Predicting patients' intention to use a personal health record using an adapted unified theory of acceptance and use of technology model : secondary data analysis

Yousef, Consuela Cheriece and Salgado, Teresa M. and Farooq, Ali and Burnett, Keisha and McClelland, Laura E. and Thomas, Abin and Alenazi, Ahmed O. and Esba, Laila Carolina Abu and AlAzmi, Aeshah and Alhameed, Abrar Fahad and Hattan, Ahmed and Elgadi, Sumaya and Almekhloof, Saleh and AlShammary, Mohammed A. and Alanezi, Nazzal Abdullah and Alhamdan, Hani Solaiman and Khoshhal, Sahal and DeShazo, Jonathan P (2021) Predicting patients' intention to use a personal health record using an adapted unified theory of acceptance and use of technology model : secondary data analysis. JMIR medical informatics, 9 (8). e30214. (https://doi.org/10.2196/30214)

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Abstract

Background: With the rise in the use of information and communication technologies in health care, patients have been encouraged to use eHealth tools such as personal health records (PHRs) for better health and well-being services. PHRs support patient-centered care and patient engagement. To support the achievement of the Kingdom of Saudi Arabia’s Vision 2030 ambitions, the National Transformation program provides a framework to use PHRs in meeting the 3-fold aim for health care—increased access, reduced cost, and improved quality of care—and to provide patient- and person-centered care. However, there has been limited research on PHR uptake within the country. Objective: Using the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical framework, this study aims at identifying predictors of patient intention to utilize the Ministry of National Guard-Health Affairs PHR (MNGHA Care) app. Methods: Using secondary data from a cross-sectional survey, data measuring the intention to use the MNGHA Care app, along with its predictors, were collected from among adults (n=324) visiting Ministry of National Guard-Health Affairs facilities in Riyadh, Jeddah, Dammam, Madinah, Al Ahsa, and Qassim. The relationship of predictors (main theory constructs) and moderators (age, gender, and experience with health apps) with the dependent variable (intention to use MNGHA Care) was tested using hierarchical multiple regression. Results: Of the eligible population, a total of 261 adult patients were included in the analysis. They had a mean age of 35.07 (SD 9.61) years, 50.6 % were male (n=132), 45.2% had university-level education (n=118), and 53.3% had at least 1 chronic medical condition (n=139). The model explained 48.9% of the variance in behavioral intention to use the PHR (P=.38). Performance expectancy, effort expectancy, and positive attitude were significantly associated with behavioral intention to use the PHR (P Conclusions: This study contributes to the existing literature on PHR adoption broadly as well as in the context of the Kingdom of Saudi Arabia. Understanding which factors are associated with patient adoption of PHRs can guide future development and support the country’s aim of transforming the health care system. Similar to previous studies on PHR adoption, performance expectancy, effort expectancy, and positive attitude are important factors, and practical consideration should be given to support these areas.

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