STEADFAST Modelling the associations between wider health and social characteristics and diabetes-related health - Identifier data flows to DfE for linkage in ONS

Cardiff University requires NHS England data for the research study: “STEADFAST - The personal cost of health conditions in childhood”.

Cardiff University’s overall aim is to quantify the links between educational outcomes and diabetes-related health outcomes, for example, how educational settings influence blood glucose levels and the time to onset of diabetes-related complications. This linkage of diabetes and education data for England and Wales arose from work by Cardiff University modelling whether rates of hospital admissions for young people living with diabetes were higher than for their peers without diabetes.

The purpose of this study is to provide a greater understanding of the interrelationship between diabetes-related health and education. The substantive motivation for this study is grounded in the evidence that most of the costs arising from diabetes come not from the day-to-day care and medications, but the complications arising from elevated blood glucose over the life course. There is currently limited evidence on the causes of less optimal diabetes management and the potential mechanisms for interventions to improve this. Thus, this study hopes to broaden the evidence base beyond the purely clinical factors to investigate the wider health and social determinants of diabetes-related health, using linked administrative data and focussing on education.

Children of school and university age with diabetes are most frequently living with type 1 diabetes, accounting for approximately 98% of cases, so the research initially focuses on this population. Education and health outcomes for children with type 2 diabetes (and other rarer forms of diabetes) are equally important however, and the analysis is replicated for each of these groups.

Under linked Data Sharing Agreement (DSA) DARS-NIC-158283-T2Q2D versions 0-2, diabetes health data covering England and Wales was shared for people born from the 1983-1984 academic year to the 2009-2010 academic year. Data linkage of the diabetes health data with school and university records was completed for a subset of 2080 people who studied at a Welsh educational institution (school, university, college). Diabetes health data included those linked from the national paediatric diabetes audit data (controlled by the Healthcare Quality Improvement Partnership (HQIP)) for individuals born 1992-1993 to 2009-2010, and the adult national diabetes audit data (from NHS England) for individuals born 1983-1984 to 2001-2002.

This Agreement, DARS-NIC-674735-Z0H6K, is a new Agreement to request the equivalent diabetes health and education data for people living in England and Wales. This Agreement should be read in parallel with DARS-NIC-669808-V6T0M and DARS-NIC-669962-W1F6D. Each DSA covers a different element of the required data flows for this study. Linked agreement DARS-NIC-158283-T2Q2D-v2 is being retained to cover the historic data flows described above, and may be amended in future to request further diabetes audit years to be linked with Welsh educational records.

The substantive dataset requested from NHS England is the National Diabetes Audit (NDA) which provides information regarding diabetes-related health for all people with diabetes. NDA data for linkage in the Secure Anonymised Information Linkage (SAIL) databank was disseminated and processed under linked agreement DARS-NIC-158283-T2Q2D versions 0-2. Data was disseminated to SAIL databank at the University of Swansea with a pseudonymised identifier only.

NDA data for people living in England and Wales is requested under linked agreement DARS-NIC-669962-W1F6D. The NDA data that is required relate to characteristics of the diabetes diagnosis (diabetes type, age at diagnosis) and measures of diabetes-related health (e.g. blood glucose levels, levels of protein in urine), and care processes (e.g. retinopathy screening for damaged blood vessels in the eye; foot exams to assess nerve or blood vessel damage). Diabetes-related health is primarily measured using blood glucose levels, directly or by using ‘HbA1c’, a proxy for blood glucose management control measured regularly as part of diabetes clinical management and recorded in the diabetes audit data. This data will be disseminated to the Office for National Statistics (ONS) – Secure Research Service (SRS) with a pseudonymised identifier only.

Cardiff University are also requesting that NHS England provide identifiable information of relevant individuals in the NDA to the organisations who hold their educational records.

Under linked agreement DARS-NIC-158283-T2Q2D versions 0-2, identifiable information for people with diabetes living in England and Wales was disseminated to England Health and Care Wales (DHCW), in order that the relevant primary and secondary education (provided to DHCW from the Welsh Government), and higher education (provided to DHCW from the Higher Education Statistics Agency (HESA)) records could be identified. The identifiers were provided alongside the same pseudonymised identifier provided to SAIL databank with the NDA data. The education data was made available for analysis by Cardiff University in a de-identified format in the SAIL databank, linked to the applicable diabetes health record via the pseudonymised identifier.

