A review of data quality assessment methods for public health information systems.
A review of data quality assessment methods for public health information systems.
复制标题
公共卫生信息系统数据质量评估方法综述。
DOI：
10.3390/ijerph110505170
复制
发表时间：
2014-05-14
影响因子：
--
通讯作者：
Yu P
中科院分区：
文献类型：
--
作者：
Chen H;Hailey D;Wang N;Yu P
准确评价公共卫生干预措施的影响和衡量公共卫生成果需要高质量的数据和有效的数据质量评估。数据、数据使用和数据收集过程作为数据质量的三个维度，都需要进行全面的数据质量评估。我们回顾了当前的数据质量评估方法。主要数据库和知名机构网站上都有相关研究。我们发现数据的维度是最经常被评估的。完整性，准确性和及时性是数据质量的49个属性中最常用的三个属性。定量评估方法主要是描述性调查和数据审核，而常见的定性评估方法是访谈和文献查阅。经检讨的研究的局限性包括不注意数据使用和数据收集过程、数据品质属性的定义不一致、未能回应数据使用者的关注，以及缺乏有系统的数据品质评估程序。这项审查研究受到数据库覆盖范围和公共卫生信息系统广度的限制。进一步的研究可以制定一致的数据质量定义和属性。应加大研究力度，评估数据使用的质量和数据收集过程的质量。
High quality data and effective data quality assessment are required for accurately evaluating the impact of public health interventions and measuring public health outcomes. Data, data use, and data collection process, as the three dimensions of data quality, all need to be assessed for overall data quality assessment. We reviewed current data quality assessment methods. The relevant study was identified in major databases and well-known institutional websites. We found the dimension of data was most frequently assessed. Completeness, accuracy, and timeliness were the three most-used attributes among a total of 49 attributes of data quality. The major quantitative assessment methods were descriptive surveys and data audits, whereas the common qualitative assessment methods were interview and documentation review. The limitations of the reviewed studies included inattentiveness to data use and data collection process, inconsistency in the definition of attributes of data quality, failure to address data users’ concerns and a lack of systematic procedures in data quality assessment. This review study is limited by the coverage of the databases and the breadth of public health information systems. Further research could develop consistent data quality definitions and attributes. More research efforts should be given to assess the quality of data use and the quality of data collection process.
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影响因子：
11.1
作者：
Forster M;Bailey C;Brinkhof MW;Graber C;Boulle A;Spohr M;Balestre E;May M;Keiser O;Jahn A;Egger M;ART-LINC collaboration of International Epidemiological Databases to Evaluate AIDS
通讯作者：
ART-LINC collaboration of International Epidemiological Databases to Evaluate AIDS
影响因子：
16.6
作者：
Batini, Carlo;Cappiello, Cinzia;Maurino, Andrea
通讯作者：
Maurino, Andrea
影响因子：
3.3
作者：
Bosch-Capblanch, Xavier;Ronveaux, Olivier;Bchir, Abdallah
通讯作者：
Bchir, Abdallah
影响因子：
2.8
作者：
Ford JB;Roberts CL;Algert CS;Bowen JR;Bajuk B;Henderson-Smart DJ;NICUS group
通讯作者：
NICUS group
影响因子：
3.4
作者：
Corriols, Marianela;Marin, Jesus;Thorn, Ake
通讯作者：
Thorn, Ake