This course provides an introduction to state-of-the-art analytical methods widely used in the healthcare industry. Students will gain exposure to a wide array of data across different healthcare settings (such as clinical data, encounter data, and health insurance claims data). The goal is to demonstrate how healthcare data can be used to generate insights and actionable items that can help various stakeholders (e.g., providers, patients, and regulatory agencies) improve business processes and deliver care at the most cost effective point. We will provide an in-depth treatment of core methods in healthcare evaluation, health economics and outcome research (HEOR), and predictive analytics. The course consists of three modules: (1) healthcare data processing and reporting; (2) quality and outcome measurement; and (3) modeling and predicting outcome and cost. We will be using R as the main statistical tool throughout the course.

Lecture Hours: 3.00 Lab Hours: 0Total Hours: 3.00