Under this Agreement, DARS-NIC-674735-Z0H6K, NHS England are requested to provide identifiable information of relevant individuals in the NDA who were living in England and Wales to the Department for Education (DfE) in order that their primary, secondary and higher education records can be identified. The identifiers will be provided alongside the same pseudonymised identifier provided to the ONS-SRS with the NDA data. The education data will be made available for analysis by Cardiff University in a de-identified format in the ONS-SRS, linked to the applicable diabetes health record via the pseudonymised identifier.

Under linked agreement DARS-NIC-669808-V6T0M, NHS England are requested to supplement the identifiable information of individuals in the National Paediatric Diabetes Audit (NPDA), provided by the Royal College of Paediatric and Child Health (RCPCH), with their names. This would be done using NHS England’s ‘Demographics’ dataset. Names can then be used by the DfE alongside other identifiers supplied by the RCPCH to retrieve the relevant educational records of individuals in the NPDA. These would be made available for analysis by Cardiff University in a de-identified format, linked to the applicable diabetes health record.

The NDA and identifiable data from NHS England will, when combined with the associated education data, allow the study to model how characteristics of a person’s diabetes impact their education and, simultaneously, how their education affects their diabetes-related health.

Educational outcomes are recorded from the time a child enters school until they leave university, including measures of attendance, attainment, and broader characteristics of the educational experience such as special educational needs and school exclusions.

The mechanisms driving the relationships between education and health can be broken down into three pathways. Firstly, diabetes-related health may affect educational outcomes, for example, through biological mechanisms, including the effects of excess glucose on the brain structure and social mechanisms such as adjusting management routines to fit in with a university lifestyle. Secondly, education may affect diabetes-related health. For example, continuing education beyond compulsory schooling might provide structure and support that facilitate better management. Thirdly, individual characteristics (observed and unobserved) may directly affect both education and diabetes-related health, such as motivation and intelligence.

To help unpick which of these are happening in the data, Cardiff University uses repeated measures of educational outcomes and health outcomes for an individual to tease out the ordering of events. For example, if a person with less optimal blood glucose levels has high rates of school absence, it would be possible to look back and see if that person had high rates of absence before they were diagnosed with diabetes. In practice, the statistician will look at many thousands of individuals at once and consider many such differences simultaneously, but the principle is the same.

The data request covers people born from 01/09/1983–31/08/2002 with diabetes, living in England and Wales, who are included in the diabetes audits (NDA and/ or NPDA) from 2003 onwards. This is anticipated to include 30,000 patient records, with linkage anticipated for 28,000 individuals. Individuals born prior to this have been excluded since their full education data, including data on their first year of university, is not available. Individuals born after 2002 will be recorded in the NPDA, which is not provided by NHS England. As the study is primarily interested in the effect of diabetes during education, cases are restricted to those diagnosed with any form of diabetes prior to age 24 or younger. Whilst university cohorts are typically 18-21, due to the high prevalence of delays in starting time at university (gap year, changing university, changing course etc.) and the varying length of courses (sandwich degrees, placements, conversion courses), the request will include all ages up to the government definition of the end of youth education, i.e. up to age 24.

The predicted ages of school students include early years (nursery and reception) aged 3-5, compulsory schooling aged 5-16, and key stage 5 ages 16-18. Some students start school early or leave later than normal, however there will be no request for additional cohorts for this contingency and will instead make this an amendment if it transpires to be an issue.

The DfE do not hold data for children educated at private schools or educated home, thus for these cases (~7%) the diabetes audit data would not be assigned a linkage ID by DfE. Unlinked cases would not form part of the core analysis, however Cardiff University would carefully examine why different cases did not link. For example, there may be noticeable patterns in children who did not link for technical linkage reasons, such as lower matching rates for children from certain minority ethnic groups where the matching algorithm may not be as efficient for those names. Cardiff University would also consider if the diabetes health outcomes are different for those children who do not link, since that may motivate a change in monitoring, for example for children who are educated in settings other than at school (home educated).

There should be no NDA cases in the requested extract that will not meet the conditions of the study. It would be expected all cases to have attended school, and those that do not attend university are still important as controls for comparison with those that did. There will be no request for controls from NHS England.

