A New Type 2 Diabetes Microsimulation Model to Estimate Long-Term Health Outcomes, Costs, and Cost-Effectiveness - Hoerger, Thomas J.; Hilscher, Rainer; Neuwahl, Simon; Kaufmann, Matthew B.; Shao, Hui; Laxy, Michael; Cheng, Yiling J.; Benoit, Stephen; Chen, Haiying; Anderson, Andrea; Craven, Tim; Yang, Wenya; et al. (Value in health, 2023)
This study aimed 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. We combined newly developed equations for complications, mortality, risk factor progression, patient utility, and cost—all based on US 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 US adults with type 2 diabetes. We then estimated the cost-effectiveness of reducing hemoglobin A1c from 9% to 7% among adults with type 2 diabetes, using low-cost, generic, oral medications. The model performed well in internal validation; the average absolute difference between simulated and observed incidence for 17 complications was < 8%. In external validation, the model was better at predicting outcomes in clinical trials than in observational studies. The cohort of US 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 hemoglobin A1c increased medical costs by $1256 and QALYs by 0.39, yielding an incremental cost-effectiveness ratio of $9103 per QALY. Using equations exclusively derived from US studies, this new microsimulation model achieves good prediction accuracy in US 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. •Existing type 2 simulation models implement risk equations derived from UK data. This model is based on newly derived risk equations developed for the United States. This model can be used to predict remaining life-years, costs, and quality-adjusted life-years for different cohorts of type 2 patients.•Existing type 2 simulation models are limited in their extendability. This microsimulation introduces a highly modular architecture that allows for easy addition of new modules (types of diabetes, complications). A wide variety of interventions can be implemented, informing policy decision making.