Proceedings of the 44th Hawaii International Conference on System Sciences - 2011
Physician Interaction with Electronic Health Records: The Influences on
Digital Natives and Digital Immigrants
Cherie Noteboom
Dakota State University
Cherie.Noteboom@dsu.edu
Abstract
The integration of EHR (Electronic Health
Records)
in
IT
infrastructures
supporting
organizations enable improved access to and
recording of patient data, enhanced ability to make
better and more-timely decisions, and improved quality
and reduced errors. Despite these benefits, there are
mixed results as to the use of EHR. The literature
suggests that the reasons for the limited use relate to
policy, financial and usability considerations, but it
does not provide an understanding of reasons for
physicians’ limited interaction and adaptation of EHR.
Following an analysis of qualitative data, collected
in a case study at a hospital using interviews, this
research explains how physicians interact with EHR.
The key contribution of this research is explaining how
physicians interact with EHR in terms of concepts that
are grounded in the real world experiences of
physicians.
1. Introduction
Research has shown that the healthcare
industry is plagued by rapidly increasing costs, poor
quality of service, lack of integration of patient care,
and lack of information access to EHR
[3,5,24,35,41,51].: “Even though U.S. medical care is
the world’s most costly, its outcomes are mediocre
compared with other industrialized nations” [9, p.2].
Medical errors are a major problem that decreases the
quality and increases the costs of the U.S. healthcare
system. Medical errors result in 98,000 deaths a year
and many more injuries, and as a result, patient safety
has become a top priority in U.S. healthcare [34].
The use of information technology (IT) has
the potential to help healthcare organizations improve
quality of service while reducing costs. The California
HealthCare Foundation [26] estimated that California
could save more than $3.2 billion a year and reduce the
number of medication-related injuries by 250,000 a
year if California healthcare clinics used electronic
health records (EHR) to handle medication ordering
and diagnostic tests. The Institute of Medicine (IOM,
2001) reported that the U.S. healthcare system is
“fundamentally broken” and called on the federal
Sajda Qureshi
University of Nebraska-Omaha
squreshi@mail.unomaha.edu
government to make a major investment in information
technology in order to achieve the changes, such as the
“commitment to technology to manage the knowledge
bases and process of care” [25, p. 178], needed to
repair the broken healthcare system.
During the past 25 years, many medical
records have been converted from a handwritten record
format to an EHR format, and studies
[3,45,58,60,12,38]
have indicated that EHR is
complicated and requires a serious, sustained
commitment to human resources, process reengineering, technology, and funding. The healthcare
system has been slow to take advantage of EHR and
realize the benefits of computerization (McDonald,
1997): that is, improved access to and records of
patient data, enhanced ability to make better and moretimely decisions, and improved quality and reduced
errors.
It is commonly assumed that U.S. healthcare
services organizations are approximately 10 years
behind the information systems (IS) curve when
compared to organizations from other industries of
comparable size and complexity [40]. According to
IOM (2001), “healthcare delivery has been relatively
untouched by the revolution in information technology
that has been transforming nearly every other aspect of
society” (p. 15). This inability to take full advantage of
computerization is unfortunate because EHR has the
potential to improve patient care and patient safety. In
2007, however, the American Hospital Association
reported that only 11% of hospitals had fully
implemented EHR, and these hospitals were likely to
be large, urban, and/or teaching hospitals. Vishwanath
& Scamurra reported less than 10% of physicians in
different practices and settings in the US use EHR,
whereas more than half of the physicians in countries
like Sweden, Netherlands and Australia have adopted
EHR [64]. Blumenthal (2009) cites only 1.5% of US
hospitals have comprehensive EHR systems. A similar
2009 study by the American Hospital Association
shows less than 2% of hospitals use comprehensive
EHR and about 8% use a basic EHR in at least one
care unit. These findings indicate the adoption of EHR
continues to be low in US hospitals [38].
