This was an investigator initiated (Dr Griffin PI) study funded by Pfizer who had no role in the conduct of the study, collection of data, data management, or analysis. Pfizer scientists reviewed and commented on the overall protocol, but had no role in this manuscript. Dr Griffin reports receiving consulting fees from Merck Inc. Drs Choma, Griffin, and Roumie had full access to the data in the study and take responsibility for the integrity and the analysis of data.
An algorithm to identify incident myocardial infarction using Medicaid data †
Article first published online: 28 AUG 2009
Copyright © 2009 John Wiley & Sons, Ltd.
Pharmacoepidemiology and Drug Safety
Volume 18, Issue 11, pages 1064–1071, November 2009
How to Cite
Choma, N. N., Griffin, M. R., Huang, R. L., Mitchel, E. F., Kaltenbach, L. A., Gideon, P., Stratton, S. M. and Roumie, C. L. (2009), An algorithm to identify incident myocardial infarction using Medicaid data . Pharmacoepidem. Drug Safe., 18: 1064–1071. doi: 10.1002/pds.1821
- Issue published online: 22 OCT 2009
- Article first published online: 28 AUG 2009
- Manuscript Accepted: 1 JUL 2009
- Manuscript Revised: 15 JUN 2009
- Manuscript Received: 4 NOV 2008
- myocardial infarction;
Studies of non-steroidal anti-inflammatory drugs (NSAIDs) and cardiovascular events using administrative data require identification of incident acute myocardial infarctions (AMIs) and information on whether confounders differ by NSAID status.
We identified patients with a first AMI hospitalization from Tennessee Medicaid files as those with primary ICD-9 discharge diagnosis 410.x and hospitalization stay of > 2 calendar days. Eligible persons were non-institutionalized, aged 50–84 years between 1999–2004, had continuous enrollment and no AMI, stroke, or non-cardiovascular serious medical illness in the prior year. Of 5524 patients with a potential first AMI, a systematic sample (n = 350) was selected for review. Using defined criteria, we classified events using chest pain history, EKG, and cardiac enzymes, and calculated the positive predictive value (PPV) for definite or probable AMI.
337 of 350 (96.3%) charts were abstracted and 307 (91.1%), 6 (1.8%), and 24 (7.1%) events were categorized as definite, probable, and no AMI, respectively. PPV for any definite or probable AMI was 92.8% (95% CI 89.6–95.2); for an AMI without an event in the past year 91.7% (95% CI 88.3–94.2), and for an incident AMI was 72.7% (95% CI 67.7–77.2). Age-adjusted prevalence of current smoking (46.4% vs. 39.1%, p = 0.35) and aspirin use (36.9% vs. 35.9%, p = 0.90) was similar among NSAID users and non-users
ICD-9 code 410.x had high predictive value for identifying AMI. Among those with AMI, smoking and aspirin use was similar in NSAID exposure groups, suggesting these factors will not confound the relationship between NSAIDs and cardiovascular outcomes. Copyright © 2009 John Wiley & Sons, Ltd.