The Assessing the Burden of Diabetes by Type in Children, Adolescents, and Young Adults (DiCAYA) Network, a CDC/NIDDK-funded collaborative, aims to create a multi-site electronic health record (EHR) -based diabetes surveillance system. Foundational to the network's efforts is the development of a computable phenotype (CP) algorithm that can identify cases of diabetes. To advance the mission of the DiCAYA network, University of Florida (UF) Health system researchers developed a pilot CP algorithm for identifying diabetes cases in youth. The CP algorithm was iteratively derived based on structured data from EHRs (UF Health system 2012-2020) . We randomly selected 500 presumed cases among individuals < 18 years old who has
(1) HbA1c ≥ 6.5%; or
(2) fasting glucose ≥ 126 mg/dL; or
(3) random plasma glucose ≥ 200 mg/dL; or
(4) diabetes-related diagnosis code from an inpatient or outpatient encounter; or
(5) prescribed, administered, or dispensed diabetes-related medication. Four reviewers independently reviewed the patient charts to determine diabetes status and type.
P.Li: None. M.Prosperi: None. B.E.Dixon: Advisory Panel; Merck Sharp & Dohme Corp. D.Dabelea: None. L.H.Utidjian: None. T.L.Crume: None. L.Thorpe: None. A.D.Liese: None. D.Schatz: Advisory Panel; Abbott Diabetes, Medtronic. M.A.Atkinson: None. M.J.Haller: Advisory Panel; SAB Biotherapeutics , Consultant; MannKind Corporation, Sanofi. E.Spector: None. E.Shenkman: None. J.Bian: None. Y.Guo: None. H.Shao: Board Member; BRAVO4HEALTH, LLC. M.A.Atkinson: None. K.Alkhuzam: None. R.S.Patel: None. W.T.Donahoo: None. S.Bost: None. T.Lyu: None. Y.Wu: None. W.Hogan: None.