Presentation (CTI)

OBJECTIVES: Health Technology Assessment (HTA) and cost-effectiveness modelling frequently rely on expert judgment to bridge critical evidence gaps. However, traditional Structured Expert Elicitation (SEE) protocols are operationally slow, resource-intensive, and vulnerable to behavioural biases. We present a cloud-based solution, the Structured Expert Elicitation Platform (SEEp), which optimises both workshop-based and asynchronous elicitation pathways to deliver an efficient, reproducible, and auditable process.
METHODS: SEEp digitalises the SEE workflow by allowing experts to complete their elicitation survey online, including specific SEE questions like chips-and-bins or low-high-best estimates. Experts can validate their estimates interactively against Kaplan-Meier, or their own responses to previous questions. The platform fits parametric curves to individual distributions and conducts mathematical aggregation via linear pooling live. To address traditional coordination and programming bottlenecks, the architecture supports a modified-Delphi approach with multiple asynchronous survey rounds or real-time results visualisations during live facilitated workshops. Outputs, including an audit trail, are exported as automated reports.
RESULTS: Across early applications, particularly in long-term survival extrapolation, platform use was associated with shorter elicitation timelines (from months to weeks) and lower delivery costs versus traditional approaches. Asynchronous surveys reduced scheduling burden for experts without compromising the data integrity and methodological rigour required by HTA bodies, including the National Institute for Health and Care Excellence, Zorginstituut Nederland, and Canada's Drug Agency.
CONCLUSIONS: Transitioning away from manual SEE protocols to a platform like SEEp can help to reduce some of the operational bottlenecks of the SEE process, improving the efficiency, transparency, and auditability of expert elicitation studies, and thereby improving the quality of evidence used to inform decisions in HTA.