ARDaC 共同数据模型促进了数据传播,并为现代临床研究提供了数据共享
Nanxin Jin1,2, Zuotian Li1,3, Carla Kettler2
1Biostatistics and Health Data Science, Indiana University School of Medicine, Indiana, USA.
Studies in health technology and informatics
|January 25, 2024
概括
开发了一个新的数据模型,ARDaC CDM,用于为酒精性肝炎网络 (AlcHepNet) 标准化复杂的临床数据. 这有助于在酒精性肝炎研究中进行数据共享和研究合作.
科学领域:
- 生物医学信息学 生物医学信息学
- 临床数据管理 临床数据管理
- 翻译研究是翻译研究.
背景情况:
- 现代临床研究产生复杂的多模式数据,包括参与者信息,治疗方法,生物样本和多组数据.
- 现有的数据模型往往难以满足这样丰富的数据集的传播和协作研究需求.
- 酒精性肝炎网络 (AlcHepNet) 需要一个强大的系统来管理和共享其广泛的研究数据.
研究的目的:
- 为酒精性肝炎网络 (AlcHepNet) 开发一个共同的数据模型 (CDM).研究数据共享 (ARDaC).
- 为了弥合REDCap电子数据捕获平台和基因组数据共享 (GDC) 数据模型之间的数据整合差距.
- 创建一个通用的,可扩展的CDM,支持现代临床研究和翻译研究.
主要方法:
- 开发了ARDaC共同数据模型 (CDM).
- 扩展了基因组数据共享 (GDC) 数据模型,以适应临床研究数据.
- 在Gen3框架内确保AlcHepNet REDCap平台与GDC数据模型之间的兼容性.
主要成果:
- ARDaC CDM成功地弥合了来自REDCap和GDC的数据模型.
- 共同开发机制 (CDM) 有助于在不同联盟和项目中协调研究数据.
- 开发的CDM支持ARDaC的持续开发和功能.
结论:
- ARDaC CDM是一个通用和可扩展的解决方案,用于管理复杂的临床研究数据.
- 该数据模型增强了AlcHepNet联盟内的数据传播和研究合作.
- 通过标准化各种数据类型,ARDaC CDM支持翻译研究.
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