To allow researchers to explore the data in the Clinical Research Data Warehouse (CRDW) prior to making a data request, the CRI operates a cohort discovery tool called BSD Leaf.
Leaf is a powerful self-service tool which provides UChicago investigators a user-friendly interface for querying de-identified electronic health record (EHR) data sourced from the UChicago Medicine (UCM) patient population. Leaf interacts directly with a regularly refreshed subset of data, derived from the EHR and encoded in the OMOP Common Data Model (CDM), and gives users the ability to build and explore cohorts in real time. Simple drag-and-drop functionality lets users quickly build an ad hoc query of the EHR, execute the query, and provide a breakdown of the cohort it discovered.
The primary use case for Leaf is cohort discovery. For example:
- The data in Leaf (including demographics, encounters, procedures, diagnoses, labs, medications) can help investigators answer a variety of preparatory-to-research questions about the patient population.
- Leaf is a useful tool to help an investigator determine if there are enough patients within the hospital system who have a given set of conditions matching the recruitment criteria for a trial.
- It can also help with planning and designing an existing study or submitting a grant proposal.
These results can inform data requests for de-identified or IRB-approved identified data, as well as helping researchers to formulate hypotheses and identify potential cohorts for research studies and clinical trials.
