Journal of Medical Internet Research (Oct 2021)
Health Care Providers’ Acceptance of a Personal Health Record: Cross-sectional Study
Abstract
BackgroundPersonal health records (PHRs) are eHealth tools designed to support patient engagement, patient empowerment, and patient- and person-centered care. Endorsement of a PHR by health care providers (HCPs) facilitates patient acceptance. As health care organizations in the Kingdom of Saudi Arabia begin to adopt PHRs, understanding the perspectives of HCPs is important because it can influence patient adoption. However, no studies evaluated HCPs’ acceptance of PHRs in the Kingdom of Saudi Arabia. ObjectiveThe aim of this study was to identify predictors of HCPs’ acceptance of PHRs using behavioral intention to recommend as a proxy for adoption. MethodsThis cross-sectional study was conducted among HCPs (physicians, pharmacists, nurses, technicians, others) utilizing a survey based on the Unified Theory of Acceptance and Use of Technology. The main theory constructs of performance expectancy, effort expectancy, social influence, facilitating conditions, and positive attitude were considered independent variables. Behavioral intention was the dependent variable. Age, years of experience, and professional role were tested as moderators between the main theory constructs and behavioral intention using partial least squares structural equation modeling. ResultsOf the 291 participants, 246 were included in the final analysis. Behavioral intention to support PHR use among patients was significantly influenced by performance expectancy (β=.17, P=.03) and attitude (β=.61, P<.01). No moderating effects were present. ConclusionsThis study identified performance expectancy and attitude as predictors of HCPs’ behavioral intention to recommend PHR to patients. To encourage HCPs to endorse PHRs, health care organizations should involve HCPs in the implementation and provide training on the features available as well as expected benefits. Future studies should be conducted in other contexts and include other potential predictors.