2016
DOI: 10.1038/ejhg.2016.52
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The risk of re-identification versus the need to identify individuals in rare disease research

Abstract: There is a growing concern in the ethics literature and among policy makers that de-identification or coding of personal data and biospecimens is not sufficient for protecting research subjects from privacy invasions and possible breaches of confidentiality due to the possibility of unauthorized re-identification. At the same time, there is a need in medical science to be able to identify individual patients. In particular for rare disease research there is a special and well-documented need for research colla… Show more

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Cited by 51 publications
(32 citation statements)
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References 39 publications
(36 reference statements)
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“…In cases of patients with rare diseases, they sometimes happen to be registered with multiple projects at the same time or at different times. When performing a cross‐sectional analysis or a unification of study resources, such as registry, reidentification is necessary . In previous cases, reidentification was performed by using unique IDs .…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…In cases of patients with rare diseases, they sometimes happen to be registered with multiple projects at the same time or at different times. When performing a cross‐sectional analysis or a unification of study resources, such as registry, reidentification is necessary . In previous cases, reidentification was performed by using unique IDs .…”
Section: Discussionmentioning
confidence: 99%
“…When performing a cross-sectional analysis or a unification of study resources, such as registry, reidentification is necessary. 16 In previous cases, reidentification was performed by using unique IDs. 17 In Japan, there is the My Number System,18 in which each citizen is provided with a unique number.…”
Section: Reidentificationmentioning
confidence: 99%
“…Moreover, efforts to make data anonymous are not always successful. Studies show the precariousness of de-identification efforts in large data sets, for example, in the reidentification of individuals with rare diseases in human genome research (Hansson et al, 2016) and the identification of personal information from Netflix data (Narayanan & Shmatikov, 2008). Given computational advances and the variety and volume of data recorded that is of a personal nature, the combination of publicly available data sets may also put individuals at risk.…”
Section: What Is Being Researched? New Data Sourcesmentioning
confidence: 99%
“…The advantage of this approach is that the researcher then has complete access to the anonymised genotypes and phenotypes, with only the identities of the samples being redacted; there is then no technical limitation as to the genetic analysis that can be performed. However, this carries certain risks because a data breach cannot be ruled out, and even if the data are anonymised, comparing anonymous genotypes with those of genotyped relatives might still reveal genetic relationships (Hansson et al 2016). In the clinical field, methods such as the random time-shifting of anonymised patient records (Hripcsak et al 2016) offer some protection whilst not being cryptographically secure.…”
Section: Introductionmentioning
confidence: 99%