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Methods to establish a Pregnancy Register in the QResearch Database.

Andrew Jhl Snelling1, Emma Copland1,2, Winnie X Mei2

  • 1Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.

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This summary is machine-generated.

A new algorithm created a pregnancy register using electronic health records, facilitating vital research on maternal health during the COVID-19 pandemic. This valuable resource captures delivery and pregnancy loss data for improved understanding of outcomes.

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Area of Science:

  • Epidemiology
  • Health Informatics
  • Reproductive Health

Background:

  • Electronic health records (EHRs) are crucial for pregnancy research due to underrepresentation of pregnant individuals.
  • Combining primary and secondary care data enhances pregnancy research capabilities.
  • This study details an algorithm for a unified pregnancy cohort within the QResearch database during the COVID-19 pandemic's emergency phase.

Purpose of the Study:

  • To develop and describe an algorithm for creating a unified pregnancy cohort in the QResearch database.
  • To facilitate pregnancy-related research by consolidating data from primary and secondary care.
  • To establish a comprehensive resource for studying pregnancy outcomes and events during a specific period.

Main Methods:

  • Linked national primary care records (QResearch®) with Hospital Episode Statistics (HES) data.
  • Included females aged 15-50 with recorded pregnancy outcomes between December 2020 and September 2022.
  • Employed a three-stage algorithm to identify pregnancy episodes and derive start dates using combined or individual data sources.

Main Results:

  • The register includes 266,758 women and 279,027 pregnancies.
  • 83.4% of pregnancies resulted in delivery (99.5% livebirths), and 16.6% were pregnancy losses.
  • Pregnancy loss rates varied by ethnicity, highest in Caribbean (23.1%) and lowest in Pakistani (13.9%) groups.
  • Data sources included HES maternity records (82.4%), primary care (10.6%), HES Admissions (3.4%), and HES Procedures (3.6%).

Conclusions:

  • The QResearch® pregnancy register is a valuable resource for future research.
  • The developed methodology is adaptable for constructing cohorts across different time periods.
  • This approach provides a comprehensive dataset on pregnancy outcomes and events.