To allow researchers to explore the data in the Clinical Research Data Warehouse (CRDW) prior to making a data request, the CRI maintains two cohort discovery tools. Cohort discovery involves finding a patient population using different inclusion criteria, such as their age, medical conditions, and procedures they have undergone. Cohort discovery tools remove barriers between clinical data and end-users by making it easier to design and run self-service queries based on a cohort of interest. Cohort discovery tools can assist investigators in answering a variety of preparatory-to-research questions about a patient population such as: 1) assisting with determining if there are enough patients within the hospital system who have a given set of conditions matching the recruitment criteria for a trial, 2) helping plan or design a existing study or grant proposal.
The two applications the CRI currently maintains are: 1) BSD Leaf and 2) ITM Leaf
Leaf applications (“Leaf”) are powerful self-service tools 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 from single or multiple institutions. Leaf was created at the University of Washington’s Institute of Translational Health Sciences. More information about the background and creation of Leaf can be found in this JAMIA article.