Analytics at Heart of Workers’ Comp Cost Containment

By Denise Johnson | January 23, 2017

To remain competitive in the marketplace, all workers’ compensation carriers will need to adopt some form of analytics, according to Rob Lewis, president of ISO Claims Partners.

Lewis outlined the benefits of using predictive analytics in all stages of a workers’ compensation claim.

Cost containment in workers’ comp is so important, said Lewis, because claim costs continue to escalate. Analytics can help minimize costs and maximize outcomes.

“The reality is that claims costs are escalating,” said Lewis. “Medical makes up a huge portion of total claims cost and it’s only getting higher. The bottom line for carriers is that it’s a competitive market. For them to be able to compete, they need to find savings and they need to maximize the outcomes of claims that they’re handling in order to be competitive in this marketplace,” Lewis said.

Using analytics and predictive modeling can drive savings and efficiency. This is achieved by identifying high complexity, high severity claims early.

“Using data and analytics can really improve the bottom line,” Lewis said. “Organizations that use analytics have been found to be twice as likely to be top quartile financial performers, five times more likely to make decisions much faster than competitors, and three times more likely to be highly effective at executing decisions.”

He said that if carriers can find those five percent of claims that amount to 80 percent of costs early, the right resources can be tapped to improve the chances the claim will have a better outcome.

“Because if you can identify those cases early, it gives you an opportunity to be able to get involved, to get the right people on the claim and to drive improved outcomes,” said Lewis. “What we found is by doing a score and providing this information back to the carriers, they’re able to from first report of injury, from first day of loss, assign the claim to an experienced adjuster to handle it, assign it to experienced legal counsel, get their best doctors on it, get the PBM [pharmacy benefit manager] involved, get medical bill review involved, intervene with the providers, make sure that the right treatment is happening and target certain cases for settlement.”

Carriers are more successful using a proactive approach versus a reactive one, he said.

“It’s taking what normally is a reactive process and making it much more proactive on behalf of the carrier so that they can get in front of these cases that cost so much money and do the right things, get the right people on it, and really drive improved outcomes,” he added.

Lewis explained that analytics can be used in all stages of a workers’ comp claim. It shouldn’t be considered only when a claim goes bad. Analytics can be used during underwriting to identify premium fraud and verify business classification. In claims, analytics can be used to assist in federal reporting requirements, to investigate potential fraud and to monitor treatment modalities.

“It helps to think about underwriting. There’s incredible pressure to write business quickly. In some situations, inappropriate premiums get utilized, writing risk beyond the tolerance level. There’s premium fraud scams that are abundant,” Lewis said. “Having predictive analytics in the underwriting group gives you an opportunity to verify business classifications, payment histories, credit scores, loss control site surveys, OSHA [Occupational Safety and Health Administration] violations, loss runs, etc. That information ultimately can help better improve the underwriting in the workers’ comp space.”

Analytics need to be managed through the entire life cycle of a claim, he said.

“The underwriting data and the claims data ultimately should talk to each other, because I think that there’s a virtuous circle there between the two that in many organizations just currently doesn’t exist,” said Lewis.

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