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Ontological specification of quality of chronic disease data in EHRs to support decision analytics: a realist review

机译：EHR中慢性病数据质量的本体规范，以支持决策分析：现实评论

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Abstract This systematic review examined the current state of conceptualization and specification of data quality and the role of ontology based approaches to develop data quality based on "fitness for purpose" within the health context. A literature review was conducted of all English language studies, from January 2000-March 2013, which addressed data/information quality, fitness for purpose of data, used and implemented ontology-based approaches. Included papers were critically appraised with a "context-mechanism-impacts/outcomes" overlay. We screened 315 papers, excluded 36 duplicates, 182 on abstract review and 46 on full-text review; leaving 52 papers for critical appraisal. Six papers conceptualized data quality within the "fitness for purpose" definition. While most agree with a multidimensional definition of DQ, there is little consensus on a conceptual framework. We found no reports of systematic and comprehensive ontological approaches to DQ based on fitness for purpose or use. However, 16 papers used ontology-specified implementations in DQ improvement, with most of them focusing on some dimensions of DQ such as completeness, accuracy, correctness, consistency and timeliness. The majority of papers described the processes of the development of DQ in various information systems. There were few evaluative studies, including any comparing ontological with non-ontological approaches, on the assessment of clinical data quality and the performance of the application.
机译：摘要这篇系统综述审查了数据质量的概念化和规范化的现状，以及基于本体的方法在健康环境中基于“出于目的的适应性”发展数据质量的作用。从2000年1月至2013年3月，对所有英语研究进行了文献综述，涉及数据/信息质量，数据适用性，使用和实施的基于本体的方法。所收录的论文均经过严格评估，并带有“上下文-机制-影响/结果”覆盖。我们筛选了315篇论文，排除了36篇重复论文，其中182篇摘要评论和46篇全文评论;留下52篇论文进行批判性评估。六篇论文将“目标适用性”定义内的数据质量概念化。尽管大多数人都同意DQ的多维定义，但在概念框架上几乎没有共识。我们没有发现关于基于目的或用途适合性的DQ系统全面的本体论方法的报道。但是，有16篇论文在DQ改进中使用了本体论特定的实现，其中大多数专注于DQ的某些方面，例如完整性，准确性，正确性，一致性和及时性。大多数论文描述了各种信息系统中DQ的开发过程。关于临床数据质量评估和应用性能的评估研究很少，包括将本体论与非本体论方法进行比较的评估。

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