Application of two-part models and Cholesky decomposition to incorporate covariate-adjusted utilities in probabilistic cost-effectiveness models.

This study aimed to explain a joint statistical procedure (two-part models and Cholesky decomposition) to incorporate second-order uncertainty from covariate adjusted mean utility functions in probabilistic cost-effectiveness models. First, two-part models were applied to obtain parameters for the utility function. Second, a new set of correlated parameters for each simulation was obtained by Cholesky decomposition. The procedure was applied to EuroQol5D-5L in the Spanish Health Survey (21,007 adults). An example for the first simulation showed that 71% of men aged 60 years, high social status and normal weight were in perfect health, and in those not in perfect health, the expected utility was 0.8474 (= 1 - 0.1526). Therefore, their estimated mean utility value was 0.9559. Mean utility values in the interval (- ∞1] were calculated and their associated uncertainty incorporated in the cost-effectiveness models, based on the uncertainty related to correlated parameters in the utilities function.