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Introduction Birth cohorts are valuable resources for studying early life, the determinants of health, disease, and development. They are essential for studying life course. Dynamic longitudinal electronic cohorts use routinely collected data, are live, and can reduce selection bias specifically associated with direct recruitment in traditional birth cohorts. However, they are limited to health and administrative data and may lack contextual information. The MIREDA (Mother and Infant Research Electronic Data Analysis) partnership creates a UK-wide birth cohort by aligning existing electronic birth cohorts to have the same structure, content, and vocabularies, enabling UK-wide federated analyses. Objectives 1) Create a core dynamic, live UK-wide electronic birth cohort with approximately 500,000 new births per year using a common data model (CDM). 2) Provide data linkage and automation for long-term follow up of births from the Clinical Practice Research Datalink (CPRD), MuM-PreDiCT and the `Born in' initiatives of Bradford, Wales, Scotland, and South London for comparable analyses. Methods We will establish core data content and collate linkable data. A suite of extraction, transformation, and load (ETL) tools will be used to transform data for each birth cohort into the CDM. Transformed datasets will remain within each cohort's trusted research environment (TRE). Metadata will be uploaded for the public to the Health Data Research (HDRUK) Innovation Gateway. We will develop a single online data access request for researchers. A cohort profile will be developed for researchers to reference the resource. Ethics Each cohort has approval from their TRE through compliance with their project application processes and information governance. Dissemination We will engage with researchers in the field to promote our resource through partnership networking, publication, research collaborations, conferences, social media, and marketing communications strategies.

Objective Construct an innovative open-learning solution that provides comprehensive training specific to Trusted Research Environments (TRE) and the broader research community of administrative data users, irrespective of their proficiency levels. DOL offers training opportunities tailored to meet each user's unique learning needs, enabling them to utilise complex, linked administrative datasets confidently and effectively for meaningful research outcomes, thereby building capacity for sustainable national data infrastructure. Approach DOL’s innovative open-learning solution offers two learning formats: adaptive and experiential. Adaptive learning provides registered users with bitesize self-paced training based on Administrative Data Research UK's priorities. Experiential learning involves online workgroups with real-world context and practical application. They meet twice a year and are designed around specific topics with frequent guest speakers who are experts in their fields. Conclusion DOL’s innovative open-learning solution empowers TREs, such as SAIL Databank, to provide well-rounded learning that fosters community support, knowledge-sharing, and networking opportunities for its users, while gathering valuable user feedback. Users can personalise learning and test their knowledge in a flexible training environment, allowing them to take charge of their learning journey. Implication In response to the increasing demand for training services from novice to advanced users, SAIL Databank adopted DOL's dual learning approach by (1) developing training courses that cover access, process, methodology, integration, and analytical tools for SAIL TRE users, (2) engaging users in a series of workgroups focused on themed datasets including Justice, Environmental, Maternal, Education, and Core Health.

Introduction When a child has suffered, or is at risk of suffering, significant harm from parents or caregivers, the local authority may issue Section 31 (s.31) Care and Supervision proceedings under the Children Act (1989). Objectives We compared the healthcare use of infants less than one year old subject to s.31 proceedings in Wales (n = 1,332),to that of a comparison group of infants not subject to s.31 proceedings (n = 204,417), between January 2011 and February 2020. Methods Population-based e-cohort study utilising data held in the Secure Anonymised Information Linkage (SAIL) Databank. Infants in s.31 proceedings were identified using the Children and Family Court Advisory and Support Service dataset. This was linked to demographic and healthcare datasets, to identify General Practice (GP) visits, emergency department (ED) attendances, and hospital admissions (emergency and elective); before the study end date or the child's first birthday for the comparison group, orbefore the s.31 application date.Regression analysis calculated event rate ratios [RR] and incidence rate ratios [IRR] for healthcare events, adjusting for widerdeterminants of health (e.g. perinatal factors, maternal mental health, deprivation), and investigated reasons for healthcare use. Results Infants in s.31 proceedings had ahigher number and incidence of healthcare events compared with the comparison group, across all healthcare settings. Differences were greatest for emergency hospital admissions (IRR = 4.03, 95% confidence interval [CI] = 3.53 - 4.59; RR = 4.60, CI = 3.90 - 5.41). "Injury and poisoning" was the main reason for emergency admissions amongst infants in s.31 proceedings. For ED presentations, emergency hospital admissions, and GP visits, there were proportionally more events for these infants across all top ten reasons for healthcare. Conclusions Findings highlight greater healthcare utilisation for infants involved in s.31 proceedings in Wales, helping to build a better understanding of their needs and vulnerabilities.

