Presentation (CTI)

OBJECTIVES: Health technology assessment (HTA) uses explicit methods to evaluate the clinical, economic, and societal value of health technologies; yet the inclusion of limited or incomplete evidence can result in uncertainty in stakeholder decision-making. Structured expert elicitation (SEE), an increasingly adopted systematic approach, is used to remove inherent biases and lack of robustness caused by limited evidence. This study sought to understand the acceptability and application of SEE methods in HTA decision-making across different authorities.
METHODS: Inclusion of SEE methods into HTA guidance was evaluated in all markets of interest (UK, Germany, France, USA, Canada, Japan, Brazil, and Australia). Systematic analysis was performed to identify explicit guidance and evaluate the acceptability of SEE methods by HTA authorities. Three unrelated case studies were evaluated to identify insights gathered from SEE methods.
RESULTS: Use of SEE methods was considered acceptable across 75% of HTA authorities, yet details of explicit methodological guidance varied. The use of SEE methods was considered most acceptable in circumstances where empirical data were lacking or incomplete; guidance on formal elicitation methods and best practice were noted by 50% of authorities. Case study review revealed that SEE methods were employed to gain insights on the following: current standard of care and unmet needs; patient pathways; long-term outcomes; treatment compliance; appreciation of patient quality of life; prescribing practices; and evaluation of economic models.
CONCLUSIONS: The possibility for negative outcomes due to uncertainty means that SEE methods are playing an increasingly important role, providing vital insights to support market access and HTA submissions. Whilst there are no current standardized guidelines on conducting SEE for HTAs, there is increased acceptability amongst authorities; particularly where documented evidence is lacking or incomplete, with case studies demonstrating that insights gathered from SEE methods are shown to improve support for positive HTA decision-making.