ArticlePediatric diabetes2014
Use of administrative and electronic health record data for development of automated algorithms for childhood diabetes case ascertainment and type classification: the SEARCH for Diabetes in Youth Study.
Article in Pediatric diabetes, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed.
- Identifying diabetic ketoacidosis encounters at diagnosis among children with type 1 diabetes in claims data.Journal of the Endocrine Society · 2026Article
- Unplanned hospitalization among advanced prostate cancer patients by diabetes status: a population-based study.JNCI cancer spectrum · 2025Article
- Youth-Onset Type 2 Diabetes: What We've Learned From Key Youth-Onset Type 2 Diabetes Studies, What We Still Don't Know, and Why It Is Important.Diabetes care · 2025Review
- Developing a Computable Phenotype for Identifying Children, Adolescents, and Young Adults With Diabetes Using Electronic Health Records in the DiCAYA Network.Diabetes care · 2025Article
- Developing an automated algorithm for identification of children and adolescents with diabetes using electronic health records from the OneFlorida+ clinical research network.Diabetes, obesity & metabolism · 2025Article
- Community profiles in northeastern and central Pennsylvania characterized by distinct social, natural, food, and physical activity environments and their relation to type 2 diabetes.Environmental epidemiology (Philadelphia, Pa.) · 2024Article
- Receipt of Diabetes Specialty Care and Management Services by Older Adults With Diabetes in the U.S., 2015-2019: An Analysis of Medicare Fee-for-Service Claims.Diabetes care · 2024Article
- Access to Specialty Care for Commercially Insured Youths With Type 1 and Type 2 Diabetes.JAMA network open · 2024Article
- The role of health system penetration rate in estimating the prevalence of type 1 diabetes in children and adolescents using electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Medical Costs Associated With Diabetes Complications in Medicare Beneficiaries Aged 65 Years or Older With Type 1 Diabetes.Diabetes care · 2023Article
- Incidence Trends of New-Onset Diabetes in Children and Adolescents Before and During the COVID-19 Pandemic: Findings From Florida.Diabetes · 2022Observational
- Medical Costs Associated With Diabetes Complications in Medicare Beneficiaries Aged 65 Years or Older With Type 2 Diabetes.Diabetes care · 2022Article
- The effects of patient out-of-pocket costs for insulin on medication adherence and health care utilization in patients with commercial insurance; 2007-2018.Journal of managed care & specialty pharmacy · 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
- Real-world treatment escalation from metformin monotherapy in youth-onset Type 2 diabetes mellitus: A retrospective cohort study.Pediatric diabetes · 2021Article
- Intensive Care Unit Admission, Mechanical Ventilation, and Mortality Among Patients With Type 1 Diabetes Hospitalized for COVID-19 in the U.S.Diabetes care · 2021Article
- Twenty years of pediatric diabetes surveillance: what do we know and why it matters.Annals of the New York Academy of Sciences · 2021Review
- Electronic Medical Record-Based Case Phenotyping for the Charlson Conditions: Scoping Review.JMIR medical informatics · 2021Article
- Article
- The accuracy of provider diagnosed diabetes type in youth compared to an etiologic criteria in the SEARCH for Diabetes in Youth Study.Pediatric diabetes · 2020Article
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
backgroundThe performance of automated algorithms for childhood diabetes case ascertainment and type classification may differ by demographic characteristics.
objectiveThis study evaluated the potential of administrative and electronic health record (EHR) data from a large academic care delivery system to conduct diabetes case ascertainment in youth according to type, age, and race/ethnicity. SUBJECTS: Of 57 767 children aged <20 yr as of 31 December 2011 seen at University of North Carolina Health Care System in 2011 were included.
methodsUsing an initial algorithm including billing data, patient problem lists, laboratory test results, and diabetes related medications between 1 July 2008 and 31 December 2011, presumptive cases were identified and validated by chart review. More refined algorithms were evaluated by type (type 1 vs. type 2), age (<10 vs. ≥10 yr) and race/ethnicity (non-Hispanic White vs. 'other'). Sensitivity, specificity, and positive predictive value were calculated and compared.
resultsThe best algorithm for ascertainment of overall diabetes cases was billing data. The best type 1 algorithm was the ratio of the number of type 1 billing codes to the sum of type 1 and type 2 billing codes ≥0.5. A useful algorithm to ascertain youth with type 2 diabetes with 'other' race/ethnicity was identified. Considerable age and racial/ethnic differences were present in type-non-specific and type 2 algorithms.
conclusionsAdministrative and EHR data may be used to identify cases of childhood diabetes (any type), and to identify type 1 cases. The performance of type 2 case ascertainment algorithms differed substantially by race/ethnicity.
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