Vojtech Huser1, Michael G. Kahn2, Jeffrey S. Brown3, Ramkiran Gouripeddi4
1National Library of Medicine, National Institutes of Health
2Department of Pediatrics, University of Colorado
3Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute
4University of Utah, School of Medicine
Email: firstname.lastname@example.org, Michael.Kahn@ucdenver.edu, email@example.com, firstname.lastname@example.org
Pacific Symposium on Biocomputing 23:628-633(2018)
© 2018 World Scientific
Open Access chapter published by World Scientific Publishing Company and distributed under the terms of the Creative Commons Attribution (CC BY) 4.0 License.
This paper summarizes content of the workshop focused on data quality. The first speaker (VH) described data quality infrastructure and data quality evaluation methods currently in place within the Observational Data Science and Informatics (OHDSI) consortium. The speaker described in detail a data quality tool called Achilles Heel and latest development for extending this tool. Interim results of an ongoing Data Quality study within the OHDSI consortium were also presented. The second speaker (MK) described lessons learned and new data quality checks developed by the PEDsNet pediatric research network. The last two speakers (JB, RG) described tools developed by the Sentinel Initiative and University of Utah's service oriented framework. The workshop discussed at the end and throughout how data quality assessment can be advanced by combining best features of each network.