146 / 2024-04-22 10:10:48

Delay time modeling of personalized follow-up policies for chronic diseases

follow-up policy; delay time; patient heterogeneity; virtual age

Follow-up policies for chronic diseases are of great significance to prevent adverse outcomes (AOs) and control medical costs. The extant literature on follow-up policies design lack the consideration of time delay that a patient experiences symptoms and goes for treatment. We stratify patient into different risk groups according to the effect of patient heterogeneity on the risk of AOs occurring. The delay time are employed for modeling the two-phase process of developing an AO. After which, two types of complications occurring within different periods are identified and the expected treatment costs are derived accordingly by introducing the stochastic process. As a result, a mixed integer nonlinear programming is constructed to determine the optimal number of follow-up checkups within the planning horizon for patients with heterogeneous risk levels. A case study of pediatric type 1 diabetes mellitus patients is presented to illustrate the applicability and feasibility of the proposed method.