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Authors: Rainer Schnell 1 ; Anke Richter 2 and Christian Borgs 3

Affiliations: 1 City and University of London, United Kingdom ; 2 Institute for Cancer Epidemiology, Germany ; 3 University of Duisburg-Essen, Germany

Keyword(s): Medical Record Linkage, Patient Identification Codes, Pseudonyms.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Confidentiality and Data Security ; Health Information Systems

Abstract: New EU regulations on the need to encrypt personal identifiers for linking data will increase the importance of Privacy-Preserving Record Linkage (PPRL) techniques over the course of the next years. Currently, the use of Anonymous Linkage Codes (ALCs) is the standard procedure for PPRL of medical databases. Recently, Bloom filter-based encodings of pseudo-identifiers such as names have received increasing attention for PPRL tasks. In contrast to most previous research in PPRL, which is based on simulated data, we compare the performance of ALCs and Bloom filter-based linkage keys using real data from a large regional breast cancer screening program. This large regional mammography data base contains nearly 200.000 records. We compare precision and recall for linking the data set existing at point t0 with new incident cases occuring after t0 using different encoding and matching strategies for the personal identifiers. Enhancing ALCs with an additional identifier (place of birth) yiel ds better recall than standard ALCs. Using the same information for Bloom filters with recommended parameter settings exceeds ALCs in recall, while preserving precision. (More)

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Paper citation in several formats:
Schnell, R.; Richter, A. and Borgs, C. (2017). A Comparison of Statistical Linkage Keys with Bloom Filter-based Encryptions for Privacy-preserving Record Linkage using Real-world Mammography Data. In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - HEALTHINF; ISBN 978-989-758-213-4; ISSN 2184-4305, SciTePress, pages 276-283. DOI: 10.5220/0006140302760283

@conference{healthinf17,
author={Rainer Schnell. and Anke Richter. and Christian Borgs.},
title={A Comparison of Statistical Linkage Keys with Bloom Filter-based Encryptions for Privacy-preserving Record Linkage using Real-world Mammography Data},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - HEALTHINF},
year={2017},
pages={276-283},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006140302760283},
isbn={978-989-758-213-4},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2017) - HEALTHINF
TI - A Comparison of Statistical Linkage Keys with Bloom Filter-based Encryptions for Privacy-preserving Record Linkage using Real-world Mammography Data
SN - 978-989-758-213-4
IS - 2184-4305
AU - Schnell, R.
AU - Richter, A.
AU - Borgs, C.
PY - 2017
SP - 276
EP - 283
DO - 10.5220/0006140302760283
PB - SciTePress

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