Description
Screening and management of patients with prediabetes can prevent diabetes and related complications. However, there are technical and clinical challenges to accurately identify these patients. We proposed methodology to overcome those challenges by using EHR data to phenotype patients at risk, assign a clinical category and support clinical decision support interventions. Herein, we share our initial findings related to the development and validation of an algorithm and resulting clinical categories: Diabetes, Pre-diabetes, Normoglycemia and No-data.
Learning Objective: Assess the accuracy of a phenotyping algorithm to identify patients with prediabetes.
Authors:
Thomas O’Byrne, Mayo Clinic
M. Regina Castro, Mayo Clinic
Che Ngufor, Mayo Clinic
Gyorgy Simon, University of Minnesota
Pedro Caraballo (Presenter)
Mayo Clinic
Presentation Materials: