ECHILD: Linked dataset newly available for research into children’s health and education

ECHILD includes linked, de-identified health and education records for around 20 million children born in England between 1 September 1984 and 31 March 2022. By joining up routinely collected information from health and education services, ECHILD enables research that explores people’s experiences across these areas of life. Through better understanding of how children’s health affects their education – and how education affects their health – ECHILD has the potential to generate evidence to inform policy that better supports children’s needs.

ECHILD is an ADR UK flagship dataset, made available through an ADR England-funded project. This project is led by Professor Katie Harron and University College London, in collaboration with the London School of Hygiene and Tropical Medicine, the Institute for Fiscal Studies, the Department of Health and Social Care, the Department for Education, NHS England and the ONS.

Professor Katie Harron said “Linking health and education data is key to addressing the decline in UK child health in recent years. Understanding the wider determinants of health, including school experiences, will help us create a clearer picture of children’s needs so that we can prioritise their health and wellbeing and enable these future adults to live long and productive lives. Opening up ECHILD to the wider research community will accelerate the impact of these data.”

About the data

The education data used to create ECHILD is taken from the National Pupil Database, including information on pupil and school characteristics, educational outcomes and social care. This is linked to health data, including:

  • birth notifications
  • mortality data
  • maternity services data
  • mental health data
  • community services data
  • Hospital Episode Statistics: information on the care of admitted patients, outpatients, and those treated in A&E.

ECHILD also contains de-identified health, education and social care data on the mothers of the children included in the dataset, through a mother-baby link. This enables researchers to investigate the effects of maternal exposures on children’s outcomes.

How this dataset can make a difference

People’s experiences across health and education can be connected in many ways. For example, children with particular health conditions may miss school more frequently, and so require extra support to catch up. However, the lack of joined up of data has meant that children’s health and education have often been treated separately in research.

By linking de-identified health and education data at a population level, ECHILD is enabling researchers to build a richer picture of how people interact with these services. The dataset can be used to answer policy-relevant questions on a wide variety of topics, such as the links between health problems during pregnancy and educational outcomes, or between academic performance and mental health issues. This in turn could support better understanding of children’s needs, and inform policymakers on the best ways to support them.

Dr Emma Gordon, ADR UK’s Director said “I am delighted to see ECHILD made securely available for public good research – this represents a significant step forward in realising ADR UK’s vision. By linking this health and administrative data for people across England, we are unlocking the potential to understand the connections between their experiences across health and education on a scale that has not been possible until now. I look forward to building on this work through the ADR England portfolio.”

Find out more about ECHILD’s public good potential.

How to access the dataset

You can find out more about the ECHILD dataset in the ADR UK Data Catalogue.

Researchers seeking to securely access this dataset must first become accredited researchers under the Digital Economy Act. Researchers should apply for accreditation through the ONS Research Accreditation Service.

Find out more about how to access the dataset on the ECHILD website.

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