Participants will learn how to understand and use three freely available sets of tools that assess the quality of OMOP v5 data. A conceptual framework for data quality will be presented, followed by hands-on instruction for installing and running all three sets of tools: Achilles Heel; PEDSnet DQA Toolkit; and DQe-c, DQe-v and automated outlier detection. The class will involve running these tools against a real dataset.
Course prerequisites: Participants should know the domains and vocabularies in the OMOP CDM, understand its person-level organization, the way concepts and concept relationships are used to represent local codes in a standardized fashion. Participants should also have at least beginner level R and SQL programming skills.
Faculty: Andrew Williams; Vojtech Huser, Ajit Londhe, Hanieh Razzaghi, Connor Callahan, Tim Bergquist
2019 OHDSI Tutorials – Data Quality (1 of 4)
Data Quality Overview
2019 OHDSI Tutorials – Data Quality (2 of 4)
DataQuality Dashboard Tutorial
2019 OHDSI Tutorials – Data Quality (3 of 4)
Testing Data Completeness with DQe c v2
2019 OHDSI Tutorials – Data Quality (4 of 4)
PEDSnet Data Quality
2019 OHDSI Tutorials – Data Quality (1 of 4)
2019 OHDSI Tutorials – Data Quality (2 of 4)
2019 OHDSI Tutorials – Data Quality (3 of 4)
2019 OHDSI Tutorials – Data Quality (4 of 4)
Tutorial Slides – Introduction
Tutorial Slides – DataQualityDashboard
Tutorial Slides – Testing Data Completeness with DQe-c-v2
Tutorial Slides – PEDSnet Data Quality
Tutorial Slides – PEDSnet DQA Tutorial
