| Literature DB >> 35854725 |
Noah Engel1, Hongjue Wang2, Xinzhuo Jiang2, Chun Yee Lau2, Jason Patterson2, Nripendra Acharya2, Maura Beaton2, Lina Sulieman3, Nishanth Pavinkurve2, Karthik Natarajan2.
Abstract
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.Entities:
Mesh：
Year: 2022 PMID： 35854725 PMCID： PMC9285158
Source DB: PubMed Journal: AMIA Annu Symp Proc ISSN： 1559-4076