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IntroductionMany jurisdictions have programmes for the large-scale reuse of health and administrative data that would benefit from greater cross-centre working. The Advancing Cross centre Research Networks (ACoRN) project considered barriers and drivers for joint working and information sharing using the UK Farr Institute as a case study, and applicable widely.
Objectives and ApproachACoRN collected information from researchers, analysts, academics and the public to gauge the acceptability of sharing data across institutions and jurisdictions. It considered international researcher experiences and evidence from a variety of cross centre projects to reveal barriers and potential solutions to joint working. It reviewed the legal and regulatory provisions that surround data sharing and cross-centre working, including issues of information governance to provide the context and backdrop. The emerging issues were grouped into five themes and used to propose a set of recommendations.
ResultsThe five themes identified were: organisational structures and legal entities; people and culture; information governance; technology and infrastructure; and finance and strategic planning. Recommendations within these included: standardised terms and conditions including agreements and contractual templates; performance indicators for frequency of dataset sharing; communities of practice and virtual teams to develop cooperation; standardised policies and procedures to underpin data sharing; an accredited quality seal for organisations sharing data; a dashboard for data availability and sharing; and adequate resource to move towards greater uniformity and to drive data sharing initiatives.
Conclusion/ImplicationsThe challenges posed by cross-centre information sharing are considerable but the public benefits associated with the greater use of health and administrative data are inestimable, particularly as novel and emerging data become increasingly available. The proposed recommendations will assist in achieving the benefits of cross-centre working.

BackgroundThere are there are considerable challenges to be addressed so the benefits of administrative data for research can be realised. Significant headway is being made, but there is great scope and appetite for further improvement.
ObjectivesThis study set out to explore good practice, barriers and bottlenecks in effective administrative data use, and to gain suggestions on how to share the good, solve the bad and improve the clunky issues.
MethodsUsing the ESRC-funded UK Administrative Data Research Network (ADRN) as the case study, a qualitative survey, focusing on the data use pathway, was carried out across the network. This encompassed a set of 18 questions spanning from acquisition to archiving. Survey responses were grouped into six themes: data acquisition; approval processes; controls on access and disclosure; data and metadata; researcher support; and data reuse and retention. The resulting information matrix was presented to participants at the All Hands meeting (April-May 2017) to facilitate discussion.
FindingsSurvey responses were received from across the network (N=27) and 95 people took part in the workshop. The combined information from the survey and workshop was used to inform set of 18 recommendations across the 6 themes, and this has been used by the ADRN directors to develop an action plan for implementation.
ConclusionsThe ADRN has broken new ground in overcoming many challenges in using administrative data for research in the UK. The recommendations and action plan show how further improvements will be made in the ADRCs, and the findings of this study are relevant more widely to other organisations working with administrative data.

IntroductionCall Detail Records (CDRs) are collected by mobile network operators in the course of service provision, and they are increasingly being used in health research. It has been identified that further work is needed to show that CDRs can be used within an ethically-founded framework that meets with social acceptability.
Objectives and ApproachThe published research literature was reviewed to identify data governance arrangements, challenges and potential opportunities for the greater use of the location element of CDRs in health research. A series of 3 workshops with members of the public (N=61) were conducted to gain views on the use of CDRs for health research. Data use scenarios of CDRs for health research were constructed to consider risk and mitigating controls. The findings were drawn together against a backdrop of legislative and regulatory requirements.
ResultsThe majority of published studies focused on low and middle income countries, often modelling the transmission of infectious diseases, and population movement following natural disasters. CDRs were used in anonymised or aggregated form, and gaining regulatory approvals varied with data provider and by jurisdiction. Only 2 people knew CDR data was being used for health research, but ultimately, most (N=49) were happy for their anonymised CDRs to be used, provided that safeguards were in place. Recommendations towards an ethically-founded framework for using CDR locations in health research are proposed, including the need for greater transparency, accountability, and the incorporation of public views for social acceptability.
Conclusion/ImplicationsDespite limitations inherent in the data, mobile phone CDRs have been used successfully in health research. People are generally amenable to the use of anonymised CDR data, but they want to be properly informed. The proposed recommendations should be taken into consideration to contribute towards a consistent, socially-acceptable, ethically founded framework.

