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Connected Bradford:  a Whole System Data Linkage Accelerator

The richness of linked population data provides exciting opportunities to understand local health needs, identify and predict those in most need of support and evaluate health interventions. There has been extensive investment to unlock the potential of clinical data for health research in the UK. H...

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Detalles Bibliográficos
Autores principales: Sohal, Kuldeep, Mason, Dan, Birkinshaw, John, West, Jane, McEachan, Rosemary R.C., Elshehaly, Mai, Cooper, Duncan, Shore, Rob, McCooe, Michael, Lawton, Tom, Mon-Williams, Mark, Sheldon, Trevor, Bates, Chris, Wood, Megan, Wright, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9682213/
https://www.ncbi.nlm.nih.gov/pubmed/36466951
http://dx.doi.org/10.12688/wellcomeopenres.17526.2
Descripción
Sumario:The richness of linked population data provides exciting opportunities to understand local health needs, identify and predict those in most need of support and evaluate health interventions. There has been extensive investment to unlock the potential of clinical data for health research in the UK. However, most of the determinants of our health are social, economic, education, environmental, housing, food systems and are influenced by local authorities. The Connected Bradford Whole System Data Linkage Accelerator was set up to link health, education, social care, environmental and other local government data to drive learning health systems, prevention and population health management. Data spanning a period of over forty years has been linked for 800,000 individuals using the pseudonymised NHS number and other data variables. This prospective data collection captures near real time activity. This paper describes the dataset and our Connected Bradford Whole System Data Accelerator Framework that covers public engagement; practitioner and policy integration; legal and ethical approvals; information governance; technicalities of data linkage; data curation and guardianship; data validity and visualisation.