Open AccessEfficient Surveillance of Childhood Diabetes Using Electronic Health Record Data
Author(s) -
Victor W. Zhong,
Jihad S. Obeid,
Jean B. Craig,
Emily Pfaff,
Joan Thomas,
Lindsay M. Jaacks,
Daniel P. Beavers,
Timothy S. Carey,
Jean M. Lawrence,
Dana Dabelea,
Richard F. Hamman,
Deborah Bowlby,
Catherine Pihoker,
Sharon Saydah,
Elizabeth J. MayerDavis
Publication year - 2016
Publication title -
online journal of public health informatics
Language(s) - English
Resource type - Journals
ISSN - 1947-2579
DOI - 10.5210/ojphi.v8i1.6459
Subject(s) - medicine , diabetes mellitus , electronic surveillance , electronic health record , health records , medical emergency , data science , data mining , pediatrics , computer science , health care , internet privacy , economic growth , economics , endocrinology
We aimed to develop an efficient surveillance approach for childhood diabetes. We analyzed EHR data from two independent US academic health care systems. Presumptive diabetes cases were identified as those having >1 of the five diabetes indicators in the past 3.5 years. EHRs of the presumptive cases were manually reviewed. We developed a stepwise surveillance approach using billing codes-based pre-specified algorithms and targeted manual EHRs review. The sensitivity and positive predictive value in both systems were approximately >90%. This stepwise surveillance approach resulted in a >70% reduction in the number of cases requiring manual validation compared to traditional surveillance methods.
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