Healthcare insurance fraud represents a growing threat, as a weakened economy creates incentives for criminals. Larry Jacobson describes a technological approach to fighting back.
THE ANSWER: ANALYTICS
Predictive analytics and rules have a synergistic relationship. As the predictive analytics algorithm identifies emerging but increasingly routine sources of waste, it can help insurers to develop new rules.
The artificial intelligence in the predictive analytics system then ‘learns’ from the new rule patterns and builds increasingly more complex, informed and accurate adaptive models.
In one case study, a pathology group had been adding a professional services modifier for analysis on standard blood work, just a small amount at a time.
While there are many tests that do require analysis, these did not. An analytic system not only identified the discrepancy, it also enabled the payer to implement a rule that no professional services modifiers were required with a specific set of tests.
These powerful systems flag only the highest-risk claims, reducing the number of legitimate claims delayed for investigation.
Providers will know that they can count on prompt and accurate payment, thereby strengthening payer-provider relations.
The analytics-based approach yields dramatic results. Many insurers have seen reductions in fraud losses of 20%-50% and lowered their loss-adjustment expenses by 20%-25%.
This is why such systems are attractive not only to individual insurers but also to major players in the healthcare industry.
For instance, Emdeon, which operates the single largest financial and administrative information exchange in the US healthcare system, is working with FICO to offer analytics-based insurance fraud protection to its client base.
One of the larger health insurers using this combination of predictive analytics and business rules is a US firm that processes more than 200 million health, dental, vision, and pharmacy claims a year.
By adding an additional set of models to score claims, the insurer quickly identified more than 250 new pursuable cases that previously went undetected using other methods, including 43 cases that ended up impacting multiple providers.
The UK insurance industry should begin its own movement to a more advanced analytical approach.
The right combination of predictive analytics and rules-based analysis allows payers to realise prepayment savings by avoiding unnecessary payments; systemic savings by correcting policy weaknesses that permitted excessive payments; and post-payment savings by identifying and dealing with suspicious providers.
This three-pronged approach gives insurers their best weapon in the war on fraud, waste and abuse.
Larry Jacobson oversees the European insurance market for predictive analytics company FICO
