THE THEORY OF PLANNED BEHAVIOR AND ITS ROLE IN TECHNOLOGY ACCEPTANCE OF ELECTRONIC MEDICAL RECORDS IMPLEMENTATION

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1 THE THEORY OF PLANNED BEHAVIOR AND ITS ROLE IN TECHNOLOGY ACCEPTANCE OF ELECTRONIC MEDICAL RECORDS IMPLEMENTATION Elaine Seeman, Department of Management Information Systems College of Business, East Carolina University (252) , Shanan G. Gibson, Department of Management College of Business, East Carolina University (252) , ABSTRACT This paper examines the extent to which the Theory of Planned Behavior explains variance in physicians acceptance of technology related to Electronic Medical Records (EMR) implementation. As anticipated, it was found that the constructs of perceived behavioral control, attitudes toward EMR technology, and perceived social pressure regarding EMR usage explained significant amounts of variance both as individual constructs and as a whole, in physician s reported intention to fully utilize EMR in their practices. INTRODUCTION At the 2005 Southeast Decision Sciences Institute conference, we presented a paper entitled The Theory of Planned Behavior and its Role in Technology Acceptance: Model Development Utilizing Computerized Physician Order Entry (CPOE) which marked the beginning of a study seeking to lay a framework for a new model of technology acceptance that incorporates the unique features of physicians and physician extenders, and the complex environment in which they work. At that juncture qualitative analysis of physician interviews supported our research assertion that the constructs associated with the Theory of Planned Behavior impacted the physicians acceptance (or lack thereof) of CPOE within the current environment. In 2006, a follow-up was provided that utilized simple descriptive statistics from a very small hospital sample as a preliminary step toward proving quantitative substantiation. Since that time, we have administered additional surveys which provide more quantitative data on technology acceptance among medical professionals. Although the technology of interest is now Electronic Medical Records implementation, not CPOE, the two share many common characteristics and are similar in many ways. The objective of this current paper is to report findings related to acceptance of EMR and present the current research agenda for extending the model. The Electronic Medical Record 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 [9] [11]. EMR technology represents a movement from paper-based care activities toward outcome-focused, evidenced based processes [10]. 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 importantly EMR technology allows physicians fast access to appropriate patient information allowing prompt diagnosis and treatment [2]. In critical

2 situations, such quick access saves lives [11]. While healthcare organizations recognize the advantages associated with the use of the EMR, adoption of the technology has been slow. To date, less than ten percent of American hospitals have implemented electronic medical record keeping as part of their technology strategy for health information [6]. 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. 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 [3]. We have based our study on this issue-physician acceptance of the Electronic Medical Record. THEORETICAL BACKGROUND The Technology Acceptance Model The Technology Acceptance Model (TAM) [4] has been and remains an important and viable tool for researchers. Research based upon TAM has offered valuable insights into how and why individuals choose to accept or reject technology. However, many of the studies utilizing the TAM or some variation of the TAM have focused on general user populations working in varying occupational settings, and utilizing a wide spectrum of information technology solutions [7] [12] [13] [14]. However, physicians and physician extenders (i.e. physician assistants and nurse practitioners) differ quite markedly from general users. They are highly educated, highly trained professionals, working in stressful and highly politicized environments. Given the complexity of the healthcare industry and its unique occupational dynamics, we feel that the TAM in and of itself, may not be an appropriate methodology for explaining technology acceptance as it applies to medical practitioners. The Theory of Planned Behavior Advocates of the Theory of Planned Behavior suggest that all behavior is motivated by individual decisions that are 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.

3 According to the Theory of Planned Behavior, individuals behave in accordance with their beliefs [1]. This theory has considerable support for behaviors in medicine, education, business, and the general population. The Theory of Planned Behavior 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 a Computerized Physician Order Entry (CPOE) system. METHODOLOGY Research Setting, Participants, and Procedures As part of an on-going, 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. Completed surveys (59% male, 41% female) were received from 102 of the physicians that were invited to participate. The average age of physician participants was 42.4 years old, 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. Survey Instrument The survey instrument used for the current study was based on questions derived from Ajzen s Planned Behavior mode [1]. Participants responded to 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 five 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 technology acceptance. All survey items are shown in Table 1 grouped by construct. Analyses In order to examine the degree to which the Theory of Planned Behavior was associated with EMR acceptance four multiple regression procedures were conducted. Details of these analyses are described in the Results section. RESULTS Four multiple regression analyses were conducted to predict acceptance of EMR. The first analysis included the five variables associated with perceived behavioral control, the second analysis included the 3 variables associated with perceived social pressure regarding EMR usage, the third analysis included the seven variables associated with attitudes toward the EMR

