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Navigating data governance approvals to use routine health and social care data to evidence the hidden population with severe obesity: a case study from a clinical academic’s perspective

BACKGROUND: Front-line professionals are uniquely placed to identify evidence gaps and the way routinely-collected data can help address them. This knowledge can enable incisive, clinically-relevant research. AIM: To document an example of the real-world approvals journey within the current NHS/High...

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Autores principales: Williamson, Kath, Nimegeer, Amy, Lean, Mike
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9669932/
https://www.ncbi.nlm.nih.gov/pubmed/36405806
http://dx.doi.org/10.1177/17449871221122040
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author Williamson, Kath
Nimegeer, Amy
Lean, Mike
author_facet Williamson, Kath
Nimegeer, Amy
Lean, Mike
author_sort Williamson, Kath
collection PubMed
description BACKGROUND: Front-line professionals are uniquely placed to identify evidence gaps and the way routinely-collected data can help address them. This knowledge can enable incisive, clinically-relevant research. AIM: To document an example of the real-world approvals journey within the current NHS/Higher Education regulatory landscape, from the perspective of an experienced nurse undertaking doctoral study as a clinical academic. METHODS: An instrumental case-study approach is used to explore the approvals process for a mixed-methods study. Relevant context is highlighted to aid understanding, including introduction of the General Data Protection Regulation and the integration of health and social care services. RESULTS: Formal approvals by nine separate stakeholders from four different organisations took nearly 3 years, including 15 initial or revised applications, assessments or agreements. Obstacles included: conflicting views on what constitutes ‘research’ or ‘service evaluation’; isolated decision-making; fragmented data systems; multiple data controllers and a changing data governance environment. The dual perspectives of being both clinician and academic using routine data are explored. CONCLUSIONS: Practitioners face a complex approvals process to use data they routinely collect, for research or evaluation purposes. Use of data during the COVID-19 pandemic has demonstrated the need for streamlining of data governance processes. Practical recommendations are outlined.
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spelling pubmed-96699322022-11-18 Navigating data governance approvals to use routine health and social care data to evidence the hidden population with severe obesity: a case study from a clinical academic’s perspective Williamson, Kath Nimegeer, Amy Lean, Mike J Res Nurs Article BACKGROUND: Front-line professionals are uniquely placed to identify evidence gaps and the way routinely-collected data can help address them. This knowledge can enable incisive, clinically-relevant research. AIM: To document an example of the real-world approvals journey within the current NHS/Higher Education regulatory landscape, from the perspective of an experienced nurse undertaking doctoral study as a clinical academic. METHODS: An instrumental case-study approach is used to explore the approvals process for a mixed-methods study. Relevant context is highlighted to aid understanding, including introduction of the General Data Protection Regulation and the integration of health and social care services. RESULTS: Formal approvals by nine separate stakeholders from four different organisations took nearly 3 years, including 15 initial or revised applications, assessments or agreements. Obstacles included: conflicting views on what constitutes ‘research’ or ‘service evaluation’; isolated decision-making; fragmented data systems; multiple data controllers and a changing data governance environment. The dual perspectives of being both clinician and academic using routine data are explored. CONCLUSIONS: Practitioners face a complex approvals process to use data they routinely collect, for research or evaluation purposes. Use of data during the COVID-19 pandemic has demonstrated the need for streamlining of data governance processes. Practical recommendations are outlined. SAGE Publications 2022-11-15 2022-11 /pmc/articles/PMC9669932/ /pubmed/36405806 http://dx.doi.org/10.1177/17449871221122040 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Article
Williamson, Kath
Nimegeer, Amy
Lean, Mike
Navigating data governance approvals to use routine health and social care data to evidence the hidden population with severe obesity: a case study from a clinical academic’s perspective
title Navigating data governance approvals to use routine health and social care data to evidence the hidden population with severe obesity: a case study from a clinical academic’s perspective
title_full Navigating data governance approvals to use routine health and social care data to evidence the hidden population with severe obesity: a case study from a clinical academic’s perspective
title_fullStr Navigating data governance approvals to use routine health and social care data to evidence the hidden population with severe obesity: a case study from a clinical academic’s perspective
title_full_unstemmed Navigating data governance approvals to use routine health and social care data to evidence the hidden population with severe obesity: a case study from a clinical academic’s perspective
title_short Navigating data governance approvals to use routine health and social care data to evidence the hidden population with severe obesity: a case study from a clinical academic’s perspective
title_sort navigating data governance approvals to use routine health and social care data to evidence the hidden population with severe obesity: a case study from a clinical academic’s perspective
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9669932/
https://www.ncbi.nlm.nih.gov/pubmed/36405806
http://dx.doi.org/10.1177/17449871221122040
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