Students gain practical experience working with the OMOP common data model (CDM) from the Observational Health Data Science and Informatics (OHDSI) community. The class will provide students with an understanding of the research challenges posed by traditional healthcare data sources and will highlight the importance of the standardized data model in addressing these challenges, specifically how the CDM can maximize the value of observational health data through facilitation of large-scale analytics. The class will explore the use of the CDM in facilitating reproducible and interoperable observational studies that are becoming the industry standards in emerging healthcare research.
Topics:
- data quality
- data characterization
- major clinical terminologies
- research cohort definitions
- how to frame an observational research question
- tools for cohort discovery such as Athena and Atlas