Faculty:
Andrew Williams, Michael Kahn, Vojtech Huser, Hossein Estiri, Hanieh Razzaghi, Connor Callahan, Tim Bergquist, Robert Miller
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.
The following videos were recorded during the fourth annual OHDSI symposium which took place October 11-13th, 2018. These recordings were made possible by generous support from EvidNet, Deloitte, Johnson & Johnson, and Bayer.
2018 OHDSI Data Quality Tutorial (1 of 5)
Introduction
OHDSI Data Quality Tutorial (2 of 5)
2018 OHDSI Data Quality Tutorial (3 of 6)
PEDSnet Data Quality
2018 OHDSI Data Quality Tutorial (4 of 5)
Testing Data Completeness
2018 OHDSI Data Quality Tutorial (5 of 5)
PEDSnet DQA Tutorial
2018 OHDSI Data Quality Tutorial (1 of 5)
2018 OHDSI Data Quality Tutorial (2 of 5)
2018 OHDSI Data Quality Tutorial (3 of 5)
2018 OHDSI Data Quality Tutorial (4 of 5)
2018 OHDSI Data Quality Tutorial (5 of 5)
Agenda
Tutorial Slides
Links to ATLAS and R Studio
Rules for Tools
Overview of the OHDSI Analysis Ecosystem
Population-Level Estimation
Patient-Level Prediction
Cohort Definition/Phenotyping
