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. 2017 Jun;14(6):880-887.
doi: 10.1513/AnnalsATS.201610-764OC.

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

Brett Ley  1 , Thomas Urbania  2 , Gail Husson  3 , Eric Vittinghoff  4 , David R Brush  5 , Mark D Eisner  6 , Carlos Iribarren  3 , Harold R Collard  1
Affiliations

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

Brett Ley et al. Ann Am Thorac Soc. 2017 Jun.

Abstract

Rationale: Population-based studies of idiopathic pulmonary fibrosis (IPF) in the United States have been limited by reliance on diagnostic code-based algorithms that lack clinical validation.

Objectives: To validate a well-accepted International Classification of Diseases, Ninth Revision, code-based algorithm for IPF using patient-level information and to develop a modified algorithm for IPF with enhanced predictive value.

Methods: The traditional IPF algorithm was used to identify potential cases of IPF in the Kaiser Permanente Northern California adult population from 2000 to 2014. Incidence and prevalence were determined overall and by age, sex, and race/ethnicity. A validation subset of cases (n = 150) underwent expert medical record and chest computed tomography review. A modified IPF algorithm was then derived and validated to optimize positive predictive value.

Results: From 2000 to 2014, the traditional IPF algorithm identified 2,608 cases among 5,389,627 at-risk adults in the Kaiser Permanente Northern California population. Annual incidence was 6.8/100,000 person-years (95% confidence interval [CI], 6.1-7.7) and was higher in patients with older age, male sex, and white race. The positive predictive value of the IPF algorithm was only 42.2% (95% CI, 30.6 to 54.6%); sensitivity was 55.6% (95% CI, 21.2 to 86.3%). The corrected incidence was estimated at 5.6/100,000 person-years (95% CI, 2.6-10.3). A modified IPF algorithm had improved positive predictive value but reduced sensitivity compared with the traditional algorithm.

Conclusions: A well-accepted International Classification of Diseases, Ninth Revision, code-based IPF algorithm performs poorly, falsely classifying many non-IPF cases as IPF and missing a substantial proportion of IPF cases. A modification of the IPF algorithm may be useful for future population-based studies of IPF.

Keywords: idiopathic pulmonary fibrosis; incidence; prevalence.

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Figures

Figure 1.
Figure 1.
Flowchart of patient selection. ICD-9 = International Classification of Diseases, Ninth Revision; ICD-9-CM = International Classification of Diseases, Ninth Revision, Clinical Modification; IPF = idiopathic pulmonary fibrosis; KPNC = Kaiser Permanente Northern California.
Figure 2.
Figure 2.
Diagram demonstrating misclassification of cases by the idiopathic pulmonary fibrosis (IPF) algorithm compared with the modified IPF algorithm. PPV = positive predictive value.
See this image and copyright information in PMC

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