Although linkage with Welsh educational data was undertaken under linked agreement DARS-NIC-158283-T2Q2D versions 0-2, data is requested for individuals resident in both England and Wales for the current request because individuals can be located across borders for their medical care or educational settings, and individuals move across borders over time. The study will combine estimates from data linked to Welsh educational records in the SAIL databank, and data linked to English educational records in the ONS-SRS, to create a single estimate for England and Wales.

Cardiff University request individual-level data for modelling changes over time for individuals, e.g. how individual differences in education experiences affect diabetes management and vice versa. Cardiff University requests identifiers only for the purpose of data linkage; however, the analysis will be carried out on de-identified data.

Cardiff University request data from 2003/04 to 2017/18 to best model trajectories of HbA1c and the time to the first onset of early complications.

Cardiff University requests data for England and Wales to ensure maximum power and generalisability of the results.

Cardiff University confirm there are no alternative, less intrusive ways of achieving the purpose. A high degree of data linkage is required for this study in order to follow the entire life course trajectories of both diabetes related health and education through the combined linkage of both the paediatric and adult diabetes audits, and education data from primary school to university. Patient identifiers are sent to different organisations than the substantive clinical data to minimise the risk of disclosure.

The request has been restricted to only the essential clinical measures and associated metadata such as date of measure, location of measure (clinic).

Cardiff University are the research Sponsor and sole data controller for this DSA.

The personal data for this study is processed under UK GDPR Article 6(1)(e) - Public Task - for academic medical research carried out as a task in the public interest. The processing is necessary for Cardiff University (as a public authority for the purposes of data protection legislation) to perform a task in the public interest. The task has a clear basis in law.

The special category personal data for this study is processed under UK GDPR Article 9(2)(j) for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject. The public interest lies in the improved evidence on the links between educational measures (school settings, absence, attainment) and health measures (HbA1c levels) for young people with diabetes. The study aims to improve care for all young people with diabetes in the education system by informing clinicians and commissioners of variation and outcomes and complications to support work to improve and standardise treatment selection choices. For these reasons, the processing also meets the conditions of Schedule 1 Part 1 paragraph 4 of the Data Protection Act 2018.

Cardiff University has approval from the Health Research Authority for data providers to set aside the common law duty of confidentiality with respect to the sharing of person identifiers in health datasets, known as a ‘Section 251 exemption’.

SAIL and DHCW are data processors for the Welsh subsets of data as described above. The DfE and ONS are data processors for the English subsets of data as described above.

The Welsh Government and HESA provide education data which is linked with NHS England data.

The RCPCH provide NPDA identifiable data to NHS England, and NPDA substantive data to the ONS-SRS. The Healthcare Quality Improvement Partnership (HQIP) are the data controller of the NPDA.

The Welsh Government, HESA, RCPCH and HQIP do not process NHS England data.

None of the organisations listed above, except Cardiff University, determine the purposes or the means of the processing of NHS England data. They are not therefore considered joint data controllers of NHS England data under this DSA.

The Medical Research Council (MRC) and UK Research & Innovation (UKRI) have provided funding for this study. The funders do not determine the purposes or the means of the processing of NHS England data and do not process the data. They are not therefore considered joint data controllers or data processors of NHS England data under this DSA.

This study uses a split file process to transfer individual-level data. The objective is to ensure that, as far as possible, every person’s health data is processed separately from the identifiers that would link that health data to a person.

Each clinical data provider assigns a study-specific pseudonymised identifier (study ID) to each participant. They then split the whole dataset into an identifiers dataset (containing variables such as NHS number, name, date of birth, postcode, and gender) and a substantive dataset (containing de-identified clinical/ education data).

The substantive data is transferred directly to the repository.

The identifiers file is shared with a trusted third party (details below) who uses the identifiers to match individuals’ ‘study ID’ (pseudonymised identifiers) to their ‘linkage ID’, and then deletes all the real-world identifiers such as names and dates of birth, before transferring the ‘study ID’ and ‘linkage ID’ into the repository where the ‘study ID’ enables re-joining of the ‘linkage ID’ to the substantive data, and the ‘linkage ID’ enables linkage to the other datasets which have been processed in the same way.

Under linked agreement DARS-NIC-158283-T2Q2D versions 0-2, the data flows were as follows:

NHS England identified people born from 01/09/1983 to 31/08/2002 (ie the 1983/84 to 2001/02 academic years) who appeared in the National Diabetes Audit (NDA) dataset and assigned them a unique study ID.

