A Proposed Algorithm for the Identification of Occupational COPD in a Cohort of Washington Workers
type: CreativeWork
description: Rationale: Approximately 31% of Chronic Obstructive Pulmonary Disease (COPD) is caused by vapor, gas, dust and fumes (VGDF). In collaboration with the Washington State Department of Labor and Industries Safety and Health Assessment and Research for Prevention Program, we report a new algorithm for surveillance of Occupational COPD. Methods: Cases were captured from workers’ compensation claims filed in Washington state between 2010-2020 using keywords, diagnosis codes (ICD), and occupational injury and illness codes. COPD was confirmed using post-bronchodilator forced-expiratory-volume-over-1-second/forced-vital-capacity (FEV1/FVC) <0.7 or alternate criteria if spirometry was unavailable. Confirmed claims were evaluated for smoking history, then VGDF exposure was determined using a COPD-specific Job Exposure Matrix based on occupation code. Results: Of 1,241 initially captured claims, 339 (27.3%) were included in the final analysis. Of these, 94 (27.7%) qualified for Occupational COPD (53 Probable, 3 Possible and 38 Work-Aggravated (WA COPD)) while 240 (70.9%) claims were Not Valid, including 53 with asthma, and 109 with acute bronchitis. Fifteen total cases that qualified for Occupational COPD were never or <10 pack year smokers, including 13 in the Probable group and 2 in the Work-Aggravated group. Occupations with expected exposure to medium or high VGDF included construction workers, firefighters, truck drivers and welders, among others, and there was overlap in occupations and hazards between Occupational COPD groups. Conclusions: This comprehensive algorithm provides a framework for Occupational COPD surveillance and diagnosis and could be used to influence resource allocation to improve safety and health in high risk occupations.
abstract: Rationale: Approximately 31% of Chronic Obstructive Pulmonary Disease (COPD) is caused by vapor, gas, dust and fumes (VGDF). In collaboration with the Washington State Department of Labor and Industries Safety and Health Assessment and Research for Prevention Program, we report a new algorithm for surveillance of Occupational COPD. Methods: Cases were captured from workers’ compensation claims filed in Washington state between 2010-2020 using keywords, diagnosis codes (ICD), and occupational injury and illness codes. COPD was confirmed using post-bronchodilator forced-expiratory-volume-over-1-second/forced-vital-capacity (FEV1/FVC) <0.7 or alternate criteria if spirometry was unavailable. Confirmed claims were evaluated for smoking history, then VGDF exposure was determined using a COPD-specific Job Exposure Matrix based on occupation code. Results: Of 1,241 initially captured claims, 339 (27.3%) were included in the final analysis. Of these, 94 (27.7%) qualified for Occupational COPD (53 Probable, 3 Possible and 38 Work-Aggravated (WA COPD)) while 240 (70.9%) claims were Not Valid, including 53 with asthma, and 109 with acute bronchitis. Fifteen total cases that qualified for Occupational COPD were never or <10 pack year smokers, including 13 in the Probable group and 2 in the Work-Aggravated group. Occupations with expected exposure to medium or high VGDF included construction workers, firefighters, truck drivers and welders, among others, and there was overlap in occupations and hazards between Occupational COPD groups. Conclusions: This comprehensive algorithm provides a framework for Occupational COPD surveillance and diagnosis and could be used to influence resource allocation to improve safety and health in high risk occupations.
author: Ronish, Bonnie E.
language: en_US
keywords: Chronic Obstructive Pulmonary Disease (COPD), exposure, occupation, Occupational COPD, vapor gas dust fumes (VGDF), worker(s) compensation, Medicine, Environmental health, Public health
date published: 2022-07-14
date modified: 2026-07-24T05:58:25Z
provider: University of Washington
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Washington

PropertyValue
property ID: Handle
value: http://hdl.handle.net/1773/48971