JMIR MEDICAL INFORMATICS

Zadvinskis et al

Original Paper

Nurses’ Experience With Health Information Technology:
Longitudinal Qualitative Study
Inga M Zadvinskis1,2, PhD, RN; Jessica Garvey Smith3, BS; Po-Yin Yen3,4,5, PhD, RN
1Riverside Methodist Hospital, OhioHealth, Columbus, OH, United States

2

Helene Fuld Health Trust National Institute for Evidence-Based Practice in Nursing and Healthcare, College of Nursing, The Ohio State University,
Columbus, OH, United States
3

Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, United States

4

Institute for Informatics, Department of Medicine, Washington University, St Louis, MO, United States5

Goldfarb School of Nursing, Barnes Jewish College, BJC Healthcare, St. Louis, MO, United States

Corresponding Author:
Po-Yin Yen, PhD, RN
Institute for Informatics
Department of Medicine
Washington University
4444 Forest Park Avenue, Suite 6318
St Louis, MO, 63108-2212
United States
Phone: 1 3142732313
Email: yenp@wustl.edu

Abstract
Background: Nurses are the largest group of health information technology (HIT) users. As such, nurses’ adaptations are criticalfor HIT implementation success. However, longitudinal approaches to understanding nurses’ perceptions of HIT remain
underexplored. Previous studies of nurses’ perceptions demonstrate that the progress and timing for acceptance of and adaptation
to HIT varies.
Objective: This study aimed to explore nurses’ experience regarding implementation of HIT over time.
Methods: A phenomenological approach was used for this longitudinal qualitative study to explore nurses’ perceptions of HIT
implementation over time, focusing on three time points (rounds) at 3, 9, and 18 months after implementation of electronic healthrecords and bar code medication administration. The purposive sample was comprised of clinical nurses who worked on a
medical-surgical unit in an academic center.
Results: Major findings were categorized into 7 main themes with 54 subthemes. Nurses reported personal-level andorganizational-level factors that facilitated HIT adaptation. We also generated network graphs to illustrate the occurrence ofthemes. Thematic interconnectivity differed due to nurses’ concerns and satisfaction at different time points. Equipment andworkflow were the most frequent themes across all three rounds. Nurses were the most dissatisfied approximately 9 months after
HIT implementation. Eighteen months after HIT implementation, nurses’ perceptions appeared more balanced.
Conclusions: It is recommended that organizations invest in equipment (ie, wireless barcode scanners), refine policies to reflectnursing practice, and improve systems to focus on patient safety. Future research is necessary to confirm patterns of nurses’
adaptation to HIT in other samples.
(JMIR Med Inform 2018;6(2):e38) doi: 10.2196/medinform.8734
KEYWORDS
health IT; electronic health record; barcode medication administration; qualitative research; adaptation

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Introduction
Background
Health information technology (HIT or Health IT) is a broadconcept that includes a variety of technologies, including
computer equipment, system software, and infrastructure thatrecords, stores, protects, and retrieves clinical, administrative,
or financial information [1]. In the United States, by 2015 96%
of all hospitals had adopted a certified electronic health record(EHR) [2]. An EHR is a repository of patient data that is stored
and exchanged securely among multiple authorized users to
support quality integrated health care [3]. While providers andpatients appreciate the positive benefits of HIT throughimproved care [4], there are also problems with HIT [5]. HIT
problems are noteworthy because they may result in delayedcare, altered clinical decision-making, and modified care
processes, which affect patient outcomes [5]. A few unintended
adverse consequences of EHRs are incomplete information,
usability issues leading to frustrating user experiences, andpatient privacy breaches [6].

