University of Alberta researchers have developed a new web-based tool to aid health professionals in determining the right treatment course for injured workers, helping them feel better and get back to work earlier.
Researchers used a form of artificial intelligence called machine learning to analyze injury and treatment records from Alberta's workers' compensation database to create a tool that recommends an appropriate course of rehabilitation. During early testing, the support tool actually outperformed clinicians.
"The goal of this tool, and all our rehabilitation strategies today, is to be able to help these people feel healthy again, participate in productive work and reintegrate into their jobs as quick as possible," said Doug Gross, an associate professor of physical therapy in the Faculty of Rehabilitation Medicine.
Gross' research is affiliated with WCB-Alberta Millard Health, a provider of occupational rehabilitation and disability management services. Much of his work focuses on finding new ways to ensure workers are physically on the right path to recoveryhealing that also helps their emotional and financial well-being and the economy, he said.
"There are huge costs economically to the workers' compensation system, so we're constantly looking to improve health-care strategies to help these workers transition back to the workplace."
Computer algorithm at core of online tool
Gross teamed up with Osmar Zaane, a professor of computing science in the Faculty of Science, to develop a computer algorithm that predicts a course of rehabilitation.
To do this, Zaane's team relied on information from a provincial database of 8,611 workers who, after undergoing initial treatments, were referred for assessments to determine whether they were ready to return to work. The database contained details about injury types, rehabilitation methods, time between injury and rehabilitation, pain measur
|Contact: Bryan Alary|
University of Alberta