dictionary the term nurse

refers to an individual who cares for others who are ill or are in poor health. The source

further describes a nurse as a person who looks after, promotes and/or directs ("Nurse,"

9

2008). In their Occupational Outlook Handbook, the Bureau of Labor Statistics (2008)

describes a nurse relative to functions of the nursing profession. According to the agency,

a nurse is responsible for treating and educating patients, as well as the community, about

multiple medical conditions. They further describe the role of the medical surgical nurse

as one who offers health promotion and fundamental medical care to clients presenting

with a myriad of medical and surgical diagnosis. The concept of technology can convey a

multitude of connotations depending upon the context in which it is utilized. In her

review of technology in nursing, Sandelowski (1999a) proposes that technology can be

described as either an object, a representation of a secondary concept, or as an

interpretant that helps to understand another phenomena. Barnard (1996) discusses the

three ways technology can be considered. Technology can be defined by the use of

machinery, tools, or instruments, the essence of technological advancement, or its‟

existence as a science. Dominating literature relative to technology in healthcare is the

broad classifications of technology emergence in information processing and the

mechanization of skill or labor (Almerud, et al., 2008; Barnard, 1996; Deese & Stein,

2004; McGillivray, Yates, & McLister, 2007; Zuzelo, et al., 2008).

Human computer interaction (HCI) literature presents several models that attempt

to evaluate or explain end-user interaction with information technology (IT) (Au, Ngai, &

Cheng, 2002; Davis, 1989; Goodhue & Thompson, 1995). However, recent literature

critiques that prior HCI models were not best suited to evaluate clinical information

systems (CIS). Despont-Gros, Mueller, and Lovis (2005) developed a model to evaluate

user interactions with clinical information systems that gives consideration to the

complexities associated with healthcare information technology (HIT). The model

10

proposes six dimensions critical to the evaluation of CIS. A brief review of the variables

as evidenced in HIT literature will be discussed. User and system characteristics were

both identified as two separate components of the model. In his presentation of the

technology acceptance model, Davis (1989) proposed that perceived usefulness and

perceived ease of use are essential system characteristics affecting successful system

implementation. Additionally user characteristics such as years of experience and

professional training were described by Huffman & Sandelowski (1997), Aspiuynall

(1979), O‟Neil (2005), and Manias et al. (2004) as factors influencing user interaction

with CIS components. Impacts to individuals and organizations are also described as a

dimension of the model. Zuzelo and colleagues (2008) have identified that although

technologies improve the efficiency and efficacy of care delivery, they also increase the

likelihood of error and potentiate clinician dissatisfaction when system gaps are present.

Simpson (2007) further addresses the organizational and process related influences on

system implementation efforts as political forces requiring synergy for successful

outcomes. His description closely correlates with the use/context/environment aspect of

the HCI model. The process characteristic of the model is addressed in literature

discussing methods to achieve a successful system implementation. Hannah, Ball, &

Edwards (2005) provide a synopsis of informatics literature suggesting that nursing and

other end users are involved early in the planning phase of CIS implementation and that

adequate resource personnel are made available during the transition.

2.3. Concept Two: Healthcare Information Technology

Healthcare information technology is not a new concept for care environments

although it has assumed new dimensions within recent years. Computers emerged into

11

the healthcare environment in the 1950‟s and evolved throughout the remainder of the

20th

century for functions relative to payroll, patient charges, inventory, research,

education, and generating statistical data (Hannah, et al., 2005). However, healthcare

computing and technology made a drastic change in the 21st century after the release of

To Err is Human by the Institute of Medicine, which called for improved safety and

efficacy in healthcare delivery (To err is human, 1999). Currently, the term healthcare

information technology refers to systems that serve as a repository for healthcare data

that can be accessed by care providers for purposes of retrieval, transfer, communication,

and/or analysis (Barnard & Gerber, 1999; Deese & Stein, 2004; Medpac, 2004; Zuzelo, et

al., 2008). The term has been used synonymously with other concepts such as clinical

information system (CIS) since a precise definition does not exist.

In a congressional report submitted by the Medicare Payment Advisory

Commission (2004), three types of information technology are evident in hospital

settings: administrative and financial, clinical, and infrastructure. Considering ambiguity

that may exist in delineating healthcare information technology from clinical information

systems, further clarification will be provided. Healthcare information technology is a

broad terminology that is inclusive of systems that can be utilized for a multitude of

healthcare related functions including scheduling, maintaining inventory, personnel

record keeping, tracking performance improvement data, and billing purposes. Clinical

information systems are a subset of HIT as these systems have a more narrowed focus

toward providing support at the point of patient care. They gather, store, analyze, and

make available clinical data for use by various members of the healthcare team. There are

multiple components of clinical systems that exist although each system is not inclusive

12

of all components. Common applications of clinical information systems include

electronic health records/electronic medical records (EHR/EMR), clinical decision

support systems (CDSS), computerized provider/physician order entry (CPOE), results

reporting, and picture archiving (Medpac, 2004). Literature addressing healthcare

information technology has often focused on select CIS applications within their work as

opposed to HIT as a whole. A description of each of these CIS components will be

provided.

In their column assessing how nurses utilize HIT for improved care, Deese and

Stein (2004) describe EMR‟s as a resource that collects and stores lifelong patient care

data which can be synchronously accessed and viewed by various members of the

healthcare team. The electronic repository for patient data can be utilized to store some or

all aspects of a client‟s paper chart including provider orders, consult reports, test results,

the medication administration record (MAR) and progress notes. They further describe

the EHR as foundational for CIS. Ambiguity persists in nursing literature regarding a

concise definition for CDSS as various conceptualizations exist. Weber (2007) presents

six different characteristic descriptions of CDSS while more exist in other informatics

and information technology (IT) research. Most readily applicable is the description of

CDSS as heuristic-based computer software systems that are designed for clinician use to

aid in clinical decision making (Hannah, et al., 2005). Utilizing embedded rules and

decision-tree algorithms, this CIS element evaluates stored patient data to generate

suggestions for clinician actions (Holroyd, et al., 2007). Considering the proposed

function of CDSS, it is essential for the nursing profession to evaluate the influence of

CDSS on practice. Weber (2007) attempted to evaluate critical care nurse specialists‟

13

interaction with CDSS, however no identifiable patterns of use could be identified that

describe how the systems impacted their practice.

Yet another component of HIT is the ability for CPOE. This functionality allows

providers the ability to electronically prescribe medications, lab tests, and/or procedures

both from within a care institution as well as from remote locations such as provider

offices, home, or from mobile handheld devices (Hannah, et al., 2005; Medpac, 2004).

The impact of a computerized provider order entry system was evaluated in surgical

patients by Stone et al. (2009). The findings suggested increased efficacy was realized

relative to decreased time between order entry and nurse receipt, however the percentage

of medication errors remained comparably equivalent to those experienced prior to

system implementation. This may be explained by the continued need for clinician

evaluation of provider orders, despite their electronic format, to determine

appropriateness for the patient considering the context of the clinical situation. The

remaining components of HIT offer less complexity and ambiguity in scope versus those

previously discussed. Results reporting is a method by which laboratory or diagnostic

results are electronically stored and later retrieved by clinicians while picture archiving

refers to the electronic communication of filmless images, such as x-rays, that can be

conveniently viewed on a computer. Providers can access image results through the EHR,

negating the need to locate films from various imaging departments (Medpac, 2004).

There is a great deal of variability regarding whether or not a newly hired nurse or

nursing student entering a CIS environment would have prior exposure to the varying

CIS elements. Regional or institutional characteristics could however serve as a predictor

considering the most proliferative use of EHR‟s is evident in urban areas and in teaching

14

institutions (Jha, et al., 2009). Inconsistency in exposure is also influenced by the

flexibility exercised by facilities in implementing a CIS. Some institutions may choose to

maintain a hybrid electronic and paper environment by implementing isolated CIS

elements such as results reporting while other functions such as writing provider orders

remains paper based. Other institutions may create a clinical environment that is 100%

electronic requiring computerized devices to access any patient information necessary for

point of care activities. For the purposes of this research, the clinical decision support

element of CIS is the focus of consideration when evaluating nurses‟ interaction with

HIT.

Also variable in healthcare is the method by which CIS elements are introduced

into an environment. No single template exists for technology integration that is widely

accepted and utilized. As a result, end-users perception and use of the technology can be

greatly impacted by their initial exposure. Literature has however detailed factors

influencing positive introduction and adoption of HIT including the establishment of a

dedicated transition team, allowing an opportunity for early end-user involvement,

piloting the proposed system with a small user group, and providing ongoing training and

support (Hannah, et al., 2005).

2.4. Concept Three: Clinical Decision Making

Clinical decision making (CDM) is an essential aspect of nursing activity as

nurses are often responsible for interpreting and responding to a large volume of data.

The concept has been theoretically defined as making judgments about and consequently

choosing amongst options (Thompson & Dowding, 2002). Weber further describes the

process by which effective decision making is achieved to be inclusive of problem

15

detection, alternatives consideration, outcomes prediction, and finally a choice selection

(Weber, 2007). Two major models exist relative to clinical decision making practices

amongst nurses, the information processing model and the intuitive humanist model

(Banning, 2008; ONeill, et al., 2005; Weber, 2007). The information processing model

emphasizes a hypothetico-deductive approach suggesting that decision making is a

rationale process following sequential algorithmic-type thinking. CDM based in this

approach has been most dominant in healthcare literature (Banning, 2008).

In early CDM work, Aspiuynall (1979) noted that nurses had improved decision

making abilities with the use of decision trees. Additionally, O‟Neil and colleagues were

in agreement that algorithms can prove beneficial in achieving optimal outcomes

considering they‟ve identified the decision making process as complex and dependent

upon internal and external clinician characteristics (ONeill, et al., 2005). The information

processing approach has been observed in the practices of novice nurses as the most

prevalent model used. In a mixed methods study conducted by Manias, Aitken, &

Dunning (2004), 25 out of 37 nurse-client interactions displayed evidence of hypothetico-

deductive reasoning. The decision making method has not only proven useful for care

delivery but also to help build nurse-patient relationships. In a 2005 publication, Wu and

colleagues described their use of a decision tree to analyze how women concluded

whether or not to have a hysterectomy. As a result of the work, nurses were able to better

understand the thought processes of their patients as well as the need for appropriate

psychological and emotional support. Despite the beneficial outcomes that have been

achieved through application of the method, it must be noted that limitations may exist

relative to the algorithm‟s structure, decision points, or incorporation of current

16

knowledge (Banning, 2008). Considering the heuristic nature of clinical decision support

systems, it can be determined that their development is most closely aligned with the

hypothetico-deductive approach to decision making.

The humanist-inductive model has underpinnings in Patricia Benner‟s novice to

expert theory of clinical competence (Benner, 1984). The basis for decision making

utilizing this model is intuition and the knowledge gained through nursing experience

(Banning, 2008). In their exploratory study of CDM practices of 459 nurses in five

different countries, Lauri et al. (2001) identified a correlation between demographic

variables and decision making styles. Workers in acute care settings, with professional

education and clinical experience were most associated with intuitive CDM while those

with lower levels of education, in long-term settings, and utilizing theoretical knowledge

were more likely to subscribe to CDM practices within the realm of the information

processing model. Tabak and colleagues (1996) had similar outcomes in their evaluation

of the cognitive processes involved in decision making. They identified that experienced

nurses utilized their past experiences as a knowledge base to aid in decision making. The

intuitive aspect of the humanist-inductive model is closely linked with experience as it

relies upon pattern recognition as a CDM tool. A deficit of the approach is that the

prompting initiated by pattern recognition may be linked with incorrect decisions and the

memory of the clinician becomes integral in categorizing cues (Banning, 2008).

The two described approaches for clinical decision making in healthcare highlight

the different cognitive styles that clinicians utilize in making choices for their patients.

Use of the information processing model versus that of the humanist-inductive model is

largely influenced by user characteristics including professional experience. As a result,

17

novice nurses are most likely to make decisions using sequential algorithmic-type

thinking that is more closely aligned with the information processing model. On the other

hand, nurses with additional clinical experience will likely consider previous professional

exposure and emerging patterns in drawing conclusions that are more intuitively rooted.

