ArticleBMC medical informatics and decision making2017
Evaluating privacy-preserving record linkage using cryptographic long-term keys and multibit trees on large medical datasets.
Article in BMC medical informatics and decision making, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Combining Real-World and Clinical Trial Data Through Privacy-Preserving Record Linkage: Opportunities and Challenges-A Narrative Review.Health science reports · 2025Article
- Accuracy of privacy preserving record linkage for real world data in the United States: a systemic review.JAMIA open · 2025Review
- Linkability measures to assess the data characteristics for record linkage.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Privacy preserving record linkage for public health action: opportunities and challenges.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Assessing the impact of privacy-preserving record linkage on record overlap and patient demographic and clinical characteristics in PCORnet®, the National Patient-Centered Clinical Research Network.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Unlocking Potential within Health Systems Using Privacy-Preserving Record Linkage: Exploring Chronic Kidney Disease Outcomes through Linked Data Modelling.Applied clinical informatics · 2022Article
- Real-World Matching Performance of Deidentified Record-Linking Tokens.Applied clinical informatics · 2022Article
- A methodological assessment of privacy preserving record linkage using survey and administrative data.Statistical journal of the IAOS · 2022Article
- Mainzelliste SecureEpiLinker (MainSEL): privacy-preserving record linkage using secure multi-party computation.Bioinformatics (Oxford, England) · 2022Article
- Validating a novel deterministic privacy-preserving record linkage between administrative & clinical data: applications in stroke research.International journal of population data science · 2022Article
- On the effectiveness of graph matching attacks against privacy-preserving record linkage.PloS one · 2022Article
- Accuracy of an Electronic Health Record Patient Linkage Module Evaluated between Neighboring Academic Health Care Centers.Applied clinical informatics · 2020Article
- A hybrid approach to record linkage using a combination of deterministic and probabilistic methodology.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Population Data Centre Profiles: Centre for Data Linkage.International journal of population data science · 2020Article
- Evaluation of approximate comparison methods on Bloom filters for probabilistic linkage.International journal of population data science · 2019Article
- Privacy preserving linkage using multiple match-keys.International journal of population data science · 2019Article
- Population-Based Linkage of Big Data in Dental Research.International journal of environmental research and public health · 2018Review
- Between Access and Privacy: Challenges in Sharing Health Data.Yearbook of medical informatics · 2018Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIntegrating medical data using databases from different sources by record linkage is a powerful technique increasingly used in medical research. Under many jurisdictions, unique personal identifiers needed for linking the records are unavailable. Since sensitive attributes, such as names, have to be used instead, privacy regulations usually demand encrypting these identifiers. The corresponding set of techniques for privacy-preserving record linkage (PPRL) has received widespread attention. One recent method is based on Bloom filters. Due to superior resilience against cryptographic attacks, composite Bloom filters (cryptographic long-term keys, CLKs) are considered best practice for privacy in PPRL. Real-world performance of these techniques using large-scale data is unknown up to now.
methodsUsing a large subset of Australian hospital admission data, we tested the performance of an innovative PPRL technique (CLKs using multibit trees) against a gold-standard derived from clear-text probabilistic record linkage. Linkage time and linkage quality (recall, precision and F-measure) were evaluated.
resultsClear text probabilistic linkage resulted in marginally higher precision and recall than CLKs. PPRL required more computing time but 5 million records could still be de-duplicated within one day. However, the PPRL approach required fine tuning of parameters.
conclusionsWe argue that increased privacy of PPRL comes with the price of small losses in precision and recall and a large increase in computational burden and setup time. These costs seem to be acceptable in most applied settings, but they have to be considered in the decision to apply PPRL. Further research on the optimal automatic choice of parameters is needed.
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