The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) format is a data standard used worldwide, making it easy for informaticists and data analysts on UF and UF Health research teams to organize and analyze data to answer their unique research questions.
The purpose of OMOP Common Data Model (CDM) is to standardize the format and content of observational healthcare data (e.g., encounters, patients, providers, diagnoses, drugs, measurements and procedures). The OMOP CDM harmonizes disparate coding systems —with minimal information loss—into a standardized vocabulary. This allows for reproducibility and collaboration across institutions.
The OMOP CDM has been adopted by the Observational Health Data Sciences and Informatics (OHDSI) collaborative, a multi-stakeholder, inter-disciplinary effort to bring out the value of observational health data through large-scale analytics. OHDSI maintains an open-source library of analytical tools for research and performance measurement using the OMOP CDM. Standardized structured query language (SQL) queries are shared in a common open-source repository, and detailed data documentation is freely available online.
Researchers can connect to OMOP Data using the ATLAS tool. ATLAS is a web-based tool developed by the OHDSI community that facilitates the design and execution of analyses on standardized, patient-level, observational data in the OMOP CDM format. Researchers will need a user account to access the ATLAS tool.
Regularly updated and IRB approved De-identified patient data readily accessible to Researchers. Dataset is available by request with a 1-2 business days turnaround. It includes each patient’s health history, demographics, vitals, diagnoses, medications, laboratory results, hospital utilization, and more. Dataset features details on over 300,000 patients diagnosed or suspected of having cancer at UF Health since Jan. 1, 2012.
Regularly updated and IRB approved De-identified patient data readily accessible to Researchers. Dataset available by request with 1-2 business days turnaround. It includes each patient’s health history, demographics, vitals, diagnoses, medications, laboratory results, hospital utilization. Line-level dataset compiles diagnoses, treatments, resource utilization and outcomes information on UF Health patients with COVID-19-like symptoms or who have undergone COVID-19 clinical testing. The data include qualifying patients seen at UF Health locations in Gainesville and Jacksonville since Jan. 1, 2020.
The Observational Health Data Sciences and Informatics (or OHDSI, pronounced “Odyssey”) program is a multi-stakeholder, interdisciplinary collaborative to bring out the value of health data through large-scale analytics. OHDSI has established an international network of researchers and observational health databases with a central coordinating center housed at Columbia University.
Figures A and B show the overall workflow process of requesting UFHealth OMOP datasets for research purposes.