↓ Skip to main content

Securizing data linkage in french public statistics

Overview of attention for article published in BMC Medical Informatics and Decision Making, October 2016
Altmetric Badge

Mentioned by

twitter
1 X user

Readers on

mendeley
18 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Securizing data linkage in french public statistics
Published in
BMC Medical Informatics and Decision Making, October 2016
DOI 10.1186/s12911-016-0366-4
Pubmed ID
Authors

Maxence Guesdon, Eric Benzenine, Kamel Gadouche, Catherine Quantin

Abstract

Administrative records in France, especially medical and social records, have huge potential for statistical studies. The NIR (a national identifier) is widely used in medico-social administrations, and this would theoretically provide considerable scope for data matching, on condition that the legislation on such matters was respected.The law, however, forbids the processing of non-anonymized medical data, thus making it difficult to carry out studies that require several sources of social and medical data.We would like to benefit from computer techniques introduced since the 70 s to provide safe linkage of anonymized files, to release the current constraints of such procedures.We propose an organization and a data workflow, based on hashing and cyrptographic techniques, to strongly compartmentalize identifying and not-identifying data.The proposed method offers a strong control over who is in possession of which information, using different hashing keys for each linkage. This allows to prevent unauthorized linkage of data, to protect anonymity, by preventing cumulation of not-identifying data which can become identifying data when linked.Our proposal would make it possible to conduct such studies more easily, more regularly and more precisely while preserving a high enough level of anonymity.The main obstacle to setting up such a system, in our opinion, is not technical, but rather organizational in that it is based on the existence of a Key-Management Authority.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 22%
Student > Master 4 22%
Student > Bachelor 3 17%
Student > Ph. D. Student 2 11%
Professor 1 6%
Other 2 11%
Unknown 2 11%
Readers by discipline Count As %
Medicine and Dentistry 6 33%
Nursing and Health Professions 2 11%
Pharmacology, Toxicology and Pharmaceutical Science 1 6%
Computer Science 1 6%
Biochemistry, Genetics and Molecular Biology 1 6%
Other 2 11%
Unknown 5 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 October 2016.
All research outputs
#18,475,157
of 22,893,031 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,578
of 1,995 outputs
Outputs of similar age
#242,059
of 319,894 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#27
of 29 outputs
Altmetric has tracked 22,893,031 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,995 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 9th percentile – i.e., 9% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 319,894 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.