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Using electronic health records to enhance surveillance of diabetes in children, adolescents and young adults: a study protocol for the DiCAYA Network

Authors :
Hui Zhou
Manmohan Kamboj
Yi Guo
Angela D Liese
Rebecca Anthopolos
Lu Zhang
John Chang
Anna Roberts
Tessa Crume
Brian E Dixon
Hui Shao
David C Lee
Lorna E Thorpe
Dimitri Christakis
Eneida A Mendonca
Katie Allen
Dana Dabelea
Giuseppina Imperatore
Mark Weiner
Meredith Akerman
Rong Wei
Kristi Reynolds
Annemarie G Hirsch
Jasmin Divers
Tianchen Lyu
Alex Ewing
Shaun Grannis
Yuan Luo
Bo Cai
Anthony Wong
Brian S Schwartz
Meda Pavkov
Meredith Lewis
Sarah Conderino
Jiang Bian
Yonghui Wu
Jihad S Obeid
Harold P Lehmann
Charles Bailey
Theresa Anderson
Elizabeth A Shenkman
Elizabeth Nauman
Christopher Forrest
Mattia Prosperi
Seho Park
Cara M Nordberg
Tessa L Crume
Anna Bellatorre
Stefanie Bendik
Marc Rosenman
Levon Utidjian
Mitch Maltenfort
Amy Shah
G Todd Alonso
Sara Deakyne-Davies
Tim Bunnell
Anne Kazak
Melody Kitzmiller
Daksha Ranade
Joseph J DeWalle
H Lester Kirchner
Dione G Mercer
Amy Poissant
Nimish Valvi
Jeff Warvel
Ashley Wiensch
Tamara Hannon
Eva Lustigova
Don McCarthy
Matthew T Mefford
George Lales
Allison Zelinski
Pedro Rivera
Thomas Carton
Victor W Zhong
Andrew Fair
Jessica Guillaume
Shahidul Islam
Alan Jacobson
Chinyere Okpara
Anand Rajan
Andrea Titus
Rebecca Conway
Toan Ong
Jack Pattee
Shawna Burgett
Bethlehem Shiferaw
Sarah J Bost
William T Donahoo
William R Hogan
Piaopiao Li
Lisa Knight
Caroline Rudisill
Jessica Stucker
Deborah Bowlby
Elaine Apperson
Deborah B Rolka
Source :
BMJ Open, Vol 14, Iss 1 (2024)
Publication Year :
2024
Publisher :
BMJ Publishing Group, 2024.

Abstract

Introduction Traditional survey-based surveillance is costly, limited in its ability to distinguish diabetes types and time-consuming, resulting in reporting delays. The Diabetes in Children, Adolescents and Young Adults (DiCAYA) Network seeks to advance diabetes surveillance efforts in youth and young adults through the use of large-volume electronic health record (EHR) data. The network has two primary aims, namely: (1) to refine and validate EHR-based computable phenotype algorithms for accurate identification of type 1 and type 2 diabetes among youth and young adults and (2) to estimate the incidence and prevalence of type 1 and type 2 diabetes among youth and young adults and trends therein. The network aims to augment diabetes surveillance capacity in the USA and assess performance of EHR-based surveillance. This paper describes the DiCAYA Network and how these aims will be achieved.Methods and analysis The DiCAYA Network is spread across eight geographically diverse US-based centres and a coordinating centre. Three centres conduct diabetes surveillance in youth aged 0–17 years only (component A), three centres conduct surveillance in young adults aged 18–44 years only (component B) and two centres conduct surveillance in components A and B. The network will assess the validity of computable phenotype definitions to determine diabetes status and type based on sensitivity, specificity, positive predictive value and negative predictive value of the phenotypes against the gold standard of manually abstracted medical charts. Prevalence and incidence rates will be presented as unadjusted estimates and as race/ethnicity, sex and age-adjusted estimates using Poisson regression.Ethics and dissemination The DiCAYA Network is well positioned to advance diabetes surveillance methods. The network will disseminate EHR-based surveillance methodology that can be broadly adopted and will report diabetes prevalence and incidence for key demographic subgroups of youth and young adults in a large set of regions across the USA.

Subjects

Subjects :
Medicine

Details

Language :
English
ISSN :
20230737 and 20446055
Volume :
14
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMJ Open
Publication Type :
Academic Journal
Accession number :
edsdoj.8ca915a32dcd4ffdbd2dee2faf1c3e56
Document Type :
article
Full Text :
https://doi.org/10.1136/bmjopen-2023-073791