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Data sharing in clinical trials – practical guidance on anonymising trial datasets

BACKGROUND: There is an increasing demand by non-commercial funders that trialists should provide access to trial data once the primary analysis is completed. This has to take into account concerns about identifying individual trial participants, and the legal and regulatory requirements. METHODS: U...

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Autores principales: Keerie, Catriona, Tuck, Christopher, Milne, Garry, Eldridge, Sandra, Wright, Neil, Lewis, Steff C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5763739/
https://www.ncbi.nlm.nih.gov/pubmed/29321053
http://dx.doi.org/10.1186/s13063-017-2382-9
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author Keerie, Catriona
Tuck, Christopher
Milne, Garry
Eldridge, Sandra
Wright, Neil
Lewis, Steff C.
author_facet Keerie, Catriona
Tuck, Christopher
Milne, Garry
Eldridge, Sandra
Wright, Neil
Lewis, Steff C.
author_sort Keerie, Catriona
collection PubMed
description BACKGROUND: There is an increasing demand by non-commercial funders that trialists should provide access to trial data once the primary analysis is completed. This has to take into account concerns about identifying individual trial participants, and the legal and regulatory requirements. METHODS: Using the good practice guideline laid out by the work funded by the Medical Research Council Hubs for Trials Methodology Research (MRC HTMR), we anonymised a dataset from a recently completed trial. Using this example, we present practical guidance on how to anonymise a dataset, and describe rules that could be used on other trial datasets. We describe how these might differ if the trial was to be made freely available to all, or if the data could only be accessed with specific permission and data usage agreements in place. RESULTS: Following the good practice guidelines, we successfully created a controlled access model for trial data sharing. The data were assessed on a case-by-case basis classifying variables as direct, indirect and superfluous identifiers with differing methods of anonymisation assigned depending on the type of identifier. A final dataset was created and checks of the anonymised dataset were applied. Lastly, a procedure for release of the data was implemented to complete the process. CONCLUSIONS: We have implemented a practical solution to the data anonymisation process resulting in a bespoke anonymised dataset for a recently completed trial. We have gained useful learnings in terms of efficiency of the process going forward, the need to balance anonymity with data utilisation and future work that should be undertaken. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13063-017-2382-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-57637392018-01-17 Data sharing in clinical trials – practical guidance on anonymising trial datasets Keerie, Catriona Tuck, Christopher Milne, Garry Eldridge, Sandra Wright, Neil Lewis, Steff C. Trials Methodology BACKGROUND: There is an increasing demand by non-commercial funders that trialists should provide access to trial data once the primary analysis is completed. This has to take into account concerns about identifying individual trial participants, and the legal and regulatory requirements. METHODS: Using the good practice guideline laid out by the work funded by the Medical Research Council Hubs for Trials Methodology Research (MRC HTMR), we anonymised a dataset from a recently completed trial. Using this example, we present practical guidance on how to anonymise a dataset, and describe rules that could be used on other trial datasets. We describe how these might differ if the trial was to be made freely available to all, or if the data could only be accessed with specific permission and data usage agreements in place. RESULTS: Following the good practice guidelines, we successfully created a controlled access model for trial data sharing. The data were assessed on a case-by-case basis classifying variables as direct, indirect and superfluous identifiers with differing methods of anonymisation assigned depending on the type of identifier. A final dataset was created and checks of the anonymised dataset were applied. Lastly, a procedure for release of the data was implemented to complete the process. CONCLUSIONS: We have implemented a practical solution to the data anonymisation process resulting in a bespoke anonymised dataset for a recently completed trial. We have gained useful learnings in terms of efficiency of the process going forward, the need to balance anonymity with data utilisation and future work that should be undertaken. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13063-017-2382-9) contains supplementary material, which is available to authorized users. BioMed Central 2018-01-10 /pmc/articles/PMC5763739/ /pubmed/29321053 http://dx.doi.org/10.1186/s13063-017-2382-9 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Methodology
Keerie, Catriona
Tuck, Christopher
Milne, Garry
Eldridge, Sandra
Wright, Neil
Lewis, Steff C.
Data sharing in clinical trials – practical guidance on anonymising trial datasets
title Data sharing in clinical trials – practical guidance on anonymising trial datasets
title_full Data sharing in clinical trials – practical guidance on anonymising trial datasets
title_fullStr Data sharing in clinical trials – practical guidance on anonymising trial datasets
title_full_unstemmed Data sharing in clinical trials – practical guidance on anonymising trial datasets
title_short Data sharing in clinical trials – practical guidance on anonymising trial datasets
title_sort data sharing in clinical trials – practical guidance on anonymising trial datasets
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5763739/
https://www.ncbi.nlm.nih.gov/pubmed/29321053
http://dx.doi.org/10.1186/s13063-017-2382-9
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