Cited by 143Digitalization, Law, and RegulationEthics in Clinical ResearchThoreau and American Literature

Big Data in medical research and EU data protection law: challenges to the consent or anonymise approach

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Mostert, Menno, Bredenoord, Annelien L, Biesaart, Monique C I H, van Delden, Johannes J M·2016·European Journal of Human Genetics

Abstract

Medical research is increasingly becoming data-intensive; sensitive data are being re-used, linked and analysed on an unprecedented scale. The current EU data protection law reform has led to an intense debate about its potential effect on this processing of data in medical research. To contribute to this evolving debate, this paper reviews how the dominant 'consent or anonymise approach' is challenged in a data-intensive medical research context, and discusses possible ways forwards within the EU legal framework on data protection. A large part of the debate in literature focuses on the acceptability of adapting consent or anonymisation mechanisms to overcome the challenges within these approaches. We however believe that the search for ways forward within the consent or anonymise paradigm will become increasingly difficult. Therefore, we underline the necessity of an appropriate research exemption from consent for the use of sensitive personal data in medical research to take account of all legitimate interests. The appropriate conditions of such a research exemption are however subject to debate, and we expect that there will be minimal harmonisation of these conditions in the forthcoming EU Data Protection Regulation. Further deliberation is required to determine when a shift away from consent as a legal basis is necessary and proportional in a data-intensive medical research context, and what safeguards should be put in place when such a research exemption from consent is provided.

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  • Natural language processing methods have shown their usefulness for extraction of structured clinical data from unstructured data elements.

    “Natural language processing (NLP) methods have shown their usefulness for extraction of structured clinical data from unstructured data elements [36], [37].”
  • Natural language processing (NLP) methods have shown their usefulness for extraction of structured clinical data from unstructured data elements.

    “Natural language processing (NLP) methods have shown their usefulness for extraction of structured clinical data from unstructured data elements[36],[37].”

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References 65 · Cited by 143

Research works printed but not linked: 1

  1. Mooney SJ, Westreich DJ, El-Sayed AM: Epidemiology in the era of Big Data. Epidemiology 2015; 26: 390–394. [DOI] [PMC free article] [PubMed] [Google Scholar]

Authors
Mostert, M., Bredenoord, A. L., Biesaart, M. C. I. H., & van Delden, J. J. M.
Affiliations
University Medical Center Utrecht (NL)
Corresponding author
Mostert, Menno
Venue
European Journal of Human Genetics
Published
2015-11-11
Volume
24
Issue
7
Pages
956-960
ISSN
  • 1018-4813 (ISSN-L)
  • 1476-5438
OpenAlex
W2129713986
Cited by
143
References
65
Citations by year
2026: 4 · 2025: 10 · 2024: 10 · 2023: 18 · 2022: 16 · 2021: 20 · 2020: 21 · 2019: 16 · 2018: 15 · 2017: 9 · 2016: 4
FWCI
126.85
Type
journal article
Language
en
Update notices
erratum (2016-06-16)
Open access
Locations
  • European Journal of Human Genetics (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Social Sciences › Law › Digitalization, Law, and Regulation
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics in Clinical Research
  • Physical Sciences › Computer Science › Information Systems › Thoreau and American Literature
Keywords
EU data protection law, sensitive personal data, data anonymization, EU data protection regulation, legitimate interests, data harmonization, data-intensive research
MeSH terms
Data Anonymization, European Union, Humans, Databases as Topic, Biomedical Research

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