While health care organizations recognize the advantages of
electronic medical records, they often do not use them. Why not?
Physician acceptance seems to be the heart of the issue, but what
explains their willingness or unwillingness to go electronic? Two
theories address the problem: Davis's technology acceptance model
and Ajzen's theory of planned behavior. A survey of physicians
based on both theories and analyzed using multiple regression analyses
showed that both theories explain attitudes toward adoption of
electronic records, but the theory of planned behavior was more
The current push for universal health care coverage and health care
reform has highlighted health information technologies as a means of
cutting costs and improving efficiencies in the health care arena
(Moment of Truth, 2009). The electronic medical record (EMR) integrates
patient information systems so that patient demographic, financial, and
medical information can be collected, accessed, transmitted and stored
in a readily available digital format (Hough, Chen, and Lin, 2005;
Steele, Gardner, Chandra, and Dillon, 2007). EMR technology represents a
movement from paper-based care activities toward outcome-focused,
evidenced-based processes (Mangalompalli, Rama, Muthivalian, Jain, and
Parinam, 2007). This shift can be an agent for change and improvement by
eliminating confusing or illegible handwritten order documentation,
minimizing transcription errors, and fundamentally reducing clinical
mistakes. Most important, EMR technology allows physicians fast access
to appropriate patient information allowing prompt diagnosis and
treatment (Chao, Jen, Chi, and Lin, 2007). In critical situations, such
quick access saves lives (Steele, et al., 2007). As such, the electronic
medical record enables physicians to make quicker, more informed
decisions because they have all patient information at their fingertips
when they need it.
While health care organizations recognize the advantages of EMR,
adoption of the technology has been slow (Abdolrusulnia et. al, 2008).
To date, less than 10% of American hospitals have implemented electronic
medical record keeping as part of their technology strategy for health
information (Gardner, 2007). In fact, predictions concerning physician
adoption of the EMR indicate that policy makers' 2014 target for
widespread implementation is unlikely (Ford, Manachemi and Phillips
2006). Reasons for the slow deployment include expenses related to
upgrading existing paper systems, funding for additional workstations
and resources, and the challenges associated with achieving and
maintaining physician buy-in and acceptance. However, according to John
Hammergren, CIO of McKesson, "It's really not a technological
barrier. The systems are available and we can provide those
interconnections. The issue is one of adoption. Are people really ready
to do this? As long as it's easier to script it out and hand it to
a voice-activated nurse, that's what the physician will do"
(Colvin, 2007). We have based our study on this issue: physician
acceptance of the electronic medical record.
Statement of the Problem
According to Al-Gahtani (2008), researchers have often addressed
the issue of why individuals who would benefit from interactive
information systems do not use them--an especially important question
for medical organizations attempting to implement EMR systems. We posit
that factors specific to physicians and the medical profession affect
adoption. Further, we suggest that pinpointing what motivates physicians
to accept technology will enable hospitals and medical practices to
design systems and tailor implementation strategies toward factors that
motivate adoption. The objective of this research is to identify those
factors by comparing the degree to which two common theories,
Davis's technology acceptance model (TAM) and Ajzen's theory
of planned behavior, successfully explain variance in medical
personnel's acceptance of electronic medical records (EMR)
The Technology acceptance model
Davis's (1989)'technology acceptance model (TAM) has been
and remains an important and viable tool for researchers. Research based
upon the TAM has offered valuable insights into how and why individuals
accept or reject technology. However, many of the studies utilizing the
TAM or some variation of it have focused on general user populations
working in varying occupational settings and utilizing a wide spectrum
of information technology solutions (Gefen and Straub, 1997; Taylor and
Todd, 1995; Veiga, Floyd, and Dechant, 2001; Venkatesh and Morris,
2000). Only recently have researchers begun to study factors related to
more specific, professional populations (Abdolrusulnia et. al, 2008,
Al-Gahtani, 2008, Kamhawi, 2008, Yi, et al., 2006). Physicians and
physician extenders (i.e., physician assistants and nurse practitioners)
differ markedly from general users. They are highly educated, highly
trained professionals working in stressful and highly politicized
environments. Given the complexity of the health care industry and its
unique occupational dynamics, we feel that the TAM in and of itself may
not be adequate for explaining technology acceptance as it applies to
The theory of planned behavior
Advocates of the theory of planned behavior (TPB) suggest that all
behavior is motivated by individual decisions based on an
individual's intention to perform that behavior. Intention to
perform a behavior, in turn, is influenced by the individual's
perceived control over the performance of that behavior, his or her
attitude toward performing the behavior, and his or her perception of
social norms (pressure or approval from important referent individuals
to perform a behavior).
