Using Sophisticated Analytics and Imbedded Intelligence to Reduce Claims Costs

Share Article

New research from York Risk Services Group uncovers both the predictive analytics and the best process to automatically incorporate analytic findings into the claims management process to significantly reduce claims costs by managing claims costs before they occur.

News Image
The Average Medical Paid for lost time claims dropped from $17,234 to $8,250, a reduction of more than 52 percent.

It’s easy to identify some claims – like spinal injuries -- that are going to carry high costs. What’s hard is proactively identifying far more subtle clues that a claim will incur high costs or have a long duration. What is harder still is operationalizing that information to consistently drive smarter medical and claim management decisions that significantly reduce claims costs.

New research from York Risk Services Group uncovers both the predictive analytics and the best process to automatically incorporate analytic findings into the claims management process. The overall approach has yielded impressive results. The Average Medical Paid for lost time claims dropped from $17,234 to $8,250, a reduction of more than 52 percent. Likewise, the Average Medical Paid for medical-only claims dropped from $786 to $727, a decrease of 7.53 percent. When the average medical paid and average total paid were tracked for specific categories of injuries, similar improvements were found.

The results of the year-long pilot of York’s new approach, called TeamComp, are published in the whitepaper “TeamComp: Managing Claims Costs Before They Occur,” which is available on

Proprietary Analytic Intelligence
York analyzed years of claim outcome, utilization review and bill review data to identify characteristics that high-cost claims exhibit before excessive costs are actually incurred. From there, the company created proprietary predictive algorithms to identify claims that begin to exhibit those characteristics. Continual electronic monitoring of all open claims ensures that claims that have the potential for “runaway” costs or extended durations are flagged immediately -- no matter when in the life of the claim the characteristic manifests.

“The key to TeamComp’s success is the way we integrate the analytic intelligence from our automated claim analysis into the overall claims management process,” explains Doug Markham, president of Managed Care for York. “It would be easy to use the analytics for ‘black box’ adjusting, but that approach can be as expensive and wasteful as ignoring the analytics all together. Instead, TeamComp automatically alerts a dedicated team of clinical review nurses whenever a claim is flagged. Their medical expertise allows them to triage the claims and analyze a multitude of medical factors to ensure that we understand the totality of issues affecting the injured worker’s recovery,” he adds.

Driving Better Decisions
The clinical review team culls out claims where the present course of action or treatment is appropriate – which avoids unnecessary managed care charges -- and focuses on claims where intervention can drive the claim to a better outcome. The team uses the claims system to deliver key information about the “at risk” claims directly to front line adjusters. From there, the adjuster partners with the triage team, the adjuster and, as appropriate, a case manager, determine the best course of action for the claim.

The expertise of the adjuster and managed care staff, combined with the analytical intelligence allows York to avoiding overutilization or treatments that the data show are unlikely to be productive – but which will drive up costs. Instead, workers can be guided to more effective treatment that will produce better results and can shorten the duration of the claim.

The claims management system functions as a delivery system for our analytical intelligence, ensuring that critical information reaches the adjuster to inform the myriad of daily decisions that can make or break efforts to manage claims costs. As it creates automated documentation for each step of claim analysis, management, and results, TeamComp continues to feed the analytical engine to refine both the current algorithms and to create new intelligence about emerging trends that can impact the cost of future claims.

“While the initial results from TeamComp are remarkable,” noted Markham, “we are committed to looking deeper at the data and conducing additional research. The pilot, of necessity, used data involving claims opened and closed during a 12-month period, so that data is still developing. Our analysis of TeamComp suggests that for claims involving more complex injuries, initial medical costs may increase, but that the early clinical review / triage and the application of appropriate care will shorten the total length of these claims and reduce their overall, long-term costs.” Continuous, rigorous monitoring of the claim data from both the pilot and our entire inventory of workers’ compensation claims will enable York to develop the next generation of analytics to drive down claims costs.

About York Risk Services Group
York Risk Services Group Inc. is a premier provider of claims handling, specialized loss adjusting, managed care, pool administration, loss control and other risk management and insurance services nationwide. York provides risk management and managed care solutions to a variety of strategic partners, including insurance carriers, self insureds, brokers, wholesalers, MGAs, programs, risk pools and public entities. York delivers customized claims solutions for all lines of business, including property, liability, professional liability, ocean and inland marine, environmental and workers’ compensation. York is based in Parsippany, New Jersey and has approximately 3,800 employees nationwide. Visit York on the web at

For more information, contact:
Anne W. Ellis
Assistant Vice President, Marketing & Communications
York Risk Services Group, Inc.
Tel: (973) 404-1282
E-mail: anne.ellis(at)yorkrsg(dot)com

Share article on social media or email:

View article via:

Pdf Print

Contact Author

Anne Ellis
Visit website