Methods and Applied Research in Decision Analysis

3 credits · Graduate School

This course offers an intermediate-level exploration into medical decision-making and health economic modeling. Course topics include formulating a decision problem, Markov cohort models, microsimulation, discrete event simulation, calibration and validation of models, uncertainty analysis, value of information analysis, and equity-informative cost-effectiveness analysis (e.g. distributional cost-effectiveness analysis). While we emphasize practical application, we also highlight the understanding of fundamental theoretical concepts, disease simulation, and economic modeling skills. Students will undertake a semester-long project, commencing from a real-world decision problem in a clinical or policy context to the development of a fully-fledged model. This hands-on project takes students through all stages of research, from formulating a question to presenting the final results, which may also lead to conference-ready models and potential manuscript development. The course welcomes PhD and Master's students, as well as medical students and residents, with an interest in decision analytic methods, simulation modeling, and cost-effectiveness analysis. [3]