Developing a Computable Phenotype for Identifying Children, Adolescents, and Young Adults With Diabetes Using Electronic Health Records in the DiCAYA Network

Abstract

OBJECTIVE The Diabetes in Children, Adolescents, and Young Adults (DiCAYA) network seeks to create a nationwide electronic health record (EHR)-based diabetes surveillance system.This study aimed to develop a DiCAYA-wide EHR-based computable phe notype (CP) to identify prevalent cases of diabetes. RESEARCH DESIGN AND METHODS We conducted network-wide chart reviews of 2,134 youth (aged 90%, except for the specificity and NPV in young adults, which were slightly lower at 83.8% and 80.6%, respectively. The final DiCAYA CP achieved >90% sensitivity, specificity,PPV, and NPV in classifying T1D, and demonstrated lower but robust performance in identify ing T2D, consistently maintaining >80% across metrics. CONCLUSIONS The DiCAYA CP effectively identifies overall diabetes and T1D in youth and young adults, though T2D misclassification in youth highlights areas for refinement. The simplicity of the DiCAYA CP enables broad deployment across diverse EHR systems for diabetes surveillance.