2.5. Summary

Since the proliferation of healthcare information technology, various authors have

assessed its‟ effect on nursing workflow, patient outcomes, as well as the nurse-patient

relationship. Despite established benefits, ambiguous perceptions about HIT have been

reported. In a phenomenological investigation, nurses in intensive care environments

reported a polarization between technologies and caring (Almerud, et al., 2008).

Similarly, decision support technologies were acknowledged as tools useful in knowledge

translation, although system process and interface concerns affect successful clinician

adoption (Holroyd, et al., 2007). From a more favorable perspective, Dykes et al. (2007)

discussed the promotion of evidenced based practice as a benefit of nurses‟ use of HIT.

They further examined the influence of CIS on communication and workflow patterns

acknowledging that technology based communication is a transition from the

synchronous communication generally preferred by healthcare providers. Yet another

aspect of nurses‟ interaction with HIT is the effect it has on aspects of metacognition.

Considering protocols and algorithms are embedded in HIT, the question has been raised

as to what form of knowledge dominates in the healthcare environment, that of the nurse

or the information system (Hanlon, et al., 2005; Kleiman & Kleiman, 2007; Sandelowski,

1999b). A directed examination of nurses‟ experiences working with HIT will provide

18

valuable insight into the evolving care dynamics present in current healthcare settings and

resulting trends in information management.

19

CHAPTER 3: DESIGN AND METHODOLOGY

3.1. Overall Approach and Rationale

Existing nursing literature fails to adequately describe how nurses interact with

HIT and its‟ subsequent effect on decision making patterns. Considering the true

relationship between nurses and technology cannot be exclusively captured through

quantitative measures, a qualitative description is essential in performing an adequate

evaluation of their subjective experiences. The use of focus group interviews of both

novice and experienced nurses provided an optimal platform for caregivers to share their

experiences, while also allowing for exploration of the research questions. While content

analysis is traditionally considered merely a qualitative data analysis method, it is

actually a fairly standard qualitative method, although less frequently identified in the

nursing literature as a method than a form of data analysis. Use of this method in the

current study allowed for the thematic description of subjective behaviors and

experiences of nurses interacting with HIT by categorizing textual data and identifying

patterns elucidated from participant narratives. This form of inquiry proved extremely

beneficial for the study as the practical integration of technology in practice and its

perceived impact on day to day clinical decision making was explicated through

descriptions of use by end-users themselves.

Existing as one of the multiple research methods available to analyze textual data,

researchers have employed the use of Content Analysis (CA) since the 18th

century. The

first message forms analyzed with this method included hymns, media articles,

advertisements, and political speeches (Elo & Kyngas, 2008). Initially appearing in

United States literature in the mid 20th

century, CA was originally used as either a

20

quantitative or qualitative method but later became more paralleled with quantitative

research as textual data was coded and categorized (Hsieh & Shannon, 2005; Mayring,

2000). Despite its long standing history in communication, journalism, sociology,

psychology, and business, CA has gained popularity amongst qualitative researchers and

has shown steady growth in nursing and other health care professions (Ernesater,

Holmstrom, & Engstrom, 2009; Graneheim & Lundman, 2004). Recent nursing literature

has included research utilizing qualitative content analysis to analyze telenurses‟

experiences working with computerized decision support (Ernesater, et al., 2009). The

study evaluated the subjective experiences of eight telenurses utilizing a telephone

network decision support system in Sweden. Utilizing content analysis of participant

responses, researchers found that the decision support technology was supportive and

improved the quality of their work. Conversely, nurses described use of the system to be

simultaneously inhibiting as they experienced discrepancies in their interpretation of data

versus that of the system. Content analysis is a beneficial method for qualitative nursing

research because of the design flexibility afforded to the investigator. The approach

allows researchers to engage in an expansive investigation of participant experiences

considering data analysis involves much more than a simplistic description of data

(Cavanagh, 1997; Elo & Kyngas, 2008).

As a research method, content analysis permits researchers the opportunity to

follow either a deductive or inductive approach to evaluate data. The selection of analysis

techniques depends upon the research question. A deductive analysis is best suited when

there are existing categories, concepts, models, or hypothesis to be tested. Conversely, an

inductive approach is preferred when there is insufficient or fragmented knowledge

21

available about the phenomena. Despite the selection of a deductive versus an inductive

approach, the researcher has a responsibility in establishing soundness in the analytic

process to ensure a clear understanding of how analysis ensued as well as existing

limitations. Termed trustworthiness, means of determining soundness in qualitative

content analysis are similar to those techniques necessary to demonstrate validity in any

qualitative work. This process often involves dissecting the research procedures and

providing detailed descriptions of the analytic design (Elo & Kyngas, 2008).

3.2. Trustworthiness

Methods for establishing the rigor of qualitative work differ from those that are

typically utilized in the conventional quantitative realm. Traditional means of evaluating

results of research conducted in the positivist paradigm are not appropriate for qualitative

content analysis considering it differs in its research purpose and interpretive processes.

In judging research originating from the naturalistic or constructivist paradigm, the term

trustworthiness is often applied to an evaluation of the quality of the work. When

evaluating the trustworthiness of qualitative research key concepts emerge. The notion of

credibility replaces internal validity, dependability replaces reliability, transferability

replaces applicability, and confirmability replaces objectivity (Munhall, 2007).

As it pertains to qualitative research, credibility involves ensuring that the raw

data was adequately and logically constructed into the derived categories and themes.

This was established through the group moderator‟s engagement in concurrent member

checking during the group session as well as allowing respondents to view and confirm

analysis results following interpretation of data. Additionally peer debriefing contributed

to establishing credibility in that two nurse researchers, myself as the principal

22

investigator and the supervising professor overseeing this study, reviewed and coded

group data and continually met until consensus was reached. Dependability in qualitative

research denotes the process and degree to which the researcher accounts for the

evolution of the phenomenon while confirmability refers to the extent to which elements

of the data can be corroborated by those who review the results (Zhang & Wildemuth,

2009, p. 313). Both dependability and confirmability are generally established through

evaluation of the research methods and findings. Dependabiltiy can be judged by

appraising adherence to the determined process as described in the research report.

Research consumers can assess confirmability by considering the process of peer

debriefing utilized by the nurse researcher as well as auditing relevant research data

including notes, memos, transcripts, and derived categories. Lastly, a measure of a

study‟s trustworthiness is the degree to which derived interpretations can be applied to

other settings, contexts, or populations. This is also referred to as transferability. While it

is not the researchers responsibility to establish applicability of outcomes in other

contexts, this element can be enhanced by the provision of comprehensive detailed

information about components of the study process and by following established criteria

for reporting qualitative research (Zhang & Wildemuth, 2009). Both elements for

improving transferability have been detailed in this research report.

3.3. Methods

Initial planning of the study began with development and refinement of the

research plan. Additionally, written approval was obtained from the Vice President of

Patient Care Services to utilize Northwest Hospital as the research site and its‟ nurses as

potential participants. To ensure compliance with institutional regulations as well as

23

participant protection, institutional review board (IRB) approval was sought and obtained

from both LifeBridge Health and Drexel University prior to the initiation of any research

activities (appendices A & B). After receiving IRB approval, recruitment notices

highlighting the proposed study were placed throughout the facility in areas frequently

accessed by registered nurses. Additionally, the nurse researcher attended staff meetings

to announce recruitment efforts for the proposed study. Interested employees were

provided with a telephone number dedicated to the research study as a means to contact

the researcher. The same contact information was included on the advertising material for

potential respondents. At the time of respondent contact, the nurse researcher reviewed

inclusion and exclusion criteria to determine if the potential participant was eligible for

study participation. Once eligibility was established, an offer was extended for

participation in the corresponding focus group on a pre-determined date and time.

Registered nurses were stratified into either the novice or experienced group depending

upon their years of experience.

To ensure participants were well informed of their role and options relevant to the

study, the nurse researcher made arrangements with the registered nurse to provide

him/her with a copy of the consent form prior to the focus group date (appendix C).

Participants were encouraged to take the consent form home to review and contact the

researcher should they have any additional questions. Written informed consent was

obtained from participants on the date of the group interview immediately preceding the

commencement of data collection. Each participating nurse was provided with a signed

copy of the written consent prior to the conclusion of the focus group interview.

24

Prior to the initiation of data collection activities, several meetings were held with

the focus group moderator to review the objective of the research as well as her role as

the facilitator. The nurse researcher reviewed the CDSS technology with the moderator

by accessing the system during one of the preparatory meetings to enhance awareness of

the participants‟ experiences. The moderator was provided with relevant literature

detailing practical methods for focus group moderation to strengthen the quality and

blend of data received from participants. Additionally, a copy of the focus group question

guide was provided prior to the focus group date. The nurse researcher and the facilitator

reviewed the focus group guide to ensure understanding of each question and its

relationship to the overall research intent. Supplemental questions were provided that

could have been used for probing should the moderator have experienced a lull in

participant discussion. On the day of data collection, the nurse researcher met with the

moderator immediately preceding each group interview to assess if any outstanding

issues needed to be addressed and to assure appropriate functioning of the digital audio

recorder. The nurse researcher met each participant at the beginning of the scheduled

group interview to obtain informed consent and to introduce the moderator, but left the

meeting room prior to the initiation of each group session.

3.4. Focus Groups

As previously stated, a focus group strategy was selected in order to engage

nurses who were interacting with information technology at various experience levels.

Focus groups can be described as group interviews undertaken “…with the ultimate goal

of observing the interactions among focus group members and detecting their attitudes,

opinions, and solutions to specific topics posed by the facilitator” (Fain, 2004, p. 160).

25

Originally utilized in marketing research, the data collection method has become

increasingly popular in social science as well as nursing work (McLafferty, 2004). Use of

this strategy not only allowed for the exchange of ideas, but also provided an opportunity

for in-group validation of experiences.

Varying literature has described groups sizes that include as few as four and as

many as 15 participants (Krueger & Casey, 2009; Marshall & Rossman, 2006;

McLafferty, 2004). Although there is no ubiquitous consensus on focus group sizes, most

are composed of 6 to 12 members (Fain, 2004; McLafferty, 2004; Stewart & Shamdasani,

1990b). Larger groups of 10 to 12 members are commonplace for marketing and

commercial research purposes. The larger size is most appropriate for discussing topics

not well explored or experienced by participants. Differing from that which is

traditionally recommended, the use of a smaller assembly of four to six members, also

referred to as a mini-focus group, has become increasingly popular. In determining a

suitable sample size for focus group construction, consideration should be given to the

purpose of the research as well as participant characteristics. Despite their infrequent use,

smaller mini-focus groups are appropriate when: (a) the intent of the research is to

understand a phenomena or behavior, (b) the issue is complex, (c) groups members have

a substantial degree of experience or expertise with the subject matter, (d) participants are

passionate about the topic, or (e) there are an extensive amount of questions to be

presented (Krueger & Casey, 2009). While not ideal, the use of mini focus groups for this

work was adequate considering the explorative intent of the research as well as the

participants‟ continuous interaction with the subject matter, healthcare information

technology. Knowledge gained from the small group provided compelling insight into the

26

shift in care processes for the nurse clinicians. Considering the group members expertise

with utilizing the healthcare information system, they were able to provide detailed

feedback about the effect of its use on their workflow and other patient care activities.

This study met many of the criteria for acceptably utilizing a mini-group in that the intent

of the research was to understand clinician behaviors, the nurses had a substantial degree

of experience with the topic, and they were passionate in their subjective depictions.

3.5. Site Selection

Participants were recruited from the Acute Care Services Division of Northwest

Hospital (NWH) in Randallstown, Maryland. A part of the LifeBridge Health System, the

institution is a 242 bed, not-for-profit community acute care hospital providing services

for medical, surgical, behavioral health, rehabilitative and hospice patients (LifeBridge

Health, 2010). The hospital employees approximately 213 registered nurses possessing

varying levels of nursing skill ("Northwest Hospital Center - Randallstown, MD," 2010).

