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Active Influenza Vaccine Safety Surveillance

Potential Within a Healthcare Claims Environment

Bibliographic Data

ID9101351
AuthorsJeffrey S Brown (0000-0002-9340-7189, Harvard University, corresponding author), Kristen M Moore (Harvard University, corresponding author), M Miles Braun (Center for Biologics Evaluation and Research), Najat Ziyadeh, Najat J Ziyadeh (0000-0002-7191-9140), K Arnold Chan (0000-0001-8161-1986, Harvard University), Grace M Lee (0000-0001-9571-5794, Harvard University, corresponding author), Martin Kulldorff (0000-0002-5284-2993, Harvard University, corresponding author), Alexander Muir Walker (0000-0001-9738-5127, Harvard Pilgrim Health Care, corresponding author), Richard Platt (0000-0002-3248-3583, Harvard Pilgrim Health Care, corresponding author)
Year2009
Volume47
Issue12
Pages1251-1257
Publication date2009-12-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueMedical Care (JOURNAL)
Journal identifiersISSN: 0025-7079 • E-ISSN: 1537-1948
PublisherOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/mlr.0b013e3181b58b5c
PMID19786905
OpenAlexW1974684439
LanguageEN
Citations received1
References cited19

BACKGROUND: Rapid safety assessment of novel vaccines, especially those targeted against pandemic influenza, is a public health priority. OBJECTIVES: Assess the feasibility of using healthcare claims data to rapidly detect influenza vaccine adverse events using sequential analytic methods. RESEARCH DESIGN: Retrospective pilot study simulating prospective surveillance using 6 cumulative monthly administrative claims data extracts. The first included encounters occurring in October; each subsequent extract included an additional month of encounters. Ten adverse events were evaluated, comparing postvaccination rates during the 2006-2007 influenza season to those expected based on rates observed in the prior season. SUBJECTS: Members of a large, multistate health insurer who had a claim for influenza vaccination during the 2005-2006 or 2006-2007 influenza seasons. MEASURES: The completeness of monthly claims extracts. RESULTS: Most vaccinations and outcomes were identified early in the 2006-2007 season; about 50% of vaccinations and short latency events were identified in the second monthly data extract, which would typically become available by mid-December, and 80% of vaccinations and events were identified in the third extract. With respect to overall claims lag, approximately 90% of vaccinations and events were identified within 1 to 2 months after vaccination, regardless of vaccination month. CONCLUSIONS: This study suggests that administrative claims data might contribute to same season influenza vaccine safety surveillance in large, defined populations, especially during a threat of pandemic influenza. Based on our previous work, we believe this method could be applied to multiple health plans' data to monitor a large portion of the US population

Antibody · Business · Immunization · Influenza vaccine · Vaccination · Vaccine safety · Data-Driven Disease Surveillance · Immunology · Influenza Virus Research Studies · Medicine · Pharmacovigilance and Adverse Drug Reactions · Virology

  • Distributed Health Data Networks

    Jeffrey S Brown, John H Holmes et al.•Medical Care•2010

  • Real-Time Vaccine Safety Surveillance for the Early Detection of Adverse Events

    Tracy A Lieu, Martin Kulldorff et al.•Medical Care•2007

Unique citing works1
Citations per year0,06
Citation span2010 - 2010 (1)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 1
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