Mother and Infant Research Electronic Data Analysis (MIREDA): A protocol for creating a common data model for federated analysis of UK birth cohorts and the life course

Seaborne, Mike, Jones, Hope, Cockburn, Neil, Durbaba, Stevo, González-Izquierdo, Arturo, Hough, Amy, Mason, Dan, Sánchez-Soriano, Carlos, Orton, Chris, Méndez-Villalon, Armando, Giles, Tom, Ford, David, Quinlan, Phillip, Nirantharakumar, Krish, Poston, Lucilla, Reynolds, Rebecca, Santorelli, Gillian and Brophy, Sinead 2024. Mother and Infant Research Electronic Data Analysis (MIREDA): A protocol for creating a common data model for federated analysis of UK birth cohorts and the life course. International Journal of Population Data Science 9 (2) , 09. 10.23889/ijpds.v9i2.2406

Preview

PDF - Published Version Available under License Creative Commons Attribution. Download (3MB) | Preview

Abstract

Introduction Birth cohorts are valuable resources for studying early life, the determinants of health, disease, and development. They are essential for studying life course. Dynamic longitudinal electronic cohorts use routinely collected data, are live, and can reduce selection bias specifically associated with direct recruitment in traditional birth cohorts. However, they are limited to health and administrative data and may lack contextual information. The MIREDA (Mother and Infant Research Electronic Data Analysis) partnership creates a UK-wide birth cohort by aligning existing electronic birth cohorts to have the same structure, content, and vocabularies, enabling UK-wide federated analyses. Objectives 1) Create a core dynamic, live UK-wide electronic birth cohort with approximately 500,000 new births per year using a common data model (CDM). 2) Provide data linkage and automation for long-term follow up of births from the Clinical Practice Research Datalink (CPRD), MuM-PreDiCT and the `Born in' initiatives of Bradford, Wales, Scotland, and South London for comparable analyses. Methods We will establish core data content and collate linkable data. A suite of extraction, transformation, and load (ETL) tools will be used to transform data for each birth cohort into the CDM. Transformed datasets will remain within each cohort's trusted research environment (TRE). Metadata will be uploaded for the public to the Health Data Research (HDRUK) Innovation Gateway. We will develop a single online data access request for researchers. A cohort profile will be developed for researchers to reference the resource. Ethics Each cohort has approval from their TRE through compliance with their project application processes and information governance. Dissemination We will engage with researchers in the field to promote our resource through partnership networking, publication, research collaborations, conferences, social media, and marketing communications strategies.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Social Sciences (Includes Criminology and Education)
Subjects:	R Medicine > R Medicine (General)
Publisher:	Swansea University
Date of First Compliant Deposit:	19 November 2025
Date of Acceptance:	24 June 2024
Last Modified:	19 Nov 2025 12:42
URI:	https://orca.cardiff.ac.uk/id/eprint/182511

Actions (repository staff only)

Edit Item