Using discrete choice experiments to inform the benefit-risk assessment of medicines: are we ready yet?

Caroline Vass, Katherine Payne

Research output: Contribution to journalArticlepeer-review


There is emerging interest in the use of discrete choice experiments (DCEs) as a means of quantifying the perceived balance between benefits and risks (quantitative benefit-risk assessment) of new healthcare interventions, such as medicines, under assessment by regulatory agencies. For stated preference data on benefit-risk assessment to be used in regulatory decision-making, the methods to generate these data must be valid, reliable and capable of producing meaningful estimates understood by decision-makers. Some reporting guidelines exist for DCEs, and for related methods such as conjoint analysis. However, existing guidelines focus on reporting standards, are general in focus, and do not consider the requirements for using DCEs specifically for quantifying benefit-risk assessments in the context of regulatory decision-making. This opinion piece outlines the current state of play in using DCEs for benefit-risk assessment and proposes key areas which need to be addressed to demonstrate that DCEs are an appropriate and valid stated preference elicitation method in this context. Methodological research is required to establish: how robust the results of DCEs are to formats and methods of risk communication; how information in the DCE can be presented effectually to respondents; whose preferences should be elicited; the correct underlying utility function and analytical model; the impact of heterogeneity in preferences; and the generalisability of the results. We believe these methodological issues should be addressed, alongside developing a ‘reference case’, before agencies can safely and confidently use DCEs for quantitative benefit-risk assessment in the context of regulatory decision-making for new medicines and healthcare products.
Original languageEnglish
Early online date23 May 2017
Publication statusPublished - 2017


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