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

Pharmacoepidemiol Drug Saf. 2013 Jan;22(1):40-54. doi: 10.1002/pds.3310. Epub 2012 Jun 29.


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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, P.H.S.
  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Algorithms*
  • Databases, Factual / statistics & numerical data*
  • Female
  • Humans
  • International Classification of Diseases
  • Male
  • Middle Aged
  • Myocardial Infarction / diagnosis*
  • Myocardial Infarction / epidemiology
  • Outcome Assessment, Health Care / methods
  • Predictive Value of Tests
  • Reproducibility of Results
  • United States
  • United States Food and Drug Administration