OHDSI is a collaborative community responsible for creating and stewarding the OMOP Common Data Model (CDM), a data standard for observational health data. The Johns Hopkins OHDSI team is a virtual group comprised of students, clinical researchers, and informatics experts working to utilize and help others utilize the OMOP CDM to perform research on observational health data. Here at Johns Hopkins, we’ve worked with our institutional partners to create a valuable dataset that can be used for research both internally and in conjunction with external research partners. We believe that observational data is the key to dramatic improvements in evidence production and, eventually, patient care.
BIDS Student & Faculty Involvement
There are many JHU students, faculty, staff, and alumni actively involved with the OHDSI community on a day-to-day basis:
- Dr. Paul Nagy serves on the OHDSI Steering Committee and is active in several Working Groups.
- 35 students attended the annual 2023 OHDSI Global Symposium in New Jersey, and two students were honored:
- Katy Sadowski received the OHDSI Titan Award for Open-Source Development for her work on the Data Quality Dashboard.
- Stephanie Hong won OHDSI Collaborator Showcase Best Contribution in the Observational Data Standards and Management category for her work in the National COVID-19 Cohort collaborative project.
- One student is working on a project to incorporate Medical Imaging into the OMOP CDM, giving researchers the ability to combine functional data with imaging parameters, like modality, slice thickness, etc.
- Another group of students are using NLP to map Social Determinants of Health – often found in free text clinical notes – into the OMOP CDM. Extracting this information from clinical notes is critical to health equity research.