OBJECTIVES: Despite the existence of many cost-effective medical and public health interventions in prevention and treatment of diabetes, prevalence and cost of diabetes are growing in China as well as the rest of world. In order to integrate and allocate health system resources to control diabetes successfully, it is necessary to develop dynamic economic evaluation for patient-centered diabetes care from a system perspective. METHODS: Based on system dynamic (SD) modeling, this study develops a framework to depict the structure and feedback loops that generate nonlinear relationship between cause and effect in diabetes management. It also uses multichannel datasets in China to validate the model and simulate the costs and effectiveness of different diabetes management interventions and the impact of health insurance policies. Specifically, the framework illustrates a patient’s decision making process in physical activities and medication choices and their related cost, clinical outcome, and quality of life over time. It also illustrates how an individual’s budget constraint, time constraints and health insurance policy influence their behaviors. The key stock and flow variables in the model are, direct and indirect costs of care, real and perceived risk of diabetes complication, quality of life (QoL), financial burdens, and exercise time.  RESULTS: AND CONCLUSIONS: The study provides insights on how to evaluate cost and effectiveness of type 2 diabetes interventions under the complex scenarios of multi-drug taking, switching drug, and lifestyle changing simultaneously. It suggests that systemic dynamic simulations on cost-effectiveness analysis based on real world data can be a new vehicle for economic analysis along with RTC trails for decision making. The study also builds up a foundation to identify key factors and obstacles in changing patient behavior and providing efficient interventions.