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. Lessons will be posted one week at a time. The previous week's lesson will remain available for the duration of the course. Students who enroll after the start date of the course will have to contact the instructor regarding missed lessons.