ArticleDiabetes care2025
Developing a Computable Phenotype for Identifying Children, Adolescents, and Young Adults With Diabetes Using Electronic Health Records in the DiCAYA Network.
Article in Diabetes care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Findings From Electronic Medical Record Review of 2500 Patients Identified With Lyme Disease Diagnoses, Test Orders, and Antibiotic Orders in the SubLyme Network.Open forum infectious diseases · 2026Article
- Using Electronic Health Records to Enhance Lyme Disease Surveillance: Protocol for the SubLyme Network.JMIR research protocols · 2026Article
- GLP-1 receptor agonists and acute diabetes complications in adults with type 1 diabetes.iScience · 2026Article
- The intersection of place and health: examining the association of social determinants of health and diabetes in children and adolescents in Florida.BMC public health · 2026Article
- Retrospective cohort study applying membership and utilisation criteria to electronic health records for diabetes incidence estimation in an integrated healthcare delivery system in Southern California.BMJ public health · 2026Article
- GLP-1 Receptor Agonists and Acute Diabetes Complications in Adults with Type 1 Diabetes: A Target Trial Emulation.medRxiv : the preprint server for health sciences · 2025Article
- Equivalence of Type 2 Diabetes Prevalence Estimates: Comparative Study of Similar Phenotyping Algorithms Using Electronic Health Record Data.JMIR public health and surveillance · 2025Article
- Prescribing Trends of Glucagon-Like Peptide 1 Receptor Agonists for Type 2 Diabetes or Obesity.JAMA network open · 2025Article
- Article
- Trends in Sodium-Glucose Cotransporter 2 Inhibitor and Glucagon‑Like Peptide‑1 Receptor Agonist Prescription Rates Among Patients With Type 2 Diabetes: An Epic Cosmos Real-World Data Analysis, 2014-2024.AACE endocrinology and diabetesArticle
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Authors and funding
37 authors.
Funding
Abstract
objectiveThe 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 phenotype (CP) to identify prevalent cases of diabetes. RESEARCH DESIGN AND
methodsWe conducted network-wide chart reviews of 2,134 youth (aged <18 years) and 2,466 young adults (aged 18 to <45 years) among people with possible diabetes. Within this population, we compared the performance of three alternative CPs, using diabetes diagnoses determined by chart review as the gold standard. CPs were evaluated based on their accuracy in identifying diabetes and its subtype.
resultsThe final DiCAYA CP requires at least one diabetes diagnosis code from clinical encounters. Subsequently, diabetes type classification was based on the ratio of type 1 diabetes (T1D) or type 2 diabetes (T2D) diagnosis codes in the EHR. For both youth and young adults, the sensitivity, specificity, and positive and negative predictive values (PPV and NPV, respectively) in finding diabetes cases were >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 identifying T2D, consistently maintaining >80% across metrics.
conclusionsThe 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.
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