During the spring of 2006, NWH began to phase out portions of its‟ paper health record

by gradually introducing elements of the Cerner clinical decision support system

including electronic health records, computerized provider order entry, results retrieval,

and an electronic medication administration record. The systems implementation

involved the administrative selection of a CIS and pilot introduction amongst small user

groups. The facility has currently adopted several aspects of the CIS including use of an

electronic medical record, computerized provider order entry, clinical decision support

elements, results reporting, and picture archiving. Discussion relative to Cerner system

use by research participants largely focused on the results reporting element as well as the

clinical decision support component. As previously described, the results reporting

27

element allows nurses to quickly retrieve various types of patient information at the point

of care. The clinical decision support component is most evident in the form of patient

care alerts. The Cerner system analyzes stored patient data utilizing embedded heuristics

and recommends subsequent clinician actions. One such example is a sepsis alert that

suggests clinicians evaluate a patient for sepsis based upon an electronic evaluation of a

patient‟s vital signs.

Despite the comprehensive nature of the current system, CIS components have

been incrementally introduced in stages since the systems adoption four years ago. Prior

to each new stage of the Cerner system implementation, staff were required to attend

classes regarding use of the new system component. Additionally, during periods of

hospital-wide Cerner implementation initiatives, designated staff were made available for

HIT concerns as a resource to bedside clinicians at the point of care. The organization

continues to employ a small e-learning department tasked with providing ongoing system

support for clinicians, as well as training newly hired nursing staff and student nurses.

Phased-in transition from paper to electronic documentation continues as the

environment is currently hybrid with records of various care elements still located in

patient‟s paper charts. For those employees entering the hospital since the 2006

introduction of Cerner, standardized classroom-based computer training is provided as a

part of clinical orientation. Regardless of skill level and experience, all nurses receive

approximately nine hours of Cerner training prior to entering the care environment. For

nurses new to the hospital, this training is reinforced in the clinical setting as staff work

with their unit based preceptor.

28

3.6. Population Sample

A purposive sample was utilized for this study in an effort to elicit rich

meaningful data. This method of sampling involves the deliberate selection of

participants who have experience with the phenomena of interest and also possess traits

of a contributable informant (Munhall, 2007). The targeted populations were novice and

experienced nurses regularly utilizing the Cerner clinical decision support system in their

clinician workflow practices. As described by Benner (1982), novice or beginner nurses

have no experience in the areas they are expected to perform while professional

competency is likely achieved after two to three years of practice when the nurse is able

to see their actions as a part of long-term goals. Considering the previous work of Benner

in developing this study, 10 years has been identified as the minimal practice timeframe

for experienced nurse as the veteran nurse will have passed the two-three year threshold

associated with the beginning nurse and also will have gained additional clinical exposure

adding to their background of experience.

Potential participants were unable to participate if they met any of the following

exclusion parameters: (a) younger than 21 years old or older than 75 years old, (b)

working in the hospital as a temporary or agency employee, (c) educationally prepared

with a Master‟s Degree in Nursing, (d) unable to read, speak, or understand English, (e)

have a self reported learning disability that interferes with the receipt or interpretation of

information, or (e) currently a novice registered nurse previously employed as a practical

nurse. An invitation to join the study was extended to potential participants who: (a)

possess a current active license as a Registered Nurse in the state of Maryland, (b) read,

speak, and understand English, (c) were employed a minimum of 16 hours per week by

29

the cooperating facility as a staff nurse on a medical/surgical unit, (d) were legally and

cognitively competent of signing their own consent to participate in a research study, and

(e) have been employed either two years or less or 10 years or more as a Registered nurse

in an inpatient hospital setting.

3.7. Protection of Human Subjects

Although medical surgical nurses interacting with healthcare information

technology in an acute care setting are not considered a vulnerable population, measures

were taken to ensure their protection in this study. As candidates volunteered to be

included in the study the nurse researcher, in accordance with the institutional review

board (IRB), obtained written informed consent from each potential participant, which

conveyed the intent to maintain confidentiality. Upon initial determination of study

eligibility, a review of the consent was provided to participants, as well as an explanation

of the purpose, risks, and benefits of the study. Candidates were then provided with an

opportunity to ask questions and clarify any unresolved concerns. The participants were

provided with a copy of the consent form prior to the focus group date to allow

participants sufficient time for review. The researcher obtained written consent from each

participant on the date of the focus group before any data collection began. Immediately

prior to obtaining written consent, participants were asked to accurately restate the

purpose of the study in addition to expectations of persons involved. Participants were

clearly informed that their involvement in the project was purely voluntary and that they

reserved the right to withdraw from participation at any time.

All data collected and analyzed as part of this study were protected from

disclosure outside the research team, thus minimizing the risk to individual participants.

30

Communication with both candidates and established participants was kept private. Initial

screening communications were conducted over the telephone from a telephone number

and line designated for the research project and only accessible by the PI. The focus

groups were held in a private locked room that once locked could only be opened by

maintenance employees and those inside the room. Additionally, no personal identifiers

were connected with the data. A unique identification number was assigned to each

participant and a log generated that was only accessible to the investigators. The PI

managed and stored all data and only shared that which was necessary with the co-

investigator. Electronic data as well as audio recordings were stored in the PI‟s locked

office. Participant demographic sheets were also securely located and double locked to

protect participant privacy. Electronic transcriptions of the audio data were maintained on

LifeBridge Health‟s secured network which is password protected and inclusive of

firewall technologies that prevent access from unauthorized users.

3.8. Data Collection

During the focus group interview, participants were asked investigator developed

questions relative to their use of and interaction with technology. The interview guide and

demographic data form were reviewed for face validity. In conjunction with the research

team/advisory committee, the nurse researcher refined the data collection instruments to

ensure targeted pieces of demographic data were collected and to facilitate a rich

discussion about the phenomena of interest. Both the interview guide and demographic

data tool are included with the final report as appendices D and E respectively. Open

ended questions were utilized to solicit participant perceptions relative to the influence of

healthcare information technology on their clinical decision making and resulting patient

31

care. Questions included “Has the clinical decision support system ever helped you to

make patient care decisions?” and “What do you think is the role of the clinical decision

support system in analyzing or interpreting patient data?” The novice group interview

lasted approximately one hour while the experienced group interview was approximately

one and one half hours in length. Both focus group interviews were audio recorded and

subsequently sent for professional transcription. Additionally, demographic data was

collected from each participant using an investigator-developed form. The form queried

participants for information such as age, gender, educational level, months and/or years

of experience as a registered nurse, perception of Cerner training, and use of technology

for purposes other than nursing care. Demographic data provided a descriptor of the study

participants in each group, their professional nursing experience, and prior exposure to

varying forms of technology.

3.9. Data Analysis

Hsieh and Shannon (2005) describe three approaches to qualitative content

analysis, conventional, directed, and summative. A conventional analysis is often

employed when there is scarce literature available about the phenomena of interest. This

approach avoids preconceived categories when analyzing the data, but rather allows

insights to emerge from the data. Directed analysis utilizes a more structured approach to

analyze data as existing research of theories are often utilized to predict or further explain

the relationship amongst variables. Lastly, summative analysis in qualitative work

involves the identification and subsequent counting of particular words or content with

the resulting purpose of exploring usage and latent meaning.

32

Considering the limited amount of research available discussing the relationship

between nursing and technology in clinical practice, a conventional analysis was utilized

which allowed for a thematic interpretation of participant responses to emerge from the

data. Zhang and Wildemuth (2009) present a structured and systematic way to process

data for qualitative content analysis. This includes the following nine steps: (a) data

preparation, (b) determining the unit of analysis, (c) development of categories/coding

scheme, (d) testing the coding scheme, (e) coding the remaining data, (f) assessing for

coding consistency, (g) interpretation of coded data, and (h) drafting the final report of

methods and findings.

Demographic data was maintained and analyzed with a SPSS statistical package

while transcribed data was managed with ATLAS.ti qualitative data analysis software.

The researcher was adequately prepared to utilize SPSS software through formalized

training received in the academic setting, while attendance at a two-day dedicated

training session served as the preparatory method for use of ATLAS.ti. The analysis

process began with transcription of the data by a professional transcription service. The

resulting records were compared against the focus group audio recordings to confirm

accuracy and inclusiveness of all participant data. The participant data was independently

reviewed and assigned preliminary codes by two nurse researchers. Utilizing electronic

and telecommunication platforms, the two researchers met weekly until consensus about

the coding schematic was achieved. Codes were subsequently grouped into categories

and later counted for frequency of occurrence in each group (appendix F). Dominant

categories were grouped and pictorially recorded in a venn diagram (appendix G) to

identify ideas that were unique to novice or experienced nurses as well as those that were

33

shared by both. Categories were later shared with a member of each of the focus groups

to confirm interpretations and contribute to the authenticity of the data.

3.10. Epoche

Considering my professional relationship with the cooperating institution as well

as the sample population, I may have biases that could potentially interfere with an

impartial evaluation of the data. For purposes of analysis, it is important that I identify

my position as the researcher as well as how I dealt with professional prejudice to

maximize objectivity in this study. While conducting this research, I functioned as an

Education Specialist with LifeBridge Health. In this role I shared responsibility for the

development and progression of new graduate nurses as well as recently hired clinical

staff. In addition to working with new staff, I provided educational support for existing

nursing personnel working in acute care areas for an array of topics including Cerner.

Oftentimes, gaining familiarity with use of the Cerner CDSS system was an area

of contention for new staff and so I‟ve frequently provided or arranged for additional

support in this area. During the initial system implementation in 2006, I functioned as a

member of the super user team teaching several of the inaugural courses and providing

after hours support. Since the implementation of the Cerner clinical decision support

system, I‟ve witnessed the change in nursing care patterns. I found the decision making

patterns of new graduate novice nurses working together with this new form of healthcare

information technology to be very intriguing. Although novice nurses are inherently in a

developmental phase, I questioned whether or not some of their faulty decision making

was a result of lack of experience or from blindly following heuristic-based computerized

directives.

34

In acknowledging my inherent biases, I engaged in bracketing throughout the

research process in an effort to minimize personal influence and express validity of the

data collection and analytic methods (Ahern, 1999). Bracketing has been described as an

active process whereby researchers identify pre-existing experience, ideas, beliefs, and/or

judgments about a phenomena and make concerted efforts toward separating them from

the research process (Ahern, 1999; Fain, 2004; Gearing, 2004). Prior to the initiation of

research activities, I shared my theoretical position with the research team as well as my

subjective experiences with the phenomena of interest. To eliminate bias during the data

collection process, an experienced group moderator was hired to conduct both focus

group sessions. This not only eliminated investigator influence, but also helped to create

an atmosphere where participants were able to freely share their experiences.

Additionally, audio recordings of the sessions were sent for professional transcription

prior to initiating the analysis process. During the data analysis phase of this study, two

nurse researchers met via teleconferencing after independently reviewing the focus group

data. Each separately assigned codes to the data and continued to meet until inter-coder

agreement was achieved. Following investigator analysis, select participants were

engaged in member checking to validate conclusions reached by the researchers. Munhall

(2007) described member checking as a process during which narrative results are shared

with research informants prior to public presentation or publication. Findings from the

data were presented to representative members of each group to verify correct

interpretation of participant responses and allow for clarity of ideas not appropriately

captured.

35

CHAPTER 4: RESULTS

4.1. Introduction

The results of this study are described and organized into three main sections.

Following a brief overview of the study, the first section describes the demographics of

study participants. The second section includes the study themes and findings with

excerpts from the two focus group interviews. A conventional analysis was utilized

which allowed for a thematic interpretation of participant data and the five main themes

that emerged from this data is presented. The third section describes support for study

findings with existing studies in nursing literature.

4.2. Overview of the Study

This study sought to examine the relationship between medical surgical nurses

and healthcare information technology in the acute care setting, and the subsequent effect

of this relationship on nurses‟ clinical decision making. The two research questions were:

Question one: How are medical surgical nurses utilizing healthcare information

technology in their current clinical practice?

Question two: Is nurses‟ clinical decision making influenced by healthcare

information technology?

A qualitative approach was essential for this research considering the limited availability

of literature describing the interaction between nurses and clinical decision support

systems in the hospital setting. To conduct an adequate exploration of nurses‟

experiences with HIT, it was necessary to allow nurses, as end users, an opportunity to

openly describe their experience with CDSS, as well as their perception of its role in the

provision of patient care. The use of focus group interviews provided a platform for

36

novice and experienced nurses to share their opinions about use of new Cerner

technology. Additionally, the group setting allowed for the exchange and validation of

ideas amongst participants having experience with the topic of interest. Considering the

explorative intent of the study, content analysis served as a suitable research and analysis

method in evaluating participant responses. Insights regarding the role of HIT in the

provision of patient care emerged from the methodological review of transcribed

participant data and subsequent themes were able to be identified.

