Objectives: We explore the policy implications of probabilistic
sensitivity analysis in cost-effectiveness analysis by applying simulation
methods to a decision model.
Methods: 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.
Results: 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.
Conclusions: Probabilistic methods can supplement multiway
sensitivity analyses to provide a more comprehensive picture of the
uncertainty associated with cost-effectiveness ratios and thereby inform