PURPOSE: The Food and Drug Administration's Mini-Sentinel pilot program initially aims to conduct active surveillance to refine safety signals that emerge for marketed medical products. A key facet of this surveillance is to develop and understand the validity of algorithms for identifying health outcomes of interest from administrative and claims data. This article summarizes the process and findings of the algorithm review of anaphylaxis. METHODS: PubMed and Iowa Drug Information Service searches were conducted to identify citations applicable to the anaphylaxis health outcome of interest. Level 1 abstract reviews and Level 2 full-text reviews were conducted to find articles using administrative and claims data to identify anaphylaxis and including validation estimates of the coding algorithms. RESULTS: Our search revealed limited literature focusing on anaphylaxis that provided administrative and claims data-based algorithms and validation estimates. Only four studies identified via literature searches provided validated algorithms; however, two additional studies were identified by Mini-Sentinel collaborators and were incorporated. The International Classification of Diseases, Ninth Revision, codes varied, as did the positive predictive value, depending on the cohort characteristics and the specific codes used to identify anaphylaxis. CONCLUSIONS: Research needs to be conducted on designing validation studies to test anaphylaxis algorithms and estimating their predictive power, sensitivity, and specificity.
PURPOSE: The Food and Drug Administration's Mini-Sentinel pilot program initially aims to conduct active surveillance to refine safety signals that emerge for marketed medical products. A key facet of this surveillance is to develop and understand the validity of algorithms for identifying health outcomes of interest from administrative and claims data. This article summarizes the process and findings of the algorithm review of anaphylaxis. METHODS: PubMed and Iowa Drug Information Service searches were conducted to identify citations applicable to the anaphylaxis health outcome of interest. Level 1 abstract reviews and Level 2 full-text reviews were conducted to find articles using administrative and claims data to identify anaphylaxis and including validation estimates of the coding algorithms. RESULTS: Our search revealed limited literature focusing on anaphylaxis that provided administrative and claims data-based algorithms and validation estimates. Only four studies identified via literature searches provided validated algorithms; however, two additional studies were identified by Mini-Sentinel collaborators and were incorporated. The International Classification of Diseases, Ninth Revision, codes varied, as did the positive predictive value, depending on the cohort characteristics and the specific codes used to identify anaphylaxis. CONCLUSIONS: Research needs to be conducted on designing validation studies to test anaphylaxis algorithms and estimating their predictive power, sensitivity, and specificity.
Authors: Yihua Xu; Xiaofeng Zhou; Brandon T Suehs; Abraham G Hartzema; Michael G Kahn; Yola Moride; Brian C Sauer; Qing Liu; Keran Moll; Margaret K Pasquale; Vinit P Nair; Andrew Bate Journal: Drug Saf Date: 2015-08 Impact factor: 5.606
Authors: Nicole C Wright; Jeffrey R Curtis; Tarun Arora; Wilson K Smith; Meredith L Kilgore; Kenneth G Saag; Monika M Safford; Elizabeth S Delzell Journal: PLoS One Date: 2015-07-10 Impact factor: 3.240
Authors: Artemio M Jongco; Sheila Bina; Robert J Sporter; Marie A Cavuoto Petrizzo; Blanka Kaplan; Myriam Kline; Susan J Schuval Journal: J Allergy (Cairo) Date: 2016-02-21