Claim severity due to fraud is a huge problem for insurancecarriers. Although there are many factors contributing to the riseof auto injury medical claim costs — including more expensivepharmaceuticals and costlier treatment options that inflate paidlosses — fraud is clearly one expense that carriers can and shouldaddress.

One specific area of medical claim abuse has appeared in PIPand/or “no-fault” states where the ability to bill more high-costprocedures has provided a lucrative opportunity for fraud. NewYork, Pennsylvania, Michigan, Minnesota, and Florida exhibitgreater claim severity compared to the overall experience in theU.S., with particular sectors of medical care such as radiology andother diagnostics on the rise. These procedures are performed notonly more frequently but also earlier in the treatment cycle. As aresult, costs are rising higher than overall medical inflation.

Expensive procedures performed earlier in the care cycle canconsume more of the claim dollar — money better spent on patientcare. In the case of radiology procedure abuse, the frequency ofcomputed tomography (CT) scans in recent years paints a picture ofunsavory medical billing practices at work. An examination of claimdata reveals a marked up tick in the number of CT scans in PIPstates compared to previously common magnetic resonance imaging(MRI). A careful examination of the necessity of these proceduresin so many auto medical claim cases in these particular statesleads one to believe that some care providers are taking advantageof an opportunity to make more money. By digging deeper, we seethat the frequency with which these CT scans occur as a result ofprovider referrals suggests medical billing fraud.

Repeat Offenders

For insurance carriers, the first step to address and preventthe problem is to identify the offending providers. Querying thedata within a defined period of time will reveal the transgressors.Instating a rules engine and monitoring system designed to “redflag” these providers and questionable procedures will alertcarriers' special investigative units (SIUs) of problems.Establishing specific rules will also help ensure that the workflowmoves in the proper direction, as seemingly innocuous proceduresmay not be flagged by all claim examiners as fraudulent.Additionally, using a rules engine will enable a carrier to applyconsistent rules in the claim work environment.

From that point, individual carriers can decide the best way toproceed, perhaps with an independent medical examination (IME),which will serve to put fraud perpetrators on notice. The goal isto change provider behavior before they submit their automotivemedical bills. Beyond individual carriers, enlisting the help ofthe National Insurance Crime Bureau (NICB) will help stop fraud byproviding enough aggregate data for authorities to startsurveillance on bad providers and pursue prosecution of repeatoffenders.

Taking action to prevent automotive medical claim fraud shouldbe part of all carriers' bill review processes. The more it becomesstandard practice, the more carriers will be able to profile fraudfrom the moment the claim arrives. Thus, carriers can catch fraudbefore it becomes as costly a problem as CT scans are in PIPstates.

The following review of data experiences has elicited somesurprising and some not-so-surprising results.

Identify and Quantify Opportunities

We must first evaluate the claim workflow and document currentprocesses to identify and quantify the opportunities for review.Then we can methodically analyze a series of standard metrics tospot potential areas for improvement. In the case of suspectedissues in radiology, we focused on all radiology current proceduralterminology (CPT) codes and billing data. The next step is usingthe data to identify a set of more unique, deep-dive analyses inspecific areas that have high potential for fraud. In the case ofradiology, the data drove us toward the “high-ticket” items such asCT scans and MRIs. To further segregate, we divided the data byU.S. region.

Once we identified the procedures for review and the geographicareas, we drew upon several years of data for comparison andbaseline analysis. For the radiology review, we used closed-claimdata and segregated the information by region: Midwest, Northeast,South, and West. We further divided the data into coverages anddiscerned between first and third parties. Here, we will focussolely on first-party billing data.

Once the data have been isolated and multiple years ofexperience are available for review, we can benchmark the data andcompare regions. Because there is variation in PIP benefits fromstate to state, policy limits have been considered.

Delving into the data elicits several unique regionalobservations. The information used for this review encompassesthree years of data — from 2005 to 2007 — totaling more than 1.5million bills and first-party claims only.

Average Charge per Claim

Figure 1 demonstrates the averagecharge per first-party claim nationally, divided into Northeast,South, Midwest, and West.

As evident in the observed charge data, claim severity is on therise. Because claim severity is the ultimate measurement andindicator in the claim environment for why dollars are spent, it isimportant to investigate the drivers. Judging from this trendinginformation, we anticipate that claim severity will continue toincrease through 2008.

Increases in provider charges have also demonstrated higherindemnity payouts (severity). Figure 2 provides an analysis andcomparison of nationally and regionally based average paid claimresults.

