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Objectives Developing a rigorous application process for linked data within the UK Longitudinal Linkage Collaboration’s Trusted Research Environment (TRE) included balancing the requirements of >20 longitudinal studies and several data providers with the need to provision data to researchers in a safe, ethical and efficient manner. Approach UK LLC was commissioned as a resource to enable the investigation of COVID-19 questions: a secure setting where longitudinal population studies (LPS) can be linked efficiently to regularly refreshed NHS electronic health records, and then accessed by researchers. UK LLC received funding to continue as a resource for any research in public good and to link to the administrative records (education, occupation, tax and benefits). To accommodate the constraints imposed by a new set of data controllers and to account for wide variety of proposals expected, we expanded our data access process. Results UK LLC has a three-stage application and review process. The addition of administrative data meant that there is additional review for those applications requesting that data (Stage 4) and need to align processes with the UK Statistics Authority. There is also need to review complexity of the data requests and ethical implications of any application to access the data. We have developed an ethics decision tree to help guide the decision making around ethics requirements. Conclusion Our process is evolving as we are trying to meet the challenge of balancing the needs of >20 studies, stakeholders, applicants, and participant/public contributors, to create a process that can handle complex needs and requirements.

Objectives Long-term sickness absence from employment has negative consequences for the economy and can lead to widened health inequalities. Sick notes (also called ‘fit notes’) are issued by general practitioners when a person cannot work for health reasons for more than 7 days. We quantified the sick note rate in people with evidence of COVID-19 in 2020, 2021 and 2022, as an indication of the burden for people recovering from COVID-19.Design Cohort study.Setting With National Health Service (NHS) England approval, we used routine clinical data (primary care, hospital and COVID-19 testing records) within the OpenSAFELY-TPP database.Participants People 18–64 years with a recorded positive test or diagnosis of COVID-19 in 2020 (n=365 421), 2021 (n=1 206 555) or 2022 (n=1 321 313); general population matched in age, sex and region in 2019 (n=3 140 326), 2020 (n=3 439 534), 2021 (n=4 571 469) and 2022 (n=4 818 870); people hospitalised with pneumonia in 2019 (n=29 673).Primary outcome measure Receipt of a sick note in primary care.Results Among people with a positive SARS-CoV-2 test or COVID-19 diagnosis, the sick note rate was 4.88 per 100 person-months (95% CI 4.83 to 4.93) in 2020, 2.66 (95% CI 2.64 to 2.67) in 2021 and 1.73 (95% CI 1.72 to 1.73) in 2022. Compared with the age, sex and region-matched general population, the adjusted HR for receipt of a sick note over the entire follow-up period (up to 10 months) was 4.07 (95% CI 4.02 to 4.12) in 2020 decreasing to 1.57 (95% CI 1.56 to 1.58) in 2022. The HR was highest in the first 30 days postdiagnosis in all years. Among people hospitalised with COVID-19, after adjustment, the sick note rate was lower than in people hospitalised with pneumonia.Conclusions Given the under-recording of postacute COVID-19-related symptoms, these findings contribute a valuable perspective on the long-term effects of COVID-19. Despite likely underestimation of the sick note rate, sick notes were issued more frequently to people with COVID-19 compared with those without, even in an era when most people are vaccinated. Most sick notes occurred in the first 30 days postdiagnosis, but the increased risk several months postdiagnosis may provide further evidence of the long-term impact.

