Advancing cross-centre research networks: learning from experience, looking to the future

Introduction Many 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 Approach ACoRN 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. Results The 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/Implications The 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

The Good, the Bad, the Clunky and . . . the Outcomes

Background There 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. Objectives This 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. Methods Using 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. Findings Survey 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. Conclusions The 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

Public Involvement & Engagement in the work of a data safe haven: a case study of the SAIL Databank

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

Towards an ethically-founded framework for the use of mobile phone CDRs in health research

Introduction Call 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 Approach The 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. Results The 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/Implications Despite 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

Developing data governance standards for using free-text data in research (TexGov)

Background Free-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. Methods We 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. Results We 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. Conclusion We 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