Evaluating cost-effectiveness of treatment options for diabetes patients using system dynamics modeling

The growing global diabetes epidemic is a serious public health problem. We developed a system dynamic model to study the cost-effectiveness of different diabetes treatment options. According to existing literature, we estimated dynamic costs and changes of hemoglobin A1c levels of two first-line monotherapies and a hypothetical innovation therapy for glycemic control over a 15-year horizon. Incremental cost-effectiveness ratios were expressed as dollars per HbA1c decrement from perspectives of the patient, insurance-payer, and society. Simulation results showed that better adherence with a more expensive and efficacious drug results in better control of HbA1c and cost-saving in the long-run. The results also showed that the cost-effectiveness ratio varied with patients' pre-determined out-of-pocket payment for health expenditure. The higher the rate of their out-of-pocket payment for extra health care expenditure to their household income, the more cost-effective it is for the innovative drug from the perspectives of the patient, insurance-payer, and society.