title: Effectiveness of Computer Automation for the Diagnosis and Management of Childhood Type 2 Diabetes: A Randomized Clinical Trial.
abstract: Type 2 diabetes (T2D) is increasingly common in young individuals. Primary prevention and screening among children and adolescents who are at substantial risk for T2D are recommended, but implementation of T2D screening practices in the pediatric primary care setting is uncommon.
  
  
  
  To determine the feasibility and effectiveness of a computerized clinical decision support system to identify pediatric patients at high risk for T2D and to coordinate screening for and diagnosis of prediabetes and T2D.
  
  
  
  This cluster-randomized clinical trial included patients from 4 primary care pediatric clinics. Two clinics were randomized to the computerized clinical decision support intervention, aimed at physicians, and 2 were randomized to the control condition. Patients of interest included children, adolescents, and young adults 10 years or older. Data were collected from January 1, 2013, through December 1, 2016.
  
  
  
  Comparison of physician screening and follow-up practices after adding a T2D module to an existing computer decision support system.
  
  
  
  Electronic medical record (EMR) data from patients 10 years or older were reviewed to determine the rates at which pediatric patients were identified as having a body mass index (BMI) at or above the 85th percentile and 2 or more risk factors for T2D and underwent screening for T2D.
  
  
  
  Medical records were reviewed for 1369 eligible children (712 boys [52.0%] and 657 girls [48.0%]; median [interquartile range] age, 12.9 [11.2-15.3]), of whom 684 were randomized to the control group and 685 to the intervention group. Of these, 663 (48.4%) had a BMI at or above the 85th percentile. Five hundred sixty-five patients (41.3%) met T2D screening criteria, with no difference between control and intervention sites. The T2D module led to a significant increase in the percentage of patients undergoing screening for T2D (89 of 283 [31.4%] vs 26 of 282 [9.2%]; adjusted odds ratio, 4.6; 95% CI, 1.5-14.7) and a greater proportion attending a scheduled follow-up appointment (45 of 153 [29.4%] vs 38 of 201 [18.9%]; adjusted odds ratio, 1.8; 95% CI, 1.5-2.2).
  
  
  
  Use of a computerized clinical decision support system to automate the identification and screening of pediatric patients at high risk for T2D can help overcome barriers to the screening process. The support system significantly increased screening among patients who met the American Diabetes Association criteria and adherence to follow-up appointments with primary care clinicians.
  
  
  
  clinicaltrials.gov Identifier: NCT01814787.
authors.affiliation: Indiana Children's Health Services Research, Department of Pediatrics, Indiana University School of Medicine, Indianapolis.
authors.forename: Tamara S
authors.initials: TS
authors.lastname: Hannon
authors.affiliation: Indiana Children's Health Services Research, Department of Pediatrics, Indiana University School of Medicine, Indianapolis.
authors.forename: Tamara M
authors.initials: TM
authors.lastname: Dugan
authors.affiliation: Department of Biostatistics, Indiana University School of Medicine, Indianapolis.
authors.forename: Chandan K
authors.initials: CK
authors.lastname: Saha
authors.affiliation: Indiana Children's Health Services Research, Department of Pediatrics, Indiana University School of Medicine, Indianapolis.
authors.forename: Steven J
authors.initials: SJ
authors.lastname: McKee
authors.affiliation: Indiana Children's Health Services Research, Department of Pediatrics, Indiana University School of Medicine, Indianapolis.
authors.forename: Stephen M
authors.initials: SM
authors.lastname: Downs
authors.affiliation: Indiana Children's Health Services Research, Department of Pediatrics, Indiana University School of Medicine, Indianapolis.
authors.forename: Aaron E
authors.initials: AE
authors.lastname: Carroll
mesh_terms: D000293:Adolescent; D000328:Adult; D001331:Automation; D002648:Child; D003201:Computers; D020000:Decision Support Systems, Clinical; D003924:Diabetes Mellitus, Type 2 / Q000175:diagnosis*; D057286:Electronic Health Records; D005260:Female; D006801:Humans; D008297:Male; D008403:Mass Screening / Q000379:methods*; D011320:Primary Health Care; D012307:Risk Factors; D055815:Young Adult