ARTIFICIAL INTELLIGENCE APPLICATIONS IN HEALTH TECHNOLOGY ASSESSMENT ACROSS ASIA-PACIFIC: A TARGETED REVIEW OF USE CASES, ADOPTION BARRIERS, AND OPPORTUNITIES.
Author(s)
Geetika Sharma, Masters of Science(MS)1, Anand Jha, MBA2, Monica Verma, MPH3.
1Ansea Consultants Pte Ltd, Pune, India, 2Ansea Consultants Pte Ltd, Singapore, Singapore, 3Associate Director, Ansea Consultants Pte Ltd, Singapore, Singapore.
1Ansea Consultants Pte Ltd, Pune, India, 2Ansea Consultants Pte Ltd, Singapore, Singapore, 3Associate Director, Ansea Consultants Pte Ltd, Singapore, Singapore.
OBJECTIVES: Health technology assessment in Asia-Pacific faces unique pressures: compressed evaluation timelines, multilingual evidence bases, limited health economics workforce, and rising submission volumes. AI tools offer potential solutions, yet their adoption in APAC HTA remains inadequate. This review mapped current and potential AI applications across HTA processes, identified key barriers, and assessed opportunities for efficiency gains in APAC.
METHODS: A targeted review (PubMed, Embase, ISPOR/HTAi publications, HTA agency websites; 2019-2026) covered eight markets: Japan, South Korea, China, Taiwan, Australia, Thailand, India, and Singapore. Data were extracted on AI tool adoption within HTA workflows, implementation barriers, and efficiency opportunities. Findings were assessed against the ISPOR GenAI Working Group framework covering systematic reviews, real-world evidence, and economic modelling. Over 40 sources met inclusion criteria.
RESULTS: While no APAC agency has published formal guidance on AI-assisted evidence submissions, many operate digital data systems amenable to AI integration: South Korea's HIRA processes claim from 50 million beneficiaries using advanced analytics; Japan's C-CAT holds 57,084 structured genomic profiles; Australia's 2024 HTA Methods Review introduced digital evidence standards. China's NHSA evaluates over 200 drugs annually. Thailand's HITAP has expanded into digital health research and presented on AI-driven solutions at PMAC 2025, and Singapore's ACE evaluates AI-based health technologies through horizon scanning, but neither has operationalised AI within HTA workflows. Key barriers included multiple distinct privacy regimes impeding cross-border AI training, multilingual submissions limiting English-trained language model applicability, and health economics AI expertise concentrated in few markets. Priority opportunities included automated multilingual literature screening and AI-assisted economic model adaptation across heterogeneous health systems.
CONCLUSIONS: AI applications in APAC HTA remain largely unrealised despite emerging infrastructure. Compressed timelines, rising submission volumes and workforce constraints make AI-assisted HTA particularly valuable to alleviate reviewer burden, yet multilingual and regulatory fragmentation require APAC-tailored solutions. Multilingual screening tools and cross-border data standards should be regional priorities.
METHODS: A targeted review (PubMed, Embase, ISPOR/HTAi publications, HTA agency websites; 2019-2026) covered eight markets: Japan, South Korea, China, Taiwan, Australia, Thailand, India, and Singapore. Data were extracted on AI tool adoption within HTA workflows, implementation barriers, and efficiency opportunities. Findings were assessed against the ISPOR GenAI Working Group framework covering systematic reviews, real-world evidence, and economic modelling. Over 40 sources met inclusion criteria.
RESULTS: While no APAC agency has published formal guidance on AI-assisted evidence submissions, many operate digital data systems amenable to AI integration: South Korea's HIRA processes claim from 50 million beneficiaries using advanced analytics; Japan's C-CAT holds 57,084 structured genomic profiles; Australia's 2024 HTA Methods Review introduced digital evidence standards. China's NHSA evaluates over 200 drugs annually. Thailand's HITAP has expanded into digital health research and presented on AI-driven solutions at PMAC 2025, and Singapore's ACE evaluates AI-based health technologies through horizon scanning, but neither has operationalised AI within HTA workflows. Key barriers included multiple distinct privacy regimes impeding cross-border AI training, multilingual submissions limiting English-trained language model applicability, and health economics AI expertise concentrated in few markets. Priority opportunities included automated multilingual literature screening and AI-assisted economic model adaptation across heterogeneous health systems.
CONCLUSIONS: AI applications in APAC HTA remain largely unrealised despite emerging infrastructure. Compressed timelines, rising submission volumes and workforce constraints make AI-assisted HTA particularly valuable to alleviate reviewer burden, yet multilingual and regulatory fragmentation require APAC-tailored solutions. Multilingual screening tools and cross-border data standards should be regional priorities.
Conference/Value in Health Info
2026-09, ISPOR Asia Pacific 2026, Bangkok, Thailand
Value in Health, Volume 55, Issue S1
Code
HTA39
Topic
Health Technology Assessment
Topic Subcategory
Decision & Deliberative Processes, Systems & Structure, Value Frameworks & Dossier Format
Disease
No Additional Disease & Conditions/Specialized Treatment Areas