Presentation (CTI)

OBJECTIVES: This research aims to assess the current and future use of AI in national and regional HTA and reimbursement processes.
METHODS: A qualitative, web-based survey was fielded via the Rapid Payer Response^TM online portal (RPR®) to 15 payers (3 each from France, Germany, Italy, Spain, and the UK) with self-reported expertise in current applications of AI in HTA and reimbursement-related processes.
RESULTS: Most surveyed payers (13/15) believe that AI can be used effectively to enhance HTA decision-making. The main benefits include faster evidence synthesis and literature review; more efficient real-world evidence and clinical trial analysis; improved assessment consistency; and operational efficiencies, including time and cost savings. Key challenges include outcome validity and reproducibility; adequate skills and training within HTA decision-makers; and limited transparency of AI-driven outputs. Most surveyed payers (13/15) report that HTA or reimbursement committees are currently in an exploration or partial implementation stage of AI adoption, and 33% anticipate wide implementation/full integration within the next 3 years. Payers expect AI to be used mainly in operational HTA tasks rather than final deliberative decision-making. Future use cases will involve internal evidence review and background research to support HTA assessments or reimbursement evaluations, real-world evidence identification, analysis, or interpretation, and early assessment of emerging technologies.
CONCLUSIONS: European payers are already piloting AI in national and regional HTA and reimbursement-related processes and expect greater integration as capabilities mature. They are optimistic about AI’s potential to improve efficiency, evidence review, and decision support, but remain cautious about current limitations related to reproducibility, transparency, and the skills and resources required for implementation. Adoption will accelerate with validation, appropriate training, and clear governance around the use of AI in HTA and reimbursement-related decision-making.