Born and Bred in (BaBi): an efficient, place-based birth e-cohort network

<ns3:p>Background Routine datasets are increasingly used in research to learn more about health and care systems over time. This paper describes the protocol for a novel, multi-site, life course e-cohort embedded in standard clinical practice: The Born and Bred in (BaBi) network. BaBi aims to link routinely collected data for mothers and babies at local and national levels for research and decision-making. Method The BaBi network e-cohort uses an active consent process, where trained healthcare practitioners (predominantly midwives) gain consent from pregnant women during their routine antenatal appointments. This is documented in electronic patient records and allows identifiable routine data from multiple health, social care, and educational sources to be linked over a mother and baby’s life. Consent to contact is also gathered, providing a platform to approach recruited participants about future research opportunities. BaBi provides a long-term, sustainable, applied research platform that promotes inclusivity in research and transparent use of data. The BaBi network aims to harness the power of locally linked routinely collected data to help shape local services and to bring together data from local cohorts to create a meta-cohort that can be used to address questions of national relevance. The model provides opportunities for all pregnant women to take part with no restrictive eligibility criteria, promoting participation from a wide range of diverse and underserved populations. The minimal participant burden, coupled with the embedded consent approach through antenatal services, aims to ensure less systematic bias in representativeness than that seen in more traditional cohort methods.</ns3:p>

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Publication Details

Journal
NIHR Open Research
Published
2025-08-18
DOI
https://doi.org/10.3310/nihropenres.13996.1
Primary Topic
Health, Environment, Cognitive Aging
Type
article
Field-Weighted Citation Impact
0.00

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article

Born and Bred in (BaBi): an efficient, place-based birth e-cohort network

Kate Robinson, J. Appleyard, Dan Mason, Kayley Ciesla et al.
NIHR Open Research
Health, Environment, Cognitive Aging
article

Born and Bred in (BaBi): an efficient, place-based birth e-cohort network

Kate Robinson, J. Appleyard, Dan Mason, Kayley Ciesla, Katharine Roberts, Maria Bryant, Sally Bridges, Diane Farrar, John Wright, Hollie Henderson, Alex Newsham, Sabah Shaib
article en

Abstract

<ns3:p>Background Routine datasets are increasingly used in research to learn more about health and care systems over time. This paper describes the protocol for a novel, multi-site, life course e-cohort embedded in standard clinical practice: The Born and Bred in (BaBi) network. BaBi aims to link routinely collected data for mothers and babies at local and national levels for research and decision-making. Method The BaBi network e-cohort uses an active consent process, where trained healthcare practitioners (predominantly midwives) gain consent from pregnant women during their routine antenatal appointments. This is documented in electronic patient records and allows identifiable routine data from multiple health, social care, and educational sources to be linked over a mother and baby’s life. Consent to contact is also gathered, providing a platform to approach recruited participants about future research opportunities. BaBi provides a long-term, sustainable, applied research platform that promotes inclusivity in research and transparent use of data. The BaBi network aims to harness the power of locally linked routinely collected data to help shape local services and to bring together data from local cohorts to create a meta-cohort that can be used to address questions of national relevance. The model provides opportunities for all pregnant women to take part with no restrictive eligibility criteria, promoting participation from a wide range of diverse and underserved populations. The minimal participant burden, coupled with the embedded consent approach through antenatal services, aims to ensure less systematic bias in representativeness than that seen in more traditional cohort methods.</ns3:p>

NIHR Open ResearchVol. 5
Bradford Teaching Hospitals NHS Foundation Trust (GB), Hull York Medical School (GB)
National Institute for Health and Care Research, Department of Health and Social Care
Openalex Percentile: Top 72%
Health, Environment, Cognitive Aging
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