Greulich Leonard, Hegselmann Stefan, Dugas Martin
Institute of Medical Informatics, University of Münster, Münster, Germany.
Institute of Medical Informatics, Heidelberg University Hospital, Heidelberg, Germany.
JMIR Med Inform. 2021 Nov 19;9(11):e29176. doi: 10.2196/29176.
Medical research and machine learning for health care depend on high-quality data. Electronic data capture (EDC) systems have been widely adopted for metadata-driven digital data collection. However, many systems use proprietary and incompatible formats that inhibit clinical data exchange and metadata reuse. In addition, the configuration and financial requirements of typical EDC systems frequently prevent small-scale studies from benefiting from their inherent advantages.
The aim of this study is to develop and publish an open-source EDC system that addresses these issues. We aim to plan a system that is applicable to a wide range of research projects.
We conducted a literature-based requirements analysis to identify the academic and regulatory demands for digital data collection. After designing and implementing OpenEDC, we performed a usability evaluation to obtain feedback from users.
We identified 20 frequently stated requirements for EDC. According to the International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) 25010 norm, we categorized the requirements into functional suitability, availability, compatibility, usability, and security. We developed OpenEDC based on the regulatory-compliant Clinical Data Interchange Standards Consortium Operational Data Model (CDISC ODM) standard. Mobile device support enables the collection of patient-reported outcomes. OpenEDC is publicly available and released under the MIT open-source license.
Adopting an established standard without modifications supports metadata reuse and clinical data exchange, but it limits item layouts. OpenEDC is a stand-alone web app that can be used without a setup or configuration. This should foster compatibility between medical research and open science. OpenEDC is targeted at observational and translational research studies by clinicians.
医疗研究和用于医疗保健的机器学习依赖于高质量数据。电子数据捕获（EDC）系统已被广泛用于元数据驱动的数字数据收集。然而，许多系统使用专有的、不兼容的格式，这阻碍了临床数据交换和元数据重用。此外，典型EDC系统的配置和财务要求常常使小规模研究无法从其固有优势中受益。
本研究的目的是开发并发布一个解决这些问题的开源EDC系统。我们旨在设计一个适用于广泛研究项目的系统。
我们进行了基于文献的需求分析，以确定数字数据收集的学术和监管要求。在设计并实现OpenEDC之后，我们进行了可用性评估，以获取用户反馈。
我们确定了20条常见的EDC需求。根据国际标准化组织/国际电工委员会（ISO/IEC）25010规范，我们将这些需求分为功能适用性、可用性、兼容性、易用性和安全性。我们基于符合法规的临床数据交换标准协会操作数据模型（CDISC ODM）标准开发了OpenEDC。移动设备支持能够收集患者报告的结果。OpenEDC是公开可用的，并根据麻省理工学院开源许可发布。
未经修改采用既定标准支持元数据重用和临床数据交换，但会限制项目布局。OpenEDC是一个独立的网络应用程序，无需设置或配置即可使用。这应促进医学研究与开放科学之间的兼容性。OpenEDC面向临床医生的观察性和转化性研究。
