Assessing the practice of data quality evaluation in a national clinical data research network through a systematic scoping review in the era of real-world data
作者:Jiang Bian, Tianchen Lyu, Alexander Loiacono, Tonatiuh Mendoza Viramontes, Gloria Lipori, Yi Guo, Yonghui Wu, Mattia Prosperi, Thomas J. George, Christopher A. Harle, Elizabeth Shenkman, William R. Hogan · 发表于:Journal of the American Medical Informatics Association · 年份:2020 · DOI:10.1093/jamia/ocaa245 · 被引用次数:98 · 研究领域:Electronic Health Records Systems、Data Quality and Management、Machine Learning in Healthcare
OBJECTIVE: To synthesize data quality (DQ) dimensions and assessment methods of real-world data, especially electronic health records, through a systematic scoping review and to assess the practice of DQ assessment in the national Patient-centered Clinical Research Network (PCORnet). MATERIALS AND METHODS: We started with 3 widely cited DQ literature-2 reviews from Chan et al (2010) and Weiskopf et al (2013a) and 1 DQ framework from Kahn et al (2016)-and expanded our review systematically to cover relevant articles published up to February 2020. We extracted DQ dimensions and assessment methods from these studies, mapped their relationships, and organized a synthesized summarization of existing DQ dimensions and assessment methods. We reviewed the data checks employed by the PCORnet and mapped them to the synthesized DQ dimensions and methods. RESULTS: We analyzed a total of 3 reviews, 20 DQ frameworks, and 226 DQ studies and extracted 14 DQ dimensions and 10 assessment methods. We found that completeness, concordance, and correctness/accuracy were commonly assessed. Element presence, validity check, and conformance were commonly used DQ assessment methods and were the main focuses of the PCORnet data checks. DISCUSSION: Definitions of DQ dimensions and methods were not consistent in the literature, and the DQ assessment practice was not evenly distributed (eg, usability and ease-of-use were rarely discussed). Challenges in DQ assessments, given the complex and heterogeneous ...