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Computational challenges and human factors influencing the design and use of clinical research participant eligibility pre-screening tools

机译:影响临床研究参与者资格预筛选工具设计和使用的计算挑战和人为因素

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摘要

BackgroundClinical trials are the primary mechanism for advancing clinical care and evidenced-based practice, yet challenges with the recruitment of participants for such trials are widely recognized as a major barrier to these types of studies. Data warehouses (DW) store large amounts of heterogenous clinical data that can be used to enhance recruitment practices, but multiple challenges exist when using a data warehouse for such activities, due to the manner of collection, management, integration, analysis, and dissemination of the data. A critical step in leveraging the DW for recruitment purposes is being able to match trial eligibility criteria to discrete and semi-structured data types in the data warehouse, though trial eligibility criteria tend to be written without concern for their computability. We present the multi-modal evaluation of a web-based tool that can be used for pre-screening patients for clinical trial eligibility and assess the ability of this tool to be practically used for clinical research pre-screening and recruitment.
机译:背景技术临床试验是推进临床护理和循证医学实践的主要机制,然而,招募此类试验的参与者所面临的挑战被广泛认为是此类研究的主要障碍。数据仓库(DW)存储大量可用于增强招聘实践的异类临床数据,但是将数据仓库用于此类活动时,由于收集,管理,集成,分析和分发的方式存在多种挑战。数据。利用DW进行招聘的关键步骤是能够使试用资格标准与数据仓库中的离散和半结构化数据类型相匹配,尽管编写试用资格标准时往往不考虑其可计算性。我们介绍了一种基于Web的工具的多模式评估,该工具可用于对患者进行临床试验资格的预筛查,并评估该工具在临床研究中的预筛查和招募中实际使用的能力。

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