4.3. Subject Demographics

A total of eight medical surgical nurses participated in the study, four novice and

four experienced. Considering nursing is a female dominated profession with only 5.8%

of RN‟s being male, the gender mix mirrored that which is evident in current nursing

trends as there was only one male participant within the sample (HRSA, 2004). The mean

age of the novice nurse was 37.5 years of age while that of the experienced nurse was

43.5 years. The average age of both groups is still less than the mean age of 46.8 reported

in the last National Sample Survey of Registered Nurses (RN) (Health Resources and

Services Administration, 2004). Also differing from national statistics of registered

nurses is the ethnic mix of research participants. Nationally, approximately 80% of

registered nurses are white while RN‟s of African American and Asian descent account

for a combined 7% of the nursing population. A more diverse group was represented in

the sample considering only 38% of participants were White and the remaining 62% self

identified as African American or Asian. The ethnic mix may partially be explained by

the progressive recruitment of internationally educated nurses to meet demands for a

larger nursing workforce. Additionally, the institution is located in close proximity to the

37

city of Baltimore, which is a predominately African-American community. Six of the

eight participants were academically prepared with an Associate‟s degree in nursing

representing 75% of the study sample. All of the respondents reported utilizing computer

technology for personal functions other than those associated with work requirements.

Additionally, all of the participants denied ever attending classes or receiving instruction

in nursing informatics. Only one of the eight respondents, an experienced nurse, reported

using clinical applications on a personal digital assistant (PDA) to aid in making patient

care decisions. A further description of participant responses to demographic data

collection follows and is also summarized in appendix H.

4.3.1. Novice Nurse Demographic Responses

The novice group was comprised of one male and three female participants, all of

whom were Associate prepared registered nurses, ranging in age from 28 to 47. Although

screening was performed for all study candidates, one respondent reported having

practiced two and a half years as a registered nurse while the nurse with the least amount

of experience reported only six months in practice. Contributions from the novice

participant with two and a half years experience were considered equally valuable

considering the lengthy amount of time required to gain the skill and experience

necessary for expert practice. Two of the nurses identified themselves as Black or African

American while the remaining two identified themselves as White. None of the novice

participants had experience working with a HIT system other than the Cerner system

utilized at the cooperating facility. Three of the four novice participants reported being

very comfortable with utilizing the Cerner technology and perceived that the initial

training received as a new hire was adequate for efficient use.

38

4.3.2. Experience Nurse Demographic Responses

All four of the experienced nurses were female and ranged from 38 to 51 years of

age with a span of 13 to 30 years of experience reported. Two group members self

identified as Asian, one as Black or African American and one as White. A mix of

educational preparation was evident in the experienced group as two of the nurses were

Bachelor‟s prepared and two were prepared at the Associate level. Additionally, one of

the Associate prepared nurses also reported having a Bachelor‟s degree with an education

concentration. Different from the novice group, only one of the experienced nurses

received their initial registered nurse training in the United States. Also different from the

novice group, two of the experienced nurses had experience utilizing another HIT system

other than Cerner. Similar to novice responses, three of the four participants perceived

the initial Cerner training to be adequate and were comfortable with utilizing it in the

clinical setting.

4.4. Themes

In subscribing to the conventional inductive approach to qualitative content

analysis, an exploration of specific responses revealed five main themes that emerged

from participant data. These ideas embody the numerous categories developed from

transcript codes and provide descriptive quality to the interaction between nurses and

healthcare information technology in the medical surgical care environment. While three

overarching themes were identified with applicability to both novice and experienced

nurses, two additional ones surfaced, one specific to the novice group and the other to

experience.

39

4.4.1. Theme One: Healthcare Information Technology as a Care Coordination Partner

Highly evident from participant data is the presumption that the integration of

healthcare information technology in the medical-surgical care setting has led to the

partnering of nurses and technology in the provision of patient care. This dynamic is

evidenced by the following categorization of coded data: presence of the nurse-

technology dyad, Cerner‟s function as a convenient depot for patient information,

Cerner‟s provision of clues or prompts to further investigate patient data, and the

increased vulnerability of nurses when the clinical information system is not available.

Whether nurses have an affinity or disdain for the clinical decision support system and its

accompanying electronic health record, an impermeable relationship exists between the

two. Both novice and experienced nurses described functions of the Cerner system

relative to the retrieval of patient information, care orders, and scheduled tasks. Their

reliance on Cerner for elements of care coordination is further supported by descriptions

of care interruptions and task uncertainty when the system is not available.

N1 –One of the best advantages of the Cerner is that it sort of schedules your day

for you because you know what you have to look ahead to, what you have to plan

for.

E1 – If this computer suddenly lost, out of the blue, you are going to get lost too.

E2 – You are dependent on the computer.

The presence of Cerner as a care coordinator partner is a manifestation of the previously

described nurse-technology dyad that is increasing evident in technology-enhanced

environments.

40

4.4.2. Theme Two: Healthcare Information Technology as a Change Agent in the Care

Delivery Environment

In discussing care patterns with use of the Cerner technology, nurses were able to

describe a palpable conversion in the patient care environment. Many of these changes

related to the transparency of user access, actions, and documentation that resulted in

functional or workflow changes amongst members of the care team.

N1 – Save time for me because it‟s fast.

Prior to the introduction of EHR‟s, no definitive methods existed to assess what

clinicians accessed health records to document care, revise forms, or place and update

patient orders. As a result of the increased transparency provided by the Cerner system,

users are more meticulous when accessing and documenting in electronic charts.

E1 - You cannot actually just open any patient because it will tell you opened

it…it will actually guide you to just mind your own business.

Additional code categories supporting Cerner‟s influence in changing the care

environment were the increased safety classification as well as the description of Cerner

as both comprehensive and restrictive.

E2 – It provides a safer environment for the nurses, especially the MAR. When it

used to be in the paper, there were more mistakes, more likely to have mistakes

because the penmanship is not too legible when they describe it – more mistakes.

4.4.3. Theme Three: Health Care Information Technology – Unable to Meet all the

Needs, of all the People, all the Time

Despite the numerous positive elements identified by nurse users, there were a

great deal of system limitations that subsequently necessitated creative thinking from the

41

staff to achieve desired outcomes. When discussing Cerner‟s deficiency in meeting some

clinical user needs, participants specifically referenced limited areas available for

individualized documentation, template-based orders that did not entirely reflect the

primary care provider‟s intent, as well as electronically scheduled medications resulting

in schedules that are heuristically based as opposed to contextually driven.

E3 – The MAR, you cannot put there, those are not given because pharmacy has

not delivered.

E4 – The time comes again,10:00 pm you give it, it is overloading the patient. Not

only that it is going to charge the patient….it is not good for the system or the

patient.

N2 – Would appreciate if we have more areas to type in a comment.

N4 - Nowhere you can write your own little note to something.

In these instances, the use of Cerner created a gap in the continuity of care.

Subsequently, both experienced and novice nurses assumed responsibility for initiating

system work-arounds to repair fissures created by mandated use of the system.

Caregivers‟ perception of CIS deficiencies can potentially have detrimental effects on

future acceptance and use. As previously alluded to, the value of clinical information

systems cannot solely be evaluated by outcome measures, end-user appraisal must also be

taken into consideration. Should users perceive the technology as incapable of meeting

essential care-functions, an impermeable lack of acceptance may arise, resulting in a

fixed dissociation from integrated use. Participants in this study were able to devise

methods to obtain pre-determined outcomes when system limitations persisted. For

example, nurses described occasions when it was contextually fitting to rearrange

42

medication administration times that were originally scheduled in the electronic MAR for

a different time. Nurse users navigated system options to reschedule or omit a medication

dose when they deemed it clinically appropriate, as opposed to adhering to timeframes

originally reflected in the CIS.

E2 - When it [medication] is not due, sometimes it does not come up…I say okay

no problem, I know what to do, you click on additional, you reschedule.

E1 - I reschedule the second dose of the medication and then I return the

medication but I write on the medication already given

N4 – I recently had a situation where the patient had the same medication ordered

in different doses for the same time to be given. And I thought something couldn‟t

be right.

4.4.4. Theme Four: Curiosity about Healthcare Information Technology – What other

Bells and Whistles Exist

While not an idea shared by both groups, curiosity about various system elements

was undoubtedly evident during the novice nurse interview. Throughout the discussion,

the inexperienced nurses inquisitively commented on the multifaceted nature of the

Cerner system. Users acknowledged that there were several system functions that aren‟t

utilized as well as documentation areas where they‟ve not been exposed.

N3 – Everyday I‟m seeing something new that I didn‟t know was there before.

N4 – Probably a thousand more things it would do that we don‟t do everyday.

Additionally, the group gave feedback about what features they‟d welcome that would

aid in their patient care activities. When considering contrasting perceptions of

experienced nurses, their interest in working with more elements of the clinical decision

43

support system may result from their initial development in a technologically enhanced

atmosphere as opposed to having previous experience with a paper-based environment.

4.4.5. Theme Five: Big Brother is Watching

Peculiar to the experienced nurses was their uneasiness with the increased

transparency provided by use of electronic health records and the clinical decision

support technology. Participants were comfortable and confident in their patient care

responsibilities and conveyed a disdain for having to intricately balance meeting

predetermined demands for computer documentation that impeded their ability to

prioritize patient care.

E3 – Sometimes it is the people around it. Sometimes, these people around it, like

the performance evaluator or anything that looks into your work, sometimes it

adds stress to yourself because they want us to put the assessment by this certain

time. Of course you cannot really do that one because you have to take care of

your patient.

Experienced nurses expressed irritation with retribution received by administrative

nursing staff tracking documentation trends not consistently in compliance with

institutional policies and procedures.

E4 – Our names are going to be printed on the billboard if we do not do our

patient response.

The perceived divide in priorities for clinical versus administrative staff has resulted in

the experienced nurses‟ view of performance improvement staff as oppositional team

members who are not abreast with the realities of direct care and subsequently most

concerned about documentation completion.

44

E1 – They do not know what is going on, you are the one who knows what is

going on although they want to check.

Experienced nurses seemingly respond to administrative pressures by continually

asserting their autonomy as care providers who are best able to determine what nursing

actions should take precedence over others.

4.5. Novice and Experienced Nurses: Perceptual Similarities and Differences

Despite differences in levels of experience, members from both the novice and

experienced nurse groups shared various perceptions about aspects of the Cerner system

and its subsequent influence on their workflow. Reported data also revealed polarized

observations that were more insular to one group versus the other. Analysis of the

transcribed data is reflected in the subsequent categorization of participant responses.

4.5.1. Shared Novice and Experience Nurse Perceptions

Initial reactions to the Cerner system were constructive and reflected the

advantageous components of the technology. Participants from both the novice and

experienced group shared positive impressions about the convenience of the program as

evident in descriptions of it making things quicker and faster as well as its ease of use.

Particular discussion regarding convenience of the system centered on easy accessibility

to patient information at the point of care, in addition to its function as a resource for

medication, diagnostic, and disease related data. Zuzelo and colleagues (2008) reported

similar time conserving efforts in their study evaluating the influence of technology on

registered nurses‟ work. Technologies were perceived as productive in eliminating the

necessity for staff to complete tasks able to be met through other technological means.

When asked about the importance of clinical decision support cues that direct

45

practitioners to consider particular etiologies for various clinical manifestations including

vital signs and/or laboratory results, two collective ideas were expressed. The first being

that the summary patient data provided to clinician users in the form of „clinical alerts‟

was perceived as a beneficial prompt to further investigate the patient‟s current health

state.

N2 – It does at least make you stop for a second and usually right away I‟ll go

verify the vitals and the labs to see if I agree that the alert is telling me something;

to see if there‟s an infection or a temperature or vitals out of line, so it does help

in that sense

E1 – I think that is one way to remind the nurses that they initially assess a septic

[patient] and if you think they are not septic anymore you still have to look after

that patient…you still have to look for those signs and symptoms; you still have to

check if they are septic.

