A Collection of Data Quality Indicators for Health Research: Rationale for an Update.

Jürgen Stausberg, Sonja Harkener, Solveig Bünz
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Abstract

Structured data are the capital of empirical health research. The value of these data relates to their quality and to their fit for use. A German guideline for the management of data quality in registries and cohort studies lists 51 quality indicators organized into the categories organization, integrity, and trueness. An update of the guideline will take into account the current view on dimensions of data, the appropriate structure for the definition of an indicator, and the collection of quality indicators itself. In the next version, the collection will explicitly address measures of metadata quality. The first step of a literature review revealed a high number of potential sources of evidence. These will be categorized into the topics dimensions, structure, and indicators respectively. Special attention will be paid to new challenges of data quality control arising from big data and artificial intelligence.

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健康研究数据质量指标集》:更新的理由。
结构化数据是健康实证研究的资本。这些数据的价值与其质量和是否适合使用有关。德国的登记和队列研究数据质量管理指南列出了 51 项质量指标,分为组织性、完整性和真实性三个类别。该指南的更新将考虑到当前对数据维度的看法、指标定义的适当结构以及质量指标收集本身。在下一个版本中,收集工作将明确涉及元数据质量的衡量标准。第一步的文献审查发现了大量潜在的证据来源。这些证据将分别归类为维度、结构和指标等主题。将特别关注大数据和人工智能给数据质量控制带来的新挑战。
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