健康研究数据质量指标的集合:更新的理由
Jürgen Stausberg1, Sonja Harkener1, Solveig Bünz1
1Institute for Medical Informatics, Biometry and Epidemiology, Faculty of Medicine, University Duisburg-Essen, Essen, Germany.
Studies in health technology and informatics
|November 22, 2024
概括
这项研究更新了德国关于健康研究注册表数据质量指南. 它结合了新的维度,指标结构和元数据质量,解决了大数据和人工智能挑战.
科学领域:
- 健康研究 数据管理 数据管理
- 数据质量保证 数据质量保证
背景情况:
- 结构化数据对于实证健康研究至关重要.
- 数据价值取决于质量和适用性.
- 德国的一项指导方针涉及51个指标的注册表和队列研究中的数据质量.
研究的目的:
- 更新德国关于数据质量管理的指南.
- 纳入当前对数据维度,指标结构和收集的看法.
- 解决元数据质量和大数据和人工智能带来的挑战.
主要方法:
- 文献审查以确定证据来源.
- 将证据分类为尺寸,结构和指标.
- 专注于新的数据质量控制挑战.
主要成果:
- 该指南的更新将考虑新的数据维度和指标结构.
- 将明确包括元数据质量措施.
- 将应对来自大数据和人工智能的新挑战.
结论:
- 更新的指南旨在加强健康研究中的数据质量管理.
- 它将为定义和收集质量指标提供一个框架.
- 更新为经验健康研究中不断变化的数据景观做好了准备.
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