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      Health Data Linkage for UK Public Interest Research: Key Obstacles and Solutions

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          Abstract

          Introduction

          Analysis of linked health data can generate important, even life-saving, insights into population health. Yet obstacles both legal and organisational in nature can impede this work.

          Approach

          We focus on three UK infrastructures set up to link and share data for research: the Administrative Data Research Network, NHS Digital, and the Secure Anonymised Information Linkage Databank. Bringing an interdisciplinary perspective, we identify key issues underpinning their challenges and successes in linking health data for research.

          Results

          We identify examples of uncertainty surrounding legal powers to share and link data, and around data protection obligations, as well as systemic delays and historic public backlash. These issues require updated official guidance on the relevant law, approaches to linkage which are planned for impact and ongoing utility, greater transparency between data providers and researchers, and engagement with the patient population which is both high-profile and carefully considered.

          Conclusions

          Health data linkage for research presents varied challenges, to which there can be no single solution. Our recommendations would require action from a number of data providers and regulators to be meaningfully advanced. This illustrates the scale and complexity of the challenge of health data linkage, in the UK and beyond: a challenge which our case studies suggest no single organisation can combat alone. Planned programmes of linkage are critical because they allow time for organisations to address these challenges without adversely affecting the feasibility of individual research projects

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          Most cited references19

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          Consensus Statement on Public Involvement and Engagement with Data Intensive Health Research

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            “You hoped we would sleep walk into accepting the collection of our data”: controversies surrounding the UK care.data scheme and their wider relevance for biomedical research

            An ‘Information Centre’ has recently been established by law which has the power to collect, collate and provide access to the medical information for all patients treated by the National Health Service in England, whether in hospitals or by General Practitioners. This so-called ‘care.data’ scheme has given rise to major and ongoing controversies. We will sketch the background of the scheme and look at the responses it has elicited from citizens and medical professionals. In Autumn 2013, NHS England set up a care.data website where citizens could record their concerns regarding the collection of health-related data by the Information Centre. We have reviewed all the comments on this website up until June 2015. We have also analysed the readers’ comments on the coverage of the care.data scheme in one of the main national UK newspapers. When discussing the responses of citizens, we will make a distinction between the problems that citizens detect and the solutions they propose. The solutions that are being perceived as the most relevant ones can be summarized as follows: citizens wish to further the common good without being manipulated into doing it, while at the same time being safeguarded against various abuses. The issue of trust turns out to figure prominently. Our analysis of reactions to the scheme in no way pretends to be exhaustive, yet it provides various relevant insights into the concerns identified by citizens as well as medical professionals. These concerns, moreover, have a more general relevance in relation to other contexts of medical data-mining as well as biobank research. Our analysis also offers important pointers as to how those concerns might be addressed.
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              Data linkage infrastructure for cross-jurisdictional health-related research in Australia

              Background The Centre for Data Linkage (CDL) has been established to enable national and cross-jurisdictional health-related research in Australia. It has been funded through the Population Health Research Network (PHRN), a national initiative established under the National Collaborative Research Infrastructure Strategy (NCRIS). This paper describes the development of the processes and methodology required to create cross-jurisdictional research infrastructure and enable aggregation of State and Territory linkages into a single linkage “map”. Methods The CDL has implemented a linkage model which incorporates best practice in data linkage and adheres to data integration principles set down by the Australian Government. Working closely with data custodians and State-based data linkage facilities, the CDL has designed and implemented a linkage system to enable research at national or cross-jurisdictional level. A secure operational environment has also been established with strong governance arrangements to maximise privacy and the confidentiality of data. Results The development and implementation of a cross-jurisdictional linkage model overcomes a number of challenges associated with the federated nature of health data collections in Australia. The infrastructure expands Australia’s data linkage capability and provides opportunities for population-level research. The CDL linkage model, infrastructure architecture and governance arrangements are presented. The quality and capability of the new infrastructure is demonstrated through the conduct of data linkage for the first PHRN Proof of Concept Collaboration project, where more than 25 million records were successfully linked to a very high quality. Conclusions This infrastructure provides researchers and policy-makers with the ability to undertake linkage-based research that extends across jurisdictional boundaries. It represents an advance in Australia’s national data linkage capabilities and sets the scene for stronger government-research collaboration.
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                Author and article information

                Journal
                Int J Popul Data Sci
                Int J Popul Data Sci
                IJPDS
                International Journal of Population Data Science
                Swansea University
                2399-4908
                2 April 2019
                2019
                : 4
                : 1
                : 1093
                Affiliations
                [1 ] Centre for Health, Law and Emerging Technologies, University of Oxford, Ewert House, Oxford, OX2 7DD, UK
                [2 ] Great Ormond Street Hospital Institute of Child Health and UCL Institute of Informatics, 222 Euston Road, London NW1 2DA, UK
                [3 ] Intensive Care National Audit & Research Centre, 24 High Holborn, London WC1V, UK
                [4 ] Data Science Building, Swansea University Medical School, Singleton Park, Swansea SA2 8PP, UK
                [5 ] Centre for Health, Law and Emerging Technologies, Melbourne Law School, Level 9, 185 Pelham Street, University of Melbourne, Victoria 3010, Australia
                Author notes
                [*] [* ] Corresponding author: M Mourby. miranda.mourby@ 123456dph.ox.ac.uk

                Statement on conflicts of interest: The authors declare they have no conflict of interest.

                Article
                4:1:09 S2399490819010930
                10.23889/ijpds.v4i1.1093
                7482514
                32935027
                a30027a5-746f-44e2-9e2b-76aa81f932b9

                This work is licensed under a Creative Commons Attribution 4.0 International License.

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                Categories
                Population Data Science

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