At a glance
The NIOSH Coal Workers’ Health Surveillance Program (CWHSP) studies respiratory disease in miners. The program provides health information to miners through health screenings and surveillance.
Overview
The CWHSP was established by the . Its mission is to detect lung disease in coal miners. The CWHSP offers health screenings for miners and allows researchers to identify disease trends across the nation.
Black lung screenings
The CWHSP provides black lung screenings to coal miners at no cost to miners. Screenings are available when miners begin working in coal mines and periodically after. For more information, go to the Black Lung Screenings page.
B Reader Program
The NIOSH B Reader Program trains and certifies physicians in the International Labour Organization, . U.S. regulations specify roles for B Readers in classifying chest x-rays of workers exposed to:
- Coal mine dust
- Crystalline silica
- Asbestos
B Readers also perform classifications in a range of other settings. These include research, legal, and evaluation for benefits.
Special notice to coal miners
Part 90
The Mine Safety and Health Administration announced an effort to raise awareness of . These regulations give coal miners with black lung the right to work in areas with lower dust. Learn more at .
National autopsy study
The Mine Safety and Health Act of 1977 authorizes the U.S. Department of Health and Human Services to provide coal miner autopsies and to pay for their submission to NIOSH. Refer to for more information.
At this time, funding is not available to pay for autopsies.
Data-use agreement
Michigan State University (MSU) researchers are developing artificial intelligence models to classify digital chest x-rays for pneumoconiosis. To assist, NIOSH has entered a data-use agreement allowing MSU to use anonymous digital chest x-rays from CWHSP.
Names and identifying information have been removed from the chest x-rays. The agreement does not allow MSU to share or use the x-rays for purposes other than this research. We hope using artificial intelligence to classify chest x-rays will help physicians perform accurate classifications using the .