Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix

BACKGROUND: The current law on anonymization sets the same standard across all situations, which poses a problem for biomedical research. OBJECTIVE: We propose a matrix for setting different standards, which is responsive to context and public expectations. METHODS: The law and ethics applicable to...

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Detalles Bibliográficos
Autores principales: Rumbold, John, Pierscionek, Barbara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2018
Materias:
Proposal
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6284146/
https://www.ncbi.nlm.nih.gov/pubmed/30467101
http://dx.doi.org/10.2196/medinform.7096
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author Rumbold, John
Pierscionek, Barbara
author_facet Rumbold, John
Pierscionek, Barbara
author_sort Rumbold, John
collection PubMed
description BACKGROUND: The current law on anonymization sets the same standard across all situations, which poses a problem for biomedical research. OBJECTIVE: We propose a matrix for setting different standards, which is responsive to context and public expectations. METHODS: The law and ethics applicable to anonymization were reviewed in a scoping study. Social science on public attitudes and research on technical methods of anonymization were applied to formulate a matrix. RESULTS: The matrix adjusts anonymization standards according to the sensitivity of the data and the safety of the place, people, and projects involved. CONCLUSIONS: The matrix offers a tool with context-specific standards for anonymization in data research.
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spelling pubmed-62841462019-01-03 Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix Rumbold, John Pierscionek, Barbara JMIR Med Inform Proposal BACKGROUND: The current law on anonymization sets the same standard across all situations, which poses a problem for biomedical research. OBJECTIVE: We propose a matrix for setting different standards, which is responsive to context and public expectations. METHODS: The law and ethics applicable to anonymization were reviewed in a scoping study. Social science on public attitudes and research on technical methods of anonymization were applied to formulate a matrix. RESULTS: The matrix adjusts anonymization standards according to the sensitivity of the data and the safety of the place, people, and projects involved. CONCLUSIONS: The matrix offers a tool with context-specific standards for anonymization in data research. JMIR Publications 2018-11-22 /pmc/articles/PMC6284146/ /pubmed/30467101 http://dx.doi.org/10.2196/medinform.7096 Text en ©John Rumbold, Barbara Pierscionek. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 22.11.2018. 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 JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Proposal
Rumbold, John
Pierscionek, Barbara
Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix
title Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix
title_full Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix
title_fullStr Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix
title_full_unstemmed Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix
title_short Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix
title_sort contextual anonymization for secondary use of big data in biomedical research: proposal for an anonymization matrix
topic Proposal
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6284146/
https://www.ncbi.nlm.nih.gov/pubmed/30467101
http://dx.doi.org/10.2196/medinform.7096
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