<![CDATA[Introduction: Electronic Medical Record (EMR) implementation is a key component of digital transformation in healthcare. This study evaluated the perceived effectiveness of EMR implementation in a regional Indonesian hospital by examining three empirically measured determinants, namely efficiency, accuracy, and system quality. The objective was narrowed to provide evidence on how these factors predict perceived EMR effectiveness within a single-site, low-resource setting without extending to unmeasured constructs such as health literacy or health promotion. Methods: A cross-sectional survey was conducted among 100 healthcare professionals using a structured, validated questionnaire. Data were analyzed using descriptive statistics, chi-square tests with effect sizes, and logistic regression with odds ratios and confidence intervals. Analyses examined how perceptions of efficiency, accuracy, and system quality predicted perceived EMR implementation effectiveness. Results: Respondents reported high perceptions of efficiency (96%), accuracy (94%), and system quality (95%). All three determinants were significantly associated with perceived EMR effectiveness (p < 0.001), with effect sizes indicating strong relationships. Logistic regression showed that system quality had the largest effect size (OR=7.02; 95% CI 2.04–24.10), followed by efficiency (OR=5.83; 95% CI 1.85–18.41) and accuracy (OR=4.26; 95% CI 1.24–14.68). These results indicate that usability and reliability are central predictors of perceived implementation effectiveness in this context. Conclusion: This single-site study provides empirical evidence on the determinants of perceived EMR implementation effectiveness in a regional Indonesian hospital. System quality emerged as the strongest predictor, emphasizing the need for user-friendly, reliable systems supported by training and governance. Because the study did not directly measure health literacy or health promotion outcomes, such impacts are identified as areas for future research rather than conclusions. The results offer practical guidance for improving EMR adoption and inform ongoing work in technology acceptance frameworks.]]>
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