The theory of planned behavior asserts that behavioral control
reflects an individual's belief regarding the ease of performing or
completing a task. Behavior control is similar to the technology
acceptance model's perceived ease-of-use construct. Indeed, the TAM
was derived in part from the theory of planned behavior. However, the
theory of planned behavior incorporates the individual's past
experience as well as a sense of control into choosing a behavior (as
opposed to having a behavior mandated).
According to the theory of planned behavior, individuals behave in
accordance with their beliefs (Ajzen, 1988). This theory has
considerable support for behaviors in medicine, education, business, and
the general population. The theory implies that doctors' attitudes,
their subjective norms, and perceived behavioral control are positively
related to their planned and actual behavior concerning the acceptance
of new organizational technology operationalized as an electronic
medical records system. Indeed, prior research by Seeman and Gibson
(2008) found that the constructs associated with the theory of planned
behavior did, in fact, explain variance in medical
personnel's' stated intention to utilize a newly implemented
EMR system. It should be noted that Ajzen stressed and other researchers
reiterated that relevant beliefs should be studied within the specific
usage context (such as EMR systems) to determine the distinct factors
causing the individual to engage in the behavior of interest (Kalify and
Taylor and Todd (1995) introduced a decomposed TPB that included
constructs from the innovation literature, the original TPB, and the
TAM. The decomposed TPB explores social norms and perceived behavioral
control more deeply by breaking them down into individual belief
dimensions. By including aspects not found in the TAM, they posited that
the decomposed TBP would give more complete understanding of usage than
does the TAM alone. In their study of students using software within a
Computer Resource Center, the decomposed TPB explained 60% of the
variance in intention compared with 57% for the pure TPB, and 52% for
the TAM (Premkumar and Bhattacherjee, 2008). The importance of social
norm is somewhat dependent on the stage of implementation. During the
early stages of implementation, when users have limited direct
experience, social norm is most important (Taylor and Todd, 1995).
Research setting, participants, and procedures
As part of an ongoing, multi-phase research endeavor examining the
implementation of electronic medical records, faculty associated with
both a medical school from a large regional university and a large
multi-physician practice were asked to complete an anonymous survey
regarding their perceptions of EMR implementation at their respective
locations. Although a "convenience sample," the physicians
sampled for the current study were chosen because they represented a
combination of doctors who worked as university faculty and private
practice physicians across multiple medical specialties. As such, they
embodied a representative sample of the general physician population.
Completed surveys (57% male, 43% female) were received from 102 of the
physicians invited to participate. The average age of physician
participants was 42.4, with an average of 13.8 years practicing
medicine, 7.2 years at the current location, and 6.7 years in their
current job position.
The survey instrument used for the current study was based on
questions derived from Davis's TAM model (Davis, 1989) and
Ajzen's planned behavior model (Ajzen, 1988). Participants
responded to questions measuring the central constructs of the TAM: the
perceived ease of use of EMR technologies and the perceived usefulness
of EMR; questions measuring the central constructs of the theory of
planned behavior: perceived behavioral control, attitudes toward EMR
technology; and perceived social pressure regarding EMR usage. In all
instances, respondents used a 7-point Likert-type scale where one was
"Not at All" and seven was "Very Much So."
To assess the criterion of technology acceptance, participants were
asked to indicate the degree to which they concurred with a statement
assessing their intention to utilize EMR technology in the future. This
is highly consistent with previous technology acceptance studies that
have utilized "intention to use technology" as indicative of
All survey items are shown in Table 1 grouped by construct.
To examine the degree to which the technology acceptance model and
the theory of planned behavior were associated with intentions to
embrace EMR, two separate multiple regression procedures were conducted.
Details of these are described in the Results section.
Two multiple regression analyses were conducted to predict
technology acceptance. The first included the variables associated with
the technology acceptance model, while the second included the variables
associated with the theory of planned behavior.
For the TAM, the regression equation was significant, R2 = .617,
adjusted R2 = .555, F (13, 101) = 9.991, p < .01. Likewise, the
regression equation for the theory of planned behavior was significant,
R2 = .721, adjusted R2 = .663, F (17, 101) = 12.469, p < .001. Based
upon this information alone, it appears that the theory of planned
behavior does the best job explaining variance in acceptance of EMR by
Next, a multiple regression analysis was conducted with both the
technology acceptance model and theory of planned behavior variables as
predictors. The linear combination of the measures was significantly
related to technology acceptance, R2 = .800, adjusted R2 = .709, F (14,
101) = 8.765, p < .01. The theory of planned behavior measures
predicted significantly over and above the technology acceptance model
variables, R2 change = .183, F (17, 101) = 3.66, p < .01, and
technology acceptance model variables also predicted significantly over
and above theory of planned behavior measures, although to a lesser
degree R2 change = .079, F (13, 101) = 1.911, p<.05. Based on these
results, it appears that the best explanatory power is obtained by a
linear combination of the variables associated with both of the
theories, and that the constructs of the theory of planned behavior play
a highly significant role in explaining EMR acceptance above and beyond
what the technology acceptance model alone is capable of explaining.