1530-1605/11 $26.00 © 2011 IEEE
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Proceedings of the 44th Hawaii International Conference on System Sciences - 2011
The research question investigated in this
study is how is physician interaction with EHR
affected by their experience with information
technology? This question is investigated through a
qualitative study that examines how physicians interact
with EHR. Open coding was used to analyze the data
and to develop concepts explaining these interactions
in terms of the events, actions and communications
carried out among the physician stakeholders.
Eisenhardt’s case study approach and open coding
analysis grounded the results in the real world
situation. As a methodological contribution, the case
study of a hospital with Eisenhardt’s case study
approach, propositions and open coding for data
analysis is an innovative combination of research
methods because it enables concepts and relationships
to be arrived at and then assessed using the enfolding
literature step from Eisenhardt and theoretical
sensitivity from open coding. This combination of
approaches strengthened the contributions of this study
by enabling the results to be generalized to models and
relationships. The research provided theoretical
contributions by presenting the Processes and
Infrastructure model dealing with digital immigrants
and digital natives. In addition, implications of this
study for future research and practice are discussed.
2. Theoretical background
Information technology has been used by
many organizations for the past 40 years.
Manufacturing, banking, finance, and other industries
have capitalized on new technology and experienced
increased quality, lower costs, and a competitive
advantage. There are many examples of IT’s benefits:
(a) improved customer relationship management and
knowledge management, (b) cost reductions, and (c)
improved quality. IT, however, has produced less
significant results in the healthcare system. It is
routinely possible to access bank accounts
electronically from anywhere in the world, but it is
often impossible to access medical information from an
office next door. IOM (2001) claimed that the
healthcare system needs to join the IT revolution, and
improved information systems may be a critical factor
for improving the healthcare system because of the
pervasive need to access, record, and share information
in order to provide high-quality medical care [59].
EHR is a journey that has just started [43].
Knowledge and learning play important roles
in the use of IT, and researchers have developed the
diffusion, adoption, and acceptance theories to explain
how people adopt, accept, and use complex
organizational technologies. Attewell (1992) defined
complex organizational technologies as “technologies
that, when first introduced, impose a substantial burden
on would-be users in terms of the knowledge needed to
use these technologies effectively” [19]. From an
organizational learning perspective, Attewell defined
technology assimilation as “a process of organizational
learning in which individuals and an organization as a
whole acquire the knowledge and skills necessary to
effectively apply the technology” [19,p. 1345]. The
burden of learning creates a knowledge barrier that
inhibits the diffusion of IT. In these cases, the use of IT
can be inhibited as much by the ability to adopt IT
systems as the desire to adopt these systems.
Consequently, IT penetration into the market from
which the stakeholders could benefit is seriously
affected and the benefit undermined.
According to Prensky (2001), digital natives
are people who have “spent their entire lives
surrounded by and using computers, video games,
digital music players, video cams, cell phones and all
the other toys and tools of the digital age” (p. 1).
Digital natives are used to receiving information
quickly, like to parallel process and multitask, prefer
their graphics before their text, prefer random access,
perform best when networked, and thrive on instant
gratification and frequent rewards. Digital immigrants
tend to adopt and use technology, but they retain their
digital immigrant accent, which can be seen in such
things as turning to the Internet for information second
rather than first, reading the manual for computer use
rather than assuming the program will teach them how
to use it, or printing their email. The differences
between digital natives and digital immigrant are
frequently a focus of training and education efforts,
and these two groups of IT users tend to favor learning
Figure 1Theoretical Lens
in different environments and learn effectively
from different methods [46].
Figure 1, Theoretical Lens, depicts the
theories and influences providing the lens for this
research effort. The healthcare system is a complex
organization characterized by independent professional
(physicians and healthcare providers) knowledge
workers working as independent professionals. The
ability for these knowledge workers to access data
effectively and efficiently would improve the quality of
work processes and patient care. However, EHR,
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Proceedings of the 44th Hawaii International Conference on System Sciences - 2011
which enable people to work effectively and efficiently
access data, have been underused by U.S healthcare
professionals such as physicians. In order to improve
the use of IT in the U.S. healthcare system, it is
necessary to understand what healthcare professionals,
especially physicians, think about their adaptation of
EHR; therefore, this research was guided by the
research question “How are physicians’ interaction
with EHR affected by their experience with IT?”. It
examined physician interaction with EHR and the
influence of digital natives and digital immigrants.
