MCFAM Seminar Series: “Analysis of Prescription Drug Utilization with Beta Regression Models"
About the lecture
The healthcare sector in the U.S. is a complex and large sector that generates about 20 percent of the country's gross domestic product. Healthcare analytics has been used by researchers and practitioners to better understand the industry. In this talk, Professor Gan will present his recent work about the use of Beta regression models to understand the variability of brand name drug utilization across different areas with the U.S. The models are fitted to public datasets obtained from the Medicare & Medicaid Services and the Internal Revenue Service. Integrated Nested Laplace Approximation (INLA) is used to perform the inference. Professor Gan will also present some numerical results showing the performance of Beta regression models.
About the speaker
Guojun Gan is an associate professor in the Department of Mathematics at the University of Connecticut, where he has been since August 2014. Prior to that, he worked at a large life insurance company in Toronto, Canada, for six years and a hedge fund in Oakville, Canada, for one year. He received a bachelor's degree from Jilin University, Changchun, China, in 2001 and master's and Ph.D. degrees from York University, Toronto, Canada, in 2003 and 2007, respectively. He is also a Fellow of the Society of Actuaries (FSA). His research interests are in the interdisciplinary areas of actuarial science and data science.