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.

IntroductionIt is widely acknowledged that population health and administrative data, especially when linked at the individual level, hold great value for research. Cross-centre working between data centres providing access to such data has the potential to further increase this value by effectively expanding the data available for research. However, there is limited published information on how to address the challenges and achieve success. The aim of this paper is to explore perceived barriers and solutions to inform developments in cross-centre working across data centres.
MethodsWe carried out a narrative literature review on data sharing and cross centre working. We used a mixed methods approach to assess the opinions of members of the public on cross-centre data sharing, and the views and experiences of among data centre staff connected with the UK Farr Institute for Health Informatics Research.
ResultsThe literature review uncovered a myriad of practical and cultural issues. Our engagement with a public group suggested that cross-centre working involving anonymised data being moved between established centres is considered acceptable. The main themes emerging from discussions with data centre staff were dedicated resourcing, practical issues, information governance and culture.
ConclusionIn seeking to advance cross-centre working between data centres, we conclude that there is a need for dedicated resourcing, indicators to recognise data reuse, collaboration to solve common issues, and balancing necessary barrier removal with incentivisation. This will require on-going commitment, engagement and an academic culture change.

BackgroundFree-text data represent a vast, untapped source of rich information to guide research and public service delivery. Free-text data contain a wealth of additional detail that, if more accessible, would clarify and supplement information coded in structured data fields. Personal data usually need to be de-identified or anonymised before they can be used for purposes such as audit and research, but there are major challenges in finding effective methods to de-identify free-text that do not damage data utility as a by-product. The main aim of the TexGov project is to work towards data governance standards to enable free-text data to be used safely for public benefit.
MethodsWe conducted: a rapid literature review to explore the data governance models used in working with free-text data, plus case studies of systems making de-identified free-text data available for research; we engaged with text mining researchers and the general public to explore barriers and solutions in working with free-text; and we outlined (UK) data protection legislation and regulations for context.
ResultsWe reviewed 50 articles and the models of 4 systems providing access to de-identified free-text. The main emerging themes were: i) patient involvement at identifiable and de-identified data stages; ii) questions of consent and notification for the reuse of free-text data; iii) working with identifiable data for Natural Language Processing algorithm development; and iv) de-identification methods and thresholds of reliability.
ConclusionWe have proposed a set of recommendations, including: ensuring public transparency in data flows and uses; adhering to the principles of minimal data extraction; treating de-identified blacklisted free-text as potentially identifiable with use limited to accredited data safe-havens; and, the need to commit to a culture of continuous improvement to understand the relationships between accuracy of de-identification and re-identification risk, so this can be communicated to all stakeholders.

IntroductionAdministrative data arising via the operation of public service delivery systems hold great benefits for citizens and society providing they can be made available for research in a safe, socially-acceptable way. In recognition of this potential, the UK Administrative Data Research Network was established in 2013 to enable new research for public benefit. However, there are considerable challenges to be overcome for effective data use, and many of these are common to administrative data enterprises in general. Using this network as a practical case study, we set out to explore the challenges, and to share the 'good', suggest solutions to the 'bad', and improve the 'clunky' issues.
MethodsA qualitative survey replicating the data use pathway was carried out across the network, followed by a workshop to discuss the summarised findings and make further suggestions. This led to a set of recommendations to inform the development of an action plan for implementation.
ResultsThe survey respondents (N=27) and workshop participants (N=95) comprised multi‑disciplinary staff from across the network. The responses were summarised by consensus of three researchers and grouped into six areas: A) Data acquisition pathway; B) Approval processes; C) Controls on access & disclosure; D) Data and metadata; E) Researcher support; and F) Data reuse & retention, leading to an embedded set of 18 recommendations. Key developments promoted by this study were the development of themed research partnerships to progress data acquisition, and a policy of data retention and reuse for research.
ConclusionThe network has broken new ground in using administrative data for research. This study has enabled the development of an evidence-based action plan to address many challenges in the effective use of administrative data. It represents a practical worked example, widely relevant to enterprises working with administrative data across the world.
KeywordsAdministrative data research, data access, data linkage