Background UK Longitudinal Linkage Collaboration (UK LLC) is the national Trusted Research Environment for the UK's longitudinal studies. The need for a clear way to communicate Longitudinal Population Study (LPS) participants’ rights was identified through public contributor consultations. UK LLC gathered public views to inform meaningful discussion with NHS England, the National Data Guardian’s Office, and the Health Research Authority to develop a new framework for agreeing consistency in assessment of the legal basis for linking participant self-reported data to participants' health records. The consultation flagged that the legislation around LPS data is complex, confusing, and often inaccessible. This means that it may prove difficult for LPS participants to fully understand who is allowed to access their data, for what purposes, under what circumstances and what their rights are. Introduction The legal basis for using LPS data is complex. Of particular importance are the UK GDPR (General Data Protection Regulations), Common Law Duty of Confidentiality, Digital Economy Act (DEA) 2017 and Section 251 of the NHS Act 2016. Our vision was to produce transparency materials to help LPS participants understand LPS data and the law. Methods We surveyed public contributors from UK LLC, Health Data Research UK and DATAMIND to establish current understanding. We worked in partnership with UK LLC’s Public Advisory Group (PAG) and external organisations to produce a series of infographics (over time also available in audio, BSL and additional languages) to reach as wide an audience as possible. We collaborated with DATAMIND throughout the project sharing insights and ideas. Results A total of 56 people participated in the survey, most of whom lived in England: 30% were LPS participants; 55% were aged 55 and over; and 18% identified as belonging to an ethnic minority group. Survey results showed that the levels of awareness of the laws/legal principles relating to the use of LPS data is generally low. The DEA was least well-known, with 11% of people aware of this legislation. The most well-known among the infographic topics was GDPR, with 88% awareness. We co-developed key messages for LPS participants on what they should be aware of as individuals, including what they should expect from their LPS. This was not a straightforward process due to the exemptions and conditions under each law/legal principle. This led to focus on highlighting the practical implications for participants rather than explaining the laws/legal principles. Across the series, participants are directed to official organisations for further information. Conclusions This series of transparency materials provides a more accessible and easy-to-understand way for LPS participants to fully understand who is allowed to access their data, for what purposes, under what circumstances and what their rights are.

Objectives We created a panel with members of the public and longitudinal study participants who review our data access requests. This panel forms an integral part of our data access application process, giving the public a say who can access the data for research. Methods We advertised our lay member vacancies using social media, newsletters, word of mouth and the internet. We appointed six people to the public panel. Our panel includes study participants, NHS service users, parents, carers, and people with experience of disability, neurodiversity, and long-term health conditions. The Panel Terms of Reference were created with help from stakeholders and study teams involved in longitudinal studies that involve the public in data access applications. This ensured that the purpose of the panel was clear. The panel reviews lay summaries and makes sure that researchers have adequate public involvement in their project. Results Panel members have reviewed 28 applications. Researchers present their research at an online meeting with the panel then answer questions from the panel members. We publish meeting minutes on our website for transparency. A 6-month review was overwhelmingly positive - all panel members indicated they felt valued. They felt able to challenge and question researchers as part of the data access application process. This provides a level of public scrutiny to our work. “I feel there’s a real value in the panel. You get a real sense that this has got such potential to make a contribution.” (panel member) We are further developing the Panel Terms of Reference with panel members. We will consider additional areas of responsibility, for example, public benefit review. Conclusion We regularly review how to improve public involvement in our work. The panel has proven its value during our application process. Therefore we are exploring with the panel a new approach to assess the public benefit of applications and what is meant by ‘public benefit research’.

Summary: Background: The COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England. Methods: In this population-based, observational cohort study we used primary care electronic health record data with linkage to hospital episode statistics data and mortality data within OpenSAFELY, a data analytics platform created, with approval of NHS England, to address urgent COVID-19 research questions. We included adults aged 18 years and over registered with a TPP practice between March 1, 2018, and April 30, 2022. We excluded those with missing age, sex, geographic region, or Index of Multiple Deprivation. We grouped ethnicity (exposure), into five categories: White, Asian, Black, Other, and Mixed. We used interrupted time-series regression to estimate ethnic differences in clinical monitoring frequency (blood pressure and Hba1c measurements, chronic obstructive pulmonary disease and asthma annual reviews) before and after March 23, 2020. We used multivariable Cox regression to quantify ethnic differences in hospitalisations related to diabetes, cardiovascular disease, respiratory disease, and mental health before and after March 23, 2020. Findings: Of 33,510,937 registered with a GP as of 1st January 2020, 19,064,019 were adults, alive and registered for at least 3 months, 3,010,751 met the exclusion criteria and 1,122,912 were missing ethnicity. This resulted in 14,930,356 adults with known ethnicity (92% of sample): 86.6% were White, 7.3% Asian, 2.6% Black, 1.4% Mixed ethnicity, and 2.2% Other ethnicities. Clinical monitoring did not return to pre-pandemic levels for any ethnic group. Ethnic differences were apparent pre-pandemic, except for diabetes monitoring, and remained unchanged, except for blood pressure monitoring in those with mental health conditions where differences narrowed during the pandemic. For those of Black ethnicity, there were seven additional admissions for diabetic ketoacidosis per month during the pandemic, and relative ethnic differences narrowed during the pandemic compared to the White ethnic group (Pre-pandemic hazard ratio (HR): 0.50, 95% confidence interval (CI) 0.41, 0.60, Pandemic HR: 0.75, 95% CI: 0.65, 0.87). There was increased admissions for heart failure during the pandemic for all ethnic groups, though highest in those of White ethnicity (heart failure risk difference: 5.4). Relatively, ethnic differences narrowed for heart failure admission in those of Asian (Pre-pandemic HR 1.56, 95% CI 1.49, 1.64, Pandemic HR 1.24, 95% CI 1.19, 1.29) and Black ethnicity (Pre-pandemic HR 1.41, 95% CI: 1.30, 1.53, Pandemic HR: 1.16, 95% CI 1.09, 1.25) compared with White ethnicity. For other outcomes the pandemic had minimal impact on ethnic differences. Interpretation: Our study suggests that ethnic differences in clinical monitoring and hospitalisations remained largely unchanged during the pandemic for most conditions. Key exceptions were hospitalisations for diabetic ketoacidosis and heart failure, which warrant further investigation to understand the causes. Funding: LSHTM COVID-19 Response Grant (DONAT15912).

