Updated on: November 29, -0001

What is the Square Root of -1? More Uses for Risk-Based Audit Technology

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Original story posted on: September 14, 2016

I recently received an email from a Monitor Mondays listener about something called TPEE, or targeted probe and educate with extrapolation. I did a little research and came across a pretty neat flowchart that described the program as a multi-phased approach to improving coding and billing compliance through provider education.

While my suspicions are always aroused when a payer claims to have “education” as a primary goal, I was actually quite encouraged that this may, in fact, be the case here. I was able to get a good amount of information about the program at the Noridian website (https://med.noridianmedicare.com/web/jea/cert-reviews/mr/probe).

On the website, under the heading “Probe Reviews,” the first paragraph begins like so: 

“When Noridian identifies a provider or service as being at risk, the potential error is validated with a prepayment probe (error validation) review. Conducting a probe review ensures that medical review activities are targeted at identified problem areas. Probe reviews are designed to obtain a sample large enough to provide confidence in the result, but small enough to limit administrative burden. The probe sample of potential problem claims is used to validate the hypothesis that such claims are being billed incorrectly or in error.”  

I was pretty impressed, and think that this is actually really cool, as it is the same approach that I have been encouraging providers to adopt with respect to their internal reviews. It is important to understand that their definition of the word “probe” is likely different from what most folks are used to encountering. In the past, a probe audit meant selecting some number of charts at random (say, 30) and then reviewing them to determine whether there is a problem. Old stuff. 

Nowadays, for more progressive organizations, a probe is conducted after a statistical or other advanced analytical technique is used to identify potential problems a priori. When I looked at the flow chart, that’s pretty much what I saw. In this case, since we have already identified those codes and/or modifiers most likely to represent a risk because of something called homogeneity (which, at its core, measures how similar things are), the probe sample size can be considerably smaller (translation: less expensive).

For Noridian, what starts the process is when a provider is selected for review based on “data analysis.” This sounds very similar to how the Centers for Medicare & Medicaid Services (CMS) uses the Fraud Prevention System, a series of predictive algorithms designed to identify potential fraud, waste, and abuse. Next, the program proceeds through three phases. 

In phase one, the contractor probes a prepayment sample of claims for a given code or code set that has been scored as exhibiting high risk. The contractor reviews the documentation to determine whether the associated provider is actually compliant. If the provider is, then the program is terminated and no more reviews are done, at least on that issue. It is reasonable to assume that the analytics will continue to review other claims, which may result in other issues being identified.  If the provider is found not to be compliant, then Noridian provides education on its findings, and after a given period of time designed to allow the provider to change its behavior, they probe another set of similar claims (phase two) for that same issue. 

And the process is repeated; if no problem is identified, the program terminates, and if there are still problems, more education is provided, a bit more time passes, and then another review occurs. If after the third phase, the same problems still exist, then Noridian proposes two possible solutions; one is to perform a random post-payment audit, with the likelihood of using extrapolation to recoup overpaid amounts and/or making a referral to another CMS contractor, which would likely be a Zone Program Integrity Contractor (ZPIC). On a separate note, for either of these actions, the provider would still have the opportunity to appeal the findings.

Many of you know me as a bit of a conspiratorialist and even more of a cynic. But in this case, it seems that Noridian has recognized the simple business axiom that it is cheaper to prevent inappropriate payments than to try to recoup them a posteriori. Considering that they are also willing to offer a “three-strikes-and-you’re-out” policy, it is hard for even the most cynical of us to find much fault with the program. I mean even I, the strongest physician advocate I know, am for preventing fraud, waste, and abuse. Because in addition to being a physician advocate, I am also a taxpayer, and if what Noridian is doing is offering free coding education to providers to help them improve compliance, then I am pressed to find a legitimate complaint. If someone out there has had a negative experience with this, I would love to hear about it, because the flow chart looks pretty fair.

I think that there are two great takeaways here. The first is that Noridian has recognized that it is more efficient to prevent than to recoup, and they are willing to invest in education to achieve that goal. The second, which is perhaps more important for the provider, is that the payers are relying more and more on advanced analytics to identify risky behavior. In provider parlance, they are engaging in risk-based auditing. Are you? Think about it; if you were able to identify potential coding and billing issues early on for less than the the cost of probe auditing, you could correct them before future claims are filed. This is the definition of efficiency, and just like it is cheaper to prevent than to recoup, it is also cheaper for a provider to bill correctly the first time than deal with denials and possible audits in the future.

In the end, I still believe that payers abuse their power, because they have access to data that no one else does and they are not willing to share. And I am still convinced that they do not have the providers’ best interests at heart. So it is still incumbent upon the provider to ensure that it does everything possible to ensure that every claim that is filed is as clean as it can be. After all, cleanliness is next to godliness.

And that’s the world according to Frank.

About the Author

Frank Cohen is the director of analytics and business intelligence for DoctorsManagement, a Knoxville, Tenn.-based consulting firm. Mr. Cohen specializes in data mining, applied statistics, practice analytics, decision support, and process improvement.

Contact the Author

 fcohen@drsmgmt.com

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