Literature DB >> 28192551

Effectiveness of Computer Automation for the Diagnosis and Management of Childhood Type 2 Diabetes: A Randomized Clinical Trial.

Tamara S Hannon1, Tamara M Dugan1, Chandan K Saha2, Steven J McKee1, Stephen M Downs1, Aaron E Carroll1.   

Abstract

Importance: 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. Objective: 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. Design, Setting, and Participants: 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. Interventions: Comparison of physician screening and follow-up practices after adding a T2D module to an existing computer decision support system. Main Outcomes and Measures: 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.
Results: 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). Conclusions and Relevance: 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. Trial Registration: clinicaltrials.gov Identifier: NCT01814787.

Entities:  

Mesh:

Year:  2017        PMID: 28192551      PMCID: PMC5972516          DOI: 10.1001/jamapediatrics.2016.4207

Source DB:  PubMed          Journal:  JAMA Pediatr        ISSN: 2168-6203            Impact factor:   16.193


  32 in total

Review 1.  The changing face of diabetes in youth: lessons learned from studies of type 2 diabetes.

Authors:  Tamara S Hannon; Silva A Arslanian
Journal:  Ann N Y Acad Sci       Date:  2015-10-08       Impact factor: 5.691

Review 2.  2. Classification and Diagnosis of Diabetes.

Authors: 
Journal:  Diabetes Care       Date:  2016-01       Impact factor: 19.112

3.  Diagnosis and classification of diabetes mellitus.

Authors: 
Journal:  Diabetes Care       Date:  2014-01       Impact factor: 19.112

4.  Use of a computerized decision aid for developmental surveillance and screening: a randomized clinical trial.

Authors:  Aaron E Carroll; Nerissa S Bauer; Tamara M Dugan; Vibha Anand; Chandan Saha; Stephen M Downs
Journal:  JAMA Pediatr       Date:  2014-09       Impact factor: 16.193

5.  Type 2 diabetes in children and adolescents. American Diabetes Association.

Authors: 
Journal:  Diabetes Care       Date:  2000-03       Impact factor: 19.112

6.  Child Health Improvement through Computer Automation: the CHICA system.

Authors:  Vibha Anand; Paul G Biondich; Gilbert Liu; Marc Rosenman; Stephen M Downs
Journal:  Stud Health Technol Inform       Date:  2004

7.  Pediatric decision support using adapted Arden Syntax.

Authors:  Vibha Anand; Aaron E Carroll; Paul G Biondich; Tamara M Dugan; Stephen M Downs
Journal:  Artif Intell Med       Date:  2015-10-01       Impact factor: 5.326

8.  Utility of hemoglobin A(1c) for diagnosing prediabetes and diabetes in obese children and adolescents.

Authors:  Paulina Nowicka; Nicola Santoro; Haibei Liu; Derek Lartaud; Melissa M Shaw; Rachel Goldberg; Cindy Guandalini; Mary Savoye; Paulina Rose; Sonia Caprio
Journal:  Diabetes Care       Date:  2011-04-22       Impact factor: 19.112

9.  Diabetes screening with hemoglobin A(1c) versus fasting plasma glucose in a multiethnic middle-school cohort.

Authors:  John B Buse; Francine R Kaufman; Barbara Linder; Kathryn Hirst; Laure El Ghormli; Steven Willi
Journal:  Diabetes Care       Date:  2012-11-27       Impact factor: 19.112

10.  The imperative to prevent diabetes.

Authors:  Robert E Ratner
Journal:  Diabetes Care       Date:  2012-12       Impact factor: 19.112

View more
  6 in total

1.  Clinician Perceptions of a Computerized Decision Support System for Pediatric Type 2 Diabetes Screening.

Authors:  Hala K El Mikati; Lisa Yazel-Smith; Randall W Grout; Stephen M Downs; Aaron E Carroll; Tamara S Hannon
Journal:  Appl Clin Inform       Date:  2020-05-13       Impact factor: 2.342

Review 2.  Harnessing Electronic Medical Records in Cardiovascular Clinical Practice and Research.

Authors:  Pishoy Gouda; Justin Ezekowitz
Journal:  J Cardiovasc Transl Res       Date:  2022-09-14       Impact factor: 3.216

3.  Improving Patient-Centered Communication about Sudden Unexpected Death in Epilepsy through Computerized Clinical Decision Support.

Authors:  Randall W Grout; Jeffrey Buchhalter; Anup D Patel; Amy Brin; Ann A Clark; Mary Holmay; Tyler J Story; Stephen M Downs
Journal:  Appl Clin Inform       Date:  2021-02-17       Impact factor: 2.342

4.  Assessment of Pediatrician Awareness and Implementation of the Addendum Guidelines for the Prevention of Peanut Allergy in the United States.

Authors:  Ruchi S Gupta; Lucy A Bilaver; Jacqueline L Johnson; Jack W Hu; Jialing Jiang; Alexandria Bozen; Jennifer Martin; Jamie Reese; Susan F Cooper; Matthew M Davis; Alkis Togias; Samuel J Arbes
Journal:  JAMA Netw Open       Date:  2020-07-01

5.  Effect of a Computer-Based Decision Support Intervention on Autism Spectrum Disorder Screening in Pediatric Primary Care Clinics: A Cluster Randomized Clinical Trial.

Authors:  Stephen M Downs; Nerissa S Bauer; Chandan Saha; Susan Ofner; Aaron E Carroll
Journal:  JAMA Netw Open       Date:  2019-12-02

6.  Sex-based differences in screening and recognition of pre-diabetes and type 2 diabetes in pediatric primary care.

Authors:  Mary Ellen Vajravelu; Joyce M Lee; Sandra Amaral; Andrea Kelly
Journal:  Pediatr Obes       Date:  2020-07-26       Impact factor: 4.000

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.