Financial Barriers Hamper AI Adoption in APAC Healthcare Systems
Financial challenges impede the adoption of AI technologies in Asia-Pacific healthcare systems.
Key Points
- • Financial constraints limit AI adoption in non-tertiary hospitals.
- • Focus on low-risk, high-impact AI use cases suggested by experts.
- • Cultural trust issues significantly influence AI acceptance.
- • Need for clear insurance frameworks regarding AI-related risks.
A recent panel discussion at HIMSS25 APAC spotlighted the financial challenges that hospitals in the Asia-Pacific region face in adopting artificial intelligence (AI) technologies. According to Dr. Gao Yujia, a representative from Singapore's National University Health System, funding limitations particularly hinder non-tertiary hospitals from embracing AI. He remarked that the existing financial models restrict many hospitals' ability to invest in AI, leading survey participants to identify costs as the primary barrier to adoption.
To mitigate these financial challenges, Shirley Golen of Amazon proposed focusing on low-risk, high-impact AI implementations, such as those addressing administrative tasks and improving workflow efficiencies. In alignment, Dr. Seyoung Jung from Seoul National University Bundang Hospital discussed the potential of plug-and-play AI products for streamlined integration. Dr. Gao also emphasized the necessity of showcasing long-term returns on AI investments, advocating for a comprehensive 10-year strategy to justify the allocation of resources.
Apart from financial constraints, cultural factors are significant in AI adoption, as Dr. Chia Te-Liao highlighted. Trust and accuracy are key elements that influence acceptance in hospitals, with the establishment of AI centers in Taiwan aimed at promoting safe AI practices. Digitalization remains a hurdle, as many institutions continue to depend on paper records, complicating AI system integration.
Additionally, discussions on insurance highlighted the ambiguity surrounding liability for AI-related errors. Dr. Liao underscored the urgent need for a framework evaluating insurance coverage linked to AI technologies in healthcare. In drawing parallels with the automotive industry, Dr. Gao expressed hope that insurance models for AI-enabled healthcare would evolve to provide reimbursements for related software use in clinical settings.