Implications for Practice
While the main purpose of this research is to advance the
development of a technology acceptance theory specific to the unique
traits and working environment of physicians and related medical
personnel, the results of this study have considerable implications for
practicing managers given the task of improving physician acceptance of
the electronic medical record. Because doctors' attitudes (toward
technology and what is appropriate when providing medical care) and
their perceived control over the EMR significantly influence their
acceptance, managers should consider these factors when promoting the
advantages and potential uses of EMR technology. According to Jensen and
Aanestaid (2007), managers should be aware of how different groups
experience and enact practices around the technology. A better
understanding of physician acceptance will allow organizations to tailor
technology implementation strategies in a way that dispels
physicians' concerns through increased participation, training, or
developmental activities. In this instance, the knowledge obtained
provides the potential for structuring the technology initiative in such
a way as to help ensure success.
Conclusions and Future Research
As pointed out by Hu et al. (1999), professionals might subtly
differ in their acceptance of technology compared with individuals in an
ordinary business setting. While the advantages of using the electronic
medical record in physician decision making are clearly recognized, this
study explores reasons beyond the TAM that explain the slow adoption of
this technology. A major contribution of this research is the finding
that the theory of planned behavior explains acceptance by this
population beyond that which is explained by TAM alone.
Future research might consider how technology adoption by
physicians is affected by other factors, such as culture. For example,
perceived usefulness appears to be more important in Western Cultures
while ease-of-use is more important to non-Western cultures in
determining intention and actual use (Schepers and Wetzel, 2007). Given
the diverse ethnicity of the physician population, studying the effect
of ethnicity on EMR acceptance could be an important contribution.
Some recent IT research has begun to focus on the continuation of
usage for accepted technologies (Premkumar and Bhattacherjee, 2008).
Khalifa and Davison, (2008) have studied the applicability of the theory
of planned behavior regarding continuance behavior. As the electronic
medical record becomes more common, further research regarding factors
influencing its use would make a contribution.
From an organizational perspective, the role of EMR as a source of
medical organizational change (Jimmieson, Peach and White, 2008) offers
an avenue of extending this research, particularly regarding how the
theory of planned behavior might assist in managing this change.
Venkatesh and Balla (2008) have suggested that research regarding
the role of interventions can aid in the decision making that may lead
to increased acceptance and better use of information technology. As the
electronic medical record moves from larger to smaller hospitals and
practices, adoption decisions and intervention create further research
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Elaine Seeman, East Carolina University
Shanan Gibson, East Carolina University
Dr. Seeman has experience in database design, systems development,
and software development and testing. Her research, which has been
published in a number of journals, explores acceptance of medical
information technologies and also public policy and regulatory issues
related to 911. In addition to teaching, Dr. Gibson is a member of the
Social Security Administration's Occupational Information
Development Advisory Panel. Her research interests include
entrepreneurship education, online training and education, and human
resources management issue, and she has published recently in several
Table 1. Survey Items
Perceived Ease of Use ([alpha] = .594)
I find EMR flexible to interact with.
I find EMR to be easy to use.
I find it easy to get EMR to do what I need it to do in my patient care
It is easy for me to become skillful in use the EMR technology.
Learning to operate EMR is easy for me.
My interactions with EMR are clear and understandable.
Perceived Usefulness ([alpha] = .859)
The primary benefit of EMR is patient safety.
EMR is related to a physician's ethical responsibility to "do no harm."
I find EMR useful for my patient care and management.
Using EMR enhances my service effectiveness.
Using EMR improves my patient care and management.
Using EMR enables me to complete patient care more quickly.
Using EMR increases my productivity in patient care.
Theory of Planned Behavior Items
Perceived Behavioral Control (alpha = .72)
I know why EMR was/is being implemented at my organization.
Individual physicians have the ability to influence the decisions
Individual physicians will influence the decisions regarding EMR.
I have the knowledge necessary to use EMR.
I have the resources necessary to use EMR.
Perceived Social Influence (alpha = .35)
Medical leadership believes that I/we should use EMR.
My feelings of responsibility toward my patients influence me to use
My peers think I/we should use EMR.
The culture here embraces EMR technology.
Attitudes Toward EMR (alpha = .87)
EMR will be successfully implemented at other organizational locations.
EMR is an appropriate tool for physicians to use.
I like the idea of using EMR.
I find EMR technology useful for my patient care and management.
Using EMR is a good idea.
Using EMR is pleasant
Using the EMR system is a wise idea.
I have embraced the EMR technology in my workplace.