aceConceptualising Health Economic Models Using a Graph Retrieval-Augmented, Agentic AI Framework with Human-in-the-Loop Validation: Proof-of-Concept Study
Objective: Health economic models (HEMs) are crucial for assessing the cost-effectiveness of healthcare interventions, informing policy decisions and guiding reimbursement strategies. This study examines the feasibility of employing generative artificial intelligence (Gen-AI) for the conceptualisation of HEMs. Two proof-of-concept studies were conducted, implementing a first-of-its-kind agentic Gen-AI-augmented approach for model conceptualisation. Methods: An agentic Gen-AI framework was developed, incorporatin…
An agentic generative AI framework produced disease concept and model structure diagrams for breast cancer and a rare disease that were checked against literature and by modelers and clinicians.
The study is described as two proof-of-concept case studies, so the findings only suggest feasibility and do not establish performance across other diseases or settings.
Evidence
- Peer-reviewedPharmacoEconomics - Open2026-10-12
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Truvace Impact Record TRV-2026-1418, v1: “Conceptualising Health Economic Models Using a Graph Retrieval-Augmented, Agentic AI Framework with Human-in-the-Loop Validation: Proof-of-Concept Study.” Truvace, 2026-10-15. /record/TRV-2026-1418 (accessed at citation time). sha256 2a98935faed66d94…
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