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A Novel Method for Involving Women of Color at High Risk for Preterm Birth in Research Priority Setting
Published on: January 12, 2018
A current landscape of provincial perinatal data collection in Canada
Kiran A Massey1, Laura A Magee2, Sheryll Dale3
1Department of Obstetrics and Gynaecology, University of British Columbia, Vancouver BC; Centre for Advanced Health Research and Evaluation, University of British Columbia, Vancouver BC; BC Women's Hospital and Health Centre, Vancouver BC.
Background:
The Canadian Perinatal Network (CPN) was launched in 2005 as a national perinatal database project designed to identify best practices in maternity care. The inaugural project of CPN is focused on interventions that optimize maternal and perinatal outcomes in women with threatened preterm birth at 22+0 to 28+6 weeks' gestation.
Objective:
To examine existing data collection by perinatal health programs (PHPs) to inform decisions about shared data collection and CPN database construction.
Methods:
We reviewed the database manuals and websites of all Canadian PHPs and compiled a list of data fields and their definitions. We compared these fields and definitions with those of CPN and the Canadian Minimal Dataset, proposed as a common dataset by the Canadian Perinatal Programs Coalition of Canadian PHPs.
Results:
PHPs collect information on 2/3 of deliveries in Canada. PHPs consistently collect information on maternal demographics (including both maternal and neonatal personal identifiers), past obstetrical history, maternal lifestyle, aspects of labour and delivery, and basic neonatal outcomes. However, most PHPs collect insufficient data to enable identification of obstetric (and neonatal) practices associated with improved maternal and perinatal outcomes. In addition, there is between-PHP variability in defining many data fields.
Conclusion:
Construction of a separate CPN database was needed although harmonization of data field definitions with those of the proposed Canadian Minimal Dataset was done to plan for future shared data collection. This convergence should be the goal of researchers and clinicians alike as we construct a common language for electronic health records.
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