Objectives UK longitudinal population studies have complex governance structures and participant safeguards. As a new Trusted Research Environment (TRE) for >20 longitudinal studies, the UK Longitudinal Linkage Collaboration (UK LLC) must ensure effective public/participant input to make central design and operational decisions whilst retaining participant trust and acceptability. Approach The UK LLC’s governance model is based on the principle that participant trust lies with their study; not supporting infrastructure providers. Therefore, the UK LLC takes responsibility for system governance and data sharing agreements whilst studies retain control over participant data and its uses. Our public/participant model reflects this. We have established centralised groups to advise on data access applications and on UK LLC communications. Simultaneously we work with study managers to gain insight from their involvement work and also commission UK LLC specific activities. Including participants as well as the public helps elicit a range of input and views. Results We have integrated public/participant input across the UK LLC by recruiting: a public panel to review applications; an advisory panel to contribute to our methodological development; and public/participant advisors to sit on the UK LLC Strategic Advisory Committee. We also work with studies’ involvement managers to draw insights from, and coordinate new, study-level involvement. This has informed the development of data application frameworks and brings a public viewpoint to decisions regarding linkage of functionally anonymous participant NHS records for research. The involvement of study participant groups has shaped the design of data flows into the TRE (e.g., where some studies do not permit the flow of address data for geospatial research) and has helped set a ‘social contract’ regarding acceptable UK LLC data use. Conclusion Working with public/participant representatives directly, and in partnership with study managers, we have developed safeguards and integrated a public/participant voice into key UK LLC activities. Our ongoing aim is to develop a sustainable new-way-of-working for record linkage in longitudinal research which is acceptable to participants and the public.

Objectives Developing a rigorous application process for COVID-19 linked data within the UK Longitudinal Linkage Collaboration’s Trusted Research Environment (TRE) included balancing the requirements of 20+ longitudinal studies and several data providers with the need to provision data to researchers in a safe and efficient manner. Approach The UK LLC is an innovative project, developing a new approach to linking >20 well-established longitudinal studies to routine health and administrative records. Setting up the process included consultation with stakeholders and other multifaceted data resources in order to implement the best practices available. We also had to acknowledge constraints imposed by a variety of data controllers and ensure meaningful public contribution. The initial process had to be flexible while we assessed the first applications, and because the TRE was regularly being updated with new data. This required an adaptive approach where the process was created, adopted, and re-evaluated in real-time. Results The UK LLC has a three-stage application and review process, starting with an enquiry through the HDRUK Innovation Gateway. Enquiries are triaged to ensure the applications meet basic requirements (UK-based, COVID-19 related, scientifically sound, and feasible) before the applicants are invited to submit a full application. The full application is then reviewed internally against the Five Safes model, in communication with applicants. Approved applications move on to the third stage which includes a review by Data Access Committees (DACs) for each study whose data is requested, and the UK LLC DAC - comprised of a public review panel advising on lay summaries and public involvement in the proposed project, and, if applicable, an additional linked data review panel on behalf of NHS Digital. Conclusion Our process is still evolving as new datasets are added and in response to feedback. However, the team has risen to the challenge of balancing this with the needs of 20+ studies, stakeholders, applicants, and participant/public contributors, to create an agile process that can handle complex needs and requirements.