Factors Affecting General Practitioners’ Readiness to Accept and Use an Electronic Health Record System in the Republic of North Macedonia:A National Survey of General Practitioners

Abstract

Background: Electronic health records (EHRs) represent an important aspect of digital health care, and to promote their use further, we need to better understand the drivers of their acceptance among health care professionals. EHRs are not simple computer applications; they should be considered as a highly integrated set of systems. Technology acceptance theories can be used to better understand users’ intentions to use EHRs. It is recommended to assess factors that determine the future acceptance of a system before it is implemented. Objective: This study uses a modified version of the Unified Theory of Acceptance and Use of Technology with the aim of examining the factors associated with intentions to use an EHR application among general practitioners (GPs) in the Republic of North Macedonia, a country that has been underrepresented in extant literature. More specifically, this study aims to assess the role of technology acceptance predictors such as performance expectancy, effort expectancy, social influence, facilitating conditions, job relevance, descriptive norms, and satisfaction with existing eHealth systems already implemented in the country. Methods: A web-based invitation was sent to 1174 GPs, of whom 458 completed the questionnaire (response rate=40.2%). The research instrument assessed performance expectancy, effort expectancy, facilitating conditions, and social influence in relation to the GPs’ intentions to use future EHR systems. Job relevance, descriptive norms, satisfaction with currently used eHealth systems in the country, and computer/internet use were also measured. Results: Hierarchical linear regression analysis showed that effort expectancy, descriptive norms, social influence, facilitating conditions, and job relevance were significantly associated with intentions to use the future EHR system, but performance expectance was not. Multiple mediation modeling analyses further showed that social influence (z=2.64; P<.001), facilitating conditions (z=4.54; P<.001), descriptive norms (z=4.91; P<.001), and effort expectancy (z=5.81; P=.008) mediated the association between job relevance and intentions. Finally, moderated regression analysis showed that the association between social influence and usage intention was significantly moderated (P=.02) by experience (Bexperience×social influence=.005; 95% CI 0.001 to 0.010; β=.080). In addition, the association between social influence and intentions was significantly moderated (P=.02) by age (Bage×social influence=.005; 95% CI 0.001 to 0.010; β=.077). Conclusions: Expectations of less effort in using EHRs and perceptions on supportive infrastructures for enabling EHR use were significantly associated with the greater acceptance of EHRs among GPs. Social norms were also associated with intentions, even more so among older GPs and those with less work experience. The theoretical and practical implications of these findings are also discussed.