Evaluation of linkage between health, education and social care administrative data for 21 million children in England

Background

Population-level administrative data cohorts hold huge potential for generating evidence to improve child health. Understanding the quality of these data is critical to enabling us to fully realise this potential. We aimed to evaluate linkage between children’s health, education and social care administrative records (ECHILD) to identify possible sources of bias.

Methods

We created four cohorts to understand the drivers of inclusion/exclusion within ECHILD. For each cohort, we calculated the linkage rate by counting the total number of eligible individuals who appeared in the ECHILD linkage spine and any of the corresponding hospital/school component datasets. We then assessed whether linkage rates varied according to sociodemographic characteristics (year of birth, sex, ethnicity, region).

Results

ECHILD currently captures 34.2 million patients and 25.3 million pupils born between September 1984 and March 2023, aged 0-38 years. Over 90% of children with hospital birth records linked to a school record (rising to 93% for those born from 2014 onwards); 88% of children attending school in 2001/02 linked to a patient record (rising to 96% for those born in 2019/20), resulting in a total of 21 million linked individuals. Substantial variation existed between sociodemographic groups, with those living in London, residing in more deprived areas, or with recorded ethnicity other than White being less likely to be included.

Conclusions

Population-level datasets such as ECHILD often under-represent specific groups. Irrespective of the mechanisms by which individuals are excluded (e.g. opt outs, linkage errors or not interacting with services), those in minoritised ethnic groups and those living in more deprived areas are most affected. Linkage evaluations are critical for understanding who is and who is not included in analyses of these data so that researchers can account for potential sources of bias within analyses.

Highlights

• We evaluated linkage quality and population coverage within ECHILD, a national, longitudinal, linked health, education and social care data resource.

• ECHILD contains linked health and education records on 21.3 million children born from 1984 onwards; linkage rates were >90% for hospital birth cohorts and >88% for school inception cohorts.

• Linkage rates varied by ethnicity, deprivation and geography, with lower representation of minoritised groups and children living in London.

• Routine linkage evaluations are essential for quantifying selection bias and supporting valid use of population-level administrative data; our findings demonstrate the importance of transparent reporting of linkage quality for population data science research.