ArticleInternational journal of technology assessment in health care2025
Development and validation of a type 2 diabetes model to estimate the cost-effectiveness of diabetes interventions across the care continuum.
Article in International journal of technology assessment in health care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesThe aim of this study is to develop a patient-level model for type 2 diabetes mellitus (T2DM) progression that can estimate the cost-effectiveness of T2DM interventions from prevention to management.
methodsWe developed an individual-level microsimulation model, the Institute of Health Economics Diabetes Model (IHE-DM), that simulates: (i) T2DM progression from normal glucose tolerance (NGT) to T2DM, (ii) the occurrence and timing of eight comorbidities and death, and (iii) the correlated progression of risk factors over time. We report model validation and use a case study to investigate the cost-effectiveness of a hypothetical T2DM prevention program.
resultsThe internal validation indicated excellent performance with mean absolute differences between the predicted and observed values for all endpoints of less than 1 percent. External validation results were mixed. The model under-predicted cumulative T2DM incidence in the first 8 years, predicted well from years eight through eleven, and over-predicted from years twelve through fifteen. Our case study estimated an incremental net monetary benefit of CAD 2,701 (USD 2,289) (95% Uncertainty Interval: CAD 1,316 to 4,000 [USD 1,115 to 3,390]) over the 15-year time horizon.
conclusionsProminent T2DM models focus on patients with diagnosed T2DM whereas our model simulates progression from NGT to T2DM and incorporates important correlations in the progression of risk factors. These adaptations allow us to evaluate preventative interventions and better capture the long-term impacts, filling an important gap in the evidence base. Our model can be used to inform future funding decisions for T2DM interventions across the care continuum.
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