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Why does this matter? ECHILD is based upon linkage between health and education records; researchers need to understand the quality of this linkage and how this might make a difference to their analysis.

What did we want to find out? We wanted to understand how many patients in ECHILD have a school record, and how many pupils have a linked health record. We also wanted to understand whether linkage rates vary for different groups of people.

What we did We created four subsets of data within ECHILD and used these to count the total number of eligible individuals and how many of these linked to a hospital/school record

What we found ECHILD contains linked health and education records on 21.3 million children born from 1984 onwards; >90% of individuals with a hospital birth record had a linked school record, and >88% of those attending state schools in England had a linked health record. Linkage rates varied by ethnicity, deprivation and geography, with lower representation of minoritised groups and children living in London.

What this means, and what’s next Assessing the quality of linkage is important to understand who is included (and excluded) in analyses of ECHILD. Our findings should support researchers to consider how gaps in the linkage might affect their analyses.  

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. 

ECHILD data used

HES: April 1997 to March 2023

NPD: September 1995 to August 2022

Preprint