BAYESIAN COST-EFFECTIVENESS ANALYSIS
- 1 January 2001
- journal article
- research article
- Published by Cambridge University Press (CUP) in International Journal of Technology Assessment in Health Care
- Vol. 17 (1) , 83-97
- https://doi.org/10.1017/s0266462301104083
Abstract
A desirable element of cost-effectiveness analysis (CEA) modeling is a systematic way to relate uncertainty about input parameters to uncertainty in the computational results of the CEA model. Use of Bayesian statistical estimation and Monte Carlo simulation provides a natural way to compute a posterior probability distribution for each CEA result. We demonstrate this approach by reanalyzing a previously published CEA evaluating the incremental cost-effectiveness of tissue plasminogen activator compared to streptokinase for thrombolysis in acute myocardial infarction patients using data from the GUSTO trial and other auxiliary data sources. We illustrate Bayesian estimation for proportions, mean costs, and mean quality-of-life weights. The computations are performed using the Bayesian analysis software WinBUGS, distributed by the MRC Biostatistics Unit, Cambridge, England.Keywords
This publication has 0 references indexed in Scilit: