Academic journal article Journal of International Technology and Information Management

Healthcare System-Use Behavior: A Systematic Review of ITs Determinants

Academic journal article Journal of International Technology and Information Management

Healthcare System-Use Behavior: A Systematic Review of ITs Determinants

Article excerpt


To understand patient and physician behavior, researchers have investigated the determinants of using healthcare information systems. Although this stream of research has produced important findings, it has yet to appreciably advance our understanding of system-use behavior in healthcare. To fill this gap, the current paper employs a systematic review to synthesize past research, reveal the key determinants of healthcare system usage, and illuminate a deeper understanding of the topic. This study thus helps healthcare researchers expand their baseline knowledge of these core determinants and conduct more fruitful future research on system-use behavior in healthcare.

Keywords: healthcare, healthcare information systems, system usage, system-use behavior, TAM, technology acceptance model


Healthcare information systems refer to any system that captures, stores, manages, or transfers information related to healthcare. In the past ten years, healthcare researchers have invested tremendous efforts to understand patient and clinician system-use behavior. Not surprisingly then, a number of research models have been developed to identify the determinants of user acceptance of information technologies in healthcare. Many of those models are mainly based on the Technology Acceptance Model (TAM) due to its practical utility and predictive power (Davis et al, 1989). However, based on our knowledge, very few studies have systematically examined the determinants of system acceptance in healthcare.

To fill this gap, the current study uses a systematic review approach to synthesize past research and to investigate the determinants of user-behavior in healthcare. A systematic review approach is very useful here because the empirical studies included in the analysis offer a variety of results of interest, which are unlikely to be obtained from a single study. By doing so, the current study not only identify key factors for using healthcare information systems but also helps to better understand clinician and patient behavior. This particular topic is of profound theoretical and practical importance, but so far it has not been directly and systematically investigated.


TAM, as shown in Figure 1, asserts that the intention to use or actual use of an information system is a function of perceived ease of use and perceived usefulness (Davis et al, 1989). To identify system-use predictors unique in the context of healthcare, the current study thus focuses on core determinants other than perceived ease of use and perceived usefulness.


To find studies, we searched bibliographic databases and electronic bibliographies in various sources in February 2016. Examples of the bibliographic databases are Business Source Premier, ScienceDirect, ABI/INFORM, and PubMed. We manually searched some journals whose back issues were unavailable in bibliographic databases. For the electronic searches, we used such key words as information system, healthcare, health care, management information systems, technology acceptance model (TAM), system use, system usage.

To locate additional studies, we also scanned bibliographies of the papers identified, and checked their potential for inclusion. This comprehensive search strategy enables us to locate as many studies as possible. Finally, studies were chosen if they satisfied these two criteria: (1) they study information systems in healthcare and (2) they investigate determinants of using information systems. In total, we scanned over 130 articles and found that 16 studies met the inclusion criteria and thus were included in this research.


Perceived Compatibility

Past research has identified compatibility as a key motivator for using healthcare information technology. Rooted in Rogers' Innovation Diffusion Theory (IDT), compatibility is defined as "the degree to which an innovation is perceived as consistent with the existing values, past experiences, and needs of potential adopters" (Rogers, 1995, p. …

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