From this cohort, NHS England provided a one-off drop of data covering 2003/04 to 2017/18 audit years, containing the substantive diabetes-related data, accompanied by study ID only, to the Secure Anonymised Information Linkage (SAIL) databank at the University of Swansea. This file contained no identifying information other than the study ID.

From this cohort, NHS England also provided a one-off drop of data covering 2003/04 to 2017/18 ‘audit years,’ containing study ID, patient name, NHS number, date of birth, gender, and postcode only to England Health and Care Wales (DHCW).

DHCW created the ‘linkage ID’, a hashed version of the NHS Number, referred to by DHCW and SAIL as the Anonymised Linkage Field (ALF), then destroyed all the identifying information (name, NHS number, date of birth, gender, postcode). After this process, the identifiers file contains only the study ID and linkage ID, along with less disclosive versions of the demographic data (gender, week of birth, lower super output area). This file was onwardly flowed to SAIL.

Within SAIL, the substantive NDA file was re-joined to the identifiers linkage field file using the study ID so that each case of the substantive data got a linkage ID.

The same process as outlined above for NDA data also happened for the other de-identified datasets that were placed in SAIL, including the National Paediatric Diabetes Audit (NPDA), Higher Educational Statistics Agency dataset (HESA), and Welsh Dataset Education Records (WED, also known as the National Pupil Database or NPD). The NPDA, HESA, and WED data were linked to the NHS England NDA data using the linkage ID.

Data accessible to Cardiff University via SAIL therefore are:

- NDA data covering England and Wales

- NPDA data covering England and Wales

- HESA (higher education) data covering England and Wales

- Primary and secondary education data for Wales only (WED)

Under this Agreement, DARS-NIC-674735-Z0H6K, the data flows are as follows:

NHS England identify individuals based in England and Wales and born between the 01/09/1983 to 31/08/2022 (ie the 1983/84 to 2001/02 academic years), in the NDA dataset under DARS-NIC-669962-W1F6D and assign them a unique study ID.

Using the NHS numbers held in the NDA, NHS England retrieves the names, date of birth, latest postcode, and gender from the Personal Demographics Service (NHS number was included for DHCW, but is not used here as Department for Education (DfE) are unable to process it).

These identifiers are sent to the DfE alongside the unique study ID. This will be a one-off deposit of data, though permission for annual refreshes of data will be sought in the future. DfE, acting as the trusted third party, will use the identifiers to match individuals’ ‘study ID’ to the ‘linkage ID’ (referred to by DfE and the Office for National Statistics (ONS) as the Pupil Matching Reference (PMR)), then destroy all the identifying information (name, date of birth, gender, postcode). After this process, the identifiers file contains only the study ID and linkage ID. (Unlike for the SAIL process, less disclosive versions of the demographic data [gender, week of birth, lower super output area], are not retained in the identifiers file). This modified identifiers file, containing only study ID and linkage ID is onwardly flowed to ONS-SRS repository where the ‘study ID’ enables re-joining of the ‘linkage ID’ to the substantive data, and the ‘linkage ID’ enables linkage to the other datasets which have been processed in the same way.

In parallel, under linked agreement DARS-NIC-669962-W1F6D, substantive deidentified NDA health data for the 2003/4 to 2017/18 audit years for the above-described cohort will be sent to the ONS Secure Research Service (SRS), with the unique study ID only. This will be a one-off deposit of data, though permission for annual data refreshes will be sought in the future.

Under linked agreement DARS-NIC-669808-V6T0M, NHS number, date of birth, postcode and gender will be provided to NHS England by the Royal College of Paediatric and Child Health (RCPCH) for individuals born in the academic birth cohorts from 1983/4 to 2001/2 who are in the NPDA. NHS England will retrieve the names of these individuals and send identifiable Demographics data (names, date of birth, latest postcode, and gender) to the DfE alongside a unique pseudonymised identifier provided by the RCPCH. This will be a one-off deposit of data, though permission for annual data refreshes will be sought in the future.

The project includes four further data flows which are not covered by the above-listed DSAs:

1. RCPCH send substantive deidentified NPDA data directly to the ONS-SRS, containing the same unique pseudonymised identifier as provided to NHS England under DARS-NIC-669808-V6T0M

2. DfE send substantive deidentified education records (compulsory education) directly to the ONS-SRS, alongside the linkage ID

3. HESA send substantive deidentified education records (higher education) directly to the ONS-SRS, alongside the linkage ID.