Longitudinal Qualitative Studies About Clinicians’
Perceptions of HIT
A myriad of individual and organizational factors influence
HIT, contributing to its complexity and multi-dimensional nature[7]. A socio-technical model offers insights for studying HIT
in complex adaptive health care systems through eight
dimensions, including: (1) hardware and software computing
infrastructure; (2) clinical content; (3) human-computerinterface; (4) people; (5) workflow and communication; (6)internal organizational policies, procedures, and culture; (7)external rules, regulations, and pressures; and (8) systemmeasurement and monitoring [8]. Researchers have studied
provider perceptions of HIT over time, describing the mixed(both positive and negative) effects of HIT. For example, atwo-year prospective, longitudinal survey of attending
physicians in three clinical areas experienced the change froma homegrown EHR to a vendor EHR [9]. Safety perceptions
dropped during the first six months, but then began to rise [9].
Physicians reported that the EHR created additional work andtheir satisfaction dropped [9]. In a similarly-designed study,
ophthalmologists did not report a significant change in overall
job satisfaction over time (3, 7, 13, and 24 months post-EHR
implementation), but they expressed concern about the EHR’s
effect on interactions with patients and their ability to create
quality documentation [10]. In primary care, even two years
after EHR implementation, the EHR learning curve andcomputer knowledge remained challenging for interprofessional
staff [11].
Longitudinal perceptions of EHRs have also been studied innurses. Intensive care unit (ICU) nurses completed twocross-sectional survey questionnaires at 3 months and 12 months
after EHR implementation and reported greater acceptance of
the EHR at 12 months compared to 3 months [12]. In contrast,
US nurses working on inpatient units within an academic
medical center reported less positive attitudes toward the EHR
18 months after implementation compared to preimplementation
and 6 months postimplementation [13]. For nurses, the timeline
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Zadvinskis et alof adaptation for new HIT varies. A study conducted in Taiwan
reported that nurses needed 3 months to understand thefunctionalities and benefits of an EHR [14]. In the United States,
ICU nurses perceived the EHR as useful (through access to
up-to-date information) at 3 months, but perceived that
usefulness was not as relevant for acceptance at 12 months [12].
The authors explained that other EHR functionalities may havegreater precedence over time to influence acceptance [12].
Positive computer attitudes are a significant predictor of fast
adaptation [15]. Although studies exist regarding clinicians’
adaptation to HIT, there is insufficient qualitative evidence
regarding facilitators, hindrances, and a longitudinal timelineof adaptation, especially among clinical nurses.

Levels of Expectation Regarding HIT
In our prior study, we found that nurses’ expectations regarding
HIT can be stratified from personal-level (human-computerinteraction) to organizational-level (quality of care) [16]. The
five levels were: (1) how easy the system is to use (ie, equipment
and system), (2) nurses’ workflow and task performance, (3)collaboration within the nursing unit, (4) nurses’ communication
across hospital disciplines and departments, and (5) the effectsof HIT on quality of care (ie, patient safety and nurse/patientsatisfaction). Each level expands from individual user concerns
to the team and the broader organization, and each level
increases in complexity. In early implementation, we found that
HIT users may be more concerned with lower-level expectations,but the timeframe for nurses’ expectations, and thus adaptation,is unknown.

Objective
We investigated HIT adaptation, which is, “a process ofmodifying existing conditions in an effort to achieve alignment”[17] involving workflow redesign, user training, and technology
maintenance [18]. This was a longitudinal qualitative study that
explored medical-surgical nurse perceptions of HIT
implementation over time. We interviewed nurses three times
after EHR and bar code medication administration (BCMA)
implementation to capture evolving adaptation of theirperceptions and behaviors in this specific job role. The objectiveof the study was to explore nurses’ experience of HIT
implementation, and how they adapted their perceptions andbehavior to HIT upgrades and optimization over time.

Methods
Overview
We conducted a phenomenological qualitative study at a large
Midwestern academic medical center. The medical center
implemented a customized commercialized EHR system (EPIC
platform [19]) in October 2011, which included computerized
provider order entry, electronic charting, and BCMA. Prior to2011, a few nursing units (ie, critical care) used some electronic
documentation. In 2011, all nursing units within the medical
center began using the new EHR system. In this study,
participants were from a medical-surgical unit that used paper
charts prior to implementation.