Objectives Under section 31 (s.31) of the UK Children Act 1989, public law care proceedings can be issued if there is concern a child is subject to, or at risk of significant harm. We examined health vulnerabilities of parents involved in public law care proceedings in the two-year period prior to involvement. Approach Our study created an anonymised individual-level population-based cohort, with a matched comparison group of parents in Wales who were not subject to care proceedings, matched on age, sex and deprivation. Family court data provided by Cafcass Cymru were linked to population-level healthcare records held within the Secure Anonymised Information Linkage (SAIL) Databank. Demographic characteristics, overall health service use and health profiles of parents of children subject to s.31 care proceedings between 2011 and 2019 were examined. Results Data were available for 8,821 parents involved in care proceedings between 2011 and 2019, with a comparison group of 32,006 parents. Nearly half (47.6%) of cohort parents resided in the most deprived quintile. Higher levels of healthcare use were found for cohort mothers and fathers compared to the comparison group across multiple healthcare settings, with the most pronounced differences for emergency department attendances (59.3% vs 37.0%). Health conditions with the largest variation between groups were related to mental health (43.6% vs 16.0%), substance use (19.4% vs 1.6%) and injuries (41.5% vs 23.6%). Conclusion This study highlights the heightened socioeconomic and health vulnerabilities of parents who experience care proceedings concerning a child. Better understanding of the needs and vulnerabilities of this population may provide opportunities to improve a range of support and preventative interventions that respond to crises in the community.

Objectives The BREATHE Health Data Research Hub for Respiratory Health was formed in October 2019 as a multi-site academic consortium with multiple industrial partners via an Industry Forum and across its wider network. BREATHE’s main mission is enhancing data services within respiratory science, funded by the UKRI Industrial Strategy Challenge Fund. Approach BREATHE leveraged expertise across its founding sites and industrial partners to create data services which could be used by multiple sectors of collaborator. Across the founding sites, BREATHE was able to mobilise datasets housed within national TREs to form real-world evidence eCohorts for rapid and efficient respiratory study (Asthma, COPD, ILD), and has worked with specialists in cohort study and genomic data to house and supply these from within our partner TRE, SAIL Databank. As well as data assets, BREATHE is able to provide clinical and data expertise to collaborators for grant submissions and on bespoke respiratory science projects. Results Including a significant period of work during the pandemic supporting COVID-19 research and also focusing on other respiratory disease science support, BREATHE is now well-placed to move towards a sustainable operating plan post-grant from March 2023. Due to the approach taken in maximising data services for multiple sectors, BREATHE is positioned to provide data linkage and sharing services (making use of its TRE, SAIL Databank), providing analytic and clinical support to respiratory research projects for customers in multiple sectors (Pharma, SMEs, Academia, NHS, Charities), and advancing synthetic data and software development, again in partnership with SAIL and our wider industry partners. Conclusion As of March 2022, BREATHE has established a portfolio of data services and projects interfacing with multiple sectors of collaborator in enhancing respiratory science projects across the UK. With population-level data assets representing Wales, Scotland, and England and the ability to work with the Northern Ireland infrastructure housed at Swansea University, BREATHE supports 4-nation respiratory science in RWE data, and provides clinical and data linkage expertise to studies such as longitudinal cohorts, pharma companies, and contract research organisations.

Introduction In Wales, the Children in Need (CIN) dataset includes information relating to needs of children and social care support. Before the Social Services and Well-being (Wales) Act 2014 came into force in April 2016, this data collection was named the Children in Need census, changing to Children Receiving Care and Support (CRCS) after this date to reflect better the children eligible for inclusion. This paper describes these datasets, their potential for research and their limitations. We describe data that researchers can access via the Secure Anonymised Information Linkage (SAIL) Databank and exploratory linkages made to health records. Methods CIN and CRCS data were transferred to the SAIL Databank using a standardised approach to provide de-identified data with Anonymised Linking Fields (ALF) for successfully matched records. The linkage method relies on the use of Unique Pupil Numbers (UPN). As such, no records are currently available for children without a UPN, which includes most under age three. ALFs enabled linkage to individual-level health data within SAIL. Health service use was compared to non-CIN/CRCS populations. Results CRCS data held within the SAIL Databank comprises 25,972 records, 81% of the total number of records reported by the Welsh Government. The CIN data contains 108,449 records, 79% of the Welsh Government's records for this data collection. Health service use of children in need, and children receiving care and support, was roughly equal to that of the non-CIN/CRCS population, except GP visits, where children in need had fewer consultations, and children receiving care and support had more consultations than the comparison population. Conclusion Researchers can access Welsh CIN and CRCS datasets through the SAIL Databank, enabling research opportunities. Work is ongoing to improve records and to understand better the health and health service use among children captured by CIN and CRCS censuses.

Introduction: On June 24 in the United Kingdom, there were 277,989 cases of COVID-19 and 39,369 deaths recorded. The government enforced a complete lockdown on March 23 that resulted in cessation of all elective admissions on 24th onward, with only acute trauma cases being admitted to hospital. This study aims to characterize the changes in trauma admissions during the first 5-week lockdown period. The hypothesis states that there would be a significant reduction in overall orthopedic trauma admissions, polytrauma, and high-energy outdoor trauma during this COVID-19 period. Methods: All trauma admissions over nearly a 5-week period from March 23, 2020, to April 26, 2020, were collated as the “COVID cohort” and compared to the “control” group of patients from the same hospitals 1 year before between March 23, 2019, and April 26, 2019. Spinal admissions and pediatrics were excluded from the study as they were managed in other regional units. Results: There was a 56% reduction in trauma admissions during the COVID-19 lockdown (133 vs. 304). A majority of the COVID cohort were admitted with fractures (89 vs. 164, P = 0.017, Chi-square test) from home with low-energy falls. Overall, fewer operations were performed than the year before. However, a greater proportion of admitted patients had a surgical orthopedic intervention rather than admission and nonoperative management. Conclusions: There was a reduction in admissions as well as reductions in high energy and occupational injuries. Elderly patients continued to fall at home or in care, sustaining hip fractures. This vulnerable group requires beds, orthogeriatric management followed by surgical intervention and social care. Orthogeriatric services must be maintained to ensure the best clinical outcomes for this group.

A mixed metal oxide W-TiO2 nanopowder photocatalyst was prepared by using the sol–gel method with a broad range of elemental compositions x = CW/(CW + CTi), including TiO2 and WO3. The material was structurally characterized and evaluated in adsorption and photocatalytic processes by testing its removal capacity of a representative pollutant methylene blue (MB) in aqueous solutions and under UV-A and sunlight illuminations. The nanopowders appeared to be more effective adsorbents than pure TiO2 and WO3 materials, showing a maximum at 15 mol% W, which was set as the tungsten solubility limit in anatase titania. At the same time, the photocatalytic decomposition of MB peaked at 2 mol% W. The examination of different compositions showed that the most effective MB removal took place at 15 mol% W, which was attributed to the combined action of adsorption and heterogeneous photocatalysis. Moreover, MB decomposition under sunlight was stronger than under UV-A, suggesting photocatalyst activation by visible light. The pollutant removal efficiency of the material with 15 mol% W was enhanced by a factor of ~10 compared to pure TiO2 at the beginning of the process, which shows its high potential for use in depollution processes in emergency cases of a great pollutant leak. As a result, a Wx=0.15-TiO2 catalyst could be of high interest for wastewater purification in industrial plants. [ABSTRACT FROM AUTHOR]

