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首页> 外文期刊>BMC Medical Informatics and Decision Making >Computational challenges and human factors influencing the design and use of clinical research participant eligibility pre-screening tools
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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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Background Clinical 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. Methods The study used a validation study, usability testing, and a heuristic evaluation to evaluate and characterize the operational characteristics of the software as well as human factors affecting its use. Results Clinical trials from the Division of Cardiology and the Department of Family Medicine were used for this multi-modal evaluation, which included a validation study, usability study, and a heuristic evaluation. From the results of the validation study, the software demonstrated a positive predictive value (PPV) of 54.12% and 0.7%, respectively, and a negative predictive value (NPV) of 73.3% and 87.5%, respectively, for two types of clinical trials. Heuristic principles concerning error prevention and documentation were characterized as the major usability issues during the heuristic evaluation. Conclusions This software is intended to provide an initial list of eligible patients to a clinical study coordinators, which provides a starting point for further eligibility screening by the coordinator. Because this software has a high “rule in” ability, meaning that it is able to remove patients who are not eligible for the study, the use of an automated tool built to leverage an existing enterprise DW can be beneficial to determining eligibility and facilitating clinical trial recruitment through pre-screening. While the results of this study are promising, further refinement and study of this and related approaches to automated eligibility screening, including comparison to other approaches and stakeholder perceptions, are needed and future studies are planned to address these needs.
机译:背景技术临床试验是推进临床护理和证明的实践的主要机制,但招聘参与者对此类试验的挑战被广为人意被认为是这些类型研究的主要障碍。数据仓库(DW)存储大量的异因临床数据,可用于增强招聘实践,但由于收集,管理,集成,分析和传播的方式,使用数据仓库时存在多种挑战数据。利用DW的招聘目的的关键步骤正在能够将试验资格标准匹配数据仓库中的离散和半结构化数据类型,尽管试验资格标准往往被编写,但不担心其可计算性。我们介绍了一种基于Web的工具的多模态评估,可用于预筛选患者临床试验资格,并评估该工具实际上用于临床研究预筛选和招聘的能力。方法采用验证研究,可用性测试和启发式评估来评估和表征软件的操作特征以及影响其使用的人类因素。结果从心脏病学和家庭医学部门的临床试验用于这种多模态评估,包括验证研究,可用性研究和启发式评估。从验证研究的结果,该软件分别证明了阳性预测值(PPV)分别为54.12%和0.7%,分别为两种类型的临床试验,分别为73.3%和87.5%的负面预测值(NPV) 。关于错误预防错误和文件的启发式原则被特征在于启发式评估期间的主要可用性问题。结论该软件旨在向临床研究协调员提供符合条件患者的初始列表,该协调员提供了协调员进一步资格筛查的起点。因为这个软件具有很高的“规则”能力,这意味着它能够去除没有资格进行研究的患者,使用建造的自动化工具,以利用现有的企业DW可以有利于确定资格和促进临床通过预先筛选审判招聘。虽然本研究的结果是有希望的,但需要进一步改进和研究自动资格筛查,包括与其他方法和利益相关者感知的比较,以及未来的研究计划解决这些需求。

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