ArticleJMIR medical informatics2025
Acceptance of Electronic Medical Records and Associated Factors Among Health Care Workers in Northwest Ethiopia: Cross-Sectional Study.
Article in JMIR medical informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundAlthough electronic medical records (EMRs) play a vital role in strengthening the health care system by improving efficiency, data management, and patient care, their development in Ethiopia is still in its early stages. Hence, most public health care facilities manage their patient information using paper-based recording, which results in errors, delays, and reduced service quality.
objectiveThis study aims to determine the level of acceptance of the EMR system and describe contributing factors.
methodsA cross-sectional study was conducted at health care facilities in Bahir City, Northwestern Ethiopia. A total of 322 health workers participated in the study, drawn from 5 health facilities that have implemented the EMR system. Descriptive statistics and bivariate and multivariate binary logistic regression were done to determine factors associated with EMR acceptance computed from mediating factors (perceived ease of use and perceived usefulness), and which is more appropriate in early-stage implementation.
resultsOut of the total 322 respondents, 256 (73%) respondents with 95% CI 67.4-78.2 had a good acceptance of using EMRs. In regression analysis, significant predictors including work experience over 10 years (odds ratio [OR] 14.32, 95% CI 4.60-44.58), income dissatisfaction (OR 0.28, 95% CI 0.10-0.82), owning a personal computer (OR 11.08, 95% CI 4.03-30.24), EMR-specific training (OR 4.71, 95% CI 1.52-14.54), basic electronic health management information system/district health information system 2 training (OR 3.06, 95% CI 1.02-9.17), and system usability (OR 38.24, 95% CI 12.26-119.27) were identified.
conclusionsThe study demonstrated a moderate level of EMR acceptance among health care workers, with system usability identified as the strongest predictor. Significant factors influencing EMR acceptance included longer work experience, ownership of a personal computer, and prior EMR or electronic health management information system/district health information system 2 training. Context-specific strategies are needed to enhance system usability, provide targeted digital health training, and improve access to technological resources in order to support broader EMR adoption in health care settings.
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