NIOSH Study Examines Machine Learning to Prevent Some Workplace Injuries

Workplace interventions can be helpful in reducing injuries while on the clock. According to the Bureau of Labor Statistics, low back strains, carpal tunnel syndrome, and other soft-tissue musculoskeletal injuries are the most frequent causes of missed workdays in the United States, and most result from ergonomic, slip, trip or fall hazards.

An effective approach is by applying ergonomics, according to National Institute for Occupational Safety and Health (NIOSH), which is the study of preventing musculoskeletal disorders through workplace design and policies.

In a recently published paper published by the Journal of Occupational and Environmental Medicine, NIOSH researchers described how they applied machine-learning to identify industries at high risk for these types of hazards.

According to the study’s lead author Alysha Meyers, Ph.D., NIOSH epidemiologist, researchers applied machine learning to identify the causes of work-related injuries using workers’ compensation records for approximately two thirds of Ohio workers.

More than 1.2 million Ohio Bureau of Workers’ Compensation claims were analyzed from 2001 to 2011 representing more than 200 industries. The researchers ranked claims for musculoskeletal injuries that could have been prevented with workplace interventions to prevent ergonomic-related injuries, or slips, trips, and falls.

“Machine learning uses algorithms to ‘teach’ a computer to perform a certain task,” Meyers explained. “For example, in our study we applied a mathematical machine-learning technique to quickly and accurately code workers’ compensation claims into one of three groups: 1) ergonomic; 2) slips, trips, and falls; and 3) other.”

The results provided researchers with information on the industries with the highest risk for these types of injuries.

Researchers found that workers in Ohio skilled nursing facilities had the highest risk for severe (more than 7 missed workdays) ergonomic-related claims, and workers in the freight trucking industry were found to be at the highest risk for severe slip, trip or fall claims, said Meyers.

Study results are already helping occupational safety and health specialists focus injury prevention efforts on high-risk occupations and industries, Meyers stated. “This activity is especially apparent in Ohio, where our study took place, but researchers in other states could use our study to develop similar approaches.”