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How can you improve your COB effectiveness?

With restricted margins and changing bargaining relationships as providers consolidate and evolve, health insurers are looking more than ever to coordination of benefits to improve their bottom lines. Fortunately, modern digital tools powered by big data analytics, artificial intelligence and machine learning have revolutionized COB for insurers by putting the patient, instead of the claim, at the center of the process.

One major challenge for effective COB management in the past has been that insurers have relied on policyholders to self-report other potential insurers that might have responsibility for paying some or all of a medical claim. This suffers not only from the standard quality challenges of consumer-provided data, but also from the general lack of sophistication most consumers have about health care and insurance. While insurers know that roughly one in five Americans has insurance coverage from multiple providers in any given year, capturing those relationships is a never-ending battle for insurer COB functions.

However, thanks to modern data analytics capabilities, insurers can improve their processes by moving from a reactive to a predictive model. Using both internal and third-party data, analytics-driven COB systems can predict which consumers are most likely to have third-party insurance coverages. This allows insurers to prioritize the claims most likely to bear fruit before they are paid out, minimizing expensive “pay and chase” claims adjusting.

One other benefit of this AI-driven model is that automating the claim recovery process with the patient at the center of the analysis enables insurers to significantly broaden the universe of claims being analyzed. While it makes no financial sense to have a human being investigate a $25 claim, those claims add up and identifying large numbers of such claims with a high likelihood of third-party payment responsibility can add up significant savings.

Insurers can unlock even more potential by combining AI-driven COB with human expertise in other fraud, waste and abuse functions to unlock an integrated “payment integrity” capability that improves claim payouts, identifies systemic vulnerabilities and their root causes, improves customer satisfaction and generates real value for an insurer’s bottom line.

Interested in learning what a modern big data solution like Lia can do to improve your COB effectiveness and contribute to your bottom line? Contact us to find out more.


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