Why was this work needed?
Health inequalities across the UK mean that some children struggle to get the care they need, and this puts extra pressure on urgent services. Children from poorer families are more likely to have long‑term health problems and are more than twice as likely to die before adulthood, even though around 1 in 5 childhood deaths could be prevented with earlier support. The current system often depends on families knowing when and how to ask for help, so many problems are missed until a child’s condition has already worsened. Therefore, a more proactive, data‑driven way to spot children at risk sooner is needed to help reduce these unfair differences. This research looked at whether a population health management approach could reveal unmet needs, enable earlier help, and provide a fairer, more systematic way of reaching children before their health deteriorates.
What happened?
Population health management (PHM) uses data and coordinated care to focus on prevention, early intervention, and ongoing support. It aims to improve the health of a group of people rather than treating patients one by one.
Using linked GP records in South London, researchers identified children under 16 with asthma, eczema or constipation and invited their families to complete an online health check. This allowed the team to assess symptoms, unmet needs and overall condition control outside of routine appointments. Children whose health check scores indicated a clinical need were then offered early intervention from specialist nurses within the Children and Young People's Health Partnership (CYPHP) service. By analysing which children were identified, who engaged and who went on to receive care, the study was able to consider how well this population health management approach worked in practice and where inequalities emerged.
What were the benefits?
The result was that 24% of the children identified with these conditions from their records engaged with the health check, and about 24% of those children went on to receive care that they may otherwise not have gotten. By proactively identifying children and offering early intervention, the system ensured that those with the greatest clinical need—particularly children from deprived and minority ethnic backgrounds—were more likely to receive timely support once they engaged
This study showed that this method of using data can help to find children with health needs who might be missed in usual care, thereby reducing health inequalities.
What type of data was involved?
The study used routinely collected primary care data which were pseudonymised [1] from GP practices across Lambeth and Southwark to identify children with asthma, eczema, or constipation. These records included diagnoses, prescriptions, and basic demographic details such as age, ethnicity, and deprivation levels. This was linked with CYPHP service data, which captured families’ responses to an online health check and records of any early intervention appointments. Together, these datasets allowed researchers to track who was identified, who engaged with the system, and who went on to receive care.
What was the legal basis for accessing the data?
The study used pseudonymised data [1] linked across primary care records and the CYPHP service. GP records were used to identify children with tracer conditions, and these were linked to CYPHP health check and care‑delivery data using an externally assigned pseudonymised NHS number.
Who funded and collaborated on this work?
This study was funded by Guy's & St Thomas' Foundation (HIF1080101KCL).
Where can I go for more information?
Glossary
[1] Pseudonymised data: personal data that has been processed to remove or replace direct identifiers so that individuals cannot be identified without additional information, which is kept separately.
- Page updated: 2 March 2026
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