Decision support for benefit-risk assessment with imprecise preference information

This project refines existing decision support software that aids decision makers in the benefit-risk assessments of medicines. Benefit-risk assessment is a complex process in which two main problems hamper forming a sound judgment. First, decision makers need to compare pharmaceuticals on multiple criteria; and second, differences in medicine preference are often gradual and imprecise. In order to aid decision makers in their judgments, earlier Escher research developed decision support software. This software can help decision makers assess available evidence and visualize benefit-risk trade-offs.

The current project further develops this software. It will enable greater discrimination between medicine preferences by implementing a way for decision makers to be more precise in their preference statements. A case study using CBG derived benefit-risk profiles of two new embolic stroke prevention therapies (dabigatran and rivaroxaban) will be conducted, in which an existing therapy (warfarin) will be compared with the new treatments. The case study produces results of scientific interest in themselves, but more importantly, this study assesses the feasibility of a further refined software tool and evaluates its user interface. This refinement allows decision makers using the software to make preference statements about medicines with greater confidence, thereby improving benefit-risk assessment.