Integration of Patients' Decision-Making in Cost-Effectiveness Analysis of Diabetes Interventions: A Simulation Study Using System Dynamics Modeling

Abstract

Markov-based and discrete event simulation models are widely used in health economic analysis to estimate the long term effects of treatment on clinical and economic outcomes. However, none of them simultaneously integrate patients’ economic resources and their medical decision making in the simulation. This study applied systems dynamics modeling into cost-effectiveness analysis (CEA) of glycemic control treatment. It explored the nonlinear dynamic impacts of patients’ behavior on the cost effectiveness of different interventions to better understand the complexity of diabetes patients’ medical choices in the real world and their impacts on the clinical and economic consequences.Our results showed that the cost-effectiveness ratio varied with patients’ out-of-pocket payment threshold for health care. It suggests that patients’ decision making of cost-related non-adherence with medication should be considered while conducting CEA for treatment of complex chronic condition like diabetes.This study offers insight into the current dynamics of health care costs and outcomes. While providing a framework for CEA with integration of diabetes treatment adherence, it opens up ways of evaluate the complexity of health care for chronic condition in the real world.