4. After the DfE ‘hashing service’ use the identifiers supplied by NHS England to identify the correct individual against their records and retrieve their PMR, the original study ID supplied by NHS England, alongside the PMR retrieved by the DfE, are onwardly flowed into the ONS-SRS.

DfE will destroy the real-world identifiers as soon as the PMR field is retrieved and the necessary pseudonymised identifiers provided to the ONS-SRS. They will provide NHS England with a data destruction certificate.

ONS-SRS staff will work with the Cardiff University project lead to link the data records within the ONS-SRS environment. Substantive NDA and NPDA data will be linked with a PMR via the original study IDs, where the DfE have been able to retrieve a PMR.

NDA, NPDA, and education data will then be linked using the PMRs.

ONS-SRS staff will support Cardiff University with the linkage evaluation for the extract to be used for research, determining what percentage of clinical records have been successfully linked together (NPDA to NDA) and linked to associated education records (NPDA to NPD, NPDA to HESA, NDA to NPD, NDA to HESA).

Unlinked clinical data will remain in the ONS-SRS environment but will not be further processed for the purposes of these Data Sharing Agreements (DARS-NIC-674735-Z0H6K, DARS-NIC-669808-V6T0M, and DARS-NIC-669962-W1F6D). Other linkage mechanisms may be explored in future to improve the success of the linkage, and data on individuals not in school or university may give rise to important information for diabetes management.

The linked de-identified data-sets will be made available for multilevel modelling analysis of the associations between education and health by Cardiff University on the ONS-SRS. The DfE will provide educational data for controls who do not have diabetes, alongside the educational data for those with diabetes, to enable Cardiff University to model the differences in outcomes.

The combining of health data with education data increases the likelihood that a person may appear as unique in the dataset; however, given that there are 30,000+ cases of young people with diabetes in England and Wales, and the high-level nature of the variables, it is unlikely that this dramatically increases the risk of re-identification. There will be no requirement or attempt to re-identify individuals for the purposes of the study or any other reason. The primary protection against reidentification is the creation of the linkage ID along with the destruction of the real-world identifiers prior to the data being put in the repository, meaning the data accessed by Cardiff University is de-identified. Secondly, ONS-SRS and Cardiff University will check data at the outset for any identifiability risks in the raw data or linked data before using it for analysis. This checking is routinely conducted by experienced analysts at ONS who use a mature process to identify small numbers, unique/rare cases, or other identifiability risks. Thirdly, researchers from Cardiff University who are accessing the data are trained not to re-identify data.

NHS England data is not being linked to any publicly available data.

Data processing is only conducted by substantive employees of the data processors who have specific teams and staff trained and explicitly employed for this purpose. Data will be accessed for analysis through secure remote gateways into the ONS-SRS. No data will be accessed outside the UK. Person identifiers (such as name and date of birth) will not be shared with third parties beyond those required to create the pseudonymised linked datasets (i.e. only DfE).

In September 2024 the ONS are updating their data repository for studies such as this one from the ONS Secure Research Environment (SRS) to the ONS Integrated Data Service (IDS). As a temporary measure ONS will move the linked data extract from the SRS to the IDS to allow continued analysis, It is expected there would be a period of crossover, with data in both ONS platforms while the amended process is set up. Cardiff University will prepare the NHSE (and CAG) amendment to capture the new processing, most importantly NHSE will no longer flow the identifiers to DfE, but instead send them directly to ONS for processing in the ONS Data Access Platform (DAP) to create a linkage ID which functions in the IDS.

Public engagement focused on both the research questions and the data processing has been carried out throughout the project, going back to 2014 before the study was funded. The largest public involvement work has been the sessions with young people with type 1 diabetes in 2020, in partnership with Diabetes UK and the MRC Regulatory Support Centre. This work is summarised in a website (https://www.adruk.org/news-publications/news-blogs/public-views-on-the-use-of-personal-identifiers-for-linking-diabetes-and-education-data-for-research-439/) with links to the full report towards the bottom of the page. Further public engagement was carried out in 2022 across 19 focus groups, the link to the work is https://dareuk.org.uk/sprint-exemplar-project-steadfast, and the report summarising this work should be released in early 2023.

