Guidance for researchers wanting to link NHS data using non-consent approaches: a thematic analysis of feedback from the Health Research Authority Confidentiality Advisory Group

Research output: Contribution to journalArticlepeer-review

Authors

  • Lauren Cross
  • Amelia Jewell
  • Margaret Heslin
  • David Osborn
  • Johnny Downs
  • Robert Stewart

Colleges, School and Institutes

Abstract

Introduction The use of linked data and non-consent methodologies is a rapidly growing area of health research due to the increasing detail, availability and scope of routinely collected electronic health records data. However, gaining the necessary legal and governance approvals to undertake data linkage is a complex process in England. Objectives We reflect on our own experience of establishing lawful basis for data linkage through Section 251 approval, with the intention to build a knowledgebase of practical advice for future applicants. Methods Thematic analysis was conducted on a corpus of Section 251 feedback reports from the NHS Health Research Authority Confidentiality Advisory Group. Results Four themes emerged from the feedback. These were: (a) Patient and Public Involvement, (b) Establishing Rationale, (c) Data maintenance and contingency, and the need to gain (d) Further Permissions from external authorities prior to full approval. Conclusions Securing Section 251 approval poses ethical, practical and governance challenges. However, through a comprehensive, planned approach Section 251 approval is possible, enabling researchers to unlock the potential of linked data for the purposes of health research.

Bibliographic note

Funding Information: LC and LEC were supported by a Medical Research Council Mental Health Data Pathfinder Award to King’s College London. LEC also received salary support from the National Institute for Health Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King’s College Hospital NHS Foundation Trust. AJ and RS are part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust and King’s College London. JD is supported by NIHR Clinician Science Fellowship award (CS-2018-18-ST2-014) and has received support from a Medical Research Council (MRC) Clinical Research Training Fellowship (MR/L017105/1) and Psychiatry Research Trust Peggy Pollak Research Fellowship in Developmental Psychiatry. MH reports funding by NIHR and the Stefanou Foundation, UK. DO is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre (BRC) at University College London Hospitals (UCLH). DO is also supported by the National Institute for Health Research ARC North Thames. This report is independent research supported by the National Institute for Health Research ARC North Thames. The views expressed in this publication are those of the author(s) and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care. Publisher Copyright: October 2020 © The Authors. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

Details

Original languageEnglish
Article number34
JournalInternational Journal of Population Data Science
Volume5
Issue number1
Publication statusPublished - 2 Oct 2020

Keywords

  • Data linkage, Non-consent approaches, Section 251, Thematic analysis