BackgroundSeveral countries restricted the administration of ChAdOx1 to older age groups in 2021 over safety concerns following case reports and observed versus expected analyses suggesting a possible association with cerebral venous sinus thrombosis (CVST). Large datasets are required to precisely estimate the association between Coronavirus Disease 2019 (COVID-19) vaccination and CVST due to the extreme rarity of this event. We aimed to accomplish this by combining national data from England, Scotland, and Wales.Methods and findingsWe created data platforms consisting of linked primary care, secondary care, mortality, and virological testing data in each of England, Scotland, and Wales, with a combined cohort of 11,637,157 people and 6,808,293 person years of follow-up. The cohort start date was December 8, 2020, and the end date was June 30, 2021. The outcome measure we examined was incident CVST events recorded in either primary or secondary care records. We carried out a self-controlled case series (SCCS) analysis of this outcome following first dose vaccination with ChAdOx1 and BNT162b2. The observation period consisted of an initial 90-day reference period, followed by a 2-week prerisk period directly prior to vaccination, and a 4-week risk period following vaccination. Counts of CVST cases from each country were tallied, then expanded into a full dataset with 1 row for each individual and observation time period. There was a combined total of 201 incident CVST events in the cohorts (29.5 per million person years). There were 81 CVST events in the observation period among those who a received first dose of ChAdOx1 (approximately 16.34 per million doses) and 40 for those who received a first dose of BNT162b2 (approximately 12.60 per million doses). We fitted conditional Poisson models to estimate incidence rate ratios (IRRs). Vaccination with ChAdOx1 was associated with an elevated risk of incident CVST events in the 28 days following vaccination, IRR = 1.93 (95% confidence interval (CI) 1.20 to 3.11). We did not find an association between BNT162b2 and CVST in the 28 days following vaccination, IRR = 0.78 (95% CI 0.34 to 1.77). Our study had some limitations. The SCCS study design implicitly controls for variables that are constant over the observation period, but also assumes that outcome events are independent of exposure. This assumption may not be satisfied in the case of CVST, firstly because it is a serious adverse event, and secondly because the vaccination programme in the United Kingdom prioritised the clinically extremely vulnerable and those with underlying health conditions, which may have caused a selection effect for individuals more prone to CVST. Although we pooled data from several large datasets, there was still a low number of events, which may have caused imprecision in our estimates.ConclusionsIn this study, we observed a small elevated risk of CVST events following vaccination with ChAdOx1, but not BNT162b2. Our analysis pooled information from large datasets from England, Scotland, and Wales. This evidence may be useful in risk-benefit analyses of vaccine policies and in providing quantification of risks associated with vaccination to the general public.

Abstract Background Medanta - The Medicity, a multi-super specialty corporate hospital in Gurugram, Haryana launched a “TB-Free Haryana” Campaign; mobile van equipped with a digital CXR machine to screen patients with presumptive Tuberculosis (TB). Objectives: In this study, we aimed to assess the (1) yield and cost analysis of two strategies using mobile digital x-ray to detect Pulmonary TB in rural Haryana. Methods An observational study was conducted on all individuals screened by either of the two case finding strategies using a mobile x-ray unit (MXU) mounted on a mobile van in District Mewat, Haryana during Jan-March 2016. Results Strategy 1: Out of 121 smear negative cases, x-rays were suggestive of TB in 39(32%), of which 24 were started on TB treatment. Cost of identifying a smear negative TB was US$ 32. Strategy 2: Out of 596 presumptive TB, chest x-rays were suggestive of TB in 108 (18%), of which 67 were started on TB treatment (56 were smear negative TB). Cost of detecting any case of TB was US$ 08 (1 USD = 64 INR). Conclusion The study reports a new initiative within a PPM model to improve the diagnosis of PTB by filling the gap in the current diagnostic infrastructure. We believe there is potential for replication of strategy 2 model in other states, although further evidence is required.

Introduction The importance of the determinants of health to health outcomes has long been established. Historically, data from each of these sectors has been captured in disparate, often siloed, sources. Attempts to integrate these data have faced a number of challenges including technical, legislative and interpretative barriers, creating inefficiencies and inhibiting knowledge sharing. Despite this, there have been notable successes where intersectoral data and health data have been brought together in a meaningful way. The establishment of strong partnerships, with academia, governments, privacy and legal sectors, and other bodies, across sectors has been key to this success. These partnerships ensure data are integrated, analyzed, and interpreted accurately and appropriately, while also leveraging existing investments and expertise. Objectives and Approach The objective of this session is to explore the role of partnerships throughout the data integration life cycle, from initial discussions, to data integration, through to connecting research output to policy impact. Each of the presenters will discuss the successes, barriers and mitigation strategies they have experienced across different jurisdictions using real world examples. Results Health research institutes globally are increasingly able to access routinely collected intersectoral data from non-health sectors. In each institute, data are unique, complex and have been collected in a manner consistent with the needs of the sector. As health research institutes work to understand the data structures and determine the best way to link, use and interpret the information according to national and international best practice guidelines, it has become clear that it is critical to undertake this in partnership with experts from each sector, who understand how the data was collected and can guide appropriate interpretation. In addition, these partnerships have enabled the connection of policy priorities in other sectors with research done in the health sector using intersectoral data. For example, in addition to supporting government health departments, health research institutes have collaborated with other government ministries including immigration, social services, and education. This session will present real world examples from local (provincial), national and international contexts, and highlight a novel data platform, being developed to minimize barriers to data access and use across sectors and jurisdictions. Conclusion / Implications The participants on this panel will demonstrate the importance of partnership throughout the data integration life cycle when working with intersectoral data using real world examples. Collaboration increases the value of integrated data to both health and non-health sectors, through the connection of policy priorities and support of research across the determinants of health.

