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Hoerger, T.J.* ; Hilscher, R.* ; Neuwahl, S.* ; Kaufmann, M.B.* ; Shao, H.* ; Laxy, M. ; Cheng, Y.J.* ; Benoit, S.* ; Chen, H.* ; Anderson, A.* ; Craven, T.* ; Yang, W.* ; Cintina, I.* ; Staimez, L.* ; Zhang, P.*

A new type 2 diabetes microsimulation model to estimate long-term health outcomes, costs, and cost-effectiveness.

Value Health 26, 1372-1380 (2023)

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OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

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