HS 339F — Advanced Topics in Health Care Data Analytics and Data Mining

Prerequisite: HS 256f or permission of the instructor. Meets for one-half semester and yields half-course credit.

Methodological course on concepts, techniques and applications of data analytics as applied to healthcare big data. Healthcare payers, providers, and government agencies around the globe have expanded their investments in all sorts of healthcare data including insurance claims, EHR, registries, surveillance, patient surveys, household surveys, and other datasets so that the healthcare industry has already entered the club of “big data” providers. In terms of techniques and methods, the course emphasizes more on the predictive analytics, certain statistical analysis on big data, and some machine learning algorithms including cluster analysis. Students will also learn about the major commercial and public episode grouper software applications as examples of supervised learning models in healthcare. Usually offered every year.
Moaven Razavi