ASSESSING UNCERTAINTY IN COST-EFFECTIVENESS ANALYSES - APPLICATION TOA COMPLEX DECISION-MODEL

A framework for quantifying uncertainty about costs, effectiveness mea sures, and marginal cost-effectiveness ratios in complex decision mode ls is presented. This type of application requires special techniques because of the multiple sources of information and the model-based com bination of data. The authors discuss two alternative approaches, one based on Bayesian inference and the other on resampling. While computa tionally intensive, these are flexible in handling complex distributio nal assumptions and a variety of outcome measures of interest. These c oncepts are illustrated using a simplified model. Then the extension t o a complex decision model using the stroke-prevention policy model is described.