New approaches using probabilistic graphical models in health economics and outcomes research
Quang A. Le · University of Southern California Digital Library · 2015
Probabilistic graphical models (PGMs) are those models that employ both probability theory and graph theory. The fundamental to the idea of a PGM is the notion of modularity, i.e. a complex system can be built by combining simpler parts. Health economics and outcomes research (HEOR) is a multidisciplinary approach to healthcare and research that incorporates number of areas of expertise including clinical research, epidemiology, health services research, economics, and psychometrics. The field has rapidly expanded in the last decade and played a crucial role in improvement the quality of healthcare. Drugs, healthcare programs, and medical devices are increasingly required to demonstrate not only their efficacy and safety characteristics, but also their superior performance in clinical effectiveness, health-related quality of life and economic outcomes. While probabilistic graphical models have become a popular tool for data analysis in health informatics, especially used to prescribe treatment or guide diagnostic decisions, their use and applications in HEOR have been limited. This three-paper dissertation introduces new approaches using probabilistic graphical models in health economics and outcomes research.