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Code-based Diagnostic Algorithms for Idiopathic Pulmonary Fibrosis. Case Validation and Improvement.

Brett Ley1, Thomas Urbania2, Gail Husson3

  • 11 Department of Medicine and.

Annals of the American Thoracic Society
|March 30, 2017
PubMed
Summary

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This summary is machine-generated.

The standard algorithm for identifying idiopathic pulmonary fibrosis (IPF) has low accuracy, misdiagnosing many patients. A modified algorithm shows potential for more reliable population studies of IPF.

Area of Science:

  • Pulmonary Medicine
  • Epidemiology
  • Health Informatics

Background:

  • Population-based studies of idiopathic pulmonary fibrosis (IPF) in the US often use diagnostic code-based algorithms lacking clinical validation.
  • This limits the accuracy of epidemiological data for IPF.

Purpose of the Study:

  • To validate a widely used International Classification of Diseases, Ninth Revision (ICD-9) code-based algorithm for IPF.
  • To develop and validate a modified IPF algorithm with improved predictive value for future research.

Main Methods:

  • The traditional IPF algorithm was applied to identify potential IPF cases in Kaiser Permanente Northern California (2000-2014).
  • A subset of 150 cases underwent expert review of medical records and chest CT scans.
  • A modified algorithm was derived and validated to enhance positive predictive value.
Keywords:
idiopathic pulmonary fibrosisincidenceprevalence

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Main Results:

  • The traditional algorithm identified 2,608 potential IPF cases, but its positive predictive value was only 42.2%.
  • Incidence was estimated at 6.8 per 100,000 person-years, higher in older, male, and white populations.
  • A modified algorithm improved positive predictive value but decreased sensitivity.

Conclusions:

  • The traditional ICD-9 code-based IPF algorithm demonstrates poor performance, leading to misclassification of many non-IPF and missed IPF cases.
  • A modified IPF algorithm may offer a more accurate approach for future population-based IPF studies.