Developing an automated algorithm for identification of children and adolescents with diabetes using electronic health records from the OneFlorida+ clinical research network

Aim To develop an automated computable phenotype (CP) algorithm for identifying diabetes cases in children and adolescents using electronic health records (EHRs) from the UF Health System. Materials and Methods The CP algorithm was iteratively derived based on structured data from EHRs (UF Health Sy...

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Veröffentlicht in:	Diabetes, obesity & metabolism obesity & metabolism, 2025-01, Vol.27 (1), p.102-110
Hauptverfasser:	Li, Piaopiao, Spector, Eliot, Alkhuzam, Khalid, Patel, Rahul, Donahoo, William T., Bost, Sarah, Lyu, Tianchen, Wu, Yonghui, Hogan, William, Prosperi, Mattia, Dixon, Brian E., Dabelea, Dana, Utidjian, Levon H., Crume, Tessa L., Thorpe, Lorna, Liese, Angela D., Schatz, Desmond A., Atkinson, Mark A., Haller, Michael J., Shenkman, Elizabeth A., Guo, Yi, Bian, Jiang, Shao, Hui
Format:	Artikel
Sprache:	eng
Schlagworte:	Adolescent Adolescents Algorithms Automation Blood Glucose - analysis Child Child, Preschool database research Diabetes Diabetes mellitus (insulin dependent) Diabetes mellitus (non-insulin dependent) Diabetes Mellitus, Type 1 - blood Diabetes Mellitus, Type 1 - diagnosis Diabetes Mellitus, Type 2 - blood Diabetes Mellitus, Type 2 - diagnosis Diagnosis Electronic Health Records Electronic medical records Female Glycated Hemoglobin - analysis Hemoglobin Humans Infant Male Phenotype Phenotypes real‐world evidence type 1 diabetes type 2 diabetes
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Zusammenfassung:	Aim To develop an automated computable phenotype (CP) algorithm for identifying diabetes cases in children and adolescents using electronic health records (EHRs) from the UF Health System. Materials and Methods The CP algorithm was iteratively derived based on structured data from EHRs (UF Health System 2012–2020). We randomly selected 536 presumed cases among individuals aged
ISSN:	1462-8902 1463-1326 1463-1326
DOI:	10.1111/dom.15987