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SampleWe used purposive sampling to recruit staff nurses who worked
on a medical-surgical unit that used EHRs and BCMA and had
a minimum of two years of working experience in theorganization. We approached participants either face-to-face or
via email and hosted private face-to-face interviews in a location
away from the clinical area to ensure privacy and avoid
disruption.

Data Collection
We used a semi-structured interview guide with additional
probes (Multimedia Appendix 1) to clarify and discover in-depth
information. Field notes were taken during and after theinterviews. We interviewed participants over three time points
based on convenience, including Round 1 (R1) 3 months
post-EHR implementation (winter 2012), Round 2 (R2) 9
months post-EHR implementation (summer 2012), and Round
3 (R3) 18 months post-EHR implementation (summer 2013).
The length of each interview ranged from 20 to 60 minutes. Allinterviews were audio-recorded and professionally transcribedverbatim. We also collected basic demographic information,
including age, gender, position, education, and years ofexperience.

Data Analysis
Three researchers (IZ, JGS, and PY) read the transcripts
independently and located relevant statements in the transcriptsthat expressed units of meaning. The researchers generated
common themes by synthesizing the meaning units. Themes
reflected a general description of the nurse participants’experience with EHRs and BCMA. The structure for the first
five themes was derived from previous work that delineatedconfirmed nurses’ expectations ranging from personal-level toorganizational-level [16]. Dimensions of the socio-technicalmodel, such as hardware, people, workflow communication,and policies, informed coding structure during qualitative
analysis. After iterative discussion and refinement, a codebook
was generated. We developed a total of 61 themes: 7 at the firstlevel and 54 at the second level. We also kept a detailed recordof our codes and their definitions as we updated them over time(Multimedia Appendix 2). Each quote was classified from one
to four themes, as one quote could contain multiple units ofmeaning (themes), which affected thematic frequency; wedefined this as theme cooccurrence. We used NVivo 10 [20], aqualitative research analysis tool, for data management andanalysis. In addition, we used Gephi, a graph visualization andexploration software [21], to illustrate the cooccurrence
relationships among themes, where nodes represented themes
and lines signified the cooccurring relationships. The network
graph was illustrated in a forced layout.

Intercoder Reliability
We assessed and established our intercoder reliability using
Cohen’s Kappa. Cohen’s Kappa has been commonly used toassess intercoder reliability, with recommendations greater than
0.7 for semi-structured interviews, especially with multiple
complex codes [22-24]. We coded 10% of the transcripts
together to establish consensus, as experts recommend [22,24].
For each independently-coded transcript, we calculated Cohen’s
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Kappa by averaging the Kappas of all themes through a multiple
independent coding comparison process [22,24,25]. In our
analysis, two researchers (IZ and JGS) independently coded
randomly selected transcripts and discussed discrepancies; athird researcher (PY) mediated the discussion to confirm final
coding. After iterative discussion, we reached a Cohen’s Kappa
of 0.82.

Results
Principal Findings
Nineteen nurses participated in the study, with some nurses
participating in multiple rounds. We conducted a total of 30
interviews: 9 from R1, 11 from R2, and 10 from R3. We wereunable to interview all nurses across all 3 rounds because somenurses were unavailable (ie, schedule conflicts, transferred to
new positions, declined participation). Among the 9 nurses thatparticipated in R1, 7 participated in R2, and 3 participated in
R3. Eleven nurses participated in only one interview, and 8
nurses participated in more than one interview. Among the 19
nurses, 17 were female. The age of the nurses ranged from 22
to 52 years old, with 3 to 25 years of working experience, and
58% (11/19) worked the day shift. Most nurses (15/19, 79%)
were Bachelor of Science in Nursing-prepared and all worked
as staff nurses. All nurses owned home computers and 79%(15/19) owned smartphones. Across all rounds, nurses rated
themselves an average of 4 out of 5 in computer competency,with 1 meaning not competent and 5 meaning very competent.
We used information saturation to determine the number ofparticipants.
We assembled themes into a table format to review nurse
perceptions over time (Multimedia Appendix 2), categorizingthem into 7 main themes with 54 subthemes. Details regarding
development of the first five primary themes, E1 to E5, aredescribed elsewhere [16]. The longitudinal approach led to thediscovery of two additional themes: adaptation andorganizational factors. Adaptation explained both internal andexternal resources that influenced acclimatization to technology
over time. Organizational factors discussed communication or
HIT decisions made by organizational leaders that influenced
nursing work. Quote examples and frequencies can be found in
Multimedia Appendix 3.

