Methods: We developed a DM economic model using Ontario-specific parameters using data on more than 734,000 persons with DM from 1992-2002. Using this new model, we conducted a cost-effectiveness analysis based on patient-level data from an observational study involving 404 patients with DM. Changes in intermediate outcomes (i.e. HbA1c, blood pressure, cholesterol, and smoking status) at the end of the intervention were measured and used as risk factors in the Ontario Diabetes Economic Model (ODEM) to estimate the cumulative first event rates for 7 DM-related complications, the mean difference in cost, and expected quality-adjusted life-years (QALYs). Incremental cost-effectiveness ratios (ICER) were calculated based on the net cost of healthcare resources associated with the program and on effectiveness estimated over a patient's lifetime. In the base case, the ICER was calculated assuming the effect of the intervention continued for 1 year using a discount rate of 3% and a time horizon of 40 years. Sensitivity analyses were conducted by varying the duration of the program and treatment effect.
Results: The multifaceted DM management program reduced HbA1c by approximately 1.02% (95% CI: -1.25%; -0.79%, p<0.001), systolic blood pressure by 1.32 mmHg (95% CI: -3.42; 0.78, p=0.219), and total cholesterol by 0.47 mg/dL (95% CI: -0.58; -0.35, p<0.001) while HDL cholesterol increased by 0.06 mg/dL (95% CI: 0.03; 0.09, p<0.001). The model predicted that these changes in risk factors would prevent 16.2 per 1,000 deaths, 15.5 per 1,000 myocardial infarctions and a relative risk reduction of 50% in first amputations. The lifetime incremental cost per QALY gained for improved diabetes management for the program effect lasting for 1 year was $5,527. However, if the program and treatment effect continued for 10 years, the ODEM estimated the ICER to be $4,448 per QALY.
Conclusions: This multifaceted diabetes management program improved short-term clinical outcomes for study participants. The results from the cost-effectiveness analysis using the ODEM reveal that the program represents good value for money and the increased costs of program implementation were partly offset as the duration of the program was increased.