BMC Medical Research Methodology (Jan 2022)

A blinded evaluation of privacy preserving record linkage with Bloom filters

  • Sean Randall,
  • Helen Wichmann,
  • Adrian Brown,
  • James Boyd,
  • Tom Eitelhuber,
  • Alexandra Merchant,
  • Anna Ferrante

DOI
https://doi.org/10.1186/s12874-022-01510-2
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 7

Abstract

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Abstract Background Privacy preserving record linkage (PPRL) methods using Bloom filters have shown promise for use in operational linkage settings. However real-world evaluations are required to confirm their suitability in practice. Methods An extract of records from the Western Australian (WA) Hospital Morbidity Data Collection 2011–2015 and WA Death Registrations 2011–2015 were encoded to Bloom filters, and then linked using privacy-preserving methods. Results were compared to a traditional, un-encoded linkage of the same datasets using the same blocking criteria to enable direct investigation of the comparison step. The encoded linkage was carried out in a blinded setting, where there was no access to un-encoded data or a ‘truth set’. Results The PPRL method using Bloom filters provided similar linkage quality to the traditional un-encoded linkage, with 99.3% of ‘groupings’ identical between privacy preserving and clear-text linkage. Conclusion The Bloom filter method appears suitable for use in situations where clear-text identifiers cannot be provided for linkage.

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