The expected outputs will be academic journal papers modelling the associations between education outcomes and trajectories of diabetes-related health.

The nature of data-based outputs would be descriptive statistics and regression coefficients, all of which would be aggregate data with small numbers (less than 10) suppressed; this is a requirement of taking any results out of the ONS-SRS and is rigorously checked by ONS analysts.

The original aim was to finish the draft of the outputs using data in SAIL disseminated under linked agreement DARS-NIC-158283-T2Q2D versions 0-2, between 21/01/2019 to 21/08/2020, though the first of these papers was only accepted for publication on 01/08/2022 by the journal ‘Diabetes Care’. It is likely that future analysis will combine estimates from data deposited in both SAIL databank and ONS-SRS, and is expected to be published before 2025.

Findings from the first paper have been presented at an invited address at the Royal College of Paediatric and Child Health annual conference and a presentation to clinicians at the Brecon Group Annual meeting.

The first research paper is based upon how measures of diabetes-related health influence educational trajectories, and shows that (i) children with diabetes have higher absence rates, but similar attainment and progression to university as their peers and (ii) HbA1c tracks with educational outcomes. Cardiff University provide tentative evidence that this link is likely to be the result of external factors affecting both education and health outcomes. Due to issues with the NPDA data, Cardiff University have not yet been able to undertake any analysis pertaining to how education settings affect HbA1c trajectories, or how external factors affect both diabetes-related health trajectories and educational trajectories.

Any further study findings will be shared with clinicians through academic publications (e.g., Diabetes Care) and presentations at national forums (e.g., Diabetes UK Conference & Brecon Scientific Meeting). The findings will be shared with the public more broadly using a plain English version of the study; this will hopefully be published in the diabetes audit report and presented by the project lead at patient forums. Further engagement work with the results will be coordinated with Cardiff University’s coproduction group of young people.

An agreement is in place with Royal College of Paediatric and Child Health to include a patient level report on associations between diabetes related health and education for their annual report. Updates and summaries will be published on the project website (https://www.cardiff.ac.uk/research/explore/research-units/childhood-health-and-education?).

A dissemination plan has been produced in partnership with Diabetes UK. This includes two papers supported by plain English reports produced by the Diabetes UK policy team. The research team and Diabetes UK have begun to meet with policymakers from England and Wales, but it is too early to say how these connections will be exploited to communicate results. All outputs will belong to Cardiff University but will be freely available to Diabetes UK to use as agreed under Cardiff University’s heads of terms. Information about how the study has already consulted young people are provided on the webpage for the first 2021 patient and public engagement workshop: https://www.adruk.org/our-work/the-personal-cost-of-health-conditions-in-childhood-engaging-the-public/public – ADR UK and the workshop report: https://www.adruk.org/fileadmin/uploads/adruk/Documents/Diabetes_Education_Public_Workshop_Report_Aug_2021_01.pdf

In the second workshop, the young people produced a video explaining how researchers use data relating to young people with diabetes. Although the video and report produced are not yet released, there is a holding version on YouTube: https://www.youtube.com/watch?v=oimfnSoENxo.

Several of the representatives from Cardiff University’s patient and public involvement sessions have become the coproduction group, helping steer the project and the next iteration of the public engagement.

Although laws exist in England and Wales to support people with health conditions in schools and universities, the legislation (and associated guidance and resulting practice) does not always meet the child's needs. In schools, there is a gap between support for special needs (which stems from the Children and Families Act 2014 and traditionally focused on support for ‘learning conditions’, e.g. dyslexia) and support for children with health conditions (which stems from the Equalities Act 2010 and traditionally focuses on support through reasonable adjustments). In universities, students lack clarity on how financial support for health conditions works, particularly for conditions like diabetes, where there is wide variation in the required amount and type of support. Students will also be adjusting to having less clinical support than they are accustomed to, having only recently transitioned from paediatric to adult services before moving to a university campus far from their ‘home’ clinical team.

The high-level goal of this study is to ensure that children living with diabetes (and their families) can (i) manage their condition to stay healthy and (ii) fulfil their potential in education. By combining health data (including HbA1c) and education data (including educational outcomes and support), the project hopes to generate robust evidence of variation in outcomes, which may motivate changes in legislation and practice. Although the primary route for an impact on health is through policy change (and the associated improvement in guidance and implementation); the project will continue to inform practitioners of the range of outcomes and thus show the scope and potential benefit from improved support, both in terms of educational outcomes and diabetes-related health outcomes, and the link between the two.

