A systematic review of validated methods for identifying pulmonary fibrosis and interstitial lung disease using administrative and claims data

• Published in: Pharmacoepidemiology and drug safety Vol. 21; no. S1; pp. 256 - 260
• Main Authors: Jones, Natalie, Schneider, Gary, Kachroo, Sumesh, Rotella, Philip, Avetisyan, Ruzan, Reynolds, Matthew W.
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 01.01.2012
• Subjects: administrative and claims data; Algorithms; coding algorithm; Databases, Factual - statistics & numerical data; Humans; Insurance Claim Review; interstitial lung disease; Lung Diseases, Interstitial - diagnosis; Lung Diseases, Interstitial - epidemiology; Mini-Sentinel; Outcome Assessment (Health Care) - methods; Pilot Projects; Predictive Value of Tests; pulmonary fibrosis; Pulmonary Fibrosis - diagnosis; Pulmonary Fibrosis - epidemiology; Sensitivity and Specificity; United States - epidemiology; United States Food and Drug Administration; United States
• ISSN: 1053-8569; 1099-1557
• DOI: 10.1002/pds.2338

ABSTRACT Purpose The Food and Drug Administration's Mini‐Sentinel pilot program initially aimed to conduct active surveillance to refine safety signals that emerge for marketed medical products. A key facet of this surveillance is to develop and understand the validity of algorithms for identifying health outcomes of interest (HOIs) from administrative and claims data. This paper summarizes the process and findings of the algorithm review of pulmonary fibrosis and interstitial lung disease. Methods PubMed and Iowa Drug Information Service Web searches were conducted to identify citations applicable to the pulmonary fibrosis/interstitial lung disease HOI. Level 1 reviews and Level 2 full‐text reviews were conducted to find articles using administrative and claims data to identify pulmonary fibrosis and interstitial lung disease, including validation estimates of the coding algorithms. Results Our search revealed a deficiency of literature focusing on pulmonary fibrosis and interstitial lung disease algorithms and validation estimates. Only five studies provided codes; none provided validation estimates. Because interstitial lung disease includes a broad spectrum of diseases, including pulmonary fibrosis, the scope of these studies varied, as did the corresponding diagnostic codes used. Conclusions Research needs to be conducted on designing validation studies to test pulmonary fibrosis and interstitial lung disease algorithms and estimating their predictive power, sensitivity, and specificity. Copyright © 2012 John Wiley & Sons, Ltd.