Background
ASEAN countries are facing multifaceted health crises driven by poverty, climate change, infectious diseases, natural disasters, and the withdrawal of external aid. In particular, the Thailand–Myanmar border region is confronting complex and intertwined challenges including a large influx of refugees from Myanmar, the termination of USAID assistance, and the reduction of free medical services. Addressing these issues requires not only the strengthening and reform of existing health systems but also the creation of social innovations and the development of organic, collaborative structures that can respond to systemic vulnerabilities. In this context, the application of Artificial Intelligence (AI) has emerged as a promising form of technological innovation.
The Japan Institute for Health Security (JIHS) has been engaged in various initiatives to support the strengthening of health systems in ASEAN countries. For instance, in support of the WHO-promoted National Essential Diagnostics List (NEDL), JIHS has contributed to improving efficiency in procurement, registration, logistics, maintenance, quality assurance, and the alignment of diagnostics with treatment protocols. JIHS has also contributed over the years to the development and implementation of health workforce strengthening strategies in the Asia region, addressing the development, allocation, continuing education, team-based work, and motivation/incentive structures for diverse health personnel. Furthermore, JIHS has worked on issues related to vulnerable populations, including migrants, by building regional networks in Asia and conducting research on risk communication and community engagement (RCCE), access to health care, and social determinants of health.
AI is increasingly being introduced as a key technology to improve health service access and system efficiency in low- and middle-income countries (LMICs), particularly in the areas of diagnostics, telemedicine, supply chain management, and epidemic forecasting. Tools such as smartphone-based AI-assisted radiographic diagnostics and multilingual chatbot systems are already demonstrating impact in underserved rural areas and refugee camps where medical personnel are scarce. However, many of these AI applications have been led by international donors or global corporations, often with insufficient consideration of local health needs and cultural contexts. Challenges remain regarding the availability of high-quality data for AI models, weak infrastructure (electricity and connectivity), limited AI literacy, and the deployment of “black-box” AI systems with poor explainability and low trust from communities.
To address these challenges, implementation strategies must incorporate ethical and institutional dimensions such as co-design with local communities, transparent and explainable AI, and decentralized data governance. AI must be treated not as a solution in itself but as a tool whose true value depends on “who it is for and who it is built with.”
This study aims to identify, evaluate, and propose AI-based strategies that contribute to the construction of a “Systems for Health” model in ASEAN countries—one that is grounded in the principles of Self-Reliance, Equity, Resilience, and Sustainability. Special focus is placed on equitable access to and effective use of diagnostic services, with initial investigation in the Thailand–Myanmar border region and subsequent consideration of potential expansion to other vulnerable settings in the region.
Objectives
This study has the following specific objectives:
- To analyze the landscape of AI introduction and governance frameworks in ASEAN countries.
- To identify key challenges and opportunities related to diagnostics access and broader health system and socio-economic conditions in vulnerable areas.
- To develop AI-based solution options for addressing these challenges, determine the necessary conditions for implementation, and make relevant policy recommendations.
Methodology
This study will adopt a multi-layered approach, combining qualitative and quantitative methods to analyze conditions ranging from policy and institutional frameworks to community-level initiatives.
The study will proceed in three phases:
• Year 1: Field research in the Thailand–Myanmar border region.
• Year 2: Development of AI-based strategies based on Year 1 findings.
• Year 3: Exploration of the applicability of proposed strategies in other ASEAN settings, and formulation of concrete recommendations through multistakeholder engagement.
Year 1 research activities are as follows:
1） Literature Review
- Collect, compile, and analyze literature on:
- The current status of migrants and refugees from Myanmar in Thailand
- Health-related responses by different stakeholders
- Communication and community engagement strategies
- Local socio-economic networking and support systems
- Special focus will be placed on examining how these elements contribute to building self-reliant, equitable, resilient, and sustainable Systems for Health in crisis-affected settings.
2) AI and Other Digital Technology Landscape Analysis
- Conduct mapping of:
- Existing and upcoming AI and digital health initiatives in Thailand
- Regulatory frameworks governing digital health
- Technical infrastructure available for health-related digital solutions
- Roles played by private sector, public authorities, and international organizations
- Identify:
- Opportunities for leveraging AI/digital technology in the Thailand–Myanmar border context
- Challenges such as infrastructure limitations, trust gaps, data privacy, and cultural mismatches
3) Field Study, Community Engagement, and AI Solution Development
- Plan and conduct fieldwork including:
- Interviews with health professionals, local authorities, community leaders, refugees, and migrants
- Workshops and focus groups with stakeholders to assess:
- Access to health services and health commodity delivery systems
- Communication and RCCE practices
- Local socio-economic networks and mutual support mechanisms
- Organize participatory discussions to co-create a vision for "Systems for Health" that are:
- Self-reliant (rooted in local capacities)
- Equitable (inclusive of migrants, minorities, informal workers)
- Resilient (politically and economically shock-resistant)
- Sustainable (aligned with social and ecological justice)
- Collaborate with local actors to explore the potential for AI and other digital solutions to:
- Streamline health system functions (especially delivery of commodities)
- Enhance risk communication and community engagement
- Support and scale up local socio-economic solidarity networks
4) Data Analysis and Development of Reports and Manuscripts
- Analyze qualitative and quantitative data collected through the above activities.
- Develop interim reports, research manuscripts, and policy recommendations through consultations with team members and stakeholders.
- Prepare for Year 2, focusing on prototyping AI solutions and policy dialogues based on the Year 1 findings.
Study Implementation and Collaboration
This study will be implemented through the following institutions and partnerships:
- Japan Institute for Health Security (JIHS)
Overall coordination and Japanese-side partnership management. Responsible for research design, ethics review, coordination with ASEAN networks, and preparation of international reports. - Institutions in Thailand including International Health Policy Program (IHPP), Ministry of Public Health, Thailand, Health System Research Institute (HSRI), Chulalongkorn University and Naresuan University
Collection of policy documents and stakeholder mapping; Planning and implementation of AI and other digital technology landscape analysis, Conducting field study, community engagement, and AI solution development. - University of the Ryukyus, Community Health and Migration Research Group
Conducting participatory observation and qualitative interviews in the Thailand–Myanmar border area. Focuses on social determinants of health and refugee/migrant access issues. - UNU-IIGH (United Nations University – International Institute for Global Health)
Advice on planning and analysis of AI and other digital technology landscape analysis including AI governance, ethics, and the influence of powerful private actors. Supports the development of explainable AI models and local implementation guidelines. - WHO Thailand Office
Technical advice on stakeholder mapping and engagement on AI and other digital technology landscape analysis and AI-based solution development in Thailand. - ERIA (Economic Research Institute for ASEAN and East Asia)
Supporting the development of ASEAN-wide frameworks for technology policy evaluation and facilitates regional policy dialogues for knowledge dissemination.
