Identifying birth defects in automated data sources in the Vaccine Safety Datalink

Elyse Olshen Kharbanda, Gabriela Vazquez-Benitez, Paul A. Romitti, Allison L. Naleway, T. Craig Cheetham, Heather S. Lipkind, Shanthi Sivanandam, Nicola P. Klein, Grace M. Lee, Michael L. Jackson, Simon J. Hambidge, Avalow Olsen, Natalie McCarthy, Frank DeStefano, James D. Nordin

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


Purpose: The Vaccine Safety Datalink (VSD), a collaboration between the Centers for Disease Control and Prevention and several large healthcare organizations, aims to monitor safety of vaccines administered in the USA. We present definitions and prevalence estimates for major structural birth defects to be used in studies of maternal vaccine safety. Methods: In this observational study, we created and refined algorithms for identifying major structural birth defects from electronic healthcare data, conducted formal chart reviews for severe cardiac defects, and conducted limited chart validation for other defects. We estimated prevalence for selected defects by VSD site and birth year and compared these estimates to those in a US and European surveillance system. Results: We developed algorithms to enumerate >50 major structural birth defects from standardized administrative and healthcare data based on utilization patterns and expert opinion, applying criteria for number, timing, and setting of diagnoses. Our birth cohort included 497 894 infants across seven sites. The period prevalence for all selected major birth defects in the VSD from 2004 to 2013 was 1.7 per 100 live births. Cardiac defects were most common (65.4 per 10 000 live births), with one-fourth classified as severe, requiring emergent intervention. For most major structural birth defects, prevalence estimates were stable over time and across sites and similar to those reported in other population-based surveillance systems. Conclusions: Our algorithms can efficiently identify many major structural birth defects in large healthcare datasets and can be used in studies evaluating the safety of vaccines administered to pregnant women.

Original languageEnglish (US)
Pages (from-to)412-420
Number of pages9
JournalPharmacoepidemiology and Drug Safety
Issue number4
StatePublished - Apr 1 2017

Bibliographical note

Publisher Copyright:
Copyright © 2017 John Wiley & Sons, Ltd.


  • congenital anomalies
  • electronic health data
  • pharmacoepidemiology
  • prevalence
  • validity


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