Overall, the national average is on the rise through the 2007year of loss claims. This is true despite the dramatic decreaseexperienced in the Northeast region. Data is based on year of loss,so one would expect a decrease in 2007 claim averages, as theseclaims are less mature than 2005 and 2006 claims. The dramaticdecrease in the Northeast is likely exaggerated by the large policylimit PIP states of New York and New Jersey.

Average Charge per Unit

Providers bill by “units” on medical bills. The units tell theinsurer how many times a procedure was performed, usually per day.The data depicted in Figure 3 demonstrates again that providercharges are increasing substantially whenreviewed according to units. These changes may stem from increasedprovider fees or the more frequent use of high-dollar medicalservices. Units are potential drivers and clues when reviewing thedata to discern why these observations are occurring.

The amounts displayed for the average unit is noteworthy becauseprovider charges — broken down to the unit values — have an impacton the average paid claim. The only way to identify these claimissues is to identify the driver and use a rules engine as a toolin recognizing the procedures for which unit values are on therise. Claim representatives can then make decisions as to whetherthe number of units are appropriate to pay.

Thus far, the data has demonstrated that severity, payments,charges, and unit costs are all on an upswing. The next step is todetermine what set of procedures or procedure may be affecting theseverity results. To accomplish this, we need to aggregate similarprocedures into groups. This also enables us to focus solely on theareas of billing that affect severity, as not all areas will.

Reviewing the code groups as depicted in Figure 4 and associatedbilling data indicates that the services keeping claimrepresentatives busy may not be driving the severity. As noted inFigure 4, the “units” are touch points for claim representatives.Sixty-five percent of bills are related to physical therapy; 27percent are classified by the HealthcareCommon Procedure Coding System (HCPCS) as durable medicalequipment, dental, ambulance, and so forth; six percent are relatedto radiology billing; and two percent are related to surgery.

The differences in the observations are related to the providercharges and allowances. In particular, although radiologyrepresents only six percent of the units (touch points) forpayment, this category comprises 30 percent of the charges and 29percent of the allowances. A similar, yet smaller portion isrelated to surgery. For this review, we will focus only on theradiology portion, as it is the most significant.

Procedure Code Analysis, Trended Nationally

It is important to consider how the procedure code groups havecontributed to the allowances and compare them nationally. Figure 5illustrates that the allowances for radiology are now narrowing thegap with physical medicine services. Allowances for radiologyservices have grown 25 to 30 percent of total allowances in theclaim data.

As stated before, creating families or groups of like procedureswill provide comparisons that will simplify the identification ofissues. We use Figure 6 to demonstrate the comparisons in thegroups for allowance of payment.

In Figure 6, it is apparent physical medicine and DME have hadlittle change and impact on the allowance on a yearly basis. Radiologydemonstrates the largest variance, followed by the surgical codes.Now that the group of codes has been identified, we can isolate thecontibutors (drivers) of the codes that are major contributors tothe severity changes.

Increased Radiology Allowances

CT scans are the procedures that most significantly contributeto increased radiology allowances. On average, CT scan charges haverisen 28 percent since 2005 and continue to swell. These CT scansin particular are driving the increase:

• Cervical CT without contrast
  (CPT code 72125)
• Head/Brain CT without contrast
  (CPT code 70450)
• Lumbar CT without contrast
  (CPT code 72131)
• Thorax CT with contrast
  (CPT code 71260)
• Abdominal CT with contrast
  (CPT code 74160)
• Pelvic CT with contrast (CPT code 72193)

Figure 7 depicts the yearly increase in CT scan allowances on anational basis.

Other than high charges, we need to consider various reasons andbilling behavior changes. In addition to the hike incharges/allowances, the data show that CT scans are performed morefrequently and closer to the date of loss than in prior years.Although this is yet to be determined as a driver, it should beconsidered. More and more states are enacting legislation toprotect the benefits paid to emergency responders and/or emergencycare. This means that emergency bills must be presented faster andahead of other care that may occur on the case. Reviewing the typesof bills and the order in which they are paid is a vital part ofclaim workflow.

Mitigation

There are a number of ways to mitigate the issue. The steps wewould advise to review this and similar issues would be:

• Use an analytical approach to establish if these observationsare occurring in claim operations.
• Once a data review has occurred, identify the drivers or CPTcodes. These codes can be input into a rules engine and flagged forreview. Rules engines have the capability to flag CPT codes withina specific time frame and frequency.
• Medical review should also be used in conjunction with thisflagging mechanism to discern whether the procedure was medicallynecessary and performed in accordance with industry standards.

Performing CT and other diagnostic testing before they aredeemed medically necessary constitutes fraud. Using the analyticapproach to trending will assist in the efficient identification ofissues and also create solutions for reviewing medical billsappropriately.