ArticleBMJ open2019
An approach to linking education, social care and electronic health records for children and young people in South London: a linkage study of child and adolescent mental health service data.
Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
43 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Rapid systematic review to identify key barriers to access, linkage, and use of local authority administrative data for population health research, practice, and policy in the United Kingdom.BMC public health · 2022Pooled it
- Assessing the feasibility of a web-based outcome measurement system in child and adolescent mental health services - myHealthE a randomised controlled feasibility pilot study.Child and adolescent mental health · 2023Trial
- Trial
- School absence and mental health service referral: Cohort study of a South London data linkage.JCPP advances · 2026Article
- Towards a new model of population mental health research and policy translation in the UK: establishing a National consortium.International journal of mental health systems · 2026Article
- Technology Matters: A model for translating digital and data science innovations into Child and Adolescent Mental Health Services.Child and adolescent mental health · 2026Article
- Commercial or industrial use of mental health data for research: primer and best-practice guidelines from the DATAMIND patient/public Lived Experience Advisory Group.Frontiers in psychiatry · 2026Article
- Transparency in the existence, use, and output of a mental health data resource: a descriptive paper from the National Institute for Health and Care Research (NIHR) Maudsley Biomedical Research Centre (BRC) Clinical Record Interactive Search (CRIS) Platform.International journal of population data science · 2025Article
- Article
- A scoping review of fair machine learning techniques when using real-world data.Journal of biomedical informatics · 2024Article
- Mother and Infant Research Electronic Data Analysis (MIREDA): A protocol for creating a common data model for federated analysis of UK birth cohorts and the life course.International journal of population data science · 2024Article
- The association between early childhood onset epilepsy and attention-deficit hyperactivity disorder (ADHD) in 3237 children and adolescents with Autism Spectrum Disorder (ASD): a historical longitudinal cohort data linkage study.European child & adolescent psychiatry · 2023Article
- A national multiple baseline cohort study of mental health conditions in early adolescence and subsequent educational outcomes in New Zealand.Scientific reports · 2023Article
- De-identified Bayesian personal identity matching for privacy-preserving record linkage despite errors: development and validation.BMC medical informatics and decision making · 2023Article
- Co-occurring homelessness, justice involvement, opioid dependence and psychosis: a cross-sectoral data linkage study.European journal of public health · 2023Article
- Linking electronic mental healthcare and benefits records in South London: design, procedure and descriptive outcomes.BMJ open · 2023Article
- Identifying Military Service Status in Electronic Healthcare Records from Psychiatric Secondary Healthcare Services: A Validation Exercise Using the Military Service Identification Tool.Healthcare (Basel, Switzerland) · 2023Article
- Implementing the English health inequalities agenda: addressing challenges to person-level, cross-sectoral data linkage, access and routine use for local authority public health.International journal of population data science · 2023Article
- Article
- Autism spectrum disorders as a risk factor for adolescent self-harm: a retrospective cohort study of 113,286 young people in the UK.BMC medicine · 2022Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
objectivesCreation of linked mental health, social and education records for research to support evidence-based practice for regional mental health services.
settingThe Clinical Record Interactive Search (CRIS) system was used to extract personal identifiers who accessed psychiatric services between September 2007 and August 2013.
participantsA clinical cohort of 35 509 children and young people (aged 4-17 years).
designMultiple government and ethical committees approved the link of clinical mental health service data to Department for Education (DfE) data on education and social care services. Under robust governance protocols, fuzzy and deterministic approaches were used by the DfE to match personal identifiers (names, date of birth and postcode) from National Pupil Database (NPD) and CRIS data sources. OUTCOME MEASURES: Risk factors for non-matching to NPD were identified, and the potential impact of non-match biases on International Statistical Classification of Diseases, 10th Revision (ICD-10) classifications of mental disorder, and persistent school absence (<80% attendance) were examined. Probability weighting and adjustment methods were explored as methods to mitigate the impact of non-match biases.
resultsGovernance challenges included developing a research protocol for data linkage, which met the legislative requirements for both National Health Service and DfE. From CRIS, 29 278 (82.5%) were matched to NPD school attendance records. Presenting to services in late adolescence (adjusted OR (aOR) 0.67, 95% CI 0.59 to 0.75) or outside of school census timeframes (aOR 0.15, 95% CI 0.14 to 0.17) reduced likelihood of matching. After adjustments for linkage error, ICD-10 mental disorder remained significantly associated with persistent school absence (aOR 1.13, 95% CI 1.07 to 1.22).
conclusionsThe work described sets a precedent for education data being used for medical benefit in England. Linkage between health and education records offers a powerful tool for evaluating the impact of mental health on school function, but biases due to linkage error may produce misleading results. Collaborative research with data providers is needed to develop linkage methods that minimise potential biases in analyses of linked data.
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