Purpose
This study aims to explore how artificial intelligence (AI) can be used to overcome the challenges associated with implementing electronic health record (EHR) systems in primary health-care facilities in Tanzania. It aims to assess the technological, organisational and environmental barriers to EHR system implementation and investigate the role of AI in optimising these systems for more effective health-care delivery.
Design/methodology/approach
The study adopts a qualitative approach, using case studies from five regions in Tanzania: Dar es Salaam, Mwanza, Morogoro, Singida and Pwani. Data were collected through 26 semi-structured interviews with health-care providers, including medical doctors, nurses, pharmacists and IT personnel. The study applied the diffusion of innovation (DOI) theory and the technology-organisation-environment framework to assess the factors affecting EHR implementation and the potential integration of AI to enhance these systems.
Findings
Key challenges include unreliable network connectivity, frequent power outages, insufficient training and complex system usability issues. Despite these challenges, EHR systems have improved patient data accessibility and workflow efficiency. AI presents opportunities to address these challenges, mainly through predictive analytics, AI-driven encryption for data security and personalised training modules. AI integration can enhance system reliability, usability and security, ultimately improving health-care outcomes.
Originality/value
This study provides valuable insights into integrating AI to optimise EHR systems in resource-constrained environments like Tanzania. It addresses a gap in the literature by focusing on how AI can be adapted to low-resource settings and provides a framework for future EHR system implementations in similar contexts. The findings contribute to the global discourse on health-care informatics and the role of AI in improving health-care systems in developing countries.
