ArticleBMC medical research methodology2022
A blinded evaluation of privacy preserving record linkage with Bloom filters.
Article in BMC medical research methodology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Article
- Geographic remoteness and chronic kidney disease outcomes: a population-based cohort study using linked pathology data.BMC nephrology · 2026Article
- Five-Year Outcomes of Chronic Kidney Disease in a Longitudinal Population-Based Cohort in Western Australia.Nephrology (Carlton, Vic.) · 2026Article
- Using general practice data for chronic disease prevalence: the impact of record linkage on estimation accuracy.BMC medical informatics and decision making · 2025Article
- Article
- Gerontologic Biostatistics and Data Science: Aging Research in the Era of Big Data.The journals of gerontology. Series A, Biological sciences and medical sciences · 2024Review
- Privacy preserving record linkage for public health action: opportunities and challenges.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Article
- Relative Effectiveness of Coronavirus Disease 2019 Vaccination and Booster Dose Combinations Among 18.9 Million Vaccinated Adults During the Early Severe Acute Respiratory Syndrome Coronavirus 2 Omicron Period-United States, 1 January 2022 to 31 March 2022.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Article
- Article
- Unlocking Potential within Health Systems Using Privacy-Preserving Record Linkage: Exploring Chronic Kidney Disease Outcomes through Linked Data Modelling.Applied clinical informatics · 2022Article
- Validating a novel deterministic privacy-preserving record linkage between administrative & clinical data: applications in stroke research.International journal of population data science · 2022Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPrivacy 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.
methodsAn 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'.
resultsThe 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.
conclusionThe Bloom filter method appears suitable for use in situations where clear-text identifiers cannot be provided for linkage.
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