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Concept for Linking De-identified Biomedical Research Data Using a Study Participant Management System

机译:使用研究参与者管理系统连接去识别的生物医学研究数据的概念

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Biomedical research projects show an increasing demand of large numbers of participants from different recruiting centers to achieve statistically significant results. The collected types of data are stored in distributed databases and are linked to the participant by different non-resolvable identifiers (layered pseudonyms) for de-identification. To ensure the quality of the gathered data, regular quality assurance analyses are required at each local center. Because of the distributed databases and layered pseudonyms the analyses can only be achieved manually. Therefore, the process is error-prone and laborious. The objective of this paper is to propose a solution concept to automate the manual process by using a local study participant management system. It orchestrates the process and enables the quality assurance analyses within a clinical data warehouse.
机译:生物医学研究项目表现出越来越多的来自不同招聘中心的参与者的需求,以实现统计上显着的结果。收集的数据类型存储在分布式数据库中,并通过不同的不可解析标识符(分层假名)链接到参与者以进行去识别。为确保收集数据的质量,每个本地中心都需要定期质量保证分析。由于分布式数据库和分层假名,分析只能手动实现。因此,该过程是错误的,易于越来越慢。本文的目的是提出解决方案概念,通过使用本地研究参与者管理系统来自动化手动过程。它策划了该过程,并在临床数据仓库内进行质量保证分析。

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