Thematic Findings
E1: Nurses’ Interaction with HIT
The E1 subthemes involved system (software) and equipment
components. Equipment addressed workstations on wheels(WOWs), scanners, and wires (wired mouse/scanners andelectrical cords). Nurses perceived equipment negatively becauseof noise, occasional (battery) power loss, and challenging use
in semi-private patient rooms and narrow, crowded hallways.
By R3, the information technology (IT) department installed
well-liked wireless BCMA scanners. System functionality
concerns included lengthy login, program shutdowns during
medication administration, and BCMA scanning issues.
Shutdowns occurred if users forgot to plug in the WOW when
not in use, leading to power loss, or sometimes for unknown
reasons. Nurses reported difficult system navigation in all
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rounds, especially during emergency documentation. In laterrounds, nurses acknowledged easier system navigation because
EHR flowsheets were updated with head-to-toe organizationthat reflected how nurses conducted physical assessments.

E2: Nursing Performance Regarding Task
Accomplishment
Nurses viewed documentation as time-consuming and arduous,
yet thorough. Nurses valued feedback on performance fromvisual indicators (green and red dots) for complete or incomplete
documentation. In R1 and R2, nurses thought documentation
was inefficient and not streamlined because it contained
elements irrelevant to their population, required too much
scrolling, appeared chaotic, and took longer than paper charting.
However, by R3 some nurses expressed that documentation
was streamlined and efficient since the IT department had
updated the EHRs to be more compact. Nonetheless,documenting rare events caused nurses stress and confusion.
For instance, blood administration involved scanning multiple
barcodes in a strange pattern and emergency documentation
had complicated screen layouts.

E3: Unit-Specific Teamwork
Since all nurses experienced glitches with EHRs, they relied on
nursing unit collaboration for assistance. Collaboration impacted
patient safety because nurses appreciated the ability to view all
records when administering medicine to other nurses’ patients.
Teamwork was also associated with improved nurses’satisfaction. Due to strong teamwork, nurses relied on one
another more than IT staff for resolving system concerns.

E4: Interdisciplinary Teamwork
E4 themes concerned communication between departments anddisciplines. Interprofessional notes helped nurses understandthe care plan promoting integrated and better care. Nurses
reviewed patient transfer information before arrival.
Unexpectedly, some departments stopped telephone handoffs,
leading to potential missed information (ie, last pain
medication). Nurses identified unequal standards between
departments, such as not scanning all medications or omitting
parts of admission documentation. Documentation standards
varied and some prescribers did not enter orders immediately
after patient assessment. Unequal standards existed in thecontext of shifting responsibilities, such as doctors asking nurses
to input their orders. This factor frustrated nurses, and they
proposed standardized documentation classes and policies toimprove interprofessional communication.

