Examine an array of quantitative methods used by health analytics practitioners to evaluate questions of efficiency and effectiveness in health care. This advanced course integrates and builds on prior coursework in statistics and data mining and provides additional exposure to advanced methodologies, such as event sequencing, analytical groupers, simulation and predictive modeling. Heavy emphasis is given to the application of methods to contemporary analytic challenges in health care, including demand/utilization forecasting, risk stratification, population health management, quality measurement, fraud detection, and cost containment from readmissions. Participants complete a series of hands-on assignments in the use of specific analytic approaches, as well as a final course project.
This is not a self-paced course. Students will progress through the course together. Course modules are released weekly, where lessons typically load on Wednesdays and are due the following Tuesdays. You can log in and work on courses at any time within that week to view lectures and complete assignments. The previous week's lesson will remain available for the duration of the course. If you enroll after the course start date, you will need to contact the instructor regarding missed lessons.