OBJECTIVE: To assess the economic impact of augmentation therapy [thiazolidinediones (TZDs) or metformin] in type 2 diabetes patients who initiated mono-therapy with sulfonylurea.METHODS: A retrospective cohort design was used to meet the study objective. Patients newly diagnosed with type 2 diabetes and initiating therapy with sulfonylurea were identified during the four-year period (1998-2001) from a Medicaid claims database. These patients were then followed till they augmented therapy by adding another oral hypoglycemic agent (TZDs or metformin) to their regimen. The date of the first prescription for a TZD or metformin was treated as the index date and type 2 diabetes-related costs in the 12-month follow-up period were assessed. Semi-logarithmic OLS models were used to estimate the impact of therapy on total diabetes-related costs. Costs were also examined separately in terms of diabetes-related Emergency Room (ER)/hospitalization, outpatient and prescription costs using appropriate two-part models.RESULTS: The final cohort consisted of 298 type 2 diabetes patients who initiated mono-therapy with sulfonylureas and augmented with either TZDs (n=96) or metformin (n=202). Results of the semi-log OLS model indicated that patients augmenting sulfonylurea therapy with metformin incurred 33.27% lower total diabetes-related costs as compared to those augmenting therapy with TZDs (p<0.001). Further breakdown of the costs indicated that there were no significant differences in diabetes-related ER/Hospitalization and outpatient costs between the two groups. However, diabetes-related prescription costs were 45.47% lower for patients augmenting with metformin as compared those augmenting with TZDs (p<0.001). CONCLUSION: Patients with type 2 diabetes initiated on mono-therapy with sulfonylureas and augmenting with metformin have significantly lower type 2 diabetes-related costs as compared to those augmenting with TZDs, primarily due to lower prescription costs. The study results can aid in making important formulary decisions and developing treatment algorithms for management of type 2 diabetes.