Optimal monitoring policies for chronic diseases under healthcare warranty

In this paper, we study a healthcare system consisting of a healthcare provider and heterogeneous patients. We consider that when a patient with a chronic condition is discharged from the hospital, the condition will deteriorate over time and may eventually result in readmissions. To slow chronic disease progression, hospitals need to make a scientific disease monitoring decision over a prespecified period to observe the status of the patient's condition and implement the necessary intervention measures. This work aims to develop a decision-making model from a cost perspective under healthcare warranties for monitoring chronic diseases, where the disease monitoring strategy consists of different types of follow-up checkups. Borrowing from reliability analysis techniques to simulate a system prone to failure, we model the disease dynamics as a reliability problem. We assume that the time to readmission after discharge follows a Weibull distribution and divide patients into different risk groups according to their individual heterogeneity. We also introduce a reduction of intensity model to measure the effect of different follow-up checkups on disease progression. Based on the proposed model, the optimal intervals of the multiple follow-up checkups for monitoring heterogeneous patients under a healthcare warranty can be derived. Finally, a case study involving diabetes patients is presented to validate the proposed model and analyse the effects of critical parameters on the optimal monitoring decisions. This work has potential for reducing hospital readmissions and healthcare costs, and the proposed model can be applied to a broad range of chronic diseases to devise patient-specific disease monitoring plans. • A decision-making model for monitoring chronic disease progression under healthcare warranties is proposed. • The proposed model includes multiple levels of follow-up checkups at different intervals. • Reliability analysis techniques are introduced to model disease dynamics and effectiveness of different follow-up checkups. • A case study is presented to demonstrate the proposed model based on data from a large general hospital in Tianjin, China.