1. Spirometry evaluation to assess performance of a claims-based predictive model identifying patients with undiagnosed COPD
- Author
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Moretz C, Annavarapu S, Luthra R, Goldfarb S, Renda A, Shaikh A, and Kaila S
- Subjects
COPD ,exacerbation ,predictive model ,clinical validation ,prevention ,Diseases of the respiratory system ,RC705-779 - Abstract
Chad Moretz,1 Srinivas Annavarapu,1 Rakesh Luthra,2 Seth Goldfarb,1 Andrew Renda,3 Asif Shaikh,2 Shuchita Kaila2 1Comprehensive Health Insights, Louisville, KY, USA; 2Boehringer Ingelheim, Ridgefield, CT, USA; 3Humana Inc., Louisville, KY, USA Background: A claims-based model to predict patients likely to have undiagnosed COPD was developed by Moretz et al in 2015. This study aims to assess the performance of the aforementioned model using prospectively collected spirometry data.Methods: A study population aged 40–89 years enrolled in a Medicare Advantage plan with prescription drug coverage or commercial health plan and without a claim for COPD diagnosis was identified from April 1, 2012 to March 31, 2016 in the Humana claims database. This population was stratified into subjects likely or unlikely to have undiagnosed COPD using the claims-based predictive model. Subjects were randomly selected for spirometry evaluation of FEV1 and FVC. The predictive model was validated using airflow limitation ratio (FEV1/FVC
- Published
- 2019