Developing a Computable Phenotype for Identifying Children, Adolescents, and Young Adults With Diabetes Using Electronic Health Records in the Diabetes in Children, Adolescents, and Young Adults (DiCAYA) Network
Authors' conclusion
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.
Study context
- Population
- Youth (aged <18 years) and young adults (aged 18 to <45 years) with possible diabetes, DiCAYA network
- Comparison
- Three alternative computable phenotypes (computable phenotype (CPs)) vs chart-review diabetes diagnosis
- Outcome
- Accuracy of CPs in identifying diabetes and its subtype
Methodological detailsnetwork-wide chart review, electronic health record (EHR)-based computable phenotype, chart review as gold standard, Chart reviews of 2,134 youth and 2,466 young adults
- Network-wide chart review
- EHR-based computable phenotype
- Chart review as gold standard
- Chart reviews of 2,134 youth and 2,466 young adults
Performance
As reported in the abstract
Identifying diabetes cases
Sensitivity, specificity, PPV and NPV in youth and young adults
>90%
Specificity in young adults
83.8%
NPV in young adults
80.6%
Further findings
Classifying T1D
- Sensitivity, specificity, PPV and NPV
- >90%
Identifying T2D
- Lower but robust performance; all metrics
- >80%
Original publication
Developing a Computable Phenotype for Identifying Children, Adolescents, and Young Adults With Diabetes Using Electronic Health Records in the DiCAYA Network. Diabetes Care. Published 31 March 2025. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →