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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
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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Swansea University
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8110887/ https://www.ncbi.nlm.nih.gov/pubmed/34007881 http://dx.doi.org/10.23889/ijpds.v5i1.1355 |
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author | Cross, Lauren Carson, Lauren Emma Jewell, Amelia Heslin, Margaret Osborn, David Downs, Johnny Stewart, Robert |
author_facet | Cross, Lauren Carson, Lauren Emma Jewell, Amelia Heslin, Margaret Osborn, David Downs, Johnny Stewart, Robert |
author_sort | Cross, Lauren |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8110887 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Swansea University |
record_format | MEDLINE/PubMed |
spelling | pubmed-81108872021-05-17 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 Cross, Lauren Carson, Lauren Emma Jewell, Amelia Heslin, Margaret Osborn, David Downs, Johnny Stewart, Robert Int J Popul Data Sci Population Data Science 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. Swansea University 2020-10-02 /pmc/articles/PMC8110887/ /pubmed/34007881 http://dx.doi.org/10.23889/ijpds.v5i1.1355 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. |
spellingShingle | Population Data Science Cross, Lauren Carson, Lauren Emma Jewell, Amelia Heslin, Margaret Osborn, David Downs, Johnny Stewart, Robert 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 |
title | 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 |
title_full | 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 |
title_fullStr | 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 |
title_full_unstemmed | 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 |
title_short | 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 |
title_sort | 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 |
topic | Population Data Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8110887/ https://www.ncbi.nlm.nih.gov/pubmed/34007881 http://dx.doi.org/10.23889/ijpds.v5i1.1355 |
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