2.1 Physician adaptation
The EHR has the potential to provide
continuity of service and could be a tool supporting
collaboration as physicians increasingly work with
each other and other service providers. Previous
technology research [47,48,49,50] has investigated
collaboration effects. The Model of E-Collaboration
Effects provides insight to inform the Physician/EHR
research in the areas of collaboration, coordination,
communication and adaptation. In addition, the
adaptation insights at the work, social and technology
levels inform this research.
The model of e-collaboration effects describes
people’s interaction with collaborative technologies.
According to the model, when people use technology
to work with each other, they go through technological,
work, and social processes in order to adapt to new
work environments [49,50]. The adaptation of new
technology in collaborative relationships occurs when
members of a group learn how new technology affects
their work relationships and the work environment
[48,49,50]. Successful collaboration requires social
adaptation by team members, who must learn to
conform to new knowledge, rules, and patterns of
interaction.
Work adaptation occurs when people adapt
the technology to their own ways of working. The
work-adaptation process takes place when groups are
involved in changing organizational norms and values
while using collaborative technology. IT affects the
work process itself and the way in which work is
carried out [49,50].
Technology adaptation occurs when people
learn how to use technological tools to achieve their
goals. The more flexible the technology, the easier it is
for people to use the technology to meet their needs.
Figure 2: Physician Adaptation Model
Physicians using technology go through technological,
work and social processes to adapt to new work
environments. IT affects work relationships and
environments.
3. Research methodology
This study uses a qualitative research method
to examine physician interaction with EHR. The
guiding research question is: “How are physicians’
interaction with EHR affected by their experience with
IT?” It uses Eisenhardt’s case study approach,
interviews as the primary data collection and open
coding for data analysis. This is an innovative
combination of research methods because it enables
concepts and relationships to be arrived at and then
assessed using the enfolding literature from Eisenhardt
and theoretical sensitivity from open coding.
Theoretical sensitivity allows the researcher to have
insight and to give meaning to the events and
happenings in the data. It allows being able to see
beneath the obvious to discover the new. The
Eisenhardt method was chosen as it: 1) Generates
relationships or theory with constant comparison
literature; 2) Emergent theory is likely to be testable
with constructs that can be readily measured; 3) High
likelihood of valid relationships, models or theory
because the theory building process is tied to data and
other evidence.
The investigation of physician interaction is
complex, vague and context specific. We do not know
why certain physicians use EHR and others choose not
to use EHR. The qualitative methods used in this
research can yield data from which process
relationships and models and richer explanations about
how and why processes and outcomes occur can be
developed [39,61,32]. Qualitative methods provide
researchers with the ability to discover relationships
from data that is systematically gathered and analyzed
[28].
Interpretivism is a type of qualitative research
that allows the researcher to ‘interpret’ or unearth the
meanings discovered in the research environment. This
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Proceedings of the 44th Hawaii International Conference on System Sciences - 2011
research is interpretivist research as defined by Klein
& Myers as it assumes that a physician’s knowledge of
reality is gained through social constructions such a
language, consciousness, shared meanings, documents,
tools, and other artifacts. Interpretive methods of
research in IS are “aimed at producing an
understanding of the context of the information system,
and the process whereby the information system
influences and is influenced by the context” [62, p.
389]. The study will use an interpretivism approach to
produce an understanding of physician interaction with
EHR.
The researcher investigates the way
physicians construe, conceptualize, and understand
events, concepts, and categories related to EHR
interaction. This allows the researcher to develop an
understanding of the physician perspective of EHR
interaction. It is necessary to utilize a rich, detailed
understanding of the physician’s feelings, thoughts and
meanings associated with the EHR. This research is
necessary to investigate the real world constraints, such
as limited ability, time constraints, environmental or
organizational limits, or unconscious habits, which
may impact the physician use or nonuse. In order to
make discoveries of this type, the researcher must have
rich detail and understanding of the physician
perspective.
