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Assessment of scalability and performance of the record linkage tool E-PIX(®) in managing multi-million patients in research projects at a large university hospital in Germany
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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7027209/ https://www.ncbi.nlm.nih.gov/pubmed/32066455 http://dx.doi.org/10.1186/s12967-020-02257-4 |
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author | Hampf, Christopher Geidel, Lars Zerbe, Norman Bialke, Martin Stahl, Dana Blumentritt, Arne Bahls, Thomas Hufnagl, Peter Hoffmann, Wolfgang |
author_facet | Hampf, Christopher Geidel, Lars Zerbe, Norman Bialke, Martin Stahl, Dana Blumentritt, Arne Bahls, Thomas Hufnagl, Peter Hoffmann, Wolfgang |
author_sort | Hampf, Christopher |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7027209 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-70272092020-02-24 Assessment of scalability and performance of the record linkage tool E-PIX(®) in managing multi-million patients in research projects at a large university hospital in Germany Hampf, Christopher Geidel, Lars Zerbe, Norman Bialke, Martin Stahl, Dana Blumentritt, Arne Bahls, Thomas Hufnagl, Peter Hoffmann, Wolfgang J Transl Med Methodology 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. BioMed Central 2020-02-17 /pmc/articles/PMC7027209/ /pubmed/32066455 http://dx.doi.org/10.1186/s12967-020-02257-4 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Methodology Hampf, Christopher Geidel, Lars Zerbe, Norman Bialke, Martin Stahl, Dana Blumentritt, Arne Bahls, Thomas Hufnagl, Peter Hoffmann, Wolfgang Assessment of scalability and performance of the record linkage tool E-PIX(®) in managing multi-million patients in research projects at a large university hospital in Germany |
title | Assessment of scalability and performance of the record linkage tool E-PIX(®) in managing multi-million patients in research projects at a large university hospital in Germany |
title_full | Assessment of scalability and performance of the record linkage tool E-PIX(®) in managing multi-million patients in research projects at a large university hospital in Germany |
title_fullStr | Assessment of scalability and performance of the record linkage tool E-PIX(®) in managing multi-million patients in research projects at a large university hospital in Germany |
title_full_unstemmed | Assessment of scalability and performance of the record linkage tool E-PIX(®) in managing multi-million patients in research projects at a large university hospital in Germany |
title_short | Assessment of scalability and performance of the record linkage tool E-PIX(®) in managing multi-million patients in research projects at a large university hospital in Germany |
title_sort | assessment of scalability and performance of the record linkage tool e-pix(®) in managing multi-million patients in research projects at a large university hospital in germany |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7027209/ https://www.ncbi.nlm.nih.gov/pubmed/32066455 http://dx.doi.org/10.1186/s12967-020-02257-4 |
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