EHR Data Quality Assessment Tools and Issue Reporting Workflows for the 'All of Us' Research Program Clinical Data Research Network.

Autor:	Engel N; The Johns Hopkins University School of Medicine, Baltimore, MD, USA., Wang H; Department of Biomedical Informatics at Columbia University Medical Center, New York, NY, USA., Jiang X; Department of Biomedical Informatics at Columbia University Medical Center, New York, NY, USA., Lau CY; Department of Biomedical Informatics at Columbia University Medical Center, New York, NY, USA., Patterson J; Department of Biomedical Informatics at Columbia University Medical Center, New York, NY, USA., Acharya N; Department of Biomedical Informatics at Columbia University Medical Center, New York, NY, USA., Beaton M; Department of Biomedical Informatics at Columbia University Medical Center, New York, NY, USA., Sulieman L; Vanderbilt University Department of Biomedical Informatics, Nashville, TN, USA., Pavinkurve N; Department of Biomedical Informatics at Columbia University Medical Center, New York, NY, USA., Natarajan K; Department of Biomedical Informatics at Columbia University Medical Center, New York, NY, USA.
Jazyk:	angličtina
Zdroj:	AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science [AMIA Jt Summits Transl Sci Proc] 2022 May 23; Vol. 2022, pp. 186-195. Date of Electronic Publication: 2022 May 23 (Print Publication: 2022).
Abstrakt:	The All of Us (AoU) Research Program aggregates electronic health records (EHR) data from 300,00+ participants spanning 50+ distinct data sites. The diversity and size of AoU's data network result in multifaceted obstacles to data integration that may undermine the usability of patient EHR. Consequently, the AoU team implemented data quality tools to regularly evaluate and communicate EHR data quality issues at scale. The use of systematic feedback and educational tools ultimately increased site engagement and led to quantitative improvements in EHR quality as measured by program- and externally-defined metrics. These improvements enabled the AoU team to save time on troubleshooting EHR and focus on the development of alternate mechanisms to improve the quality of future EHR submissions. While this framework has proven effective, further efforts to automate and centralize communication channels are needed to deepen the program's efforts while retaining its scalability. (©2022 AMIA - All rights reserved.)
Databáze:	MEDLINE
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