Identifying the Influential Dynamic Inputs in Cost-Effectiveness Analyses

Objectives Compare cost-effectiveness estimates calculated using a static approach to pricing over time with an approach that accounts for price changes over time (a dynamic approach) and identify which dynamic inputs have the greatest influence on cost-effectiveness. Methods A panel of economic modeling experts identified cost-effectiveness analysis model inputs that change over time, possible values for each dynamic input, and approaches for incorporating dynamic inputs into an economic model. Informed by the advisory panel, static and dynamic cost-effectiveness estimates were calculated for 4 cases: (1) a chronically administered treatment for a chronic condition, (2) a chronically administered treatment for a catastrophic condition, (3) a 1-time treatment for a chronic condition, and (4) a 1-time treatment for a catastrophic condition. Results The static cost-effectiveness estimate was less favorable than the dynamic estimate for a chronically administered drug by between 82% (case 1) and 62% (case 2), and for a 1-time drug by between 34% (case 3) and 27% (case 4). For chronically administered treatments, the post-loss-of-exclusivity price had the greatest impact on cost-effectiveness. For 1-time treatments, the age of individuals at baseline and the discount rate had a greater impact on cost-effectiveness than the drug’s assumed price changes. Conclusions Compared with a static approach, a dynamic approach can result in substantially different cost-effectiveness estimates, especially for treatments administered over time. To incorporate dynamics, research should prioritize estimating price changes after loss of exclusivity.