Future Directions for Cost-effectiveness Analyses in Health and Medicine.

OBJECTIVES: In 2016, the Second Panel on Cost-effectiveness in Health and Medicine updated the seminal work of the original panel from 2 decades earlier. The Second Panel had an opportunity to reflect on the evolution of cost-effectiveness analysis (CEA) and to provide guidance for the next generation of practitioners and consumers. In this article, we present key topics for future research and policy. METHODS: During the course of its deliberations, the Second Panel discussed numerous topics for advancing methods and for improving the use of CEA in decision making. We identify and consider 7 areas for which the panel believes that future research would be particularly fruitful. In each of these areas, we highlight outstanding research needs. The list is not intended as an exhaustive inventory but rather a set of key items that surfaced repeatedly in the panel's discussions. In the online Appendix , we also list and expound briefly on 8 other important topics. RESULTS: We highlight 7 key areas: CEA and perspectives (determining, valuing, and summarizing elements for the analysis), modeling (comparative modeling and model transparency), health outcomes (valuing temporary health and path states, as well as health effects on caregivers), costing (a cost catalogue, valuing household production, and productivity effects), evidence synthesis (developing theory on learning across studies and combining data from clinical trials and observational studies), estimating and using cost-effectiveness thresholds (empirically representing 2 broad concepts: opportunity costs and public willingness to pay), and reporting and communicating CEAs (written protocols and a quality scoring system). CONCLUSIONS: Cost-effectiveness analysis remains a flourishing and evolving field with many opportunities for research. More work is needed on many fronts to understand how best to incorporate CEA into policy and practice.

Duke Scholars

Author Gillian Denise Sanders Schmidler Population Health Sciences