Dynamic Monitoring and Control of Irreversible Chronic Diseases with Application to Glaucoma

47 Pages Posted: 18 Feb 2016

See all articles by Pooyan Kazemian

Pooyan Kazemian

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Jonathan Helm

Indiana University - Kelley School of Business - Department of Operation & Decision Technologies

Mariel Lavieri

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Joshua Stein

University of Michigan at Ann Arbor - Medical School

Mark P. Van Oyen

University of Michigan at Ann Arbor

Date Written: February 16, 2016

Abstract

To effectively manage chronic disease patients, clinicians must know (1) how to monitor each patient (i.e., when to schedule the next visit and which tests to take), and (2) how to control the disease (i.e., what levels of controllable risk factors will sufficiently slow progression). Our research addresses these questions simultaneously and provides the optimal solution to a novel linear quadratic Gaussian state space model. For the new objective of minimizing the relative change in state over time (i.e., disease progression), which is necessary for management of irreversible chronic diseases, we show that the classical two-way separation of estimation and control holds, thereby making a previously intractable problem solvable by decomposition into two separate, tractable problems while maintaining optimality. The resulting optimization is applied to the management of glaucoma. Based on data from two large randomized clinical trials, we validate our model and demonstrate how our decision support tool can provide actionable insights to the clinician caring for a patient with glaucoma. This methodology can be applied to a broad range of irreversible chronic diseases to optimally devise patient-specific monitoring and treatment plans.

Keywords: chronic disease monitoring, treatment control, glaucoma, target IOP, linear quadratic Gaussian systems modeling, optimal control theory, dynamic programming

Suggested Citation

Kazemian, Pooyan and Helm, Jonathan and Lavieri, Mariel and Stein, Joshua and Van Oyen, Mark P., Dynamic Monitoring and Control of Irreversible Chronic Diseases with Application to Glaucoma (February 16, 2016). Kelley School of Business Research Paper No. 16-22, Available at SSRN: https://ssrn.com/abstract=2733399 or http://dx.doi.org/10.2139/ssrn.2733399

Pooyan Kazemian (Contact Author)

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

1205 Beal Avenue
Ann Arbor, MI 48109
United States

Jonathan Helm

Indiana University - Kelley School of Business - Department of Operation & Decision Technologies ( email )

Business 670
1309 E. Tenth Street
Bloomington, IN 47401
United States

Mariel Lavieri

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

1205 Beal Avenue
Ann Arbor, MI 48109
United States

Joshua Stein

University of Michigan at Ann Arbor - Medical School ( email )

Ann Arbor, MI
United States

Mark P. Van Oyen

University of Michigan at Ann Arbor ( email )

500 S. State Street
Ann Arbor, MI 48109
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
217
Abstract Views
836
rank
158,693
PlumX Metrics