How do you prevent MSK injuries? Use AI, says expert

Expert explains how employers can use AI data to avoid injuries, instead of dealing with them after the fact

How do you prevent MSK injuries? Use AI, says expert

Musculoskeletal (MSK) injuries are a costly problem – and using artificial intelligence (AI) to prevent them will give employers a big boost, according to an expert.

“In North America, it's about a $460-billion problem,” says Reed Hanoun, founder and CEO of 3motionAI, in talking with Canadian HR Reporter.

Having access to data could help employers prevent such injuries, he says.

“The most important thing any employer should do is to get an assessment or a view of their MSK exposure within their employee population. Without having that macro view of risk at the enterprise level, it's going to be very difficult for the employer to intervene and avoid injuries from happening.”

Work-related repetitive stress injuries (RSI) are the most widespread occupational health hazard facing North America, according to a previous report. Nearly two million workers suffer work-related musculoskeletal disorders (MSDs) every year, and about 600,000 lose time from work as a result, according to the report.

In 2022, the federal government claimed that over 10,000 accepted lost-time injuries due to musculoskeletal and connective tissue injuries were reported in 2019, citing data from the Association of Workers' Compensation Boards of Canada (AWCBC).

How do employers deal with MSK injuries?

The problem is that often employers deal with MSDs “after the fact,” says Hanoun.

“Conventionally, that's how the problem is addressed – when an injury occurs,” he says. “It tends to be very reactive.”

MSK injuries and repetitive strain injuries (RSI) account for more than 40% of all lost-time injuries allowed by Ontario’s Workplace Safety and Insurance Board (WSIB), according to the Ontario Nurses’ Association.

How can AI help with MSK injuries?

Using the powers of AI, employers can get the data that they need and make adjustments, says Hanoun, citing 3motionAI’s experience.

“Let's say an employer decides to look at the risks dynamically through 3motionAI. They scan the different employees essentially performing the same way for different jobs, they're able to see the output in a dashboard of analyzed data, where they can look at where the risk is on that particular employee, or across an employee population, and make some decisions on what they should do to reduce their risk.”

Those lessons can be as simple as seeing a large number of employees exposed to back or shoulder injury risks.

“From that data, they could say: ‘Maybe we should look at the ergonomics of that particular task that's creating that risk exposure on the employee population’. And then they would back this up, they would look at the ergonomics of that task and make changes potentially to the requirements of that particular task.”

Using that data, employers can also consider automation and wellness tips for employers, he says.

“We can use the data that the AI extracts and we can empower the employer to say: ‘Okay, now we've got some decisions to make. What's the best approach?’.” 

There is growing research linking chronic pain and poor mental health and though it appears to be ‘invisible,’ it’s crippling your workforce, according to a previous report.

Chiropractic care can be a key way to treat MSK injuries, according to a previous report.

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