E5: Quality of Care
E5 themes related to quality of care and nurse satisfaction.
Although BCMA reduced some medication errors, the potential
for error remained because BCMA did not verify multi-dose
medication containers (like insulin) and prescribers could still
input orders incorrectly. Additional potential for errors duringphysical assessment documentation could occur due to therepetitive nature of electronic documentation (mouse clicking),
leading to distraction and loss of attention. Patient-nurse
interactions were also altered because nurses had to position
their backs to patients to document on WOWs. In addition,occasionally WOWs logged nurses off or malfunctioned, leading
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to pain medication delays that negatively impacted care. During
R1 and R2, nurses were so frustrated with learning the systemthat they did not appreciate potential improvements in patientcare quality. However, by R3, after nurses adapted to EHRs,
they frequently mentioned better quality of patient care throughaccess to patient history, notes from all disciplines,
task/documentation reminders, and improved patient safety.
Perceptions of care quality improved in R3 compared to R1 andR2.
When the EHR system was first implemented, some nurses felt
scared or intimidated, although eventually it met expectations
or appeared that it would in the future. The most common
expectation was reduced documentation that would allow for
more time with patients, which did not happen, leading todisappointment. Nurses’ dissatisfaction and satisfaction werementioned with similar frequencies in R1 and R3, although in
R2 nurses were more dissatisfied than satisfied. The greatest
sources of nurse dissatisfaction were equipment, system
functionalities, inefficient documentation, and lengthy logins.
Conversely, nurses were satisfied with BCMA error reduction,
workflow simplification, patient protection, better care, anddocumentation thoroughness and reminders. By R3, after nurses
adapted, some nurses expressed that the EHR system offered
more time for higher-quality patient care.

Adaptation
Adaptation affected nurses’ acclimatization to new technology
over time. Nurses discussed self-learning through personal
motivation, practice, and long-term use. Self-learning occurred
through the EHR playground, where nurses could explore the
EHR layout. However, training was a major concern withrushed, fast, and overwhelming classes that were provided too
far in advance of implementation. Nurses commented thattraining classes did not reflect nurses’ workflow; they only
showed system design and navigation.

Organizational Factors
Organizational factors, such as policies, requirements, anddecisions made by leadership, were frequently mentioned withnurses’ dissatisfaction. Clinicians expected leaders to explain
rationale for HIT decisions that would impact clinical practice.
For example, nurses were not aware of the rationale for policies
not allowing a copy/paste function, or real-time documentation
which expected nurses to chart assessments immediately aftercare. Nurses expected hospital leadership to be more aware of
bedside nursing workflow and resolve issues quickly. Leadership
added requirements or responsibilities but did not retire
old/unnecessary requirements, which added to nursing workand complicated workflow. Nurses expected leadership to
advocate for system features to improve nursing workflow, sothat they could spend more time at the bedside.
Nurses’ suggestions for improvement grew with each roundand were often related to the system and equipment. Somesuggestions were incorporated by R3, such as an exact timestamp and wireless scanners. Nurses were thankful that nursing
management filtered information regarding important EHR
updates that affected nursing work. Nurses valued leadership’s
feedback on their performance regarding percent of scanned
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medications, and advised leadership to be patient, remain
supportive, provide resources, and answer questions.

Visualization of Theme and Subtheme
Interrelationships
We used Gephi to create a network (relationship) graph ofthemes for each round. Each quote contained one to four themes,
while the edges/lines revealed theme cooccurrence within thesame quote (Figure 1). Larger size nodes (bubbles) illustrate
more frequent themes; thicker lines illustrate stronger
relationships/cooccurrence. The numbers within nodes are alabeling mechanism, and do not represent the frequency of thequotes. All graphs used the same scale to facilitate thematiccomparisons between rounds. Themes are organized by color,
with E1 as green, E2 as blue, E3 as red, E4 as yellow, E5 as
purple, adaptation as orange, and organizational factors as black.
Nurses’ dissatisfaction was related to equipment anddocumentation. (#1): Equipment was a great concern in R2 andR3 and was strongly associated with (#34): Nurses’
dissatisfaction in R3, as evidenced by the thick interrelationshipline. (#9): Documentation inefficient and (#11): Documentation
not streamlined decreased with each round, especially in R3,
and they were associated with (#34): Nurses’ dissatisfaction.
(#35): Nurses’ expectations of EHR strongly reflected their(#34): Dissatisfaction in R2.

