A New Method to Determine the Optimal Willingness to Pay in Cost-Effectiveness Analysis.

Objective: To provide a new approach to estimate optimal willingness to pay (WTP) for health technology assessment (HTA).

Study Design: This analysis specified utility as a function of income and calibrated it using estimates of relative risk aversion, from which the optimal WTP (K) can be determined using Garber and Phelps' results (1997).

Methods: This analysis used the highly flexible Weibull utility function, calibrated with estimates of relative risk aversion (r*) derived from multiple data sources. The analysis centered on r* = 1 and conducted sensitivity analysis on r* and key Weibull parameters. For a range of income (M), graphs demonstrated how K/M and K vary with M. Results were compared with estimates of K and K/M from alternative models. Extrapolation from a representative individual to population-wide health plans was discussed.

Results: Using r* = 1 and central values of other key parameters, K/M (at average income for developed nations) was approximately 2× annual income. Both K and K/M rose with income. Sensitivity analysis showed that results depend moderately on the chosen value of r* and specific Weibull utility function parameters. At average income, the optimal K/M ratio (2×) was modestly lower than many standard recommendations (typically 3× average income) and substantially lower than estimates using value-of-statistical-life approaches.

Conclusions: The new model, although not yet perfected, provides a different way to identify the WTP cutoff for HTA. Extrapolation to more than twice the calibration income ($50 000) is advised against. Analysis of other approaches to estimate the optimal K reveal potential upward biases.