Physicians have demonstrated great variation
in EHR
use
depending on specialization
[22,27,7,13,14,30,42,13,14] and type of practice
ownership [13,14]. Physicians have the ability to
choose to directly utilize the EHR or to avoid use of
the EHR. In addition, the physician has the ability to
impact others in the organization by the nature of their
position. Therefore, they were selected as the target
interview audience. The physician selection was based
on the literature review and was designed to emphasize
variety within the sample.
Open coding is used to analyze the data and
develop concepts as they relate to physician interaction
with EHR. The qualitative method and open coding
analysis enables discovery of the relationships in the
real world situation. This is an innovative combination
of research methods because it enables concepts and
relationships to be arrived at and then assessed using
the enfolding literature from Eisenhardt and theoretical
sensitivity from open coding. Theoretical sensitivity
allows the researcher to have insight into and to give
meaning to the events and happenings in data.
“Insights do not just occur haphazardly; rather, they
happen to prepared minds during interplay with the
data [57, p. 47]”. Eisenhardt’s enfolding the literature
step complements the development of sensitivity. “An
essential feature of theory building is the comparison
of the emergent concepts, theory, or hypotheses with
the extant literature [17, p. 544]”. This research utilized
theoretical sensitivity and enfolding the literature to
develop the lens for the effort.
In
order
to
investigate
physicians’
interactions, this research employs a case study with
interviews to elicit perceptions, meanings, feelings,
reasons and comments. Observation and document
gathering will be secondary methods of data collection.
Open coding is used for creation of a relationships,
models or theory that is “inductively derived from the
study of the phenomenon it represents. That is, it is
discovered, developed and provisionally verified
through systematic data collection and analysis of data
pertaining to that phenomenon [56, p.23]”. The study
used the Eisenhardt case study approach with the
enfolding literature step to strengthen the results.
Case studies have been used to provide
description [31], generate and test theory [23,44]. The
goal of this research is to gain a rich description of
physician’s interactions with EHR, analyze the data
and generate relationships or a theory. This study used
the seven step Eisenhardt method for building theories
from case study research. It is well matched to the open
coding analysis selected as the case study process is
“highly iterative and tightly linked to the data [17, p.
532].” Participants in the study are physicians selected
from Research Medical Center.
Research Design
The research design is interpretive and
qualitative. It ensures the data is grounded in real
world experience and at the same time allows
discovery of new concepts and relationships.
Qualitative procedures are used to provide a means for
accessing unquantifiable facts about the actual
physicians the researcher observes, talks to and
interviews. As a result, the qualitative techniques
enable the researcher to share in the understandings
and perceptions of physicians. The qualitative method
developed for this research is appropriate for
discovering reasons that describe physicians’
interactions with EHR.
There are several reasons why the qualitative
methods used in this research enable an examination of
the factors that affect physician interaction with EHR:
(a) There is a need to collect context-specific measures
of job characteristics rather than exclusively relying on
context-independent instruments; (b) IS research needs
to collect measures, not just the concrete outputs of the
system, that show how a system impacts the processes
inside an organization; and (c) it is dangerous to overrely on unidirectional causality relationships between
dependent and independent variables because richer
insights may be gained by focusing on the complexity
of the interrelationships between dependent and
independent variables [28]. The qualitative method
used in this study provides information that reveals
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Proceedings of the 44th Hawaii International Conference on System Sciences - 2011
what physicians think about the quality, meaning,
perception and context of EHR interactions.
The examination of the relationship between
IT and organizations and people broadens the field of
IT; however, this type of research produces added
complexity, greater imprecision, the possibility of
different interpretations of the same phenomena, and
the need to take these issues into account when
considering an appropriate research approach [23]. The
use of a case study method to discover relationships or
to generate theory minimizes these risks. The
Eisenhardt method was chosen as it: 1) Generates
relationships or theory with constant comparison
literature; 2) Emergent theory is likely to be testable
with constructs that can be readily measured; 3) High
likelihood of valid relationships or theory because the
theory building process is tied to data and other
evidence.
