In this tutorial, we will introduce participants to steps along the journey from data to evidence using the OMOP Common Data Model, OHDSI tools and scientific best practices.
In each 50-minute segment, the class will learn the conceptual framing of the problem and approach to the solution. Then, the class will have the opportunity to have hands-on exposure to design and implementation of analyses and interpretation of results. The course will be motivated by a real use case: using observational data to generate evidence about the relationship between an exposure and outcome, and will highlight how the suite of OHDSI tools and practices can enable such learning.
This class is designed for newcomers to the OHDSI community who are looking for a high-level summary across a wide range of topics covered within the OHDSI community. It’s also designed for those in the OHDSI community who may be focused in one particular area of the journey who want exposure to the other areas, so they can better understand how their work contributes to be ‘big picture’, and advances the mission to improve health by empowering a community to collaboratively generate the evidence that promotes better health decisions and better care.
Agenda • Times are EST & subject to change:
8:30 am • Overview of the OHDSI Journey: where are we going? – Patrick Ryan
9:00 am • OMOP Common Data Model and vocabulary – Clair Blacketer
9:50 am • Energy break
10:00 am • ETL a source database into OMOP CDM – Melanie Philofsky
10:50 am • Energy break
11:00 am • Creating cohort definitions – Asieh Golozar
11:50 am • Lunch break
12:30 pm • Phenotype evaluation – Gowtham Rao
1:20 pm • Energy break
1:30 pm • Characterization – Kristin Kostka
2:20 pm • Energy break
2:30 pm • Estimation – Martijn Schuemie
3:20 pm • Energy break
3:30 pm • Prediction – Jenna Reps
4:20 pm • Recap of the OHDSI Journey, where do we go from here? – George Hripcsak