A blinded evaluation of privacy preserving record linkage with Bloom filters
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) Ho...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2022-01-01
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| Series: | BMC Medical Research Methodology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12874-022-01510-2 |
| _version_ | 1818752851326795776 |
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| author | Sean Randall Helen Wichmann Adrian Brown James Boyd Tom Eitelhuber Alexandra Merchant Anna Ferrante |
| author_facet | Sean Randall Helen Wichmann Adrian Brown James Boyd Tom Eitelhuber Alexandra Merchant Anna Ferrante |
| author_sort | Sean Randall |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-18T04:58:02Z |
| format | Article |
| id | doaj.art-a076390086f24a0880293d612472ce5e |
| institution | Directory Open Access Journal |
| issn | 1471-2288 |
| language | English |
| last_indexed | 2024-12-18T04:58:02Z |
| publishDate | 2022-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Research Methodology |
| spelling | doaj.art-a076390086f24a0880293d612472ce5e2022-12-21T21:20:13ZengBMCBMC Medical Research Methodology1471-22882022-01-012211710.1186/s12874-022-01510-2A blinded evaluation of privacy preserving record linkage with Bloom filtersSean Randall0Helen Wichmann1Adrian Brown2James Boyd3Tom Eitelhuber4Alexandra Merchant5Anna Ferrante6Centre for Data Linkage, School of Public Health, Curtin UniversityWA Data Linkage Branch, WA Department of HealthCentre for Data Linkage, School of Public Health, Curtin UniversityCentre for Data Linkage, School of Public Health, Curtin UniversityWA Data Linkage Branch, WA Department of HealthWA Data Linkage Branch, WA Department of HealthCentre for Data Linkage, School of Public Health, Curtin UniversityAbstract 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.https://doi.org/10.1186/s12874-022-01510-2Record linkagePrivacy preserving record linkageEvaluationPrivacy |
| spellingShingle | Sean Randall Helen Wichmann Adrian Brown James Boyd Tom Eitelhuber Alexandra Merchant Anna Ferrante A blinded evaluation of privacy preserving record linkage with Bloom filters BMC Medical Research Methodology Record linkage Privacy preserving record linkage Evaluation Privacy |
| title | A blinded evaluation of privacy preserving record linkage with Bloom filters |
| title_full | A blinded evaluation of privacy preserving record linkage with Bloom filters |
| title_fullStr | A blinded evaluation of privacy preserving record linkage with Bloom filters |
| title_full_unstemmed | A blinded evaluation of privacy preserving record linkage with Bloom filters |
| title_short | A blinded evaluation of privacy preserving record linkage with Bloom filters |
| title_sort | blinded evaluation of privacy preserving record linkage with bloom filters |
| topic | Record linkage Privacy preserving record linkage Evaluation Privacy |
| url | https://doi.org/10.1186/s12874-022-01510-2 |
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