BackgroundTrusted Research Environments provide a legitimate basis for data access along with a set of technologies to support implementation of the "five-safes" framework for privacy protection. Lack of standard approaches in achieving compliance with the "five-safes" framework results in a diversity of approaches across different TREs. Data access and analysis across multiple TREs has a range of benefits including improved precision of analysis due to larger sample sizes and broader availability of out-of-sample records, particularly in the study of rare conditions. Knowledge of governance approaches used across UK-TREs is limited.
ObjectiveTo document key governance features in major UK-TRE contributing to UK wide analysis and to identify elements that would directly facilitate multi TRE collaborations and federated analysis in future.
MethodWe summarised three main characteristics across 15 major UK-based TREs: 1) data access environment; 2) data access requests and disclosure control procedures; and 3) governance models. We undertook case studies of collaborative analyses conducted in more than one TRE. We identified an array of TREs operating on an equivalent level of governance. We further identify commonly governed TREs with architectural considerations for achieving an equivalent level of information security management system standards to facilitate multi TRE functionality and federated analytics.
ResultsAll 15 UK-TREs allow pooling and analysis of aggregated research outputs only when they have passed human-operated disclosure control checks. Data access requests procedures are unique to each TRE. We also observed a variability in disclosure control procedures across various TREs with no or minimal researcher guidance on best practices for file out request procedures. In 2023, six TREs (40.0%) held ISO 20071 accreditation, while 9 TREs (56.2%) participated in four-nation analyses.
ConclusionSecure analysis of individual-level data from multiple TREs is possible through existing technical solutions but requires development of a well-established governance framework meeting all stakeholder requirements and addressing public and patient concerns. Formation of a standard model could act as the catalyst for evolution of current TREs governance models to a multi TRE ecosystem within the UK and beyond.

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.

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 National Health Service (NHS) number (or equivalent) at adoption, as part of creating the new identity. The SAIL Databank holds data on child and family court cases from 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, or members of the general public, ...

Background: Clinical free-text data (eg, outpatient letters or nursing notes) represent a vast, untapped source of rich information that, if more accessible for research, would clarify and supplement information coded in structured data fields. Data usually need to be deidentified or anonymized before they can be reused for research, but there is a lack of established guidelines to govern effective deidentification and use of free-text information and avoid damaging data utility as a by-product. Objective: This study aimed to develop recommendations for the creation of data governance standards to integrate with existing frameworks for personal data use, to enable free-text data to be used safely for research for patient and public benefit. Methods: We outlined data protection legislation and regulations relating to the United Kingdom for context and conducted a rapid literature review and UK-based case studies to explore data governance models used in working with free-text data. We also engaged with stakeholders, including text-mining researchers and the general public, to explore perceived barriers and solutions in working with clinical free-text. Results: We proposed a set of recommendations, including the need for authoritative guidance on data governance for the reuse of free-text data, to ensure public transparency in data flows and uses, to treat deidentified free-text data as potentially identifiable with use limited to accredited data safe havens, and to commit to a culture of continuous improvement to understand the relationships between the efficacy of deidentification and reidentification risks, so this can be communicated to all stakeholders. Conclusions: By drawing together the findings of a combination of activities, we present a position paper to contribute to the development of data governance standards for the reuse of clinical free-text data for secondary purposes. While working in accordance with existing data governance frameworks, there is a need for further work to take forward the recommendations we have proposed, with commitment and investment, to assure and expand the safe reuse of clinical free-text data for public benefit.