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Toward the Development of Data Governance Standards for Using Clinical Free-Text Data in Health Research: Position Paper
BACKGROUND: Clinical free-text data (eg, outpatient letters or nursing notes) represent a vast, untapped source of rich information that, if more accessible for research, would clarify and supplement information coded in structured data fields. Data usually need to be deidentified or anonymized befo...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7367542/ https://www.ncbi.nlm.nih.gov/pubmed/32597785 http://dx.doi.org/10.2196/16760 |
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author | Jones, Kerina H Ford, Elizabeth M Lea, Nathan Griffiths, Lucy J Hassan, Lamiece Heys, Sharon Squires, Emma Nenadic, Goran |
author_facet | Jones, Kerina H Ford, Elizabeth M Lea, Nathan Griffiths, Lucy J Hassan, Lamiece Heys, Sharon Squires, Emma Nenadic, Goran |
author_sort | Jones, Kerina H |
collection | PubMed |
description | BACKGROUND: Clinical free-text data (eg, outpatient letters or nursing notes) represent a vast, untapped source of rich information that, if more accessible for research, would clarify and supplement information coded in structured data fields. Data usually need to be deidentified or anonymized before they can be reused for research, but there is a lack of established guidelines to govern effective deidentification and use of free-text information and avoid damaging data utility as a by-product. OBJECTIVE: This study aimed to develop recommendations for the creation of data governance standards to integrate with existing frameworks for personal data use, to enable free-text data to be used safely for research for patient and public benefit. METHODS: We outlined data protection legislation and regulations relating to the United Kingdom for context and conducted a rapid literature review and UK-based case studies to explore data governance models used in working with free-text data. We also engaged with stakeholders, including text-mining researchers and the general public, to explore perceived barriers and solutions in working with clinical free-text. RESULTS: We proposed a set of recommendations, including the need for authoritative guidance on data governance for the reuse of free-text data, to ensure public transparency in data flows and uses, to treat deidentified free-text data as potentially identifiable with use limited to accredited data safe havens, and to commit to a culture of continuous improvement to understand the relationships between the efficacy of deidentification and reidentification risks, so this can be communicated to all stakeholders. CONCLUSIONS: By drawing together the findings of a combination of activities, we present a position paper to contribute to the development of data governance standards for the reuse of clinical free-text data for secondary purposes. While working in accordance with existing data governance frameworks, there is a need for further work to take forward the recommendations we have proposed, with commitment and investment, to assure and expand the safe reuse of clinical free-text data for public benefit. |
format | Online Article Text |
id | pubmed-7367542 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-73675422020-08-07 Toward the Development of Data Governance Standards for Using Clinical Free-Text Data in Health Research: Position Paper Jones, Kerina H Ford, Elizabeth M Lea, Nathan Griffiths, Lucy J Hassan, Lamiece Heys, Sharon Squires, Emma Nenadic, Goran J Med Internet Res Original Paper BACKGROUND: Clinical free-text data (eg, outpatient letters or nursing notes) represent a vast, untapped source of rich information that, if more accessible for research, would clarify and supplement information coded in structured data fields. Data usually need to be deidentified or anonymized before they can be reused for research, but there is a lack of established guidelines to govern effective deidentification and use of free-text information and avoid damaging data utility as a by-product. OBJECTIVE: This study aimed to develop recommendations for the creation of data governance standards to integrate with existing frameworks for personal data use, to enable free-text data to be used safely for research for patient and public benefit. METHODS: We outlined data protection legislation and regulations relating to the United Kingdom for context and conducted a rapid literature review and UK-based case studies to explore data governance models used in working with free-text data. We also engaged with stakeholders, including text-mining researchers and the general public, to explore perceived barriers and solutions in working with clinical free-text. RESULTS: We proposed a set of recommendations, including the need for authoritative guidance on data governance for the reuse of free-text data, to ensure public transparency in data flows and uses, to treat deidentified free-text data as potentially identifiable with use limited to accredited data safe havens, and to commit to a culture of continuous improvement to understand the relationships between the efficacy of deidentification and reidentification risks, so this can be communicated to all stakeholders. CONCLUSIONS: By drawing together the findings of a combination of activities, we present a position paper to contribute to the development of data governance standards for the reuse of clinical free-text data for secondary purposes. While working in accordance with existing data governance frameworks, there is a need for further work to take forward the recommendations we have proposed, with commitment and investment, to assure and expand the safe reuse of clinical free-text data for public benefit. JMIR Publications 2020-06-29 /pmc/articles/PMC7367542/ /pubmed/32597785 http://dx.doi.org/10.2196/16760 Text en ©Kerina H Jones, Elizabeth M Ford, Nathan Lea, Lucy J Griffiths, Lamiece Hassan, Sharon Heys, Emma Squires, Goran Nenadic. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 29.06.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Jones, Kerina H Ford, Elizabeth M Lea, Nathan Griffiths, Lucy J Hassan, Lamiece Heys, Sharon Squires, Emma Nenadic, Goran Toward the Development of Data Governance Standards for Using Clinical Free-Text Data in Health Research: Position Paper |
title | Toward the Development of Data Governance Standards for Using Clinical Free-Text Data in Health Research: Position Paper |
title_full | Toward the Development of Data Governance Standards for Using Clinical Free-Text Data in Health Research: Position Paper |
title_fullStr | Toward the Development of Data Governance Standards for Using Clinical Free-Text Data in Health Research: Position Paper |
title_full_unstemmed | Toward the Development of Data Governance Standards for Using Clinical Free-Text Data in Health Research: Position Paper |
title_short | Toward the Development of Data Governance Standards for Using Clinical Free-Text Data in Health Research: Position Paper |
title_sort | toward the development of data governance standards for using clinical free-text data in health research: position paper |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7367542/ https://www.ncbi.nlm.nih.gov/pubmed/32597785 http://dx.doi.org/10.2196/16760 |
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