Zadvinskis et al
in R2. (#25): Communication across disciplines wasincreasingly connected to (#30): Better care and (#36): Nurses’satisfaction. (#36): Nurses’ satisfaction was consistently
concurrent with (#31): Error reduction. As nurses began toadapt to HIT, the (#16): Impact on workflow decreased by R3.
The longitudinal approach led to discovery of two additional
themes: adaptation and organizational factors. (#51): Users
adapt became more prominent in later rounds compared toearlier rounds. (#53): Policies were strongly connected to (#34):
Nurses’ dissatisfaction in all rounds.
Due to the research approach, nearly all quotes could be related
to (#34): Nurses’ dissatisfaction or, conversely, (#36): Nurses’satisfaction. Aside from these themes, (#1): Equipment and(#16): Impact on workflow were most frequent across all threerounds. In R1, the most common themes were (#16): Impact
on workflow and (#37): Patient experience/satisfaction. In R2,
the most common themes were (#1): Equipment, (#16): Impact
on workflow, and #(24): Nursing unit collaboration. In R3, (#1):
Equipment remained as the top theme, followed by (#37):
Patient experience/satisfaction. Themes grew and changed ateach time point and were interconnected differently based on
the nurses’ main concerns and satisfactions at different time
points. Visually, the R3 graph was the most balanced as nurses’
perceptions seemed to be equally scattered across all themes
compared to R1 and R2.

There were trends in collaboration, communication, quality ofcare, and workflow. (#24): Nursing collaboration was greatest
Figure 1. Visualization of theme and subtheme interrelationships.

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Discussion
Overview
This study explored the trajectory of change through aqualitative analysis of nurses’ experiences after EHR and BCMA
implementation at three time points: 3, 9, and 18 months. We
used the socio-technical model [8] to guide our discussion. Two
dimensions of the socio-technical model are not addressed(“external rules, regulations, and pressures” and “systemmeasurement and monitoring”) because nurses did not express
opinions related to these dimensions.

Hardware and Software Computing Infrastructure
Nurses shared opinions regarding HIT equipment. Workstationpreferences varied: some nurses liked working with portableworkstations so they could store medications in locked drawers,
while other nurses desired fixed workstations in patient rooms
or portable tablets. Mobile devices may promote nurses’ ability
to document at the bedside and point-of-care [26]. Nurses
appreciated equipment that improved functionality, such as
fingerprint login scanners and wireless input devices (scanners).

Clinical Content
Nurses offered multiple system suggestions: they wanted
illuminated new and abnormal laboratory results, parameters
for holding medication (eg, blood pressure), andunacknowledged orders to be highlighted in red. Nurses
suggested system recognition and display of insidious abnormal
trends, such as increasing white blood cell counts or decreasing
hemoglobin. Physical assessment customization, such as
removal of irrelevant fields or adding fields/drop-down boxes,
would improve nurses’ documentation. EHR navigation could
be improved with a help sheet or search tab with a glossary or
key words. A patient calendar to track scheduled tests would
help prepare patients and improve workflow, communication,and possibly patient satisfaction.

Human-Computer Interface
Clinician involvement in HIT design is a potential strategy forsuccessful adaptation [27]. Nurses expressed frustration thatclinician input was not adequately integrated into the system.
Communication regarding end-user requests facilitates success[28]. Previous research indicates that when nurses were involved
in refining the usability of an existing EHR, end-user satisfaction
increased and nurse-sensitive quality indicators improved,
including fewer catheter-associated urinary tract infections,improved documentation of the presence of pressure ulcers, andfewer restraints [29]. Nurses offered suggestions for workflow
redesign and EHR modifications via email request, discussion
with the Nurse Manager, and during IT meetings.

People (Training and Peer Support)
Training and competency are sociotechnical factors that affect
HIT adaptation [30]. Nurses may improve their competency
and technology proficiency through practice. In this study, EHR
training began months prior to implementation with nurses
attending four one-hour educational training sessions. During
training and early implementation, nurses were encouraged topractice documentation in the EHR playground. Although this
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sample of nurses rated their proficiency with technology ascompetent (4 out of 5), nurses working in other settings may
feel less proficient or less IT-literate. Low IT literacy is a known
barrier to EHR implementation [31,32], and it may be helpful
to improve clinicians’ computer literacy prior to implementation.
Training programs may be customized to different nurses’
learning needs to promote adaptation. Nurses viewed superusers as instrumental for adapting to HIT. This finding is similar
to another study in which clinicians viewed super users as
supportive, familiar, and knowledgeable regarding day-to-day
work [33], but different from another study that showed having
super users did not contribute to meaningful HIT use [34].
Effective super users may be characterized by being proactive,
providing comprehensive explanations, using positive framing,and freely sharing information [33].