Novice nurse users did however express that repetition of such alerts could be

desensitizing. Secondly, both groups maintained that the decision making practices of the

nurse superseded that of the clinical decision support system as evident in one experience

nurses‟ response, “…do not rely on the computer itself.” Yet another observation shared

about interaction with the program during patient care activities is its propensity to

restrict individualized documentation despite the vast and comprehensive documentation

abilities available. Users expressed that Cerner provides them with flexibility in their

documentation options but that fixed categorical selections may not fully capture the

intent of the care provider.

46

E2 – That selection is fixed already but sometimes other doctors want something

else. But even if they modify, you cannot really find it on the computer what they

want to order. So sometimes they put it as a miscellaneous order.

Several studies evaluating nursing and technology have also reported dichotomous

perceptions of the beneficial yet restrictive properties of healthcare information

technology. Swedish telenurses working with a telephone based clinical decision support

system conveyed that system elements complemented their existing knowledge but

simultaneously reported use of the system could be inhibiting if they disagreed with the

technological guidance (Ernesater, et al., 2009). Wikstrom, Cederborg, & Johanson

(2007) provide a summarized report of earlier research proposing that the actions of RN‟s

are restricted by various forms of technology. When describing their use of and

interaction with the new clinical decision support technology, nurses indirectly described

their dependence on the system and increased vulnerability without it. This dependence

was not conveyed with regards to physically providing patient care, but rather the need of

the HIT system to provide essential information stored within that directs patient care

activities. Compounding the issue of dependence, novice and experienced nurses alike

described feeling lost when the system was unavailable due to periods of downtime

because of their reliance on it to organize care activities.

N3 – I think it would be very difficult if it goes down to know everything you

have to do for all of your patients.

N4 - It keeps you reminded so to speak. You know, as to what to do at different

times, which is very good.

47

E1 – If this computer is suddenly lost, out of the blue, you are going to get lost

too.

E2 - So your computer always needs to be like always on. It needs to be hung

around my neck.

Considering the proliferative nature of healthcare information technology, it is not

surprising that numerous articles report the emerging care partnership evident between

nurses and forms of information technology, namely clinical information systems. In

evaluating the results of an international survey of 933 nurses use of technology in 14

countries, researchers approached the study with the supposition that nurses and

computerized technology have become inseparable and as such should be considered a

partnership if beneficial, safe, and effective outcomes are to be achieved (McGillivray, et

al., 2007). A qualitative evaluation of the meaning of technology to 12 healthcare

workers in an intensive care unit revealed clinicians reliance on technology for functions

relative to care coordination considering users description of “…technology as a support

they trusted in their everyday practice” (Wikstrom, et al., 2007, p. 190). Their reliance

was more specifically described relative to the direction and organization of medical

interventions.

4.5.2. Novice Nurse Perceptions

Most of the ideas expressed by the novice group were not isolated to nurses with

minimal experience, but rather shared amongst participants from both groups. As a result,

the majority of the findings from the novice group are expressed in the results segment

describing collective novice and experienced perceptions. In addition to ideas previously

conveyed, one additional observation emerged. Novice nurses expressed an interest in the

48

multifaceted nature of the system. Transcript comments reflected inquisitive inquiry into

what other program features may exist as well as functionalities yet to be explored.

N2 – Probably another hundred applications that it‟ll do that I‟m not aware of.

N4 - Everyday I‟m seeing something new that I didn‟t know was there before.

Nursing literature does validate that nurses welcome new and innovative technologies

providing they are efficient and user-friendly. If not, clinicians will implore the use of

work-arounds to achieve outcomes and bypass more complex and time consuming

technological resources (Zuzelo, et al., 2008). In evaluating the ideas expressed by the

novice nurse, it is interesting to note their lack of independent views as evident in the

experienced interview.

4.5.3. Experience Nurse Perceptions

While nurses in the experienced group shared many overlapping ideas with their

novice colleagues, analysis of their transcript data revealed many passionately conveyed

views not previously presented. A positive system element not identified by novice

nurses but recognized by the experienced group was the enhanced patient safety achieved

through integration with the HIT system as they reported a decreased likelihood of error.

A facet of the system identified as increasing safety included the transparency of clinician

actions considering Cerner maintains electronic fingerprints of actions performed.

Additionally, elimination of ineligible handwriting was identified a positive factor

resulting in increased protection considering plausible mistakes resulting from

inaccurately interpreted written communication.

49

E1 - It provides a safer environment for the nurses, especially the MAR. When it

used to be in the paper, there were more mistakes, more likely to have mistakes

because the penmanship is not too legible when they describe it, more mistakes.

Their perceptions are closely aligned with various studies detailing the numerous

beneficial outcomes of healthcare information technology including enhanced safety

(Ball & Lillis, 2000; Bower, 2005; Courtney, Demiris, & Alexander, 2005; To err is

human, 1999).

Despite presenting numerous positive aspects of the system, experienced users

communicated that the presence of the Cerner system could also easily serve as

interference to the nurse‟s care routine. Various factors contributed to this viewpoint

including the speed of the system, which was described by experienced users as slow

when considering the time consuming nature of entering patient data and retrieving data

from a large database.

E2 - Because of a lot of information that has been input in the computer and like say

all of us are using the computer, it slows the computer down. It slows the pace of

your work because of that.

Yet another factor contributing to the perception of Cerner as an impediment to care is its

role in communication between care providers. Nurses reported that a side effect of

allowing multiple users to access patient information from various locations is decreased

communication and collaboration between clinicians. Experienced nurses described that

less real communication exists considering many relevant pieces of patient data can be

retrieved and appraised through use of the computer technology without contacting other

members of the healthcare team. Logistical considerations around use were also a source

50

of frustration and presented as a barrier to patient care. Issues included finding an

accessible computer and battery sustainability of the computers on wheels.

E3 - As soon as you unplug it, plunk, it is not working. It takes time to reboot

again…When you want to do your bedside care, it takes a lot of time wasted when

you want to do the computer stuff and the patient care.

E4 - You have to go to the other computer, look for another computer, that is a lot

of time wasted already. Sometimes there are a lot of students coming on the unit.

No computer that you can use.

E1 - I am waiting on the hourglass for it to load up and it is just time, and time…I

feel like I am being pulled away from bedside nursing to do the computer,

computer, computer, and computer…that is not why I got into nursing for.

Such frustrations surrounding logistical use, fragmented care because of interruptions in

the exchange of clinician communication, and the time-consuming nature of

electronically entering patient data into clinical information systems have been cited as

reasons supporting the perception of clinical information systems as potential

impediments to patient care activities(Almerud, et al., 2008; McGillivray, et al., 2007;

Wikstrom, et al., 2007; Zuzelo, et al., 2008). The required use of Cerner was described as

a frustrating impediment to care not only because of time and access considerations, but

also due to institutional requirements about the timeliness of documentation. Clinicians

are required to complete computerized forms within pre-determined timeframes to be

considered in compliance with established policies and procedures. Per participant

responses, attempting to meet time requirements for documentation posed difficulty in

balancing patient needs versus expectations of the facilities.

51

E2 - We are compliant anyway, it is just that the four hour timeframe or whatever,

it is not enough for us because there are a lot of things that are going to go on

around us, a lot of things happening on the floor.

E4 - We know how to document the things that we need to document properly,

but they do not really need to rush us, rush us or stress us because the more they

are going to do that kind of thing we are going to make mistakes.

Experienced participants reported an oppositional view of non-clinical nursing staff as a

result of their persistent struggles with responding to patient care needs and also adhering

to expectations enforced by administrative staff. During the group interview, members

conveyed that unrealistic documentation expectations exist and that administrative staff is

out of touch with the realities surrounding providing patient care.

E1 - People in the office that are always chasing us around need to be on the floor

one day out of the month.

E3 - They do not know what is going on, you are the one who knows what is

going on although they want to check.

A phenomenological assessment of ten healthcare providers caring for patients in a

technologically intense environment also reported the tension that exist between

balancing the art of nursing with meeting an apparent shift in nursing priorities. Authors

reported that respondents conveyed “It is more prestigious to document technological

procedures than, for instance, to write that you comforted the patient with talk”

(Almerud, et al., 2008). As a result of differences in the value of care priorities for

clinical versus that of administrative staff, there is an emerging polarization of care team

members, thus straining essential clinical relationships. Despite workflow changes

52

influencing care provision in their technologically enhanced environment, the group

vehemently asserted their autonomy as primary decision makers and care providers.

Nursing literature describes the importance of mastering technology or else risk being

subjected to servitude under it. It is proposed however that mastery of mechanized

support is not inherent for all nurses but rather achieved by obtaining a blend of clinical

experience and theoretical competence (Almerud, et al., 2008). The assertion of an

authentic clinical presence by experienced nurses can be explained by their degree of

exposure to varying clinical scenarios resulting in their enhance ability to contextually

evaluate the meaning and value of technology in their environment. Experienced nurses

reported knowing what care decisions needed to be made dependent upon individual

patient characteristics and outcome expectations.

E1 – Nurse runs the show and makes decisions.

E2 – It does not have any brain. It does not tell you wrong order, wrong order. It

will not tell. If you keep on following what is there, you have to think too, you

have to think and you have to be vigilant.

Zuzelo et al. (2008) describe nurses as experts in achieving work-arounds by

circumventing technology system elements. Their apparent navigation around problems

may successfully them to achieve an outcome but does little to resolve the initial

presenting problem. In using the clinical decision support system, the nurses took

different measures to achieve goals they independently established without assistance

from the HIT system.

53

E3 - The computer does not have a mind, it does not have intellect. It only follows

what you and me enter there. So you as a nurse, you are the one, making

decisions. You run the computer, the computer should not run you.

E1 - I know what I want to do with my patient first before I go to the computer

thing.

E4 - When it [medication] is not due, sometimes it does not come up…I say okay

no problem, I know what to do, you click on additional, you reschedule.

In discussing the impact of the Cerner system on their workflow, nurses communicated

an appreciation for less technologically enhanced care environments. Specific attention

was directed toward mechanical flagging systems that were used by physicians to serve

as a visual indication of newly placed patient care orders. Nurses reported in the current

computerized order entry setting, orders could easily be missed if the electronic chart is

not frequently accessed. Additionally, the experienced group took liberty in sharing their

belief that older nurses having been introduced to Cerner maintain a preference for paper-

based documentation. However, what must be considered is that nurses‟ evasion of

system processes and reversion to „old‟ routines likely results from the perceived

complexity and interference of new technologically enhanced methods of providing

patient care.

54

CHAPTER 5: SUMMARY & IMPLICATIONS FOR FUTURE RESEARCH

5.1. Overview of Study

This study sought to explore two focal points with regards to the interaction

between healthcare information technology and nurses, the first being how medical

surgical nurses are utilizing HIT in their current clinical practice. The second aim was to

examine the influence of HIT on nurses‟ clinical decision making. Utilizing qualitative

content analysis, data from two homogeneous focus groups of novice and experienced

nurses was analyzed to evaluate the identified research questions. During the focus group

interviews, respondents expressed many overlapping views of the Cerner system and its

effect on their patient care activities. Additionally, polarized perceptions were expressed

with some ideas isolated to the experienced group while others were particular to the

novice group. Nurses participating in the group interviews primarily conveyed

information relative to the impact of Cerner HIT on their workflow practices as well as

contextual experiences when interacting with the system.

5.2. Conclusions

The initial aims of this study were twofold: (a) evaluate whether or not nurses‟

clinical decision making was influenced by healthcare information technology and (b)

evaluate how medical-surgical nurses are utilizing HIT in their current clinical practice.

Previous research examining nurses‟ use of CDSS has similarly reported both positive

and negative perceptions of new information technology and its subsequent effect on

workflow considerations. In their evaluation of telenurses‟ experiences working with

computerized decision support technology, Ernesater, Holmstrom, & Engstrom (2009)

found similar findings to those presented in the current study. Data received utilizing

55

semi-structured interviews and analyzed using qualitative content analysis

correspondingly revealed what the authors referred to as a duality of perceptions in

working with computerized decision support. Authors found that the telenurses gave

negative feedback about the system likely because of its rigidity, but simultaneously

valued the structure, information, and prompts it provided. These beneficial care

coordination functions were useful to both novice and experienced nurses in the current

study as they aided in organizing care for assigned patient groups.

