ArticleDigital health
Perceptions of AI-supported training for electronic health record use in Tanzania: A preliminary exploratory study.
Article in Digital health. 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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6 authors.
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Abstract
Background: In low- and middle-income countries, electronic health record (EHR) implementation is often undermined by insufficient user training and digital literacy gaps. Emerging tools such as artificial intelligence (AI)-supported personalised training have the potential to address these challenges, but their applicability and perceived value in resource-constrained contexts remain unclear. Objective: This study examined healthcare professionals' perceptions of AI-supported personalised training for EHR use in Tanzanian public hospitals. It assessed perceived benefits, barriers to EHR utilisation, preferred design features and factors influencing user readiness, guided by the Sociotechnical Systems (STS) theory. Methods: A preliminary exploratory cross-sectional survey was conducted with 20 healthcare professionals from two public hospitals in Dodoma, Tanzania. Data was collected using structured, self-administered questionnaires and analysed descriptively with supplementary inferential tests. Participants' self-assessed proficiency, training experiences and views on AI-supported training were assessed. Results: Most participants (90%) had never received AI-based training, yet 85% expressed strong interest and 90% believed it could improve EHR proficiency. Preferred features included simulation-based learning (75%), real-time in-system guidance (65%) and progress-tracking dashboards (50%). Major barriers to EHR use were inadequate training (75%), poor interface usability (60%), limited technical support (50%) and data privacy concerns (55%). A significant positive correlation was found between years of experience and self-rated EHR proficiency ( Conclusion: Healthcare professionals in Tanzania demonstrated readiness and optimism towards AI-powered personalised training as a means to enhance EHR competence and overcome persistent skill and support gaps. Viewed through the STS lens, the findings underscore the need to align technological innovation with human and organisational capacity for sustainable digital health transformation. Further research with larger samples and real-world pilot interventions is recommended to evaluate feasibility, trust and long-term impact.
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