A New Type 2 Diabetes Microsimulation Model to Estimate Long-term Health Outcomes, Costs, and Cost-Effectiveness

Published in Value in Health, 2023

Recommended citation: Hoerger, T.J., Hilscher, R., Neuwahl, S., Kaufmann, M. B., Shao, H., Laxy, M., Cheng, Y.J., Benoit, S., Chen, H., Anderson, A. and Craven, T., Yang, W., Cintina,, I., Staimez., L., Zhang, P., the Look AHEAD Research Group. (2023). A New Type 2 Diabetes Microsimulation Model to Estimate Long-term Health Outcomes, Costs, and Cost-Effectiveness. Value in Health https://www.sciencedirect.com/science/article/abs/pii/S1098301523026153


Objective: To develop a microsimulation model to estimate the health effects, costs, and cost-effectiveness of public health and clinical interventions for preventing/managing type 2 diabetes.
Methods: We combined newly developed equations for complications, mortality, risk factor progression, patient utility, and cost—all based on U.S. studies—in a microsimulation model. We performed internal and external validation of the model. To demonstrate the model’s utility, we predicted remaining life-years, quality-adjusted life-years (QALYs), and lifetime medical cost for a representative cohort of 10,000 U.S. adults with type 2 diabetes. We then estimated the cost-effectiveness of reducing HbA1c from 9% to 7% among adults with type 2 diabetes, using low-cost, generic, oral medications.
Results: The model performed well in internal validation; the average absolute difference between simulated and observed incidence for 17 complications was less than 8%. In external validation, the model was better at predicting outcomes in clinical trials than in observational studies. The cohort of U.S. adults with type 2 diabetes was projected to have an average of 19.95 remaining life-years (from mean age 61), incur $187,729 in discounted medical costs, and accrue 8.79 discounted QALYs. The intervention to reduce HbA1c increased medical costs by $1,256 and QALYs by 0.39, yielding an incremental cost-effectiveness ratio of $9,103 per QALY.
Conclusions: Using equations exclusively derived from U.S. studies, this new microsimulation model achieves good prediction accuracy in U.S. populations. The model can be used to estimate the long-term health impact, costs, and cost-effectiveness of interventions for type 2 diabetes in the United States.