Considering findings from data collected from both groups, nurses clinical

decision making is not overtly influenced by the use of healthcare information

technology. Nurses interacting with the Cerner system in the cooperating facility utilized

clinical decision support prompts as a signal to further evaluate and appraise patient

needs and progress. Irrespective to the level of experience, consensus was reach in

confirming that the ultimate responsibility for making patient care decisions was that of

the nurse due to limited individualization of CDSS and their inability to critically judge

evolving clinical dynamics. Despite working collaboratively together, the domineering

relationship established amongst clinicians working with clinical decision support

systems validates that nurses maintain a hierarchical connection with their technologic

care coordination partners. The nurses‟ perceived that decision elements of HIT play a

supportive role to clinician knowledge and judgment and is incapable of replacing it.

The systems‟ limitations in meeting all the needs of all the people all the time

likely prohibits a complete reliance on its‟ clinical decision support components resulting

in clinician‟s re-appraisal of computerized decision points. Both novice and experienced

users were able to articulate their role in information management. However, what must

56

remain a primary focus for administrators, educators, and healthcare informaticists is

whether or not users with minimal experience will know when the CIS falls short of

considering contextual clinical data, thus necessitating their responsible subversion

(Hutchinson, 1990). This concern is relevant as the novice nurses in this study were not

as passionate as their experienced counterparts in asserting their intuitive knowledge of

patient care practices independent of information technology likely because of their

limited professional patient care practice.

Cerner users having practiced as a RN for ten or more years undoubtedly

displayed characteristics of decision-making closely aligned with that of the humanist-

inductive model. The model proposes inductive decision-making emerges from intuition

and experience-based knowledge. Nurses described an innate familiarity with what care

practices were necessary for their patients. This study suggests that CIS will never be

able to account for the tacit knowledge gained through experience and clinical exposure.

Their embedded heuristics are rightfully based-upon evidenced based practice (EBP);

however they are limited to only one element of evidence-based practice, an integration

of appraised clinical evidence. The nursing literature describes two additional

components of EBP to include patient‟s values and professional clinical experience

(Melnyk & Fineout-Overholt, 2005). The continued growth of registered nurses able to

ascertain an authentic professional self is predicated on their ability to remain perceptive

to the subjective variable aspects of EBP, the patient and the clinician.

Establishing a continued authentic professional presence was an effort for some

participants as evident by their compelled need to assert their autonomy in functioning as

the care provider able to effectively determine what patient care priorities were of most

57

importance to the patient. The tension felt by nurses attempting to establish and maintain

autonomy in technological enhanced environments will likely remain commonplace in

nursing as the proliferation of CIS continues. Despite some of the struggles and

frustrations communicated by participants, there was an overall appreciation for various

elements of the system. Nurses welcomed the easier accessibility to patient information, a

concise location for summary clinical data, as well as the clinical decision support cues

that prompted more focused investigation of the patient‟s health state.

In describing interactions with the Cerner system, a clear correlation with the

humanist-inductive model of decision making was evident in the decision making

patterns of experienced nurses. They utilized knowledge gained through experience to

guide their patient care practices. However, novice users surprisingly did not clearly

validate or dispel the association of the information processing model with novice

decision making. When interacting with the Cerner system novice nurses conveyed that

their decision making superseded that of information technology in relation to patient

care matters. Nonetheless, they did verbalize knowledge of and adherence to algorithmic

type functions during periods of system downtime that their experienced counterparts

were unable to articulate.

E2 – I do not even know if I can fill out that MAR, or if I forget it. You go to this

one, initial that one, that time that you have to do. I do not even know how to do

that one. There is a form, a checklist like, buddy system. There are a lot of things

you have to do, if it is downtime I think.

Novice nurses‟ blurred use of decision making practices is not distinct in this study likely

due to the focused examination of one environmental interaction. A more broad

58

evaluation of the practice patterns of novice nurses is necessary to further identify their

decision making style.

The emergence of the care-coordination partnership answers the second research

question relative to how medical-surgical nurses are utilizing HIT in their practice. The

clinical decision support technology purports to aid clinicians in their decision making.

Both novice and experienced users described interaction with the technology consistent

with its use as an assistive resource as opposed to that of a fixed rule. This finding is

comforting when considering previous research has raised concern with whether or not

essential clinical cognitive processes would be affected by advanced forms of technology

(Kleiman & Kleiman, 2007; Zuzelo, et al., 2008).

Although there were passionately conveyed arguments about negative aspects of

the system, users conveyed a general acceptance of the HIT. Davis (1989) illustrates that

user acceptance of information technology can be assessed by evaluating two main end-

users perceptions: perceived usefulness & perceived ease of use. Users from the novice

group described the system as user friendly and were able to identify various useful

elements. Albeit that experienced nurses expressed an obvious love-hate relationship with

the Cerner technology‟s impact on workflow considerations, they too shared subjective

impressions that supported their opinion of perceived usefulness and perceived ease of

use.

A likely consideration for the differences in passionately expressed views by the

experienced group describing many negative impacts on workflow considerations versus

the usage discussion amongst the novice nurses is the degree of nursing exposure.

Participants with less than two years of experience entered the care setting as a registered

59

nurse after the implementation of the Cerner system. As a result, their initial exposure to

professional nursing, clinical documentation, and development of a care routine began in

a technologically enhanced environment. Novice participants, without previous exposure

to working in a paper-based institution as a professional nurse, have no basis for

comparison of how the Cerner system impacts their care routine – that is they don’t know

what they don’t know. On the other hand, their experienced counterparts had to adapt to

providing and documenting care in a manner different from that which they‟d grown

familiarity. This shift can be regarded as both positive and negative for different reasons.

The knowledge and skill learned without technological support is essential in making

patient-centered decisions that reflect prioritized care needs. These traits assist clinicians

to regroup and rebound during periods of Cerner unavailability. Conversely, veteran

nurses with engrained workflow patterns primarily conducive to paper-based systems,

may resist progressive changes in the care environment. Such resistance could

inadvertently result in compromises with quality of care considering the evidenced based

shift to electronic health records (To err is human, 1999).

5.2.1 Significance to Nursing

The increased prevalence of clinical information systems in healthcare has aided

in increasing various quality outcomes relative to safety and continuity of care. However

favorable benefits cannot be achieved without appropriate technology integration in

academic and practice settings. Optimizing the relationship between nurses and

technology requires attention and forethought regarding all entry points into the

technologically evolving healthcare arena. This study has significant implications when

considering the development of undergraduate nursing students, the training of new

60

graduate nurses entering the care setting, and the preparation of existing nursing

professionals who transition into technologically enhanced environments.

The 2009 Essentials of Baccalaureate Education for Professional Nursing Practice

Faculty Tool Kit (American Association of Colleges of Nursing) details as its fourth

essential the need to prepare graduate nurses to effectively manage information and

patient care technology. Educators are specifically directed to “Provide

opportunities/assignments for students to: Use simulation and electronic medical records

to access and analyze data relevant to the patient situation” (American Association of

Colleges of Nursing, 2009, p. 6). Skills relative to the management of patient care

technology are not merely suggested, but rather considered critical in providing quality

care. Results of this study contribute to the narrow body of literature addressing how

nurses integrate the use of healthcare information technology in their care practices. By

accessing these findings, nurse educators will have increased insight when developing

curricula that stresses the importance of navigating HIT systems and managing the

patient information derived from them.

Those participating in the development of new graduate nurses in the clinical

setting can also benefit from the current exploration of nurse-technology interactions. The

introduction of CDSS into a healthcare environment have been purported to aid in

knowledge translation by filling gaps created by clinician underuse of information

generated by research (Holroyd, et al., 2007). However nursing literature has identified

that clinical decision support systems have assumed a role more closely aligned with

information management as opposed to having a pronounced presence in knowledge

translation. That is, clinicians utilize the resource to access stored patient information and

61

perform subsequent independent analysis as opposed to relying upon knowledge gained

from algorithmic based logic (Courtney, et al., 2005). Appropriate nursing adoption of

CDSS involves a blend of “…technical skills, social acceptance, and workplace culture “

(Courtney, et al., 2005, p. 317). Additional literature further describes the risk for

mechanized nurse functions possibly resulting in diminished professional competence

(Ernesater, et al., 2009). Staff development nurses as well as preceptors of new graduate

nurses are ideally best situated to ensure novice professional s are groomed to exude self-

reliance in prioritization and maintain autonomy in decision making while utilizing

information yielded from CIS as supportive aids. In evaluating the interaction between

technology and novice and experienced nurses as presented in this study, staff

responsible for the development of new nursing professionals can structure orientation

plans to reflect efforts geared toward mastering appropriate use of HIT as well as

corresponding evaluation measures.

Lastly, findings from the study have significance when considering the

transformed care environment experienced nurses encounter when transitioning to the use

of CIS. These nurses have established care routines and practices that are certainly

impacted by the use of electronic health records and computerized documentation. Such a

shift in care practices can ultimately result in nurses‟ rejection of the system, problematic

and inconsistent use, and subsequently compromised quality of care. By considering the

passionately expressed views of nurses who‟ve experienced an evolution of care

environments, institutions integrating technology elements can consider and attempt to

minimize sources of frustration and discontent in an effort to achieve seamless CDSS

implementation and established quality outcomes.

62

5.3. Limitations of Study

While this research significantly contributes to the body of healthcare information

technology literature, the study had limitations that should be considered by consumers

when reviewing derived data. These limitations were mainly relevant to the qualitative

research design, the sample size, and the contextually based analysis. A relatively small

sample size was utilized to collect data and subsequently may not have been

representative of the larger population of interest. Additionally the contextual and

qualitative nature of this research could possible limit the applicability of findings to

other settings. Variable interpretations of participant data are possible considering the

subjective influence of qualitative analysis. However, the researcher has met the

responsibility of detailing research and analytic methods to aid in transferring knowledge

derived from this study into appropriate settings.

5.4. Recommendations for Future Research

This research adds to the narrow body of literature addressing the intricate

relationship between nurses and healthcare information technology in current clinical

settings. Additional work is needed that explores the subjective experiences of end-users

responsible for achieving enhanced quality outcomes possible with use of CDSS. Nurses,

as the largest proportion of healthcare workers, are the ideal population to provide this

insight considering their innate responsibility for care coordination and information

appraisal. Further research is also needed to assess the cohesiveness of care teams

working in environments utilizing CDSS. An apparent divide between clinical and

administrative staff should be further evaluated for its presence and impact on care

quality. Assessment of cohesiveness should also consider communication patterns of staff

63

working in computer based environments as opposed to those who do not. Finally, a

continued palpable determination of the ability of nurses with varying levels of

experience to individually establish and maintain professional confidence and

competence is essential. Registered nurses must retain their clinical reasoning abilities

and changes in the environment of care necessitate periodic evaluations.

64

List of References

Ahern, K. J. (1999). Pearls, pith, and provocation: Ten tips for reflexive bracketing.

Qualitative Health Research, 9(3), 407-411.

Almerud, S., Alapack, R. J., Fridlund, B., & Ekebergh, M. (2008). Caught in an artificial

split: A phenomenological study of being a caregiver in the technologically

intense environment. Intensive & Critical Care Nursing, 24(2), 130-136.

American Association of Colleges of Nursing. (2009). Nurse faculty tool kit for the

implementation of the baccalaureate essentials. Retrieved September 4, 2009,

from http://www.aacn.nche.edu/Education/pdf/BacEssToolkit.pdf

Ammenwerth, E., Iller, C., & Mahler, C. (2006). IT-adoption and the interaction of task,

technology and individuals: A fit framework and a case study. BMC Medical

Informatics & Decision Making, 6, 3.

Aspiuynall, M. J. (1979). Use of decision tree to improve accuracy of nursing diagnosis.

Nursing Research, 28, 182-185.

Au, N., Ngai, E. W. T., & Cheng, T. C. E. (2002). A critical review of end-user

information system satisfaction research and a new research framework.

International Journal of Management Science, 30(6), 451-478.

Ball, M. J., & Lillis, J. C. (2000). Health information systems: Challenges for the 21st

century. AACN Clinical Issues, 11(3), 386-395.

Banning, M. (2008). A review of clinical decision making: Models and current research.

