Use of administrative and electronic health record data for development of automated algorithms for childhood diabetes case ascertainment and type classification: The SEARCH for Diabetes in Youth Study

Pediatric Diabetes

Volumn 15, Issue 8, 2014, Pages 573-584

  Zhong, Victor W ^a   Pfaff, Emily R ^b   Beavers, Daniel P ^c   Thomas, Joan ^a   Jaacks, Lindsay M ^a   Bowlby, Deborah A ^d   Carey, Timothy S ^b   Lawrence, Jean M ^e   Dabelea, Dana ^f   Hamman, Richard F ^f   Pihoker, Catherine ^g   Saydah, Sharon H ^h   Mayer Davis, Elizabeth J ^a,i  

^a University of North Carolina   (United States)

^b UNIVERSITY OF NORTH CAROLINA   (United States)

^c WAKE FOREST SCHOOL OF MEDICINE   (United States)

^d MEDICAL UNIVERSITY OF SOUTH CAROLINA   (United States)

^e KAISER PERMANENTE   (United States)

^f Food Science and Human Nutrition   (United States)

^g UNIVERSITY OF WASHINGTON   (United States)

^h NATIONAL CENTER FOR CHRONIC DISEASE PREVENTION AND HEALTH PROMOTION   (United States)

ⁱ UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

Author keywords

Administrative data; Case ascertainment; Childhood diabetes; Electronic health record; Type classification

Indexed keywords

GLUCAGON; GLUCAGON LIKE PEPTIDE 1; INSULIN; METFORMIN; SULFONYLUREA;

ADOLESCENT; ADULT; ALGORITHM; ARTICLE; CHILD; CONTROLLED STUDY; DIABETIC KETOACIDOSIS; DISEASE CLASSIFICATION; ELECTRONIC MEDICAL RECORD; ETHNIC DIFFERENCE; FEMALE; HUMAN; INSULIN DEPENDENT DIABETES MELLITUS; LABORATORY TEST; MAJOR CLINICAL STUDY; MALE; MEDICAL RECORD REVIEW; NEWBORN; NON INSULIN DEPENDENT DIABETES MELLITUS; PREDICTIVE VALUE; PREVALENCE; PRIORITY JOURNAL; CLASSIFICATION; DIABETES MELLITUS, TYPE 1; DIABETES MELLITUS, TYPE 2; ELECTRONIC HEALTH RECORD; INFANT; MASS SCREENING; PRESCHOOL CHILD; PROCEDURES; STANDARDS; YOUNG ADULT;

ADOLESCENT; ADULT; ALGORITHMS; CHILD; CHILD, PRESCHOOL; DIABETES MELLITUS, TYPE 1; DIABETES MELLITUS, TYPE 2; ELECTRONIC HEALTH RECORDS; FEMALE; HUMANS; INFANT; INFANT, NEWBORN; MALE; MASS SCREENING; YOUNG ADULT;

EID: 84920285045     PISSN: 1399543X     EISSN: 13995448     Source Type: Journal    
DOI: 10.1111/pedi.12152     Document Type: Article

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