Bayesian methods in health economics
Seminar of the Master in Advanced Artificial Intelligence, UNED.
Speaker
Prof. Gianluca Baio
University College London (UCL), UK.
Date
Thursday, 11th June 2015.
Place
Computer Science School, UNED, room 4.17
c/ Juan del Rosal, 16. 28040 Madrid.
How to arrive
Abstract
Bayesian modelling for costeffectiveness data has received much attention in both the health economics and the statistical literature, in recent years. Costeffectiveness data are characterised by a relatively complex structure of relationships linking a suitable measure of clinical benefit (e.g. qualityadjusted life years) and the associated costs. Simplifying assumptions, such as (bivariate) normality of the underlying distributions, are usually not granted, particularly for the cost variable, which is characterised by markedly skewed distributions. In addition, individuallevel data sets are often characterised by the presence of structural zeros in the cost variable. Hurdle models can be used to account for the presence of excess zeros in a distribution and have been applied in the context of cost data. We extend their application to costeffectiveness data, defining a full Bayesian specification, which consists of a model for the individual probability of null costs, a marginal model for the costs and a conditional model for the measure of effectiveness (given the observed costs). We present the model using a working example to describe its main features.
Related links
 Gianluca Baio's blog: Bayesian statistics, health economics and random stuff.
 Book: G. Baio. Bayesian Methods in Health Economics. Chapman Hall/CRC, Boca Raton, FL, 2012.
 Costeffectiveness analysis with OpenMarkov.

Programa Modular Herramientas de Gestión e Investigación Sanitaria (UNED).