Clinical Epidemiology (Jun 2022)

Identifying Pediatric Diabetes Cases from Health Administrative Data: A Population-Based Validation Study in Quebec, Canada [Corrigendum]

  • Nakhla M,
  • Simard M,
  • Dube M,
  • Larocque I,
  • Plante C,
  • Legault L,
  • Huot C,
  • Gagné N,
  • Gagné J,
  • Wafa S,
  • Benchimol EI,
  • Rahme E

Journal volume & issue
Vol. Volume 14
pp. 767 – 768

Abstract

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Nakhla M, Simard M, Dube M, et al. Clin Epidemiol. 2019;11:833–843. The authors have advised there is an error in the diagnostic codes used to validate the cases of diabetes. The code “251.X” was never included in the validation algorithm and was erroneously included in the list of ICD-9 codes in the final revision phase of the manuscript. The authors apologize for this error. Page 835, Diagnostic accuracy section, second sentence, the text “We determined the diagnostic accuracy (sensitivity, specificity, PPV, NPV) of a variety of algorithms, using combinations of physician billings and hospital admissions over 1 or 2 years bearing a diagnosis code of diabetes mellitus (ICD-9 250.X, 251.X; ICD-10 E10.X-14. X)” should read “We determined the diagnostic accuracy (sensitivity, specificity, PPV, NPV) of a variety of algorithms, using combinations of physician billings and hospital admissions over 1 or 2 years bearing a diagnosis code of diabetes mellitus (ICD-9 250.X; ICD-10 E10.X-14. X)”. Read the original article

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