A Whole Systems Approach to Addressing Wider Determinants of Health: The Case of Connected Bradford

Abstract: 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 40 years have been linked for more than 600,000 individuals using the pseudonymised NHS number and other data variables. This prospective data collection captures near real time activity. Using recently developed interactive dashboards, we can demonstrate how researchers, stakeholders, and policy makers can use Connected Bradford to shape early interventions and influence policy to prevent adverse life outcomes across the district. The application of this interactive tool in developing and answering research questions will be discussed using 2 case studies:

1. Using the Early Years Foundation Stage Profile (EYFSP) as a screener for children’s long-term educational outcomes: Evidence from a population linked database (by Dr Megan Wood)

The benefits of early identification and intervention are well-established but often time- and resource-expensive. The aim of this study was twofold: i) replicate previous findings showing the relationship between the Early Years Foundation Stage Profile (EYFSP) and later educational outcomes at the end of Key Stage One and Special Education Needs (SEN) status; ii) illustrate the potential of using connected data for improving children’s life chances.

2. Can air filtration devices reduce illness transmission in classrooms? (by Sam Relins)

It is becoming increasingly clear that classroom air quality has an impact on the health of our school children. Studies have shown that poorly ventilated classroom spaces contribute to an increase in transmission of airborne illnesses. This study aims to evaluate the effectiveness of these interventions as children returned to school in September 2021 and over the Delta and Omicron waves of the virus.

Bios:

Rob Shore - Rob's role is funded by the NIHR and he is embedded into the local authority in Bradford to develop data sharing of council datasets to Connected Bradford as well as promoting research collaboration. It is also his responsibility to manipulate and transform raw datasets into Observational Medical Outcomes Partnership (OMOP) standards on the Connected Bradford platform ready for academics and researchers to use. Recent examples include routine local authority data for adult and children’s social care. He also supported Bradford Council’s successful HDRC bid. This bid will help establish Bradford Council as a local authority leader in generating and using health determinants research to support decision making and democratic accountability.

Dr Megan Wood - Megan is a Research Data Analyst for ActEarly and Connected Bradford. She received her PhD from the University of Leeds in 2021 where she investigated sociodemographic determinants of children’s fine motor development using data from the Born in Bradford cohort. She has been involved in Born in Bradford since 2015 when she was a research and implementation assistant during her undergraduate degree. Currently, her work spans across several projects, including the development of the Connected Bradford linked database and producing case studies to show the value and potential of linked data at a population level.

Sam Relins - Sam is a Research Fellow based at the Bradford Institute for Health Research with a special interest in data science applied statistics and machine learning. He is working on the Connected Bradford project that falls under the ActEarly Healthy Learning theme. His current work aims to exemplify the power of this connected data, including analysis of Autism Spectrum Disorders and the interactions of neurodivergent individuals with different public services and the effect of classroom air quality on transmission of illness in schools.

ActEarly Methods Club: A Whole Systems Data Linkage Accelerator