Introduction There is no power for change greater than a community discovering what it cares about.1 The Health Data Platform (HDP) will democratize British Columbia’s (population of approximately 4.6 million) health sector data by creating common enabling infrastructure that supports cross-organization analytics and research used by both decision makers and cademics. HDP will provide streamlined, proportionate processes that provide timelier access to data with increased transparency for the data consumer and provide shared data related services that elevate best practices by enabling consistency across data contributors, while maintaining continued stewardship of their data. HDP will be built in collaboration with Swansea University following an agile pragmatic approach starting with a minimum viable product. Objectives and Approach Build a data sharing environment that harnesses the data and the understanding and expertise about health data across academe, decision makers, and clinicians in the province by: • Enabling a common harmonized approach across the sector on: • Data stewardship • Data access • Data security and privacy • Data management • Data standards • To: • Enhance data consumer data access experience • Increase process consistency and transparency • Reduce burden of liberating data from a data source • Build trust in the data and what it is telling us and therefore the decisions made • Increase data accessibility safely and responsibly Working within the jurisdiction’s existing legislation, the Five Safes Privacy and Security Framework will be implemented, tailored to address the requirements of data contributors. Results The minimum viable product will provide the necessary enabling infrastructure including governance to enable timelier access, safely to administrative data to a limited set of data consumers. The MVP will be expanded with another release planned for early 2021. Conclusion / Implications Collaboration with Swansea University has enabled BC to accelerate its journey to increasing timelier access to data, safely and increasing the maturity of analytics by creating the enabling infrastructure that promotes collaboration and sharing of data and data approaches. 1 Margaret Wheatley

Introduction The BREATHE Health Data Research Hub is a consortium of five academic institutions and several industry partners seeking to facilitate and accelerate respiratory science initiatives and outcomes. Unlocking organisational, jurisdictional, and scientific challenges, such as differing and inherent complexities with data standards, incongruous governance, and disparate data access mechanisms for over 100 diverse UK datasets are key aims. Objectives and Approach Central to the data effort is the UK Secure eResearch Platform (SeRP UK), and its flagship tenancy, the SAIL Databank. Onboarding datasets, making them remotely available to the respiratory research community, is a key approach. Datasets targeted range from population cohort studies, to respiratory trials data, routine healthcare datasets, and specialist ‘omics data. Partnerships with national safe havens and providers such as eDRIS and NHS Digital will enable BREATHE to expedite and improve wider sharing of datasets for the respiratory science. Data improvements focus on datasets from primary, secondary, and tertiary care from national healthcare systems, ‘respiratorising’ these datasets and increasing utility for academic and industry respiratory scientists. Incorporating dataset metadata and access permutations into national cataloguing systems at HDR UK, standardising metadata, and interoperability for in-scope datasets form a concerted data quality improvement effort. Results Facilitating data sharing through initiatives such as BREATHE will increase visibility and accessibility for datasets within respiratory science, whilst addressing national cultural and governance issues to data sharing. BREATHE data sharing processes will allow for team science to be undertaken in a highly collaborative manner and allow for best practise in data collection and sharing to flow to nationwide datasets in respiratory science. Conclusion / Implications Collaborative hubs with scientific domain expertise can be created and leveraged to accelerate data sharing and data science within the scientific area. These collaborative efforts can however be translated to other disease-specific efforts, and indeed disease agnostic platform solutions.

