By ERNEST FEIRER, vice president and general manager of LexisNexis Claims Solutions
Everyone agrees that the overall cost of medical care, from the cost of the services provided to the resulting premiums individuals and employers pay, is simply too high. Insurers are constantly working to improve efficiency and effectiveness in medical bill review units. Carriers also are more aggressive than ever in employing sophisticated process and analytics to help detect healthcare abuse and fraud.
Yet almost all the work to date has been done within individual line-of-business verticals, such as personal lines, commercial lines like workers' comp and general liability, and healthcare. Many of the larger carriers in all three areas have provider fraud units or special investigation unit (SIU) specialists, working every day to link common threads together from claims file and billing data. Still, even the more sophisticated of these provider fraud units generally focus on only a single line-of-business vertical.
Fraud rings are aware of this weakness and count on it. Recent analysis suggests that providers identified as engaged in anomalous behavior in healthcare also show similar patterns in personal auto. Because the different vertical SIU units operate in isolation from one another, larger patterns of fraud are not readily discovered.
What can be done? The simple answer: Carriers should take a more holistic approach to treatment abuse and fraud.
The most obvious approach is probably also the most problematic. If medical data itself were shared between carriers--both within P/C companies and across P/C and healthcare--analytics that looked across the entire body of data would be able to detect broad patterns otherwise missed in a more limited view of the data. But various privacy laws like HIPAA and HITECH place prohibitive restrictions on how medical data can be used and shared particularly between healthcare and P/C insurers.
Within property/casualty insurance, there have been limited attempts to create contributory databases of cross-company provider information. That's a step in the right direction. Even industry organizations like the National Insurance Crime Bureau (NICB), however, have a tough time getting access to a broad pool of shared data. Also, information submitted to organizations like the NICB represents only a small subset of the overall claims population. To be effective, this approach may require significant changes in law.
The next approach is the sharing of the results of investigations rather than the data itself. Within the P/C industry, the NICB exists as a clearinghouse for entities identified as potentially engaged in fraudulent activity. Within healthcare, the Special Investigation Resource and Intelligence System (SIRIS) database serves a similar purpose.
There exists an opportunity for greater cooperation between healthcare and P/C. This opportunity presents itself in the sharing of provider, participant and ongoing investigative information among these organizations and the respective company SIUs that they work with. Though potential legal barriers to such collaboration need to be addressed, greater leverage of the Coalition Against
Insurance Fraud, National Health Care Anti-Fraud Association (NHCAA) and NICB can help to facilitate this.
Another effective approach involves not only pooling of internal data across verticals within a company, but also combining that with external data (e.g., identity information, licensing databases and TIN databases) and using advanced analytics to identify claims, participants and providers that warrant additional scrutiny. Large public records databases have the ability to draw relationships between providers and their relatives and associates, which can link together their activity to reveal suspicious characteristics of providers and patterns between entities independent from their activities within a given business vertical.
For example, initially a single provider may have been identified as having been involved in fraudulent activity in one particular area. Leveraging large volumes of data accumulated over long periods of time, public records databases can then identify other providers associated with this provider--individuals linked across multiple degrees of separation by common phone numbers, addresses and business locations. If examination of the billing and claims patterns associated with these other providers reveals similar questionable behavior, this may be evidence of a fraud ring. Once identified, the impact on future claims by the ring can be mitigated.
Ultimately, the most effective methodology is to utilize all of the possible techniques simultaneously. Carriers are beginning to more effectively mine internal data, access and analyze pertinent external data, and combine both data sets with advanced analytics to get more timely and actionable information on providers and the claims associated with them. With actionable information received earlier in the lifecycle of the claim, insurers can more proactively address fraud before payment is made, rather than later in the life of the claim where they are in the more traditional "pay and chase" mode.
This kind of holistic approach provides carriers, the industry and state departments of insurance with multiple benefits. First, going across verticals allows individual companies a much broader foundation of data, which means the resulting information is that much more powerful. Second, combining the more robust internal data set with public information provides companies the opportunity to spot relationships that they would not likely find using only internal data. The holistic approach also allows company SIUs to coordinate more effectively with industry fraud fighting organizations, like the NICB. Finally, these new findings can help state insurance department fraud units to more effectively identify and pursue multicompany rings, which results in benefits to all insurance companies.
The bottom line: Insurers have an opportunity to take the lead in showing the public that they are being creative and aggressive in their approach to containing the cost of healthcare by proactively mining data across these verticals, combining their own information with public data, and applying advanced analytics to ferret out individual fraud, organized fraud and provider fraud.
January 1, 2011
Copyright 2011© LRP Publications