Coronary heart disease (CHD) has been the leading cause of mortality worldwide. There have been multiple contradictory studies that investigated sex-specific differences in risk factors for CHD. Here, we tested the assertion that given a complex study result from the literature, we could quickly reproduce the study on this topic. To achieve that we mimicked the variables by generating matching phenotype definitions using OHDSI tools, and performed the statistical analyses on electronic health record data.

Learning Objective: After participating in this session, the learner should be better able to:

1. Understand and be able to discuss the current medical evidence for the risk factors associated with coronary heart disease and female-male differences in these risk factors
2. Learn challenges and possible solutions in reproducing studies using electronic health record data
3. Learn advantages and disadvantages of Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) and its tools


Anna Ostropolets (Presenter)
Columbia University

Linying Zhang, Columbia University
Jami Jackson Mulgrave, Columbia University
George Hripcsak, Columbia University

Presentation Materials: