JMIR Publications

ABSTRACT

Background:

Electronic health records (EHRs) represent an important aspect of digital healthcare and in order to promote their use further, we need to better understand the drivers of their acceptance among healthcare professionals. The EHR is not a simple computer application, but should be considered as a highly integrated sets of systems. Technology acceptance theories can be utilized to better understand users’ intentions towards using EHRs. It is recommendable to assess factors which determine future acceptance of the system before it is implemented.

Objective:

This study used a modified version of the Unified theory of acceptance and use of technology (UTAUT) with the aim to examine the factors that are 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 the extant literature. More specifically this research has assessed the role of technology acceptance predictors such as performance expectancy, effort expectancy, social influence, facilitating conditions, job relevance, descriptive norm, and satisfaction (with existing e-Health systems already implemented in the country).

Methods:

An online 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 system. Job relevance, descriptive norm, satisfaction with currently used e-Health systems in the country, and computer/the Internet use were also measured.

Results:

Hierarchical linear regression analysis showed that effort expectancy, descriptive norms, social influence, facilitating conditions, and job relevance, but not performance expectancy, were significantly associated with intentions to use the future EHR system. Multiple mediation modelling 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 intentions was significantly moderated (p = .022) by experience (Bexperience×social influence = .005, 95%CI = .001 - .010, β = .080). Additionally, the association between social influence and intentions was significantly moderated (p = .029) by age (Bage×social influence = .005, 95%CI = .001 - .010, β = .077).

Conclusions:

Expecting less effort in using the EHR, and the perception of supportive infrastructure to enable EHR use were significantly associated with greater acceptance of EHR among GPs. Social norms were also associated with intentions, even more so amongst older GPs and those with less work experience. The theoretical and practice implications of the findings are discussed.