This event is designed for U-M IOE PhD students and faculty and is also open to all U-M students, faculty and staff.

Title:
Genetic Testing Strategies and Flexible Treatment Plans for the Management of Cardiovascular Diseases

Abstract:
Cardiovascular diseases are considered the leading cause of death in the US and worldwide. The management of cardiovascular diseases can be improved by (1) incorporating novel procedures, such as genetic testing, and (2) providing physicians and their patients with flexibility in the implementation of protocols. To understand the clinical and policy implications of genetic testing in cardiovascular diseases, I present a thoroughly validated simulation model to evaluate the impact of genetic information across different populations in the US. Building upon this work, I illustrate a framework that combines dynamic programming with value of information analysis to simultaneously determine optimal cholesterol treatment and genetic testing decisions. To benefit from experts’ opinions and allow for users’ preferences in the implementation of mathematical models, I next introduce a framework that integrates approximate dynamic programming and statistical multiple comparisons to obtain sets of near-optimal treatment choices. By analyzing the structure of the sets, I characterize their behavior with respect to the modeling data and identify when they can be ordered according to the context of the problem. I show how this method can be applied in medical practice by finding hypertension treatment plans for a large population in the US. To conclude my talk, I will discuss future opportunities at the intersection of operations research and statistics to support medical decision-making in practice.

Bio:
Wesley’s research interest lies at the intersection of operations research and statistics, with an emphasis on stochastic simulation and optimization to support decision-making in practice. His current research addresses healthcare applications at a population and patient level. Using population-level data, he focuses on modeling future supply, demand, and allocation of organs for transplantation. Using patient-level data, he develops personalized treatment plans and testing strategies for cardiovascular diseases. Wesley has an ongoing collaboration with the University of Michigan Hospital Medical School, the School of Public Health at the University of Michigan, and the U.S. Department of Veterans Affairs.

Wesley is a recipient of the National Science Foundation Graduate Research Fellowship. Throughout his Ph.D. studies, he has also received the Judith Liebman Award and an honorable mention in the Minority Issues forum from the Institute for Operations Research and the Management Sciences, an American Statistical Association sponsored best poster award at the Michigan Student Symposium for Interdisciplinary Statistical Sciences, as well as a Rackham Merit Fellowship. In addition to his Ph.D. in Industrial and Operations Engineering, Wesley is partaking in the dual master’s program offered by the Department of Statistics at the University of Michigan.