Presentation (CTI)

OBJECTIVES: To support value-based adoption of AI-enabled digital health technologies, many HTA agencies now integrate economic evaluation—including cost-effectiveness and budget-impact analyses—into their decision frameworks. As AI-based MedTech continues to enter the Korean market, early-stage assessment becomes critical. This study explores whether established economic evaluation frameworks from international HTA systems can be integrated into Korea’s Scientific Advice (SA) program, which offers early guidance on evidence generation and regulatory alignment for innovative health technologies.
METHODS: We performed a structured review of AI-related HTA reports and economic evaluation frameworks from four jurisdictions: NICE (UK), CADTH (Canada), ICER/PHTI (US), and SBU (Sweden). A total of 18 reports were included—12 from Canada, 4 from the UK, and 1 each from the US and Sweden. Reports were evaluated for use of economic modeling, QALY-based metrics, real-world evidence (RWE), clinically relevant endpoints, and population specification—key elements in value-based decision making.
RESULTS: The UK demonstrated relatively active use of economic evaluations, with four AI-based technologies included in NICE guidance. In Canada, most HTA reports relied on systematic reviews, providing limited economic evidence. In the US, one digital diabetes management report was identified under the ICER-PHTI digital health assessment framework, which incorporated elements of economic evaluation. Sweden assessed AI-based mammography as cost-effective within its dual-reader system; however, the generalizability of these findings may be limited in contexts like Korea, where such clinical practices are not in place.
CONCLUSIONS: Economic evaluations should be adapted to national health policy, clinical practice, and deliberative processes. Given the implications of emerging technologies, context-specific modeling is essential. In the Korean setting, incorporating economic evaluation into the Scientific Advice (SA) process may support early-phase value assessment and strategic planning for AI-based technologies. Moreover, this approach could be extended to a broader range of health interventions, enabling SA to serve as a platform for economic evaluation guidance across diverse technologies.