Healthcare Decision Making and Analytics

Catalog description

This course is designed to introduce the students to a wide range of methods and applications of decision science and analytics in healthcare management and medical decision making. The primary objective of the course is to provide the students with the necessary technical knowledge and skills to understand mathematical and statistical models used in health decision making. Further, the course aims to provide the students with hands-on experience required to leverage such methods for evaluating clinical interventions, choosing the best treatment, and informing public health policy. Course topics include decision trees, Markov decision models, Monte Carlo simulation, cost-effectiveness analysis, sensitivity analysis, utility theory, bootstrapping and subgroup analysis, prediction and classification methods, and using computer software to build and analyze health decision analysis models. Prereq: MBAP 403 or MBAP 403H.