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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.

ABSTRACT: 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 nature of real-world data, exist.

Conclusion: The practice of DQ assessment is still limited in scope. Future work is warranted to generate understandable, executable, and reusable DQ measures.

SUBMITTER: Bian J

PROVIDER: S-EPMC7727392 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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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.

Bian Jiang J Lyu Tianchen T Loiacono Alexander A Viramontes Tonatiuh Mendoza TM Lipori Gloria G Guo Yi Y Wu Yonghui Y Prosperi Mattia M George Thomas J TJ Harle Christopher A CA Shenkman Elizabeth A EA Hogan William W

Journal of the American Medical Informatics Association : JAMIA 20201201 12

<h4>Objective</h4>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).<h4>Materials and methods</h4>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 systemat ...[more]

PMID: 33166397

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Dataset Information

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.

Publications

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.

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