Predicting Acceptance of Electronic Medical Records: Is the Technology Acceptance Model Enough?
Seeman, Elaine, Gibson, Shanan, SAM Advanced Management Journal
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 important.
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) technologies. …