Applying Theoretical Frameworks to Explicate Physician Acceptance of Computerized Physician Order Entry (CPOE)

This paper reports the findings of a pilot study undertaken to ascertain the feasibility of incorporating the Theory of Planned Behavior and the Taxonomy of Work Values into the explanation of physician technology acceptance of a new organizational technology – Computerized Physician Order Entry (CPOE). While Davis’s Technology Acceptance Model has received much empirical support, we posit that certain complexities associated with the physician population and the hospital environment warrant the inclusion of other theoretical models as a means of furthering our understanding of technology acceptance. Although preliminary in nature, this study finds support for the inclusion of both the Theory of Planned Behavior and the Taxonomy of Work Values in further research examining this complex phenomenon. INTRODUCTION This study examines the feasibility of utilizing the constructs associated with the Theory of Planned Behavior (TPB) (Ajzen, 1988) as well as the Taxonomy of Work Values (Dawis, 1984) to explicate physician acceptance of Computerized Physician Order Entry (CPOE) beyond that which is possible with the Technology Acceptance Model (TAM) (Davis, 1989) alone. We posit that although the TAM is useful in explaining general technology acceptance behavior, certain complexities associated with the physician end-user population require expanding the theoretical framework to include the TPB and specific work values. This pilot study seeks to ascertain the appropriateness of incorporating the Theory of Planned Behavior and the Taxonomy of Work Values into the study of physician technology acceptance within the healthcare environment. Computerized Physician Order Entry is an automated clinical decision support intervention that enables healthcare organizations to improve patient safety, clinician workflow processes and resource utilization. CPOE embraces the precepts embodied within the concept of “evidence-based medicine” (Hieb & Handler, 2001), and may minimize the risk to a medical organization’s reputation and financial viability. Kaushal and Bates (n.d.) provide the following definition of CPOE in the National Library of Medicine’s “Health Services/Technology Assessment Text (HSTAT)”: CPOE refers to a variety of computer-based systems of ordering medications, which share the common features of automating the medication ordering process. Basic CPOE ensures standardized, legible, complete orders by only accepting typed orders in a standard and complete format. Almost all CPOE systems include or interface with CDSSs of varying sophistication. Basic clinical decision support may include suggestions or default values for drug doses, routes, and frequencies. CPOE embodies a shift from traditional, paper-based care coordination activities to automation of the order entry processes. As such CPOE represents a dramatic step forward for healthcare organizations. This shift can be an agent for change, eliminating confusing or illegible hand-written order documentation, minimizing transcription errors and fundamentally reducing clinical mistakes. A study examining the market perception of CPOE vendors defined CPOE as a system that “. meets the IT requirement of direct care providers such as nurses and physicians D. Rosenthal, E. Seeman & S. Gibson 2005 Volume 14, Number 4 62 founded upon a CPR (Computer-based or Clinical Patient Record) to assist in charting, supports physician order entry (POE) and provides rules-based alerting and reminders (Klas, 2002). In an effort to add flexibility to the processes and change hospitals face when implementing CPOE systems, the Leapfrog Group now defines the point at which hospitals have fully implemented CPOE to be when prescribers enter at least 75% of medication orders via the CPOE system (Health Data Management, 2004). Moreover, with regard to the utilization of computerized order entry, the Leapfrog group has broadened its definition of “physicians” to include all clinicians authorized to order pharmaceuticals for patients. Physician workflow potentially becomes more efficient with CPOE due to the embedded rules and artificial intelligence technology that incorporate knowledge tools and clinical decision support capabilities, ultimately enabling physicians to spend more quality time with their patients. Numerous groups, including the Joint Commission on Accreditation of Healthcare Organizations (JCAHO), the Leapfrog Group, the National Quality Forum, and other researchers and organizations in this country have recognized the medical, fiscal, and overall strategic advantages associated with investing in technology that places physicians at the center of the order entry process. Despite the obvious advantages and documented improvements to patient outcomes that have been associated with the use of CPOE, as of 2000 only one third of all U.S. hospitals had installed automated order entry systems – with a mere 1 percent of those