Data for Paper EHR (Behavioral Intention)

The COVID-19 pandemic highlighted the crucial role of electronic health records (EHRs) in data sharing for patient care coordination and disease surveillance, offering real-time, patient-centered information. EHRs have been globally recognized for improving healthcare quality, enhancing care efficiency, and reducing costs, with potential benefits in resource-limited settings. Despite the numerous benefits, challenges in EHR adoption persist in such settings, including computer illiteracy, lack of training, and infrastructure limitations. The need to address factors influencing nurses' behavioral intention to use EHRs in resource-limited settings led to the proposal of a modified Unified Theory of Acceptance and Use of Technology (UTAUT) model specifically tailored for such settings. The study employed a cross-sectional research design where the data was collected from nurses in resource-limited settings at a single point in time. The foundational UTAUT model was adopted and enhanced with additional constructs and moderating factors specific to resource-limited settings. The multiple regression analysis on the main study variables demonstrated significant positive effects of performance expectancy, effort expectancy, personal innovativeness, and attitude toward use on nurses’ behavioral intention to use EHRs, with computer anxiety negatively impacting it. Additionally, moderators such as age, IT experience, professional experience, and education significantly influenced the main study variables (except no impact of age on resistance to change), suggesting that nurses' characteristics impact their behavioral intention to use EHRs.