Generative AI as a catalyst for EHR adoption: addressing challenges in Tanzanian healthcare

Augustino Mwogosi

Chapter 9 in Multidisciplinary Movements in AI and Generative AI, 2025, pp 162-178 from Edward Elgar Publishing

Abstract: This chapter explores the transformative potential of Generative AI (GenAI) in addressing the barriers impeding electronic health record (EHR) system implementation in Tanzanian primary healthcare facilities. It identifies vital challenges, including technical, organizational, and socio-cultural barriers, that hinder the successful adoption of EHR systems in the region. GenAI, exemplified by models like GPT, GAN, and DALL-E, is positioned as a solution to streamline data management, enhance decision support, and foster patient engagement. By automating data entry, generating real-time recommendations, and providing personalized training modules, GenAI can improve EHR system adoption in resource-limited settings. The chapter also highlights global examples of successful GenAI implementation in healthcare. It proposes its potential application within Tanzanian healthcare, offering a hypothetical scenario for practical integration. The regulatory and ethical considerations surrounding the use of AI in healthcare are addressed, emphasizing the importance of a robust regulatory framework and ethical safeguards to ensure patient data privacy and unbiased decision-making. This chapter contributes valuable insights for policymakers, healthcare practitioners, and technologists seeking to enhance healthcare delivery through AI-driven EHR systems in developing countries like Tanzania.

Keywords: GenAI; Electronic health records; EHR; Tanzanian healthcare; AI-driven decision support (search for similar items in EconPapers)
Date: 2025
ISBN: 9781035358656
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