Journal of Clinical Nursing, 17(2), 187-195.

Barnard, A. (1996). Technology and nursing: An anatomy of definition. International

Journal of Nursing Studies, 33(4), 433-441.

Barnard, A. (1999). Nursing and the primacy of technological progress. International

Journal of Nursing Studies, 36(6), 435-442.

Barnard, A., & Gerber, R. (1999). Understanding technology in contemporary surgical

nursing: A phenomenographic examination. Nursing Inquiry, 6(3), 157-166.

Barnard, A., & Sandelowski, M. (2001). Technology and humane nursing care:

(Ir)reconcilable or invented difference? Journal of Advanced Nursing, 34(3), 367-

375.

65

Benner, P. (1982). From novice to expert. The American Journal of Nursing, 82(3), 402-

407.

Benner, P. (1984). From novice to expert: Excellence and power in clinical nursing

practice. Upper Saddle River: Prentice Hall.

Bower, A. G. (2005). The diffusion and value of healthcare information technology.

Santa Monica: RAND Health.

Bureau of Labor Statistics. (2008). Occupational outlook handbook: Registered nurse.

Retrieved October 30, 2008, from http://www.bls.gov/oco/ocos083.htm

Cavanagh, S. (1997). Content analysis: Concepts, methods and applications. Nurse

Researcher, 4, 5-16.

Courtney, K. L., Demiris, G., & Alexander, G. L. (2005). Information technology:

Changing nursing processes at the point-of-care. Nursing Administration

Quarterly, 29(4), 315-322.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of

information technology. MIS Quarterly, 13(3), 319-340.

Deese, D., & Stein, M. (2004). The ultimate health care IT consumers: How nurses

transform patient data into a powerful narrative of improved care. Nursing

Economics, 22(6), 336-341.

Despont-Gros, C., Mueller, H., & Lovis, C. (2005). Evaluating user interactions with

clinical information systems: A model based on human-computer interaction

models. Journal of Biomedical Informatics, 38(3), 244-255.

Dykes, P. C., Hurley, A., Cashen, M., Bakken, S., & Duffy, M. E. (2007). Development

and psychometric evaluation of the impact of health information technology (I-

HIT) scale. Journal of the Medical Informatics Association, 14(4), 507-514.

Elo, S., & Kyngas, H. (2008). The qualitative content analysis process. Journal of

Advanced Nursing, 62(1), 107-115.

Ernesater, A., Holmstrom, I., & Engstrom, M. (2009). Telenurses' experiences of

working with computerized decision support: Supporting, inhibiting and quality

improving. Journal of Advanced Nursing, 65(5), 1074-1083.

Fain, J. A. (2004). Reading, understanding, and applying nursing research: A text and

workbook (2nd ed.). Philadelphia: F.A. Davis Company.

66

Gearing, R. E. (2004). Bracketing in research: A typology. Qualitative Health Research,

14(10), 1429-1452.

Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual

performance. MIS Quarterly, 19(2), 213-236.

Graneheim, U. H., & Lundman, B. (2004). Qualitative content analysis in nursing

research: Concepts, procedures and measures to achieve trustworthiness. Nurse

Education Today, 24(2), 105-112.

Hanlon, G., Strangleman, T., Goode, J., Luff, D., O'Cathain, A., & Greatbatch, D. (2005).

Knowledge, technology and nursing: The case of NHS direct. Human Relations,

58(2), 147-171.

Hannah, K. J., Ball, M. J., & Edwards, M. J. A. (Eds.). (2005). Introduction to nursing

informatics (3rd ed.). New York: Springer-Verlag.

Health Resources and Services Administration. (2004). The registered nurse population:

Findings from the 2004 national sample survey of registered nurses. Retrieved

May 26, 2010, from

http://bhpr.hrsa.gov/healthworkforce/rnsurvey04/appendixa.htm#1

Henderson, A., & Henderson, A. (2006). The evolving relationship of technology and

nursing practice: Negotiating the provision of care in a high tech environment.

Contemporary Nurse, 22(1), 59-65.

Holroyd, B. R., Bullard, M. J., Graham, T. A., Rowe, B. H., Holroyd, B. R., Bullard, M.

J., et al. (2007). Decision support technology in knowledge translation. Academic

Emergency Medicine, 14(11), 942-948.

HRSA. (2004). The registered nurse population 2004. Retrieved July 27, 2009, from

http://bhpr.hrsa.gov/healthworkforce/rnsurvey04/3.htm

Hsieh, H. F., & Shannon, S. (2005). Three approaches to qualitative content analysis.

Qualitative Health Research, 15(9), 1277-1288.

Huffman, C., & Sandelowski, M. (1997). The nurse-technology relationship: The case of

ultrasonography. Journal of Obstetric, Gynecologic, & Neonatal Nursing, 26(6),

673-682.

Hutchinson, S. A. (1990). Responsible subversion: A study of rule-bending among

nurses. Scholarly Inquiry for Nursing Practice, 4(1), 3-17.

67

Jha, A. K., DesRoches, C. M., Campbell, E. G., Donelan, K., Rao, S. R., Ferris, T. G., et

al. (2009). Use of electronic health records in U.S. hospitals. New England

Journal of Medicine, 360, 1628-1638.

Kleiman, S., & Kleiman, A. (2007). Technicity in nursing and the dispensation of

thinking. Nursing Economics, 25(3), 157-161.

Krueger, R. A., & Casey, M. A. (2009). Focus groups: A practical guide for applied

research (4th ed.). Thousand Oaks, California: Sage Publications.

Lauri, S., Salantera, S., Chalmers, K., Ekman, S. L., Kim, H. S., Kappeli, S., et al. (2001).

An exploratory study of clinical decision-making in five countries. Journal of

Nursing Scholarship, 33(1), 83-90.

LifeBridge Health. (2010). Retrieved March 15, 2010, from

http://www.lifebridgehealth.org/northwest.cfm

Manias, E., Aitken, R., & Dunning, T. (2004). Decision-making models used by 'graduate

nurses' managing patients' medications. Journal of Advanced Nursing, 47, 270-

278.

Marshall, C., & Rossman, G. B. (2006). Designing qualitative research. Thousand Oaks,

California: Sage Publications.

Mayring, P. (2000). Qualitative content analysis. Forum: Qualitative Social Research,

1(2). Retrieved from

http://www.inteligenciacolectiva.org/principal_proyectos_metodologia_qca.pdf

McGillivray, R., Yates, S., & McLister, B. (2007). Nurses and technology: An

international survey. Biomedical Instrumentation & Technology, Supplement, 19-

31.

McLafferty, I. (2004). Focus group interviews as a data collecting strategy. Journal of

Advanced Nursing, 48(2), 187-194.

Medpac. (2004). Information technology in healthcare (Report to the congress: New

approaches in medicare).

Melnyk, B. M., & Fineout-Overholt, E. (2005). Evidenced-based practice in nursing &

healthcare: A guide to best practice. Philadelphia: Lippincott, Williams, &

Wilkins.

Munhall, P. L. (2007). Nursing research: A qualitative perspective (4th ed.). Boston:

Jones and Bartlett Publishers.

68

Northwest Hospital Center - Randallstown, MD. (2010). Retrieved March 15, 2010,

from http://www.hospital-data.com/hospitals/NORTHWEST-HOSPITAL-

CENTER-RANDALLSTO576.html

Nurse. (2008). Retrieved October 30, 2008, from http://www.merriam-

webster.com/dictionary/nurse

ONeill, E. S., Dluhy, N. M., Chin, E., Oneill, E. S., Dluhy, N. M., & Chin, E. (2005).

Modelling novice clinical reasoning for a computerized decision support system.

Journal of Advanced Nursing, 49(1), 68-77.

Sandelowski, M. (1999a). Nursing, technology and the millennium. Nursing Inquiry,

6(3), 145-145.

Sandelowski, M. (1999b). Troubling distinctions: A semiotics of the nursing/technology

relationship. Nursing Inquiry, 6(3), 198-207.

Simpson, R. L. (2004). Nursing informatics. The softer side of technology: How IT helps

nursing care. Nursing Administration Quarterly, 28(4), 302-305.

Simpson, R. L. (2007). The politics of information technology. Nursing Administration

Quarterly, 31(4), 354-358.

Stewart, D. W., & Shamdasani, P. N. (1990a). Focus Groups: Theories and Practice.

Newbury Park: Sage Publications.

Stewart, D. W., & Shamdasani, P. N. (1990b). Focus groups: Theory and practice (Vol.

20). Newbury Park, California: Sage Publications.

Stone, W. M., Smith, B. E., Shaft, J. D., Nelson, R. D., Money, S. R., Stone, W. M., et al.

(2009). Impact of a computerized physician order-entry system. Journal of the

American College of Surgeons, 208(5), 960-967.

Summers, A. D. (2007). Three nursing legacies: Nightingale, medicine, and technology

and their impact on nursing practice. Asian Journal of Nursing, 10(1), 6-11.

Tabak, N., Bar-Tal, Y., & Cohen-Mansfield, J. (1996). Clinical decision making of

experienced and novice nurses. Western Journal of Nursing Research, 18(5), 534-

547.

Taylor, R., Bower, A., Girosi, F., Bigelow, J., Fonkych, K., & Hillestad, R. (2005).

Promoting health information technology: Is there a case for more-aggressive

action? Health Affairs, 24(5), 1234-1245.

69

Thompson, C., & Dowding, M. (2002). Clinical Decision Making and Judgement in

Nursing. London: Churchill Livingstone.

To err is human. (1999). (Report). Washington, D.C.: Institute of Medicine.

Weber, S. (2007). Critical care nurse practitioners and clinical nurse specialists interface

patterns with computer-based decision support systems. Journal of the American

Academy of Nurse Practitioners, 19(11), 580-590.

Wikstrom, A. C., Cederborg, A. C., & Johanson, M. (2007). The meaning of technology

in an intensive care unit: An interview study. Intensive & Critical Care Nursing,

23(4), 187-195.

Wu, S. M., Chao, Y., Yang, C. F., & Che, H. L. (2005). Decision making tree for women

considering hysterectomy. Journal of Advanced Nursing, 51, 361-368.

Zhang, Y., & Wildemuth, B. (2009). Qualitative analysis of content. In B. Wildemuth

(Ed.), Applications of social research methods to questions in information and

library science (pp. 308-319). Westport, CT: Librabries unlimited.

Zuzelo, P. R., Gettis, C., Hansell, A. W., & Thomas, L. (2008). Describing the influence

of technologies on registered nurses' work. Clinical Nurse Specialist, 22(3), 132-

142.

70

Appendix A: LifeBridge Health IRB Approval

71

Appendix B Drexel University IRB Approval

72

73

Appendix C: Informed Consent Document

74

75

76

77

78

79

80

81

82

83

Appendix D: Focus Group Interview Guide

1. Tell me about your experiences utilizing the Cerner clinical documentation

system in the clinical environment.

2. Can you describe how using the Cerner clinical decision support system has

affected or impacted your care?

3. Can you give specific examples of when the decision support system was

helpful and when it was not helpful.

4. Can you talk about specific occurrences when the system has helped you in

making a decision for your patients.

5. Describe for me times when it was not appropriate to follow the direction of

the Cerner clinical documentation system?

6. What do you think is the role of the clinical decision support system in

analyzing or interpreting patient data?

84

Appendix E: Demographic Data Collection Form

Demographic Data Form

Thank you for agreeing to participate in this study. The demographic data here is being

collected as part of a research study titled “Is Nurses‟ Clinical Decision Making

Influenced by Healthcare Information Technology: A Qualitative Content Analysis”.

Please complete all portions of the instrument. Your comments are very important. In the

form, please select or enter the response that bests describe your choice of the answer(s).

1. Age: Please enter your age in years.

2. Gender (select one)

Male

Female

3. Please enter the amount of time in years you have been practicing as a Registered

Nurse

4. Indicate your level of preparation to function as a Registered Nurse. Identify all

educational levels that apply.

Diploma

Associates Degree

Bachelor‟s Degree

Other:

Specify

5. If currently enrolled in a nursing program, please indicate the level of your studies.

BSN

MSN

DNP/PhD

6. Please indicate any additional credentials you currently possess and specify the

discipline

Associate‟s Degree

Bachelors Degree

Master‟s Degree

Doctorate

85

Certification

7. Please indicate specific area(s) of practice where you have worked. Specify if not

listed.