The qualitative study uses the Eisenhardt
research method to produce in-depth descriptions of
reasons for physician interaction with EHR. The
research strategy focuses on understanding the
dynamics present in a setting. The study follows
Eisenhardt’s (1989) seven-step approach to research:
electronic transcripts. This data was collected over a
period of six months from October 2009 to March
2010. While analyzing the transcripts of the interviews,
“labels of meaning” were identified and placed next to
the relevant occurrence. Occurrences were events,
happenings, actions, feelings, perspectives, actions and
interactions. Categorization of the coding was done in
two phases. First, the data obtained from the interviews
was coded into broad categories. The interview data
was analyzed using Strauss & Corbin’s (1998) open
coding method. Open coding was used to
conceptualize raw data by naming and categorizing the
phenomena through close examination of the data.
During open coding, data was broken down into
discrete parts, closely examined and compared for
Table 1 Physician Description
Figure 3: Research Methodology
This approach is consistent with generally
accepted approaches to develop relationships or theory
from cases (Walsham, 1993; Yin, 1984; Eisenhardt,
1989; Baskerville & Myers, 2004). Eisenhardt’s
method complements the open coding approach by
providing the ‘enfolding literature’ step. The
comparison of the emergent concepts, categories, and
theories with conflicting concepts, categories, and
theories discussed in the literature produces internal
validity, and a comparison of emerging concepts,
categories, and theories to similar concepts, categories,
and theories discussed in the literature produces
generalizability [17]. This process continually builds
the researcher’s theoretical sensitivity.
4. Results & analysis
The data for this analysis was comprised of
seven physician interviews and represented 66 pages of
similarities and differences. The coding process
yielded 833 coded quotes. The data representing
events, happenings, actions and interactions that were
found to be conceptually similar in nature or related in
meaning were grouped under abstract concepts that
best represent the phenomenon. According to Strauss
and Corbin (1998), although events or happenings
might be discrete elements, the fact that they share
common characteristics or related meanings enables
them to be grouped. Based on their ability to explain
what is going on, certain concepts were grouped under
more abstract higher order concepts which Strauss and
Corbin (1998) term category. Categories have analytic
power because they can have the potential to explain
why physicians may or may not use the technology and
potentially
predict
the
effects
of
certain
implementations on physicians’ use. The 833 labels
were categorized to compare codes across the
interviews. The categories were derived by tabulating
the number of occurrences of related concepts.
Reliability of these groupings was achieved
through theoretical sensitivity, iterative coding and
theoretical sampling. Strauss and Corbin (1998)
suggest that theoretical sensitivity is required to enable
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Proceedings of the 44th Hawaii International Conference on System Sciences - 2011
the researcher to interpret and define data and thus
develop relationships, models or theories that are
grounded, conceptually dense and well integrated.
Sources of theoretical sensitivity are the literature,
professional and personal experiences. Additional
reliability was achieved through the iterative use of
open and axial coding to bring out the concepts and
discover any causal relationships or patterns in the
data. Strauss and Corbin (1998, p.98) state that “though
open and axial coding are distinct procedures, when the
researcher is actually engaged in the analysis he or she
alternates between the two modes”. Along with the
groupings of abstract concepts (open coding) and
identification of causal conditions (axial coding), that
lead to the occurrence or development of a
phenomenon, additional coding was carried out
iteratively using theoretical sampling.
Further reliability was achieved through
theoretical sampling, which is the sampling of data on
the basis of concepts that have proven theoretical
relevance to evolving relationships, models or theories.
The form of open sampling used was open sampling
which is associated with open coding. Open sampling
was used to select additional interview data. The ‘slices
of data’ (Urquhart 2009) of all kinds are selected by a
process of theoretical sampling, where the researcher
decides on analytical grounds where to sample from
next. Glaser and Straus (1967, p. 3) state that the
researcher does not approach reality as a tabula rasa
but must have a perspective that will help him or her
abstract significant categories from the data based on
the constructs identified in the literature.
