Title

Validation of acute myocardial infarction in the Food and Drug Administration's Mini-Sentinel program

Authors

Sarah L. Cutrona, University of Massachusetts Medical SchoolFollow
Sengwee Toh, Harvard Medical School
Aarthi Iyer, Harvard Pilgrim Health Care Institute, Boston
Sarah Foy, University of Massachusetts Medical School
Gregory W. Daniel, Brookings Institution
Vinit P. Nair, Humana Inc.
Daniel Ng, Kaiser Permanente
Melissa G. Butler, Kaiser Permanente
Denise M. Boudreau, Group Health Center for Health Studies
Susan Forrow, Harvard Pilgrim Health Care Institute, Boston
Robert J. Goldberg, University of Massachusetts Medical SchoolFollow
Joel M. Gore, University of Massachusetts Medical SchoolFollow
David D. McManus, University of Massachusetts Medical School WorcesterFollow
Judith A. Racoosin, Food and Drug Administration
Jerry H. Gurwitz, University of Massachusetts Medical SchoolFollow

UMMS Affiliation

Department of Medicine, Division of Geriatric Medicine; Meyers Primary Care Institute; Department of Medicine, Division of Cardiovascular Medicine

Publication Date

2013-1

Document Type

Article

Subjects

Myocardial Infarction; Algorithms; Outcome Assessment (Health Care)

Disciplines

Cardiology | Cardiovascular Diseases | Health Services Administration | Health Services Research

Abstract

PURPOSE: To validate an algorithm based upon International Classification of Diseases, 9(th) revision, Clinical Modification (ICD-9-CM) codes for acute myocardial infarction (AMI) documented within the Mini-Sentinel Distributed Database (MSDD).

METHODS: Using an ICD-9-CM-based algorithm (hospitalized patients with 410.x0 or 410.x1 in primary position), we identified a random sample of potential cases of AMI in 2009 from four Data Partners participating in the Mini-Sentinel Program. Cardiologist reviewers used information abstracted from hospital records to assess the likelihood of an AMI diagnosis based on criteria from the Joint European Society of Cardiology and American College of Cardiology Global Task Force. Positive predictive values (PPVs) of the ICD-9-based algorithm were calculated.

RESULTS: Of the 153 potential cases of AMI identified, hospital records for 143 (93%) were retrieved and abstracted. Overall, the PPV was 86.0% (95% confidence interval; 79.2%, 91.2%). PPVs ranged from 76.3% to 94.3% across the four Data Partners.

CONCLUSIONS: The overall PPV of potential AMI cases, as identified using an ICD-9-CM-based algorithm, may be acceptable for safety surveillance; however, PPVs do vary across Data Partners. This validation effort provides a contemporary estimate of the reliability of this algorithm for use in future surveillance efforts conducted using the Food and Drug Administration's MSDD.

Copyright © 2012 John Wiley & Sons, Ltd.

Keywords

UMCCTS funding

DOI of Published Version

10.1002/pds.3310

Source

Pharmacoepidemiol Drug Saf. 2013 Jan;22(1):40-54. doi: 10.1002/pds.3310. Link to article on publisher's site

Journal/Book/Conference Title

Pharmacoepidemiology and drug safety

Related Resources

Link to article in PubMed

PubMed ID

22745038

Repository Citation

Cutrona SL, Toh S, Iyer A, Foy S, Daniel GW, Nair VP, Ng D, Butler MG, Boudreau DM, Forrow S, Goldberg RJ, Gore JM, McManus DD, Racoosin JA, Gurwitz JH. (2013). Validation of acute myocardial infarction in the Food and Drug Administration's Mini-Sentinel program. Meyers Health Care Institute Publications. https://doi.org/10.1002/pds.3310. Retrieved from https://escholarship.umassmed.edu/meyers_pp/591