The objective of this Faculty Early Career Development (CAREER) grant is to create new methodology that enables the integration of operational and disease management decisions for patients with chronic diseases. This project focuses on (1) determining when and how to screen, monitor and treat chronic-disease patients given that each patient's disease progression parameter values are not known, (but learned over time), and (2) improving resource allocation given optimal screening, monitoring and treatment decisions over the patient's lifetime. Through a multidisciplinary collaboration with clinicians and managers, the new methodologies created in this award will first be applied to the management of three chronic diseases: glaucoma, bladder cancer, and hypertension. However, it is anticipated that these methodologies will be applicable to other chronic diseases as well. This work will support graduate, undergraduate, and precollege students with attention to underrepresented students. The results of the project will be widely disseminated to engineering and medical communities through user-friendly tools, conference presentations, and journal publications.
The research team will create a novel modeling framework that combines results in survival analysis with a representation of disease progression and intervention using continuous, partially observable state space models of patients within the population. This will be done by (1) dynamically incorporating each patient's disease history into the parameterization of the stochastic model of disease-state evolution, rather than using static population-wide parameter values, (2) comparing policies that lead to improvements from each patient's perspective, rather than those that are based on using constrained resources to improve the health outcomes of the population, and (3) exploiting structural properties of the state-space disease-evolution models to enhance the computation of optimal solutions to problems that use these models in the unified methodology.