Medical/Surgical

Operating Room

Oncology

Staff Development/Educator

College Professor/Instructor

Radiation Oncology

Surgical Intensive Care

Pediatric

Pediatric Intensive Care

Clinical Coordinator

Nurse Manager

Gastroenterology

Cardiac Cath Laboratory

Obstetrics / Gynecology

Informatics

Quality Management

Ambulatory Care

Outpatient Surgery

Emergency Room

Urgent Care

Home Care

Radiology

Medical Intensive Care

Neonatal Intensive Care

Post Anesthesia Care Unit

Administrator

Hospice

Research

Chemotherapy Infusion

Clinic

Risk Management

Hemodialysis

Rehabilitation

Other:

Specify

8. Please specify your race and ethnicity.

Race

Ethnicity

Hispanic or Latino

Not Hispanic

American Indian/Alaskan

Native

Asian

Black or African American

Native Hawaiian/Pacific

Islander

86

White

9. Do you utilize a personal computer for purposes other than LifeBridge work

requirements?

Yes – Please specify purpose

Banking

School Work

Searching/Entertainm

ent

No

Other

10. Have you had instructions/classes in any nursing program in informatics?

No

Yes: Specify program type

How long ago did instruction take place?

Less than 2 years ago

Between 2 to 5 years

N/A

Between 5 to 10 years

Over 10 years ago

87

11. Have you ever worked with another electronic clinical documentation system other

than the Cerner clinical documentation system?

No

Yes: Specify system

12. Which Statement best describes your comfort level with utilizing the Cerner system?

I am very comfortable

I am somewhat comfortable

I am neither comfortable or uncomfortable

I am somewhat uncomfortable

I am very uncomfortable

13. Do you believe that the initial instruction you received about using the Cerner clinical

documentation system was adequate for you to effectively utilize it in your current

practice?

Yes

No

14. Was your initial RN training received in the United States?

Yes

No

15. Do you utilize clinically-based applications on a PDA device to help you make

patient care decisions?

Yes – Specify

No

88

Appendix F: Categorical Analysis of Findings

FINDINGS DISCUSSION (THEMES)

Advantages

Convenient

It‟s a good program (N2)

Makes things quicker/faster (N2, E1)

More convenient than using the paper

chart (N2, E2)

User friendly

It‟s a good program (N2)

User friendly (E3, N2)

Disadvantages

Hinders communication

Less real communication (E1)

Use of computerized documentation

by different departments decreases

collaborative clinician-to-clinician

communication (E5)

Time consuming because of slow

system

Entering clinical documentation time

consuming for users (E1)

Frustration exists because the system

is slow from so much information

contained in it (E4)

Logistical problems affect use

COWS should be regularly serviced

and maintained

Flaws in the system exist (E1)

Frustrations with Cerner system

prompted by logistical considerations

of access and availability (E1)

Negative interaction concerns

between system and user not

necessarily related to Cerner system

but general computer functionality

(E4)

(HIT & Clinical decision making)

Provides puzzle clues - Cerner promotes

user investigation

Cerner forces clinicians to take their time

in documenting care (E1)

Cerner promotes critical thinking for the

nurse (E1)

False alerts remain throughout the

admission seen as both positive and

negative (E2)

System alerts prompt clinician actions even

before patient interaction (E1)

System pop-ups remind clinicians about

patient care considerations (E1)

System promotes user investigation

(E4,N6)

Clinician reasoning supersedes Cerner

directives & analysis / Nurse Hierarchy

Clinical reasoning utilized to initiate

interventions that may be appropriate but

perhaps aren‟t official orders (E1)

Clinician assessment valued over CDSS

interpretation of clinical data (E2,N5)

Computer does not have intellect, nurse

runs the show and makes decisions (E3)

Need for further clinician evaluation of

Cerner medication orders (E1, N2)

Nurse clinician enters documentation to

reflect when medication is not appropriate

to be given (E1)

Nurse must implement system

workarounds to achieve outcomes not

supported by the system (E1)

(How nurses are utilizing HIT)

Nurse-technology dyad Care

coordination partner

Care elements may be missed due to

89

Cerner-User Interactions

Transparency

Cerner maintains an electronic

fingerprint of user activity that guides

clinicians to mind their own business

(E1)

Cerner provides evidence of rationales

for care delays (E1)

Cerner provides transparent,

consistent detailed information

without user interpretation (E2)

Increases safety

Accessing patient information

maintained in Cerner helps to alleviate

errors in care (E1)

Safer documentation environment that

decreases likelihood of error (E3)

System promotes safer environment

for the hospital and patient (E1)

Both comprehensive and restrictive

Cerner offers flexibility in

documentation options (E3)

Clinician response to CDSS analysis

of data influenced by institutional

rules regarding CDSS interpretation

of data (E2N1)

Comprehensive documentation

abilities (E1, N2)

Documentation options may be too

exhaustive (N2)

Fixed categorical selection of patient

care orders does not always include

what the provider really wants to

order (E1)

Limited ability to individualize

documentation (E1, N4)

Orders that are not appropriately

entered into the system will not be as

readily available for system user

because they will appear in

unexpected sections (E1)

Multifaceted system

Numerous system functions available

downtime (E2)

CDSS maintains schedule of patient care

activities for clinicians to perform (E1,N2)

Miscategorization of orders may not be

carried out as ordered thus relying on

verbal communication of provider intent

(E1)

Not on the right track without Cerner (E3)

Periods of Cerner downtime interrupts

workflow (E2)

Possibility of missed orders if computer is

not frequently accessed (E3)

Reliance on CDSS components to aid in

organizing patient care activities (E1, N3)

Cerner serves as a convenient depot for

patient information

Allows for quicker access to patient

diagnostic tests (E1)

CDSS used as a resource for information

(E3, N3)

System provides some helpful patient

summary information (E3, N2)

Useful research functions available at the

point of care for clinicians (E2)

Resource in provision of patient care

Emergence of oppositional team members/

Big brother is watching

Administrative staff more task centered as

opposed to care centered (E1)

Administrative staff have unrealistic

documentation expectations compared to

the reality of providing direct patient care

(E3)

Administrative staff out of touch with

realities of providing bedside care (E3)

Negative remediation from performance

improvement staff for untimely

documentation (E1)

Pressure exists from documentation

performance improvement department that

conflicts with patient care routine (E5)

Pressure/struggle exists between having

90

that aren‟t utilized (N5)

Unfamiliarity with all documentation

areas (N1)

Promotes communication

Interdisciplinary collaboration

prompted by Cerner beneficial (E2,

N1)

Process of providing patient care

quicker because of results that are

communicated more efficiently (E1)

Added stressor

Clinical documentation poses added

stress (E1)

Frustrated staff may kick cows (E1)

Sense of loss without Cerner during

downtime

Unfamiliar with what to do during

downtime (E2)

Pre-existing ideas/approach to patient

care

Push-pull struggle between balancing

patient care and administrative

restraints for clinical documentation

Time struggles exists relative to

timely documentation and provision

of patient care (E1)

Being pulled away for care interferes

with Cerner documentation efforts

(E1)

Computer documentation completed

for administrative purposes of

performance improvement (E1)

It is not possible to meet all the

documentation expectations and

provide patient care (E1)

Individual user characteristics affect

interaction with the system

Fears / Potential Disadvantages

time to provide patient care and accessing

e-mail to receive system update

information (E2)

Struggle to maintain autonomy

Nurse can program themself to care for

patient without computer interference (E1)

Nurse knows what they‟d like to do before

interacting with the computer (E1)

HIT as an impediment/interference to

patient care

Added a hundred pounds on my back (E1)

Cerner system takes users away from

patient care (E2)

Interacting with Cerner can slow down

patient care (E1)

Less human contact with patients (E2)

Patient care provided prior to Cerner

clinical documentation to minimize

interruptions in care routine (E1)

Slow speed of system pulls users away

from the bedside, interfering with nursing

care (E4)

Integration has resulted in vulnerability of

nurses

Feel lost without Cerner as a reference

when system is unavailable (E2, N4)

Integration and reliance on HIT causes

nurses to forget what they are suppose to

do during their care day (E2)

Loss of control during downtime (E1)

Independent clinician assessment,

reasoning, & interpretation remains

critical despite CDSS

Common sense required in using the

Cerner system (E1)

Computer does not have intellect, nurse

runs the show and makes decisions (E3)

Computerized documentation still requires

nurse to pause and think about what they

are documenting despite availability of

forms (E1)

91

Weary of ‘Too much’ clinical

technology in the future consents,

nursing notes, excessive alerts

Weary of electronic consents in the

future (E2)

Weary of nursing notes being entered

– switch from paper to electronic (E1)

Weary of too many decision support

cues from Cerner (N1)

Necessary to be a prudent nurse in

evaluating system orders (E1)

Necessary to look at provider orders not

just directives about when to give

medications (E1)

Nurses may question duplicate orders

appearing in Cerner (E1)

Nurses using Cerner system in providing

patient care is not a task centered, but

rather involves levels of cognitive

processing (E1)

Providers contacted regarding orders in

Cerner system that don‟t seem to be

appropriate (N2)

Success of Cerner dependent on users, not

system itself (E1)

System does not discriminate user scope of

practice (N4)

HIT is not ‘all knowing’ – not fully

reflective of entire clinical picture

Clinical documentation may not fully

capture what is going on in the clinical

environment (E2)

System interprets patient data & sometimes

generates false alerts (E1, N4)

Back to the Basics???

Appreciation for basic flagging systems

that visually alerted nurse to updated

patient information (E2)

Necessary to know how to function and

perform basic nursing without the Cerner

system (E1)

Sometimes preference exists for basics of

paper documentation (E3)

92

Good program that

adds convenience

Comprehensive in

options but equally

restrictive for users

Provides puzzles clues

that ultimately promote

user investigation

Nurse hierarchy over

HIT system (weighted

toward experienced)

Nurse-technology Dyad

Increased vulnerability

of nurses

Appendix G: Venn Diagram Comparison of Data Categories

Experienced

Cerner easily an interference

Time

Consideration

Hinders Communication

Logistical problems

Added Stressor

Interferes with care

Increased Safety

Transparency /

Big Brother

Struggle to balance patient

Care & meet administrative

Demands regarding

Documentation

Assertion of nurse autonomy

Appreciation for

‘basics’ of nursing

Novice

Multifaceted System

93

Appendix H: Demographic Data Summary

Sample Characteristic Experience Level

Novice N=4

Experienced N=4

N=8 %

Personal

Demographics

Mean Age

Novice

Experienced

37.5

43.5

-

-

Race

White

African American

Asian

Novice

Experienced

Novice

Experienced

Novice

Experienced

N=2

N=1

N=2

N=1

N=0

N=2

25%

12.5%

25%

12.5%

0%

25%

Mean Practice Years

as a RN

Novice

Experienced

1.38

19

-

-

Initial RN training

Associate Degree

Baccalaureate Degree

Novice

Experienced

Novice

Experienced

N=4

N=2

N=0

N=2

50%

25%

0%

25%

Gender

Male

Female

Novice

Experienced

Novice

Experienced

N=1

N=0

N=3

N=4

12.5%

0%

37.5%

50%

94

Vita

An‟Nita C. Moore is a native of the United States of America, born and raised in the

suburbs surrounding Baltimore, Maryland. She obtained her undergraduate nursing

degree from Coppin State University in 2001 and her Master of Public Health degree in

2004 from Morgan State University. Dr. Moore completed her doctoral nursing studies in

2010 from Drexel University with nursing education being her primary concentration.

Considering her commitment to nursing education, Dr. Moore has begun to develop a

progressively evolving career in the field as she has teaching experience with nursing

students, as well as both experienced and novice nursing professionals. She has served as

a clinical nursing instructor for three nursing schools as well as an inpatient educator for

experienced nursing staff in the hospital setting. Her most recent teaching position is as

an Assistant Professor of Nursing with Morgan State University teaching principles of

medical/surgical nursing and health assessment. Dr. Moore has received several academic

awards and honors for her successes and is published in the Journal of National Black

Nurses‟ Association as part of a team of researchers evaluating cardiovascular disease in

African American women.