背景:卫生信息系统中的数据质量具有复杂的结构,由多个维度组成。这项研究旨在确定健康信息系统的常见数据质量元素。
方法:进行了文献综述,并在WebofKnowledge中运行了搜索策略,科学直接,翡翠,PubMed,Scopus和GoogleScholar搜索引擎作为跟踪参考的附加来源。我们找到了760份文件,排除314个重复项,关于摘要审查的339篇和关于全文审查的167篇;留下58篇论文供批判性评估。
结果:目前的审查表明,14个标准被归类为健康信息系统数据质量的主要维度,包括:准确性,一致性,安全,及时性,完整性,可靠性,可访问性,客观性,相关性,可理解性,导航,声誉,效率和价值增加。准确性,完整性,和及时性,是文学中使用最多的三个维度。
结论:目前,在评估卫生信息系统数据质量的维度上,缺乏统一性和潜在的适用性。通常,不同的方法(定性,定量和混合方法)用于评估所审查出版物中健康信息系统的数据质量。因此,由于定义维度和评估方法不一致,必须将数据质量的维度分类为有限的一组主要维度。
BACKGROUND: Data quality in health information systems has a complex structure and consists of several dimensions. This research conducted for identify Common data quality elements for health information systems.
METHODS: A literature review was conducted and search strategies run in Web of Knowledge, Science Direct, Emerald, PubMed, Scopus and Google Scholar search engine as an additional source for tracing references. We found 760 papers, excluded 314 duplicates, 339 on abstract review and 167 on full-text review; leaving 58 papers for critical appraisal.
RESULTS: Current review shown that 14 criteria are categorized as the main dimensions for data quality for health information system include: Accuracy, Consistency, Security, Timeliness, Completeness, Reliability, Accessibility, Objectivity, Relevancy, Understandability, Navigation, Reputation, Efficiency and Value- added. Accuracy, Completeness, and Timeliness, were the three most-used dimensions in literature.
CONCLUSIONS: At present, there is a lack of uniformity and potential applicability in the dimensions employed to evaluate the data quality of health information system. Typically, different approaches (qualitative, quantitative and mixed methods) were utilized to evaluate data quality for health information system in the publications that were reviewed. Consequently, due to the inconsistency in defining dimensions and assessing methods, it became imperative to categorize the dimensions of data quality into a limited set of primary dimensions.