Workflow and Communication
In the socio-technical model for studying HIT, the clinicalworkflow involved with operating HIT systems must be
consistent with internal policies and procedures [8]. Lack ofcongruency between policy and practice was a source of nursing
frustration in this study. For example, prior to EHR
implementation, nurses working 12 hours would reassesspatients and write, “unchanged from previous assessment” inthe paper chart, which was supported by policy. After EHR
implementation, nurses had to redocument a complete physicalassessment every 8 hours, because IT developers set the systemfor eight-hour tours of duty for nurses, which was inconsistent
with practice. Therefore, numerous nurses expressed the desire
for a copy and paste function, but this can inadvertently lead toclinical harm [35]. Organizations interested in using a copy andpaste function may benefit from adopting best practices fromthe Partnership for Health IT Patient Safety [35]. Eventually,
the physical documentation assessment policy in the EHR was
modified to reflect nursing workflow.

Internal Organizational Policies, Procedures, andCultureNurses voiced that a reduced patient load (better nurse staffing)
was very helpful for adapting to the new system. During thefirst day of EHR implementation, medical-surgical nurses caredfor only one or two patients. By R3, nurses returned to caring
for four to five patients, but some nurses continued to struggle
with completing documentation requirements. In the future,augmented clinical HIT (where nurse staffing decisions are
based on patient volume, acuity levels, etc [36]) may become
more commonplace.
A 2013 integrative review found that strong leadership ensuresthat the team works toward successful HIT implementation [37].
Modification of hospital policies and environment may benecessary, especially when HIT changes are directed by a vendor[38]. Leaders are expected to communicate a clear vision and
expectations related to HIT for clinicians [39]. Users’
expectations are a considerable psychological factor that affects
EHR adoption [40]. Leadership may need to develop
expectations for staff accountabilities [39] to maintain HIT ingood working order (eg, plug in workstations when not in use,report broken equipment).

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Timing of Adaptation to HIT

better productivity due to increased charges, improved work
relative value units, and less time writing orders [45], nurses
may not experience HIT value because there is no direct linkin billing systems between individual nurses and patients [47].
Nurses’ productivity (hours of nursing care per patient day) isbuilt into hospital room and board charges, so HIT may not beable to capture the work value of individual users like nurses[47]. Conversely, nurses’ experience with HIT may be similar
to other clinicians’ experience. A qualitative study that aimed
to understand physicians’ and nurses’ experience with EHRs
found no major perceived differences based on profession [48].
A commonality among all professions appears to be the needfor communication when implementing new HIT [46].

Adaptation to HIT over time may be explained in part by the
Gartner Hype Cycle [41], which describes maturity and adoptionof new technologies and applications. The Hype Cycle includes
five phases: (1) innovation trigger, (2) peak of inflated
expectations, (3) trough of disillusionment, (4) slope ofenlightenment, and (5) plateau of productivity. The peak ofnurses’ dissatisfaction occurred in R2, approximately ninemonths after HIT implementation. This finding may be due tonurses’ high expectations not being met at that time,corresponding with the Hype Cycle “trough of disillusionment.”
Nurses began to grow impatient regarding supposed EHR
benefits. Previous research indicates that nurses’ expectationsfor HIT include availability, speed, decreased work load, andease of use [42]. In this study, nurses were able to provide
suggestions and feedback to align HIT with their expectations
regarding nursing workflow, training, and technology. However,
the effectiveness of such communication is unclear. Researchalso indicates that nurses want to improve HIT throughsuggestions, but low communication levels and lack of feedback
are barriers to enhancing system performance [43]. Variables
related to nurses’ acceptance of EHRs include
training/education, facilitating conditions, social influences,observability, and job relevance [44].

