Claims managers tap injury recovery data to improve treatment, drive better outcomesPosted On: May. 4, 2021 12:00 AM CST
Data analytics and predictive modeling are helping workers compensation claims managers better understand injuries and mitigate potential problems.
“Of all the things we are doing this is making the biggest impact,” said Chris Schaffer, Wilton, Connecticut-based CEO of Charles Taylor TPA, a subsidiary of Charles Taylor Ltd.
For example, predictive modeling can use data analytics to identify slow recovery concerns for an injured worker who is overweight and has comorbidities. “If we know we are going to likely have a higher-dollar claim, we know we should put extra mitigation tactics on that,” he said. Early attention to such claims can drive down costs, he said.
Use of data analytics has also led to some surprises, Mr. Schaffer said.
For example, data shows that most workers with expensive shoulder injuries are likely to follow the same early treatment protocol as any worker with a shoulder injury with little variance, Mr. Schaffer said.
“Through our artificial intelligence and analysis of claims … we found that for the first five months a shoulder claim is just a shoulder claim and the adjuster is not likely to have an impact. … This allows us to deploy resources where and when we can make an impact,” he said.
Data analytics modeling deployed by Liberty Mutual Insurance Co. has helped flag claims, moving them into a “complex group” for enhanced case management, said Patrick Hiles, the insurer’s St. Louis-based vice president and manager of the south region for workers compensation.
“We have several models that we run in the background on a claim,” he said, adding that for some common claim characteristics there’s a “high level of reliability those claims may have an issue with severity.”
Mike Hessling, Rollings Meadows, Illinois-based CEO, North America, of Gallagher Bassett Services Inc., said the data approach helps the industry “understand the levers that help drive better claims outcomes.”