Introduction: The long-term health and wellbeing of adoptees is under-researched. One reason for this has been limited data accessibility regarding the adoption process, and another is a practice common in some UK jurisdictions of changing the NHS number (or equivalent) at adoption, as part of creating the new identity. The SAIL Databank holds data from the Wales Children and Family Court Advisory and Support Service (Cafcass Cymru), together with children’s social care data, and can link these with routine health and administrative data in anonymised form. However, because the linkage key at SAIL is based on an encryption of the NHS number, working with pre- and post-adoption records for longitudinal research remains a major challenge. We set out to explore the legal implications of, and social support for, linking these records for use in anonymised form for longitudinal research. Methods: We reviewed the main legislation and regulations governing the use of data about adoptees in England and Wales. We gauged support for a social licence in Wales by carrying out interviews with individuals who had been involved in the adoptions process, and by engaging with general public groups for their views. We drew out the main emerging themes and, in combination with the review, propose a way forward. Results: The legal review indicated that there are provisions in the Family Procedure Rules (England and Wales) and the General Data Protection Regulation that can be relied upon for the lawful processing of adoption data into anonymised form for research. The main points of concern about linking pre- and post-adoption records were privacy, data security, the need to limit the number of organisations involved in data sharing, and re-identification risk. The over-riding message was favourable with longitudinal research seen as strongly beneficial. Conclusion: This study has indicated that in Wales, there is no legal impediment, nor major objection from individuals involved in the adoptions process, as well as the general public for the use of adoption data in anonymised form, in a data safe haven. This includes the linkage of pre- and post‑adoption records to enable novel longitudinal research to take place. The provisos were that robust safeguards must be in place, and that the research should aim to benefit adoptees and to improve policy and practice. We conclude that it is reasonable to proceed with caution to develop practical ways to link pre- and post‑adoption records in a data safe haven.

Background: The SAIL Databank is a data safe haven established in 2007 at Swansea University (Wales). It was set up to create new opportunities for research using routinely-collected health and other public service datasets in linkable anonymised form. SAIL forms the bedrock of other Population Data Science initiatives made possible by the data and safe haven environment. Aim: The aim of this paper is to provide an overview of public involvement and engagement in connection with the SAIL Databank and related Population Data Science initiatives. Approach: We have a public involvement and engagement policy for SAIL in the context of Population Data Science. We established a Consumer Panel to provide advice on the work of SAIL and associated initiatives, including on proposed uses of SAIL data. We reviewed the topics discussed and provide examples of advice to researchers. We carried out a survey with members on their experiences of being on the Panel and their perceptions of the work of SAIL. We have a programme of wider public engagement and provide illustrations of this work. Discussion: We summarise what this paper adds and some lessons learned. In the rapidly developing area of Population Data Science it is important that people feel welcome, that they are encouraged to ask questions and are provided with digestible information and adequate consideration time. Citizens have provided us with valuable anticipated and unanticipated opinions and novel viewpoints. We seek to take a pragmatic approach, prioritising the communication modes that allow maximum public input commensurate with the purpose of the activity. Conclusion: This paper has set out our policy, rationale, scope and practical approaches to public involvement and engagement for SAIL and our related Population Data Science initiatives. Although there will be jurisdictional, cultural and organizational differences, we believe that the material covered in this paper will be of interest to other data focused enterprises across the world.

Background The great benefits of linking health datasets for research in the public interest have long been demonstrated. More recently, we are seeing an increase in the availability of wider administrative data, such as employment, education and housing, to add new opportunities for population data science. However, there are challenges to be overcome in selecting a data linkage approach. Main Aim We set out to examine various data linkage approaches, and to formulate some high level questions to inform decision-making. Methods We used published literature to review various data linkage methods in theory and in practical settings. The study was commissioned by the UK Government Statistical Service and a key focus was privacy and confidentiality in data linkage. Results The questions we formulated are based on: Legislative position; Information systems; Nature of datasets; Knowledge-base; Aims and purposes; Ground truth; and Environment. Conclusion There are many factors influencing the selection of a data linkage approach. While not exhaustive, our set of questions covers some of the major ones. The findings of the study are being taken forward by UK Government Statistical Service and government departments to inform decision-making on options for data linkage research and the greater availability of their datasets.