This data analysis produced technological,
work and social adaptation categories. The numbers of
occurrences are shown in the figure below:
Figure 4: Physician Adaptation Occurrences
A further analysis of adaptation at each of the
three levels revealed the level the physicians are able to
use EHR to support their work practices, level of
technological
comfort
and
social
interactions/connections.
Category
Description
Work
The physician perspective
of EHR usage on physician
work.
Subcategories:
Positive Work Impact,
Negative Work Impact,
Productivity.
The Physician perspective
on implications of IT
Context on EHR usage.
Sub-categories:
System
Development, Hardware &
Configuration,
Training,
Documentation,
Desire
Integrated
Systems,
Downtime Concern.
The Physician perspective
on implications of Social
Context on EHR usage.
Technologic
al
Social
Total
Occu
rrenc
es
197
75
18
285
Technological adaptation amongst physicians
appears to be influenced by their level of comfort and
experience with technology. While older physicians are
opinion leaders with respect to clinical decisions,
younger physicians are frequently leaders in using
information technology [1]. This is supported by this
research as indicated by the data, such as:
rather than sitting down and thinking “could
this be something else, what am I missing, what else
could it be?” and we don’t have time to that anymore,
you don’t have time to use our clinical skills to take
care of our patient. Now, with that being said, we have
a whole generation of physicians coming up that are
not as good at their clinical skills. I am not as good at
my clinical skills as my elder colleagues. They can
walk into a room and diagnose something because they
were good clinicians.
Now, with that being said, we have a whole generation
of physicians coming up that are not as good at their
clinical skills. I am not as good at my clinical skills as
my elder colleagues. They can walk into a room and
diagnose something because they were good clinicians.
Now we look at a patient and say what do they have
and then we look at the data and make the data fit what
we want it to. Does the data fit what it could possibly
be rather than I think it’s this, what do I need datawise to confer? And so I think with EHR we are doing
a lot of it, we are spending more time trying to find out
what it could be with data rather than talking to a
patient.
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Proceedings of the 44th Hawaii International Conference on System Sciences - 2011
I think that people that are coming out of training in
the last 5 years would have similar thought processes
to me on use and benefits of technology. I think that
every 10 years you are going to see a generation of
different people that even it’s just more of who they are
and what they do.
I think that the exact opposite…the people that have
been here for 20 years and have had a little tough time
adapting to, not just new technology, but how fast new
technology is updated. The change process and the
changes continue to happen…it’s a logarithmic
progression. Every 5 years the change, I mean, the
change we have seen in the last 5 years is
exponentially greater than the change we saw in the 5
year period 10-15 years ago. You have to learn to use
a new phone and computer every couple of years now.
Research by Qureshi & Noteboom (2004)
discovered Digital Immigrants and Digital Natives
vary in the approach to technology adaptation and
work adaptation. The digital natives frequently
complained about the lack of features and usability of
the technology tools. This group appeared to be less
willing to adapt their work style to the toolset
provided. The Digital Immigrants tended to express
limited technical expertise and adapted their work to
the toolset provided. The Digital Immigrants had much
higher levels of work adaptation than the Digital
Natives.
According to this research, Digital Natives
had lower levels of technological adaptation than
Digital Immigrants. They tended to be less willing to
adapt to the toolset provided, had higher demands from
their toolset and frequently requested additional
features. The physicians in this study, primarily
Digital Immigrants, clearly have high levels of work
adaptation.
Work adaptation
generated
197
occurrences. The digital immigrants averaged 34
occurrences and the digital natives averaged 22
occurrences. This suggests that the physicians studied
in this research support the higher levels of work
adaptation by Digital Immigrants. Similar conclusion
was made in the research by Anderson (1997), where
he reported older physicians are opinion leaders with
respect to clinical decisions; younger physicians are
frequently leaders in using information technology. As
we move forward with the implementation of EHR,
this difference has potential to affect future success as
the Digital Natives enter the physician roles. This is
illustrated in figure 5: Digital Natives Digital
Immigrants Process & Infrastructure Model.
