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简化临床试验中的电子数据捕获:通过网络服务实现工作流程嵌入式图像和生物信号文件的集成与分析。

Simplifying electronic data capture in clinical trials: workflow embedded image and biosignal file integration and analysis via web services.

作者信息

Haak Daniel, Samsel Christian, Gehlen Johan, Jonas Stephan, Deserno Thomas M

机构信息

Department of Medical Informatics, Uniklinik RWTH Aachen, Pauwelsstr. 30, 52057, Aachen, Germany,

出版信息

J Digit Imaging. 2014 Oct;27(5):571-80. doi: 10.1007/s10278-014-9694-z.

Abstract

To improve data quality and save cost, clinical trials are nowadays performed using electronic data capture systems (EDCS) providing electronic case report forms (eCRF) instead of paper-based CRFs. However, such EDCS are insufficiently integrated into the medical workflow and lack in interfacing with other study-related systems. In addition, most EDCS are unable to handle image and biosignal data, although electrocardiography (EGC, as example for one-dimensional (1D) data), ultrasound (2D data), or magnetic resonance imaging (3D data) have been established as surrogate endpoints in clinical trials. In this paper, an integrated workflow based on OpenClinica, one of the world's largest EDCS, is presented. Our approach consists of three components for (i) sharing of study metadata, (ii) integration of large volume data into eCRFs, and (iii) automatic image and biosignal analysis. In all components, metadata is transferred between systems using web services and JavaScript, and binary large objects (BLOBs) are sent via the secure file transfer protocol and hypertext transfer protocol. We applied the close-looped workflow in a multicenter study, where long term (7 days/24 h) Holter ECG monitoring is acquired on subjects with diabetes. Study metadata is automatically transferred into OpenClinica, the 4 GB BLOBs are seamlessly integrated into the eCRF, automatically processed, and the results of signal analysis are written back into the eCRF immediately.

摘要

为了提高数据质量并节省成本,如今的临床试验使用提供电子病例报告表(eCRF)的电子数据捕获系统(EDCS)来进行,而非纸质病例报告表。然而,此类EDCS未充分融入医疗工作流程,且缺乏与其他研究相关系统的接口。此外,尽管心电图(例如作为一维(1D)数据的示例)、超声(二维数据)或磁共振成像(三维数据)已在临床试验中被确立为替代终点,但大多数EDCS无法处理图像和生物信号数据。本文介绍了一种基于世界上最大的EDCS之一OpenClinica的集成工作流程。我们的方法由三个组件组成,分别用于(i)研究元数据的共享,(ii)将大量数据集成到eCRF中,以及(iii)自动图像和生物信号分析。在所有组件中,元数据通过网络服务和JavaScript在系统之间传输,二进制大对象(BLOB)通过安全文件传输协议和超文本传输协议发送。我们在一项多中心研究中应用了闭环工作流程,该研究对糖尿病患者进行长期(7天/24小时)动态心电图监测。研究元数据自动传输到OpenClinica中,4GB的BLOB无缝集成到eCRF中,自动进行处理,信号分析结果立即写回到eCRF中。

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A partnership approach for Electronic Data Capture in small-scale clinical trials.一种小规模临床试验中电子数据采集的合作方法。
J Biomed Inform. 2011 Dec;44 Suppl 1(Suppl 1):S103-S108. doi: 10.1016/j.jbi.2011.05.008. Epub 2011 May 30.

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