Background/Rationale Linked administrative datasets offer great potential for research, but also present major challenges—including the preparation of operational data into a form suitable for efficient research, complex and computationally demanding analysis, and the need to capture and share information about dataset contents and research methods. Main Aim The analytical services team in the Secure Anonymised Information Linkage (SAIL) Databank is creating interconnected tools and systems to automate the preparation and analysis of research data and to curate information about datasets and research methods. Our underlying goal is to make linked data research orders of magnitude faster and cheaper, as well as improve its consistency and quality. Methods Several key developments are ongoing: • Automation of data quality checking. • Management of dataset metadata. • Processing of raw source datasets into cleaned, research-ready data assets. • The Concept Library, an application for creating, using, and sharing knowledge about research definitions and methods. • A suite of R packages for analysis. Web Application Programming Interfaces will allow these pieces to work together as an integrated system enabling efficient research. Results Initial versions of dataset quality checking, cleaned datasets, and R code to implement common tasks are already in day-to-day use by researchers within SAIL. An advisory group has been convened to help guide the work. For example, shared library code that flags conditions within health data has been used across multiple projects; a cleaned dataset measuring follow-up within primary care has been used by more than 100 projects. Conclusion Our proof-of-concept work demonstrates the ability of shared code and cleaned data to meet needs across multiple projects, saving effort and standardizing results. Ongoing work to develop and integrate these tools should further streamline the research process, increasing the output and public benefit of SAIL and other data sources.

Background Not enough is known about how the family justice system is working, the children and families using these services, and their wider outcomes beyond their involvement with the family court. The Nuffield Family Justice Observatory (FJO) Data Partnership, comprising a bespoke analysis platform hosted within the Secure Anonymised Information Linkage (SAIL) Databank and analytical teams at Lancaster and Swansea Universities, has been established to address this knowledge deficit. Methods Family justice data is being deposited in the SAIL Databank. Data are acquired using a standardised split-file approach, stored in an anonymised format and made available to projects as linked data using a unique encrypted project anonymised linkage field. These data can be augmented with a wealth of available health, education and other governmental/social routinely collected datasets, and future data acquired from other sources, for a range of research projects. Results Children and Family Court Advisory and Support Service (Cafcass) Cymru data has been transferred to the SAIL Databank, and agreements to transfer the Cafcass England data are being finalised. Applications are now welcomed to use these data to enhance understanding of the family justice system and children and families involved with the family courts in public and private law. Access will be facilitated through the SAIL Databank, subject to relevant governance procedures. Conclusion We will discuss the rationale of the Nuffield FJO Data Partnership, and how it aims to a) increase capacity and capability of researchers and data scientists utilising family justice and other relevant administrative datasets, b) improve understanding about the family justice system using data from the Cafcass in England and Wales, c) demonstrate the complexities and value of data linkage, and d) assist future policy and practice development. We will discuss matching rates for the Cafcass Cymru data and linkages that have been made to other datasets within the SAIL Databank. We will also set out the support available from the partnership to those wishing to access and utilise family justice data.

Background/rationale Nations with advanced child protection systems place considerable emphasis on the developmental salience of infancy. However, this emphasis is not matched by any differentiated analysis of the timing of family court intervention in the lives of infants or the final legal order outcomes of these cases. This presentation shares findings from the first ever population profiling study of infants subject to care proceedings within the family justice system in England and Wales. Aim To estimate the proportion of all infant care proceedings cases issued within 7 days and 4 weeks of birth and describe case and infant characteristics; to calculate incidence rates over time and by local authority and family court region; to describe and compare legal order outcomes according to age. Methods/approach Data was extracted from case management records produced by the Children and Family Court Advisory and Support Service (Cafcass) England and Wales. Records were first restructured to link infants to legal order outcome data and birth mother records. Incidence rates were calculated using ONS mid-year population estimates and annual live births. Within the SAIL Databank, Welsh infant records were linked to birth registration and community child health data to produce a fuller picture of infant characteristics in Wales. Results The cohort we created comprised all infants recorded as subjects within care proceedings in England (2007/08-2016/17) and Wales (2011/12-2018/19). The study captured the high proportion of infant cases that are issued at/close to birth, but also marked regional and local authority variation in incidence rates. Conclusion High rates of adoption, particularly for babies born to mothers without a previous family court history, have prompted calls for new preventative solutions. The President of the Family (Court) Division in England has initiated a review of legal proceedings at birth.