Figure 5 Digital Natives Digital Immigrants Process
& Infrastructure Model
In addition, the various processes and
infrastructure identified in this research case study do
not encourage adaptation. Hence, the frustration
amongst physicians and their loss in productivity
through the use of EHR exists.
“The major problem with technology is
adoption and that most systems are not designed by
people who do clinical work.”
“I am not there every day I have trouble
navigating that particular system. Plus it is not as user
friendly; it doesn’t think for you, there is too much
information, too many boxes of checkmark data that is
not appropriate for patient care.”
“And to make, and it’s going to be very hard
because we all have different brains and we all see
things differently, I am a visual person, so when I see it
on one sheet and I see all the information I need it is
very easy for me to go through that. But to go through
page after page after page after page and it’s really
only a few hours of time doesn’t work for my brain.”
The development of EHR appears to have
repeated a common development challenge. The
physician perspective of the necessary change is
reflected in a seminal Simon quote, “This is an old
weakness in engineering design, not peculiar to
computers: we are fascinated with our technical
capabilities and design sophisticated hammers which
go around looking for nails that are shaped so as to be
hammerable by them (p. 135).”
Like groupware, EHR appear to be a new
technology that is considered additional work resulting
in reduced productivity by the physicians required to
use it. At the same time, the benefits of using these
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Proceedings of the 44th Hawaii International Conference on System Sciences - 2011
technologies have been touted by administrators and
politicians.
5. Summary & conclusions
The research employed a qualitative research
design to discover reasons of physician interaction with
EHR and generate the Digital Natives Digital
immigrants Process and Infrastructure Model
explaining the categories, constructs and relationships.
A case study with open-ended interviews was used to
elicit perceptions, meanings, feelings, reasons and
comments. Open coding was used for creation of
categories, relationships and models that were
grounded in real world experience. The research was
based on the Eisenhardt approach with the enfolding
the literature step to increase theoretical sensitivity and
to strengthen the results.
The research was guided by lenses created
from theories of diffusion, model of e-collaboration
effects, technology acceptance theory, physicians as
knowledge workers, digital natives and digital
immigrants and challenges of learning barriers
associated with learning and technology. It was an
important area of study to provide insights for
discovering physician perspective on interaction with
EHR and generating and explaining the categories,
constructs and relationships related to physician
perspective of EHR. People use systems to meet their
particular work needs, or they resist them or fail to use
them. EHR can provide some major benefits in direct
support of patient care: They are touted as a vast
improvement over the paper record in reporting,
organizing and locating clinical information. They are
touted as an improvement in physicians’ decisionmaking by providing protocols, reminders and alert;
and they can be designed to coordinate and manage
patient care. Therefore, it is important to understand
the physician perspective related to EHR and to
understand the major components to be addressed to
influence physician adaptation of EHR into their work
practices and knowledge processes. This information
could help practitioners develop strategies to optimize
the interaction with EHR and the study could
contribute to the quality of care, quality of data,
effectiveness and efficiency gains and patient safety. In
addition, the results of the study could guide future
attempts to integrate EHR into the fabric of healthcare
organizations. Ultimately, it can contribute to
improved patient care and safety.
A relevant and interesting direction for future
research is expanding the focus on the influence of
digital immigrants and digital natives on technology
adaptation. As the focus of information technology
continues to support many professional domains, the
number of digital natives will continue to change the
demographics of many professional work groups.
Research to provide insight in this area would be
beneficial.
Practice needs to consider the potential
influence of digital natives and digital immigrants and
their representation in the workplace. Research has
indicated a difference in their adaptation of technology.
With the changing demographics of the workplace, this
will become a more important issue for practice. In
addition, exploring the subcategories of infrastructure
and processes provides opportunity to improve these
areas.
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