Comparison of Nurses’ Experience With HIT With
Other Clinicians
Previous research indicates that clinician satisfaction with HIT
is mixed, which may be related to clinical documentation
practice, workload, and productivity [45]. Physicians havereported dissatisfaction with template-based HIT documentation[45], possibly due to their high autonomy needs to prioritize
work tasks [46]. In the current study, nurses also expressed
dissatisfaction with template-based physical assessment because
documentation was not streamlined. Nurses may be moreaccustomed to template-based documentation than physicians
due to the use of standardized nursing care plans and clinicalcare pathways in the profession. However, if the HIT template
does not match nurses’ mental model for accomplishing tasks,
they will be dissatisfied.
Physicians and nurses may differ in perceptions of productivity
after HIT implementation. While physicians may experience

Study Limitations
Generalizability of these findings is limited due to sampling
nurses from one unit within an academic medical center.
Self-selection bias may have occurred from voluntary
participation. The timing of interview rounds was based uponinterviewer availability rather than change theory. Although we
conducted 30 interviews, some nurses participated over multiple
time periods and the group comprised a small sample size
(n=19). Despite the small sample size, recurrence of similar
themes across multiple individuals established information
saturation and data quality.

Conclusion
A longitudinal qualitative approach for studying HIT adaptation
facilitated understanding of thematic relationships over time.
Although thematic interconnectivity differed due to nurses’
concerns and satisfaction at different time points, some trends
were noted. Nurses appeared the most dissatisfied in R2, butmany sources of dissatisfaction may be rectified, such as new
equipment, refined policies, and improved systems to focus on
patient safety. Approximately 18 months after HIT
implementation, nurses’ perceptions appeared more balanced,
as indicated by more consistent thematic frequencies and weakercooccurrences in the Gephi chart. Balanced thematic distribution
and interconnectivity within Gephi charts may be a visualindicator of HIT adaptation progress. Future research isnecessary to confirm if researchers can replicate these findings
in other samples.

Acknowledgments
The authors would like to thank the computer science student Xiaonan Ji for providing the Gephi graph. We thank Esther Chipps,
Laura Droll, and Kelly Torrence at The Ohio State University Wexner Medical Center for coordinating the recruitment, and allparticipating nurses for their time and effort.

Conflicts of Interest
None declared.

Multimedia Appendix 1
Semistructured interview guide.
[PDF File (Adobe PDF File), 328KB-Multimedia Appendix 1]

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Zadvinskis et alMultimedia Appendix 2
Theme codebook and definitions.
[PDF File (Adobe PDF File), 38KB-Multimedia Appendix 2]

Multimedia Appendix 3
Themes with quote examples.
[PDF File (Adobe PDF File), 394KB-Multimedia Appendix 3]

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Abbreviations
BCMA: bar code medication administration
E: theme
EHR: electronic health record
HIT: health information technology
ICU: intensive care unit
IT: information technology
R: round (of data collection)
WOW: workstation on wheels

Edited by G Eysenbach; submitted 11.08.17; peer-reviewed by D Hanauer, A Khan; comments to author 30.11.17; revised version
received 08.02.18; accepted 07.04.18; published 26.06.18
Please cite as:
Zadvinskis IM, Garvey Smith J, Yen PY
Nurses’ Experience With Health Information Technology: Longitudinal Qualitative StudyJMIR Med Inform 2018;6(2):e38
URL: http://medinform.jmir.org/2018/2/e38/
doi: 10.2196/medinform.8734
PMID: 29945862©Inga M Zadvinskis, Jessica Garvey Smith, Po-Yin Yen. Originally published in JMIR Medical Informatics(http://medinform.jmir.org), 26.06.2018. This is an open-access article distributed under the terms of the Creative Commons
Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction
in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete
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