ArticleDiabetes care2020
Detection of Diabetes Status and Type in Youth Using Electronic Health Records: The SEARCH for Diabetes in Youth Study.
Article in Diabetes care, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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The trial behind it
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Who cites it
14 citing papers in PubMed.
- Using Electronic Health Records to Enhance Lyme Disease Surveillance: Protocol for the SubLyme Network.JMIR research protocols · 2026Article
- Trends in Youth-Onset Type 2 Diabetes, 2013-2024.The New England journal of medicine · 2026Article
- The intersection of place and health: examining the association of social determinants of health and diabetes in children and adolescents in Florida.BMC public health · 2026Article
- Machine learning models for predicting new-onset diabetes following acute pancreatitis using real-world data.BMJ public health · 2026Article
- Developing a Computable Phenotype for Identifying Children, Adolescents, and Young Adults With Diabetes Using Electronic Health Records in the DiCAYA Network.Diabetes care · 2025Article
- Examination of Prediabetes and Diabetes Testing Among US Pediatric Patients With Overweight or Obesity Using an Electronic Health Record.Childhood obesity (Print) · 2024Article
- Article
- Incidence of Diabetes Among Youth Before and During the COVID-19 Pandemic.JAMA network open · 2023Article
- Using Electronic Health Records for the Learning Health System: Creation of a Diabetes Research Registry.JMIR medical informatics · 2022Article
- Using an Electronic Health Record and Deficit Accumulation to Pragmatically Identify Candidates for Optimal Prescribing in Patients With Type 2 Diabetes.Diabetes spectrum : a publication of the American Diabetes Association · 2022Article
- Determining diagnosis date of diabetes using structured electronic health record (EHR) data: the SEARCH for diabetes in youth study.BMC medical research methodology · 2021Article
- Twenty years of pediatric diabetes surveillance: what do we know and why it matters.Annals of the New York Academy of Sciences · 2021Review
- Underlying Medical Conditions Associated With Severe COVID-19 Illness Among Children.JAMA network open · 2021Article
- Demographic and Metabolic Risk Factors Associated with Development of Diabetic Macular Edema among Persons with Diabetes Mellitus.Ophthalmology scienceArticle
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
objectiveDiabetes surveillance often requires manual medical chart reviews to confirm status and type. This project aimed to create an electronic health record (EHR)-based procedure for improving surveillance efficiency through automation of case identification. RESEARCH DESIGN AND
methodsYouth (<20 years old) with potential evidence of diabetes (
resultsThe sample included 5,308 true cases (89.2% type 1 diabetes). The rule-based algorithm outperformed regression for overall accuracy (0.955 vs. 0.936). Type 1 diabetes was classified well by both methods: sensitivity (
conclusionsAn ICD-10 algorithm combined with targeted chart reviews accurately identified diabetes status/type and could be an attractive option for diabetes surveillance in youth.
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