Determinants of effective electronic health record utilization in hospital settings: Evidence from Uganda

The implementation of Electronic Health Record (EHR) systems has expanded across healthcare institutions in low- and middle-income countries; however, effective utilization remains inconsistent, particularly in resource-constrained healthcare settings. This study examined determinants influencing effective EHR utilization among healthcare professionals in selected hospitals within the Greater Bushenyi region of Uganda. Guided by the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), Digital Competence Framework, and Socio-Technical Systems Theory, the study employed a cross-sectional explanatory survey design. Data were collected from 228 healthcare professionals using a structured questionnaire, representing a response rate of 91.2%. Data were analyzed using descriptive statistics, Pearson correlation, and multiple regression techniques. The findings revealed that effective EHR utilization is significantly influenced by human, organizational, technical, and system-level factors. Organizational factors emerged as the strongest predictor of effective EHR utilization (β = 0.378, p < 0.001), followed by system factors (β = 0.298, p < 0.001), technical factors (β = 0.189, p = 0.022), and human factors (β = 0.175, p = 0.014). Correlation analysis further indicated significant positive relationships between all determinants and effective EHR utilization (r = 0.410–0.527, p < 0.01). The regression model explained 44.0% of the variance in effective EHR utilization (R² = 0.440). The study concludes that effective EHR utilization extends beyond system adoption and depends on the alignment of digital competence, organizational readiness, technical usability, and infrastructural reliability. The findings provide evidence-based guidance for healthcare administrators and policymakers seeking to strengthen sustainable EHR utilization and improve healthcare service delivery in resource-constrained settings.