PROBABILISTIC SENSITIVITY ANALYSIS IN COST-EFFECTIVENESS

Abstract

We explore the policy implications of probabilistic sensitivity analysis in cost-effectiveness analysis by applying simulation methods to a decision model. We present the multiway sensitivity analysis results of a study of the cost-effectiveness of vaccination against pneumococcal bacteremia in the elderly. We then execute a probabilistic sensitivity analysis of the cost-effectiveness ratio by specifying posterior distributions for the uncertain parameters in our decision analysis model. In order to estimate probability intervals, we rank the numerical values of the simulated incremental cost-effectiveness ratios (ICERs) to take into account preferences along the cost-effectiveness plane. The 95% probability intervals for the ICER were generally much narrower than the difference between the best case and worst case results from a multiway sensitivity analysis. Although the multiway sensitivity analysis had indicated that, in the worst case, vaccination in the 85 and older age group was not acceptable from a policy standpoint, probabilistic methods indicated that the cost-effectiveness of vaccination was below $50,000 per quality-adjusted life-year in greater than 92% of the simulations and below $100,000 in greater than 95% of the simulations. Probabilistic methods can supplement multiway sensitivity analyses to provide a more comprehensive picture of the uncertainty associated with cost-effectiveness ratios and thereby inform policy decisions.