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

• Published in: Production and operations management Vol. 28; no. 5; pp. 1082 - 1107
• Main Authors: Kazemian, Pooyan, Helm, Jonathan E., Lavieri, Mariel S., Stein, Joshua D., Van Oyen, Mark P.
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.05.2019; Blackwell Publishers Inc
• Subjects: chronic disease monitoring and treatment; Chronic illnesses; Decision support systems; Disease; Disease management; Glaucoma; Kalman filter; medical decision making; Optimization; personalized care; personalized care; chronic disease monitoring and treatment; medical decision making; glaucoma; Kalman filter
• ISSN: 1059-1478; 1937-5956; 1937-5956
• DOI: 10.1111/poms.12975

To manage chronic disease patients effectively, clinicians must know (i) how to monitor each patient (i.e., when to schedule the next visit and which tests to take), and (ii) 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 objective of minimizing the relative change in state over time (i.e., disease progression), which is necessary for managing irreversible chronic diseases while also considering the cost of tests and treatment, we show that the classical two‐way separation of estimation and control holds. This makes 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 devise patient‐specific monitoring and treatment plans optimally.