Assessment of scalability and performance of the record linkage tool E-PIX

Data privacy protection Data quality Duplicate detection Identity management Patient data Record linkage

Journal

Journal of translational medicine
ISSN: 1479-5876
Titre abrégé: J Transl Med
Pays: England
ID NLM: 101190741

Informations de publication

Date de publication:
17 02 2020
Historique:
received: 01 11 2019
accepted: 04 02 2020
entrez: 19 2 2020
pubmed: 19 2 2020
medline: 15 5 2021
Statut: epublish

Résumé

The identity management is a central component in medical research. Patients are recruited from various sites, which requires an error tolerant record linkage method, to ensure that patients are registered only once. In large research projects or institutions, the identity management has to deal with several thousands or millions of patients. In environments with large numbers of patients the register process could lead to high runtimes caused by record linkage. The Central Biomaterial Bank of the Charité (ZeBanC) searched for an identity management solution, which can handle millions of patients in large research projects with an acceptable performance. The goal of this paper was to simulate the registration of several million patients using the E-PIX service at Charité - Universitätsmedizin Berlin. The E-PIX service was evaluated in terms of needed runtimes, memory requirements, and processor utilization. A total of at least 20 million patients had to be registered. The runtimes to register patients into databases with various sizes should be examined, and the maximum number of patients, which the E-PIX service could handle, should be determined. Tools were set up or developed to measure the needed runtimes, the memory used and the processor usage to register patients into various sizes of databases. To generate runtimes close to reality, modified patient data based on transposed real patient data were used for the simulation. The transposed patient data were sent to E-PIX to measure the runtimes of the registration process. This measurement was repeated for various database sizes. E-PIX is suitable to manage multi-million patients within a dataset. With the given hardware, it was possible to register a total of more than 30 million patients. It was possible to register more than 16 thousand patients per day into this database. The E-PIX tool fulfills the requirements of the Charité to be used for large research projects. The use of E-PIX is intended for the research context in the Charité.

Sections du résumé

BACKGROUND
The identity management is a central component in medical research. Patients are recruited from various sites, which requires an error tolerant record linkage method, to ensure that patients are registered only once. In large research projects or institutions, the identity management has to deal with several thousands or millions of patients. In environments with large numbers of patients the register process could lead to high runtimes caused by record linkage. The Central Biomaterial Bank of the Charité (ZeBanC) searched for an identity management solution, which can handle millions of patients in large research projects with an acceptable performance. The goal of this paper was to simulate the registration of several million patients using the E-PIX service at Charité - Universitätsmedizin Berlin. The E-PIX service was evaluated in terms of needed runtimes, memory requirements, and processor utilization. A total of at least 20 million patients had to be registered. The runtimes to register patients into databases with various sizes should be examined, and the maximum number of patients, which the E-PIX service could handle, should be determined.
METHODS
Tools were set up or developed to measure the needed runtimes, the memory used and the processor usage to register patients into various sizes of databases. To generate runtimes close to reality, modified patient data based on transposed real patient data were used for the simulation. The transposed patient data were sent to E-PIX to measure the runtimes of the registration process. This measurement was repeated for various database sizes.
RESULTS
E-PIX is suitable to manage multi-million patients within a dataset. With the given hardware, it was possible to register a total of more than 30 million patients. It was possible to register more than 16 thousand patients per day into this database.
CONCLUSIONS
The E-PIX tool fulfills the requirements of the Charité to be used for large research projects. The use of E-PIX is intended for the research context in the Charité.

Identifiants

pubmed: 32066455
doi: 10.1186/s12967-020-02257-4
pii: 10.1186/s12967-020-02257-4
pmc: PMC7027209
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

86

Références

J Transl Med. 2014 May 23;12:144
pubmed: 24886498
BMC Med Inform Decis Mak. 2015 Feb 07;15:2
pubmed: 25656224
Methods Inf Med. 2015;54(4):364-371
pubmed: 26196494

Auteurs

Christopher Hampf (C)

Institute for Community Medicine, Section Epidemiology of Health Care and Community Health, University Medicine Greifswald, Ellernholzstr. 1-2, 17475, Greifswald, Germany. christopher.hampf@uni-greifswald.de.

Lars Geidel (L)

Independent Trusted Third Party, University Medicine Greifswald, Ellernholzstr. 1-2, 17475, Greifswald, Germany.

Norman Zerbe (N)

Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.

Martin Bialke (M)

Institute for Community Medicine, Section Epidemiology of Health Care and Community Health, University Medicine Greifswald, Ellernholzstr. 1-2, 17475, Greifswald, Germany.

Dana Stahl (D)

Independent Trusted Third Party, University Medicine Greifswald, Ellernholzstr. 1-2, 17475, Greifswald, Germany.

Arne Blumentritt (A)

Independent Trusted Third Party, University Medicine Greifswald, Ellernholzstr. 1-2, 17475, Greifswald, Germany.

Thomas Bahls (T)

Institute for Community Medicine, Section Epidemiology of Health Care and Community Health, University Medicine Greifswald, Ellernholzstr. 1-2, 17475, Greifswald, Germany.

Peter Hufnagl (P)

Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.

Wolfgang Hoffmann (W)

Institute for Community Medicine, Section Epidemiology of Health Care and Community Health, University Medicine Greifswald, Ellernholzstr. 1-2, 17475, Greifswald, Germany.

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Classifications MeSH