OHDSI is a collaborative community responsible for creating and stewarding the OMOP Common Data Model (CDM), a 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 chairs the Medical Imaging and Open Source Working Groups.
2024 Highlights
- 50+ students attended the annual 2024 OHDSI Global Symposium in New Jersey, and two students were honored:
- Dr. Cindy Cai received an OHDSI Titan Award.
- Here is a list of all of our presentations:
- Streamlining Research Data Standardization: AI-READI Survey Instrument Data Elements and MoCA Measurement Data Elements are curated and mapped utilizing a Standardized Value Set Mapping Table for transformation into the OMOP Common Data Model – OHDSI
- Towards Reproducible Imaging Research: Implementation of DICOM to OMOP CDM – OHDSI
- Common Data Elements for Maternal Health Research: An OMOP-CDM Concept Mapping Study – OHDSI
- A Computable Phenotype for Time Toxicity of Elective Tracheostomy – OHDSI
- Comparative Analysis of OMOP CDM Database Profiles Across Institutions and Future Research Implications – OHDSI
- Comparative Safety of Second-line Antihyperglycemic Agents in Older Adults with Diabetes: Insights from the LEGEND-T2DM study – OHDSI
- Multi-national Patterns of Individual Cardioprotective Agents as Second-line Treatments for Type 2 Diabetes Mellitus: a LEGEND-T2DM Study – OHDSI
- Measuring Severe Maternal Morbidity: A Pilot OHDSI Electronic Health Record Network Study – OHDSI
- Comorbidities among patients with Severe Maternal Morbidity: A comparison of conditions identified through active hospital-based surveillance versus OMOP CDM – OHDSI
- Measuring Low-Value Primary Care with OMOP Common Data Model in the Adult Primary Care Registry – OHDSI
- Implementation and Evaluation of the Prevalence of Low-Value Care Procedures Using the OHDSI Network: A Case Study of Early Peripheral Vascular Interventions for Claudication – OHDSI
- Comparing IRB Review of OHDSI Network Studies: Sharing Experience and Guidance – OHDSI
2023 Highlights
- We had 35 faculty, staff, and students attend the conference.
- 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.