Study outcomes for children in schools: This will focus on how rates of absence and attainment trends are associated with diabetes management. The longitudinal (annual measures) nature of the data means that researchers can compare outcomes over time; for example, annual measures of school absence can help show the changes in missed schooling before vs after a diagnosis of diabetes, in addition to comparing absence rates with similar children who were not diagnosed with diabetes. Similarly, regular measurements of HbA1c allow researchers to identify changes in blood glucose management as a child moves from primary school to secondary school. If differences exist, clinical teams may choose to give additional support based on non-clinical (educational) challenges that may influence diabetes management.

Study outcomes for children leaving school: Students with diabetes who are leaving compulsory schooling will transition to A-levels, vocational courses, or the labour force, and the study will model how these choices subsequently impact the trajectories of HbA1c. For example, the study may find that those who choose not to continue formal education beyond age 16 have less structure, affecting their diabetes management. If differences exist, clinical teams may choose to provide extra support or delay the transition from paediatric to adult diabetes care until after the transition to employment is complete.

Study outcomes for higher education students: The work focusing on universities will look for changes in trajectories of diabetes management, for example, comparing those that live at home with those who move away to attend university, identifying whether there is a significant change in management and the timings of that change. Differences may be seen in HbA1c during the first term as students try to reconcile good management routines with university social life, or perhaps HbA1c may not alter until the stress of the final year of university with impending high-stakes exams. If differences exist, clinical teams may choose to be more proactive in supporting the transition between home and university care and arrange follow-up appointments, both at home and at university, scheduled at times that fit around academic term dates.

Study outcomes for young adults: The research on young adults focuses on how childhood HbA1c levels and educational outcomes determine early adult health outcomes. This study focuses on the ‘double whammy’ effects of a history of sub-optimal HbA1c levels and lower educational outcomes. Relevant determinants might include individual factors (e.g. special educational needs or behavioural issues), school factors (e.g. lack of appropriate support), or family-level factors (e.g. socioeconomic status). If differences do exist, clinical teams may choose to flag individuals earlier who are struggling with diabetes management and education as being particularly vulnerable and receive additional support in the adult care setting, with potential health and social benefits to the individuals (who are most likely to develop early diabetes-related complications).

In partnership with Diabetes UK the project held a series of public workshops which reported the expected measurable benefits from the perspective of patient and public involvement participants (https://www.adruk.org/fileadmin/uploads/adruk/Documents/Diabetes_Education_Public_Workshop_Report_Aug_2021_01.pdf, and included: more understanding by others of what they are going through, more support with managing diabetes in schools, and earlier intervention at times of high stress. There was a focus on diabetes-education interactions during transition from paediatric to adult diabetes care – this comes amongst many other stressful events that teenagers go through, not least of which were the GCSE exams.

Participants focused on the benefit of bridging the gap in educational experiences between children with type 1 diabetes versus those without – “ensuring an equal playing field”. Participants reported a lack of knowledge around the impact of type 1 diabetes on education, which they felt was likely to be large. They felt that a study of this kind could influence policy, and ultimately the education setting, which in turn could result in a better experience for young people. A related point was the hope for increased general awareness and understanding of how type 1 diabetes might affect individuals beyond direct medical outcomes.

The study has been lucky in terms of the timings of the opportunities to contribute to the policy debate. Cardiff University were able to provide evidence, based on analysis of the Welsh data, to the new Additional Learning Needs Bill for Wales and the Special Educational Needs and Disabilities Green Paper in England, though these are yet to report their findings so have not yet resulted in any change in practice.

To support public involvement and engagement, the study team has given presentations of the results obtained so far to practitioners (e.g., the Royal College of Paediatrics and Child Health annual conference, the Brecon Annual Meeting of type 1 diabetes practitioners in Wales), patients (e.g., the Yorkshire and Humber Young People’s Diabetes Network Annual Meeting), and researchers (The Type 1 Diabetes Consortium at the Diabetes UK conference). The findings have been well received by clinicians, who report that they feed back some of the findings, particularly the ‘good news story’ that overall, children with diabetes attain in school as well as their peers without diabetes. Practitioners have also reported that the quantification of expected absence (average and range) has also been useful to provide a benchmark for children with diabetes.