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Validation of anaphylaxis in the Food and Drug Administration's Mini-Sentinel
University of Massachusetts Medical School Faculty Publications
  • Kathleen E. Walsh, University of Massachusetts Medical School
  • Sarah L. Cutrona, University of Massachusetts Medical School
  • Sarah Foy, University of Massachusetts Medical School Worcester
  • Meghan A. Baker, Brigham and Women's Hospital
  • Susan Forrow, Harvard Pilgrim Health Care Institute, Boston
  • Azadeh Shoaibi, U.S. Food and Drug Administration
  • Pamala A. Pawloski, HealthPartners Research Foundation
  • Michelle Conroy, Massachusetts General Hospital
  • Andrew M. Fine, Harvard Medical School
  • Lise E. Nigrovic, Harvard Medical School
  • Nandini Selvam, HealthCore, Inc.
  • Mano S. Selvan, Humana Inc.
  • William O. Cooper, Vanderbilt University
  • Susan E. Andrade, University of Massachusetts Medical School
UMMS Affiliation
Meyers Primary Care Institute; Department of Pediatrics; Department of Medicine
Publication Date
Document Type

PURPOSE: We aim to develop and validate the positive predictive value (PPV) of an algorithm to identify anaphylaxis using health plan administrative and claims data. Previously published PPVs for anaphylaxis using International Classification of Diseases, ninth revision, Clinical Modification (ICD-9-CM) codes range from 52% to 57%.

METHODS: We conducted a retrospective study using administrative and claims data from eight health plans. Using diagnosis and procedure codes, we developed an algorithm to identify potential cases of anaphylaxis from the Mini-Sentinel Distributed Database between January 2009 and December 2010. A random sample of medical charts (n = 150) was identified for chart abstraction. Two physician adjudicators reviewed each potential case. Using physician adjudicator judgments on whether the case met diagnostic criteria for anaphylaxis, we calculated a PPV for the algorithm.

RESULTS: Of the 122 patients for whom complete charts were received, 77 were judged by physician adjudicators to have anaphylaxis. The PPV for the algorithm was 63.1% (95%CI: 53.9-71.7%), using the clinical criteria by Sampson as the gold standard. The PPV was highest for inpatient encounters with ICD-9-CM codes of 995.0 or 999.4. By combining only the top performing ICD-9-CM codes, we identified an algorithm with a PPV of 75.0%, but only 66% of cases of anaphylaxis were identified using this modified algorithm.

CONCLUSIONS: The PPV for the ICD-9-CM-based algorithm for anaphylaxis was slightly higher than PPV estimates reported in prior studies, but remained low. We were able to identify an algorithm that optimized the PPV but demonstrated lower sensitivity for anaphylactic events.

  • UMCCTS funding
DOI of Published Version
Walsh, K. E., Cutrona, S. L., Foy, S., Baker, M. A., Forrow, S., Shoaibi, A., Pawloski, P. A., Conroy, M., Fine, A. M., Nigrovic, L. E., Selvam, N., Selvan, M. S., Cooper, W. O. and Andrade, S. (2013), Validation of anaphylaxis in the Food and Drug Administration's Mini-Sentinel. Pharmacoepidem. Drug Safe., 22: 1205–1213. doi: 10.1002/pds.3505. Link to article on publisher's site
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Link to Article in PubMed
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Citation Information
Kathleen E. Walsh, Sarah L. Cutrona, Sarah Foy, Meghan A. Baker, et al.. "Validation of anaphylaxis in the Food and Drug Administration's Mini-Sentinel" Vol. 22 Iss. 11 (2013) ISSN: 1053-8569 (Linking)
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