4 technology, and the final analysis will include all of the items associated with the theory of planned behavior in order to determine if greater amounts of variance are explained when using all three of the constructs together. The regression equation with the perceived behavioral control variables was significant, R 2 =.292, adjusted R 2 =.256, F (5) = 7.938, p <.01. Likewise, the regression equation for perceived social influence was also significant, R 2 =.281, adjusted R 2 =.259, F (3) = , p <.01. The regression question for attitudes toward EMR was also significant, R 2 =.694, adjusted R 2 =.671, F (7) = , p <.01. Based on these results, attitudes toward EMR measures appear to be better predictors of technology acceptance. Lastly, a multiple regression analysis was conducted with all of the theory of planned behavior constructs as predictors. The linear combination of the measures was significantly related to technology acceptance, R 2 =.722, adjusted R 2 =.673, F (15) = , p <.01. Perceived Behavioral Control Items (alpha =.52) Q1: Individual physicians have the ability to influence the decisions regarding EMR. Q2: Individual physicians will influence the decisions regarding EMR. Q3: I have control over whether or not I use EMR. Q4: I have the knowledge necessary to use EMR. Q5: I have the resources necessary to use EMR. Perceived Social Influence Items (alpha =.35) Q1: Medical leadership believes that I/we should use EMR. Q2: My peers think I/we should use EMR. Q3: The culture here embraces EMR technology. Attitudes Toward EMR Items (alpha =.87) Q1: I like the idea of using EMR. Q2: I find EMR flexible to interact with. Q3: I find EMR technology useful for my patient care & management. Q4: Using EMR is a good idea. Q5: Using EMR is pleasant Q6: Using the EMR system is a wise idea. Q7: I have embraced the EMR technology in my workplace. Table 1. Theory of Planned Behavior Construct Items DISCUSSION & FURTHER RESEARCH

5 As was stated at the outset, we believe that the medical personnel involved in many technology initiatives differ greatly from the general population frequently analyzed in technology acceptance contexts. They are highly educated, highly trained professionals, working in stressful and highly politicized environments. Given the complexity of the healthcare industry and its unique occupational dynamics, we feel that the TAM in and of itself, may not be an appropriate methodology for explaining technology acceptance as it applies to medical practitioners. Consistent with this belief, the current study has indicated that intention to adopt EMR by medical personnel can be at least partially attributed to the constructs that are associated with the Theory of Planned Behavior. Although all three constructs had significant predictive power, and as such should be considered when implementing a major technology initiative, it appears that one s efforts to promote EMR acceptance would best be directed toward shaping physician s attitudes. Future research should continue to consider other factors which may facilitate technology acceptance (such as the role of occupational values), and to test newer, more complex models of technology acceptance, such as the Unified Theory of Acceptance and Use of Technology (UTAUT) model [15]. Past research has also indicated that both gender and age may play roles in technology usage and adoption patterns, and it would be of interest to examine whether or not this applies to a highly educated population such as the medical personnel examined here. REFERENCES [1] Ajzen, I. (1988): Attitudes, Personality and Behavior. Milton Keynes (UK): Open University Press. [2] Chao, C., Jen, W., Chi, Y, and Lin, B. (2007) Improving patient safety with RFID and mobile technology, International Journal of Electronic Healthcare, Vol. 3, No. 2 pp [3] Colvin, G. (2007) Wiring the Medical World, Fortune, February 19, 2007, Vol. 155, No. 3 pp [4] Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), [5] Ferren, A. (2002). Gaining MD Buy-In: Physician Order Entry. Journal of Healthcare Information Management, 16(2), 67. [6] Gardner, Tom. Six Trends to Bank On Fortune, 6/25/2007, Vol. 155 Issue 12, p85-92 [7] Gefen, D. & Straub, D. (1997). Gender Differences in the Perception and Use of An Extension to the Technology Acceptance Model. MIS Quarterly, 21(4), [8] Hieb, B. & Handler, T. (2001). The Critical Role of Orders in the Delivery of Healthcare. Gardner Research AV [9] Hough, C.B.H., Chen, J.C.H. and Lin, B. (2005) Virtual health/electronic medical record: current status and perspective, International Journal of Healthcare Technology and Management, Vol. 6, No. 3, pp [10] Mangalompalli, A., Rama, C, Muthiyalian, R., Jain, A.K, and Parinam, A.M. (2007) Highend clinical domain information systems for effective healthcare delivery, International Journal of Electronic Healthcare, Vol. 3, No. 2 pp [11] Steele, R., Gardner, W., Chandra, D., and Dillon, T.S (2007) Framework and prototype for a secure XML-based electronic health records system, International Journal of Electronic Healthcare, Vol. 3, No. 2 pp ).

6 [12] Taylor, S. & Todd, P. (1995). Assessing IT Usage: The Role of Prior Experience. MIS Quarterly, 19(4), [13] Veiga, J., Floyd, S., & Dechant, K. (2001). Towards Modeling the Effects of National Culture on IT Implementation and Acceptance. Journal of Information Technology, 16, [14] Venkatesh, V. & Morris, M. (2000). Why Don t Men Ever Stop to Ask for Directions? Gender, Social Influence, and their Role in Technology Acceptance and Usage Behavior.MIS Quarterly, 24(1), [15] Venkatesh, V., Morris, M., Davis, G., & Davis, F. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3),

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