Rapid identification of myocardial infarction risk associated with diabetes medications using electronic medical records.

Abstract Objective: To assess the ability to identify potential association(s) of diabetic medications with myocardial infarction (MI) using usual care clinical data obtained from the electronic medical record. Research Design and Methods: We defined a retrospective cohort of patients (n=34,253) treated with a sulfonylurea, metformin, rosiglitazone, or pioglitazone in a single academic health care network. All patients were over 18 years of age with at least one prescription for one of the medications between January 1 st , 2000 and December 31 st , 2006. The study outcome was acute MI requiring hospitalization. We used a cumulative temporal approach to ascertain the calendar date for earliest identifiable risk associated with rosiglitazone compared to other therapies. Results: 11,200, 12,490, 1,879, and 806 patients were prescribed sulfonylurea, metformin, rosiglitazone, or pioglitazone therapy, respectively. 1,343 MIs were identified. After adjustment for potential MI risk factors, relative risk for MI with rosiglitazone was 1.3 (95% CI, 1.1-1.6) compared to sulfonylurea, 2.2 (95% CI, 1.6-3.1) compared to metformin, and 2.2 (95% CI 1.5-3.4) compared to pioglitazone. Prospective surveillance using these data would have identified increased risk for MI with rosiglitazone compared to metformin within 18 months of its introduction with a risk ratio of 2.1 (95% CI 1.2-3.8). Conclusions: Our results are consistent with a relative adverse cardiovascular risk profile for rosiglitazone. Our use of usual care electronic data sources from a large hospital network represents an innovative approach to rapid safety signal detection that may enable more effective post-marketing drug surveillance.