Preventing chronic diseases is an essential aspect of medical care. Physicians monitor patients' risk factors and prescribe necessary medication to aim toward better health outcomes, which means that all patients achieve their health potential while accounting for socially and demographic diverse patient populations. Monitoring too frequently may be unnecessary and costly; however, monitoring the patient infrequently means the patient may forgo needed treatment and experience adverse events related to the disease. To accomplish the optimal monitoring policy, we develop models that: (1) Estimate the patient disease progression and (2) Define policies to prevent chronic diseases using sequential decision-making models. We estimate these stochastic models based on longitudinal observational data from electronic health records for a large cohort of patients seen in the national U.S. Veterans Affairs health system. As a result, these models facilitate clinical interventions for cardiovascular diseases, as they help identify high-risk patients. Also, healthcare providers can now rely on additional tools to decide how to manage chronic diseases accurately across demographic subgroups. I will end the talk by discussing how I will build upon this body of work to address healthcare opportunities for improvement.

Presenter Bio:
Daniel F. Otero-Leon is a Ph.D. candidate in the department of Industrial and Operations Engineering (IOE) at the University of Michigan and is co-advised by Dr. Brian Denton and Dr. Mariel Lavieri of IOE. His research interests are generally in operations research and, more specifically, in stochastic models and stochastic dynamic programming with applications to service systems, including health systems and revenue management. His dissertation research is in the area of data-driven models for improving decision-making in the context of cardiovascular disease, with the help of clinical collaborators at the U.S. Department of Veteran Affairs. His work seeks to develop new frameworks that aim for health equity by considering patients' health disparities in disease prevention policies.