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07:27 PM
James Ruototo, SAS
James Ruototo, SAS

Drawing the Line Between Fraud and Abuse in PIP Claims

Many organizations who focus exclusively on hard fraud may be hampering their proactive detection capabilities.

The Insurance Research Council (IRC) estimates that about one-third of paid auto injury claims in Florida contain some form of fraud or abuse. But where is the line between hard fraud and abusive medical billing? This definition can greatly influence how these claims are handled and whether or not SIU needs to be involved.

Hard Fraud

The IRC categorizes claim fraud as "when a claimant, attorney, medical provider, or other participant in the claim materially misrepresents all or some aspects of the claim." This is in contrast to abuse, or what they call claim buildup, "when injuries are exaggerated or reported losses are inflated by unnecessary or excessive treatment or other expenses." While I credit IRC for at least providing some definition, the issue is far from clear. When, exactly, do exaggerations become material misrepresentations? That question is at the heart of many SIU resource discussions.

One of the biggest challenges in addressing this issue is that it is often difficult to determine whether or not a misrepresentation is material to the claim unless you conduct an investigation. But investigations cost money and SIU leaders need to prioritize the work to maximize the value of their investigative resources. Many organizations have an increasing focus on hard fraud, organized rings, and medical mills. This approach is logical since there are significant dollars at risk and there is little debate about pursuing fraud investigations involving fictitious accidents or providers who bill for services they did not actually render. However, insurers who only focus investigative resources on these cases may be hampering their proactive detection capabilities.

To SIU or Not?

In a recent example, a particular medical provider was identified by a fraud detection technology framework as being high risk for possible fraudulent behavior. Upon review, the insurer decided that this provider may have been engaged in abusive medical billing but not hard fraud and the case was not sent to SIU. Several weeks later, authorities arrested the clinic owner and several employees and charged them with insurance fraud for running a full-fledged medical mill. In this example, the abusive medical billing was an indicator of hard fraud.

Among the findings in the IRC study are increased utilization and billing for diagnostic imaging, chiropractors and pain clinics. A PIP claimant in Florida is 50 percent more likely to have an MRI than PIP claimants nationwide. The IRC found similar treatment patterns in the metro New York city area. Are these treatment patterns indicative of fraud or abusive treatment? The answer is likely some of both. Fraudulent claims likely contain abusive medical billing. The IRC has identified expensive diagnostic procedures as "major drivers of overall medical costs in auto injury claims" and such drivers can help fuel medical mill scams.

Drawing a Line in the Sand

It is becoming increasingly difficult to differentiate between suspected fraud and suspected medical billing abuse. As providers migrate from the 17,000 diagnosis codes in ICD 9 to the 155,000 codes in ICD 10, corresponding CPT coding continues to evolve, and the medical community transitions to electronic health records, things are only going to get more complex. Rising pressure from political and economic forces continue to put strain on medical treatment providers. Legitimate providers are seeking ways to maximize their revenue in order to remain profitable while more unscrupulous providers push the limits of their billing creativity into abusive or fraudulent territory. In this environment insurers must remain vigilant and leverage technology and analytics to help them maintain a proactive stance in detecting and preventing fraud.

About the Author: James Ruotolo is an insurance fraud technologist, thought leader and the Principal for Insurance Fraud Solutions at SAS. Connect with him on Twitter or LinkedIn.

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