organizations mandating its use by physicians (Ferren, 2002). STATEMENT OF THE PROBLEM The potential for improved outcomes and increased patient safety realized by CPOE is recognized by the healthcare industry. However, according to a 2003 Leapfrog Group report (Leapfrog Group, 2003) very few U.S. hospitals have implemented any level of automated order entry processes that feature medical error notification capabilities. The explanation for this paradox is multi-faceted. CPOE represents a major operational and cultural shift for healthcare organizations regardless of their size or scope. However, within the healthcare environment, it is imperative that IT systems provide concurrent support between the clinical and business objectives. More importantly, if a system does not represent the “realities” of the health care delivery process, then the needs of the caregivers may not be met, and there exists a risk that the system will not be used (Dhillon, 2005). Physicians, nurses and extenders function in a healthcare ecosystem known for its highly technical and specialized patois, which can be confusing and nebulous to the many non-medical professionals within the healthcare organization. Within the guise of IT systems design and implementation, there is a strong need for clear and concise communications between the medical personnel and the Information Systems (IS) staff. Chen, Miller, Jiang, & Klein (2005) propose that the existence of a “communication gap” between IS users and IS professionals may play a part in impeding the successful implementation of technology solutions if the communication skill requirements (both oral and written) that are perceived and expected by both the IS users and IS professionals are not appropriately aligned. Expenses related to upgrading existing order entry systems for enhanced medication order processing, funding for additional workstations and resources, specialized systems training, and the challenges associated with achieving and maintaining physician buy-in and acceptance have all contributed to the limited success that CPOE has achieved thus far. It is within the context of physician acceptance of the Computerized Physician Order Entry technology that we base this study. Physicians are highly educated, highly trained professionals, working in stressful and highly politicized medical environments. We posit that physicians accept technology based not solely upon the variables of perceived usefulness (PU) and perceived ease-of-use (PEU) – the integral constructs of TAM (Davis, 1989) – but also upon factors specific to physicians and the medical profession. The objective of this pilot study is to examine whether or not a relationship exists between the constructs associated with the Theory of Planned Behavior, the Taxonomy of Work Values and physicians’ acceptance of technology. Applying Theoretical Frameworks Journal of International Technology and Information Management 63 LITERATURE REVIEW The Technology Acceptance Model A recent article in the popular press (Healey, 2004) contends that computerizing physician orders is an early example of technical innovation that will change both the delivery of healthcare and the physician-patient relationship. However, the organizational changes associated with the implementation of new technology are seldom whole-heartedly welcomed by the employees tasked with utilizing those technologies (Lorence & Spink, 2004; Agarwal & Karahanna, 2000; Venkatesh & Morris, 2000; Agarwal & Prasad, 1999; Hu; Chau, Sheng & Tam, 1999). Davis’ technology acceptance model (1989) has been the dominant theory and remains an important and viable tool for researchers in this arena. According to Chau (1996), it is perceived usefulness and perceived ease of use that are hypothesized and empirically supported as the fundamental determinants of user acceptance of a given new technology. The TAM’s utility is evidenced by the numerous modifications and augmentations that have been made by researchers to address the question of technology acceptance as it relates to variables such as gender differences (Venkatesh & Morris, 2000; Gefen & Straub, 1997), user inexperience (Taylor & Todd, 1995), and culturally induced beliefs (Veiga, Floyd & Dechant, 2001). Some of the more significant contributions to the initial TAM research are summarized below. Chau (1996) divided perceived usefulness into two types: Near-term usefulness and long-term usefulness. In his study, near-term usefulness had the more significant influence on the behavioral intention to use a technology. Other research has corroborated this finding that perceived usefulness is most important in the early stages of technology adoption when learning to use the technology is a major concern (Agarwal & Prasad, 1997; Davis et al., 1989). In 2000 Venkatesh and Davis published the results of four longitudinal field studies that tested an extension (TAM2) of the original technology acceptance model. TAM2 avowed that user acceptance was significantly influenced by socia