(Preprint)

BACKGROUND Electronic Personal Health Records (ePHRs) are secure web-based tools that enable individuals to access, manage, and share their medical records. England recently introduced a nationwide ePHR called Patient Online. As with ePHRs in other countries, adoption rates of Patient Online remain low. Understanding factors affecting patients’ use of ePHRs is important to increase adoption rates and improve the implementation success of ePHRs. OBJECTIVE This study aims to examine factors associated with patients’ use of ePHRs in England. METHODS The Unified Theory of Acceptance and Use of Technology (UTAUT) was adapted to the use of ePHRs. To empirically examine the adapted model, a cross-sectional survey of a convenience sample was carried out in four general practices in West Yorkshire, England. Factors associated with use of ePHRs were explored using Structural Equation Modelling (SEM). RESULTS Of 800 eligible patients invited to take part in the survey, 624 (78%) participants returned a valid questionnaire. Behavioural intention was significantly influenced by performance expectancy (β=0.57, P<0.001), effort expectancy (β=0.16, P<0.001), and perceived privacy and security (β=0.24, P<0.001). The path from social influence to behavioural intention was not significant (β=0.03, P=0.183). Facilitating conditions and behavioural intention significantly influenced use behaviour (β=0.25, P<0.001; β=0.53, P<0.001, respectively). Performance expectancy significantly mediated the effect of effort expectancy and perceived privacy and security on behavioural intention (β=0.19, P<0.001; β=0.28, P=0.001, respectively). Age significantly moderated three paths; PEBI, EEBI, and FCUB. Sex significantly moderated only the relationship between performance expectancy and behavioural intention. Two paths were significantly moderated by education and internet access: EEBI and FCUB. Income moderated the relationship between facilitating conditions and use behaviour. The adapted model accounted for 51% of the variance in performance expectancy, 76% of the variance in behavioural intention, and 48% of the variance in use behaviour. CONCLUSIONS This study identified the main factors that affect patients’ use of ePHRs in England, which should be taken into account for the successful implementation of these systems. For example, developers of ePHRs should involve patients in the process of designing the system to consider functions and features that fit patients’ preferences and skills, thereby, create a useful and easy to use system. The proposed model accounted for 48% of the variance in use behaviour, indicating the existence of other, as yet unidentified, factors that influence adoption of ePHRs. Future studies should confirm the effect of the factors included in the current model and to identify additional factors.