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Securizing data linkage in french public statistics

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.
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Maxence Guesdon, Eric Benzenine, Kamel Gadouche, Catherine Quantin. Securizing data linkage in french public statistics. BMC Medical Informatics and Decision Making, BioMed Central, 2016, 16 (1), pp.129. ⟨10.1186/s12911-016-0366-4⟩. ⟨hal-01377334⟩

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