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评估记录链接工具E-PIX在德国一家大型大学医院的研究项目中管理数百万患者数据时的可扩展性和性能。

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.

作者信息

Hampf Christopher, Geidel Lars, Zerbe Norman, Bialke Martin, Stahl Dana, Blumentritt Arne, Bahls Thomas, Hufnagl Peter, Hoffmann Wolfgang

机构信息

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

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

出版信息

J Transl Med. 2020 Feb 17;18(1):86. doi: 10.1186/s12967-020-02257-4.

Abstract

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.

摘要

背景

身份管理是医学研究的核心组成部分。患者从多个地点招募,这需要一种容错的记录链接方法,以确保患者仅被注册一次。在大型研究项目或机构中,身份管理必须处理数千或数百万患者。在患者数量众多的环境中,注册过程可能因记录链接而导致运行时间过长。夏里特中心生物材料库(ZeBanC)寻求一种身份管理解决方案,该方案能够在大型研究项目中以可接受的性能处理数百万患者。本文的目的是使用柏林夏里特大学医学中心的E-PIX服务模拟数百万患者的注册情况。对E-PIX服务在所需运行时间、内存需求和处理器利用率方面进行了评估。总共至少需要注册2000万患者。应检查将患者注册到不同大小数据库中的运行时间,并确定E-PIX服务能够处理的最大患者数量。

方法

设置或开发工具来测量将患者注册到不同大小数据库中所需的运行时间、使用的内存和处理器使用率。为了生成接近实际的运行时间,基于转置的真实患者数据修改后的患者数据用于模拟。将转置后的患者数据发送到E-PIX以测量注册过程的运行时间。针对不同的数据库大小重复此测量。

结果

E-PIX适用于管理数据集中的数百万患者。在给定的硬件条件下,总共可以注册超过3000万患者。每天可以向该数据库注册超过1.6万名患者。

结论

E-PIX工具满足了夏里特用于大型研究项目的要求。E-PIX的使用旨在用于夏里特的研究环境。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4664/7027209/a10e2512c260/12967_2020_2257_Fig1_HTML.jpg

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