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Description

This study aims to identify the clinical use cases for utilizing and evaluating our cohort discovery tool based on an information retrieval (IR) framework. Two practical clinical applications have been found: identifying patient cohorts for retrospective clinical studies, and recruiting patients for clinical trials. Retrospective cohort studies, one of the research areas that mostly rely on the EHR data, have been used to evaluate population health and identify risk factors. Enabled by the Rochester Epidemiology Project (REP), many cohorts have been created with EHR data. Another clinical use case is clinical trial recruitment, which is fundamental to the success of randomized clinical trials since it remains the biggest barrier to clinical and translational research. Mayo Clinic ranks No. 1 among 51 academic institutions in terms of both number of clinical trials and number of results reported. The data of a number of completed clinical trials and recruited patients are available at Mayo Clinic to evaluate the approach.

Learning Objective: What is cohort discovery?
How does information retrieval (IR) facilitate cohort discovery?
What are the clinical use cases for utilizing and evaluating a cohort discovery tool based on an IR framework?

Authors:

Yanshan Wang (Presenter)
Mayo Clinic

Andrew Wen, Mayo Clinic
Sijia Liu, Mayo Clinic
Jennifer St. Sauver, Mayo Clinic
Adil Bharucha, Mayo Clinic
Chunhua Weng, Columbia University
Hongfang Liu, Mayo Clinic

Presentation Materials:

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