Decision Sciences in Clinical Research
Modeling the potential impact of a health intervention on disease outcomes can be extremely useful in gaining an understanding of the underlying biology or epidemiology of a disease, in designing research studies, and in assessing whether an intervention is economically feasible. This course focuses on basic modeling techniques, with an emphasis on decision analysis and cost-effectiveness analysis, and the application of these techniques to the student's own research. Topics covered include basic decision theory, basic principles of economic analysis in health care, decision trees, Markov models, infectious disease models, and economic analysis of clinical trials, how to review a decision/cost-effectiveness analysis, and the application of models for research and policy analysis. Prerequisite: None. Credits: 2.
Topics
- basic decision theory
- basic principles of economic analysis in health care
- decision trees
- Markov models
- infectious disease models
- and economic analysis of clinical trials
- how to review a decision/cost-effectiveness analysis
- and the application of models for research and policy analysis
Topics explicitly listed in official catalogue description
Sources
- Course catalogue ↗2026-2027