Apply Bayesian Network Approaches to Study Health Outcomes;Final rept. 1 Jul 03-31 Dec 03

摘要

In today's healthcare environment, innovative knowledge discovery approaches in large and healthcare databases via data mining techniques have been actively used in the analysis of these data. Of particular interest are Bayesian networks, which have recently emerged as powerful data mining algorithms for pattern recognition and classification. The purpose of this study was to explore the feasibility of using Bayesian networks (BN) in studying health outcomes. This study used the HIV Cost and Services Utilization Study (UCSUS) dataset consisting of 2,864 HIV positive adults. According to the results of this study, the BN method successfully captured relationships explaining complex patterns of human behavior in health service utilization. The BN approaches also contributed to the discovery of the influential predictors that lead to an increase of the models' predictive performance. This study provided new insight in working with large healthcare databases. When attempting to discover unknown relationships that might be missed by traditional analysis methods alone, investigators should consider the use of BNs.