Identifying pregnancy episodes in the Vaccine Safety Datalink [abstract] Abstract uri icon
Overview
abstract
  • Background/Aims: The need for research on the safety of vaccination during pregnancy is widely recognized. Large, population-based data systems like the Vaccine Safety Datalink (VSD) may be useful for this research, but identifying pregnancies using electronic medical record (EMR) and claims data can be challenging. Methods: We modified an existing pregnancy identification algorithm originally developed by Kaiser Permanente Northwest to identify pregnancy outcomes and dates using the standardized VSD data files. We validated the algorithm by calculating the percent agreement in pregnancy outcome type, end date, and gestational age between the algorithm and manual medical record review. At each site, we randomly sampled 15 episodes within four outcome type strata (live births, spontaneous abortions, elective abortions, and other pregnancy outcomes) for a total of 60 episodes per site. Seven of eight VSD sites participated. Results: We identified 595,929 pregnancy episodes ending in 2002-2006 among women 12-55 years of age. Of these pregnancies, 75% ended in live births, 12% in spontaneous abortions, and 9% in elective abortions. We were able to confirm a pregnancy on or near the algorithm-specified pregnancy start and end dates for 99% of live births, 93% of spontaneous abortions, 92% of elective abortions, and 90% of other outcomes. The agreement between the algorithm-identified and the abstractor- indentified outcome date ranged from 70% (elective abortion) to 96% (live birth) depending on outcome type. When gestational age was available in the EMR, agreement ranged from 82% (other) to 98% (live birth) depending on outcome type. Discussion: The VSD algorithm accurately identifies pregnancy episodes across participating sites using the standardized VSD data files. Additional manual record review may be needed to improve the precision of the pregnancy date estimates depending on specific study needs. This algorithm will allow us to conduct large, population-based studies of the safety of vaccination during pregnancy.

  • publication date
  • 2012
  • published in
    Research
    keywords
  • Adverse Effects
  • Data Systems
  • Drugs and Drug Therapy
  • Pregnancy
  • Vaccination
  • Additional Document Info
    volume
  • 10
  • issue
  • 3