Applied Machine Learning in Health Policy & Economics

Course Director: Yongkang Zhang, PhD

This course offers a comprehensive introduction to applied machine learning models in the context of health policy and health economics. Students will learn how to develop, evaluate, and deploy machine learning models to study important health policy and economic topics across different care settings, such as predicting mortality to support hospice decision making, risk adjustment for insurance plans, and machine learning boosted causal inference methods for health policy evaluations. Throughout the course, we will focus on understanding the potential disparities associated with machine learning-based decision making in health policy and health economics.