Insights on the current and future state of AI adoption within health systems in Southeast Asia: A qualitative study (Preprint)

Abstract

<sec> <title>BACKGROUND</title> Artificial intelligence (AI) holds potential to enhance health systems worldwide. However, in Southeast Asia (SEA) — a region with heterogeneity in geopolitical and socioeconomic development — the implementation of AI in the healthcare sector remains understudied. </sec> <sec> <title>OBJECTIVE</title> This study aims to explore the current and future state of health AI adoption across health systems in SEA from the perspective of a broad range of regional stakeholders. </sec> <sec> <title>METHODS</title> Thirty-one semi-structured interviews were conducted with key informants working or involved in the implementation of AI-enabled technologies within health systems in Brunei Darussalam, Indonesia, Myanmar, Singapore, Thailand, Vietnam, and the Philippines. Participants represented the public, private, and non-profit sector. Interviews were analysed using standard coding and thematic analysis methodology. </sec> <sec> <title>RESULTS</title> To the key informants, AI technology acceptance holds promise for adoption and integration in the health sector. Disparities in digital transformation were viewed as critical impediments, including infrastructure as a barrier to AI adoption, market access concerns, and limited investment. Nevertheless, technology governance and data governance were considered as essential for ethical integration of AI into healthcare systems. Key informants perceived that AI has the potential to transform health systems including population health management, accessibility to services, operations management, financing and healthcare payment, and personalised medicine. </sec> <sec> <title>CONCLUSIONS</title> Our study provides new perspectives on the key facilitators of and barriers to AI adoption across health systems in SEA. The fundamental pillars of investment in digital infrastructure, technology governance, and data governance must be built if AI is to be successfully implemented and ultimately contribute to the transformation of health systems in the region. </sec>

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