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Understanding how to build a social licence for using novel linked datasets for planning and research in Kent, Surrey and Sussex: results of deliberative focus groups
INTRODUCTION: Digital programmes in the newly created NHS integrated care boards (ICBs) in the United Kingdom mean that curation and linkage of anonymised patient data is underway in many areas for the first time. In Kent, Surrey and Sussex (KSS), in Southeast England, public health teams want to us...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Swansea University
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476239/ https://www.ncbi.nlm.nih.gov/pubmed/37671318 http://dx.doi.org/10.23889/ijpds.v5i3.2114 |
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author | Ford, Elizabeth Rees-Roberts, Melanie Stanley, Kathryn Goddard, Katie Giles, Sarah Armes, Jo Ikhile, Deborah Madzvamuse, Anotida Spencer-Hughes, Victoria George, Abraham Farmer, Chris Cassell, Jackie |
author_facet | Ford, Elizabeth Rees-Roberts, Melanie Stanley, Kathryn Goddard, Katie Giles, Sarah Armes, Jo Ikhile, Deborah Madzvamuse, Anotida Spencer-Hughes, Victoria George, Abraham Farmer, Chris Cassell, Jackie |
author_sort | Ford, Elizabeth |
collection | PubMed |
description | INTRODUCTION: Digital programmes in the newly created NHS integrated care boards (ICBs) in the United Kingdom mean that curation and linkage of anonymised patient data is underway in many areas for the first time. In Kent, Surrey and Sussex (KSS), in Southeast England, public health teams want to use these datasets to answer strategic population health questions, but public expectations around use of patient data are unknown. OBJECTIVES: We aimed to engage with citizens of KSS to gather their views and expectations of data linkage and re-use, through deliberative discussions. METHODS: We held five 3-hour deliberative focus groups with 79 citizens of KSS, presenting information about potential uses of data, safeguards, and mechanisms for public involvement in governance and decision making about datasets. After each presentation, participants discussed their views in facilitated small groups which were recorded, transcribed and analysed thematically. RESULTS: The focus groups generated 15 themes representing participants’ views on the benefits, risks and values for safeguarding linked data. Participants largely supported use of patient data to improve health service efficiency and resource management, preventative services and out of hospital care, joined-up services and information flows. Most participants expressed concerns about data accuracy, breaches and hacking, and worried about commercial use of data. They suggested that transparency of data usage through audit trails and clear information about accountability, ensuring data re-use does not perpetuate stigma and discrimination, ongoing, inclusive and valued involvement of the public in dataset decision-making, and a commitment to building trust, would meet their expectations for responsible data use. CONCLUSIONS: Participants were largely favourable about the proposed uses of patient linked datasets but expected a commitment to transparency and public involvement. Findings were mapped to previous tenets of social license and can be used to inform ICB digital programme teams on how to proceed with use of linked datasets in a trustworthy and socially acceptable way. |
format | Online Article Text |
id | pubmed-10476239 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Swansea University |
record_format | MEDLINE/PubMed |
spelling | pubmed-104762392023-09-05 Understanding how to build a social licence for using novel linked datasets for planning and research in Kent, Surrey and Sussex: results of deliberative focus groups Ford, Elizabeth Rees-Roberts, Melanie Stanley, Kathryn Goddard, Katie Giles, Sarah Armes, Jo Ikhile, Deborah Madzvamuse, Anotida Spencer-Hughes, Victoria George, Abraham Farmer, Chris Cassell, Jackie Int J Popul Data Sci Population Data Science INTRODUCTION: Digital programmes in the newly created NHS integrated care boards (ICBs) in the United Kingdom mean that curation and linkage of anonymised patient data is underway in many areas for the first time. In Kent, Surrey and Sussex (KSS), in Southeast England, public health teams want to use these datasets to answer strategic population health questions, but public expectations around use of patient data are unknown. OBJECTIVES: We aimed to engage with citizens of KSS to gather their views and expectations of data linkage and re-use, through deliberative discussions. METHODS: We held five 3-hour deliberative focus groups with 79 citizens of KSS, presenting information about potential uses of data, safeguards, and mechanisms for public involvement in governance and decision making about datasets. After each presentation, participants discussed their views in facilitated small groups which were recorded, transcribed and analysed thematically. RESULTS: The focus groups generated 15 themes representing participants’ views on the benefits, risks and values for safeguarding linked data. Participants largely supported use of patient data to improve health service efficiency and resource management, preventative services and out of hospital care, joined-up services and information flows. Most participants expressed concerns about data accuracy, breaches and hacking, and worried about commercial use of data. They suggested that transparency of data usage through audit trails and clear information about accountability, ensuring data re-use does not perpetuate stigma and discrimination, ongoing, inclusive and valued involvement of the public in dataset decision-making, and a commitment to building trust, would meet their expectations for responsible data use. CONCLUSIONS: Participants were largely favourable about the proposed uses of patient linked datasets but expected a commitment to transparency and public involvement. Findings were mapped to previous tenets of social license and can be used to inform ICB digital programme teams on how to proceed with use of linked datasets in a trustworthy and socially acceptable way. Swansea University 2023-01-30 /pmc/articles/PMC10476239/ /pubmed/37671318 http://dx.doi.org/10.23889/ijpds.v5i3.2114 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 Ford, Elizabeth Rees-Roberts, Melanie Stanley, Kathryn Goddard, Katie Giles, Sarah Armes, Jo Ikhile, Deborah Madzvamuse, Anotida Spencer-Hughes, Victoria George, Abraham Farmer, Chris Cassell, Jackie Understanding how to build a social licence for using novel linked datasets for planning and research in Kent, Surrey and Sussex: results of deliberative focus groups |
title | Understanding how to build a social licence for using novel linked datasets for planning and research in Kent, Surrey and Sussex: results of deliberative focus groups |
title_full | Understanding how to build a social licence for using novel linked datasets for planning and research in Kent, Surrey and Sussex: results of deliberative focus groups |
title_fullStr | Understanding how to build a social licence for using novel linked datasets for planning and research in Kent, Surrey and Sussex: results of deliberative focus groups |
title_full_unstemmed | Understanding how to build a social licence for using novel linked datasets for planning and research in Kent, Surrey and Sussex: results of deliberative focus groups |
title_short | Understanding how to build a social licence for using novel linked datasets for planning and research in Kent, Surrey and Sussex: results of deliberative focus groups |
title_sort | understanding how to build a social licence for using novel linked datasets for planning and research in kent, surrey and sussex: results of deliberative focus groups |
topic | Population Data Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476239/ https://www.ncbi.nlm.nih.gov/pubmed/37671318 http://dx.doi.org/10.23889/ijpds.v5i3.2114 |
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