Does It Constitute Fraud?

Every provider and manager in medical billing has experienced situations where insurance companies have underpaid them. It doesn’t matter what kind of provider you are. There are many examples of these, so the question is, “How many are there, and how many are you aware of?” in part because the payers are not transparent about this.  In fact, they will blatantly communicate something false in an ERA or EOB so that it appears as though the payment amount was correct.

 

An interesting question is, “Are they actually mistakes? Do insurance companies mistakenly underpay you?” because that certainly is their assertion: these are accidents. They underpay you accidentally.  The question of intent is important because this is a necessary component of fraud, that it was done intentionally.

 

Logic might tell you that the simplest solution is not that insurers made a mistake, but they’re intentionally trying to underpay you since they have a huge financial incentive to do so. The question is, “How do you prove that?” without access to their systems to be able to show that they’re doing it intentionally or that there are policies.

We assert that it is in fact fraud since we believe it was done intentionally based on the data, which we will discuss below. 

Insurance Employee Verification

 

Some of our employees had worked for insurance companies in the past prior to working with us. They had recounted that some payers have quotas. For creating problems so that they did not have to pay the claim.  They were told to make some claims disappear or they had to throw away / delete them, or were told to deny claims for no good reason intentionally in order to meet certain thresholds. We realize that this is hearsay effectively and not definitive proof of this specific question of whether underpayments are intentional.

 

What Data Tells Us

Data can tell quite a story.  In this case, it would help us identify whether or not these were accidents or whether they were intentional underpayments, which would support a case of fraud. When you look at behavior in the natural world, if something is random and there is no intentional thought or action, data follows a cert pattern.  This is what you would call random or “accidental”.  If you look at whether or not insurance companies underpay you or overpay you, you would expect to see a somewhat normal distribution around overpayments and underpayments. That means about half of the payments are underpayments, versus half of them are overpayments when they’re paid incorrectly.

 

A normal distribution means that you would expect the largest amount of deviations from correct payments would be small, but some smaller number of outliers where there are large overpayments or underpayments.  These are known as the “tails”.

 

There are two parts to the analysis of whether there is intent to underpay on the part of payers. The first is, “What does the pattern of payment look like?”  In other words, what shape does it follow?  The answer is that the payment pattern does not look anything remotely close to a normal distribution, where half of them are above, and half are below. In practice, we see the overwhelming majority of the incorrect payments are UNDERPAYMENTS and just a very small number of overpayments, like the following chart. This should be symmetrical.  While we might expect some payers to have better or worse systems and processes that result in a higher proportion of mistakes or incorrect payments, we should still expect that regardless of the number or percent, that these are distributed close to normal if they were random.  This clearly shows that this is not accidental behavior; that there is some intent there to underpay, regardless of whether it’s by payer policy or by system design.  It is clear that since it’s so lopsided with more underpayments than overpayments that this is not random or accidental. It is intentional.

 

Refunds

The other critical proof of the intent to defraud that you can see in the data relates to refunds. In the rare event where a health insurance company makes an overpayment, it typically asks for a refund of that overpayment.  Often it does not ask for a refund, but simply withholds a corresponding payment amount in the next batch of payments sent to the provider. 

How many of you have experienced that? All hands are going to go up. It’s 100%. Everybody has had an insurance company come back and say, “Hey! We overpaid you. Now, we’re just basically taking the money back.”

 

Ask yourself the next question – how many of you now have experienced the opposite situation, where a payer contacts you proactively and says, “Hey! By the way, we underpaid you last month. Here’s some more money.” I’m guessing no hands are going up at this stage.  Coincidence?

 

The Proof

 

If you think through that process that the insurance company must undergo in order to find where it overpaid a provider, it must mean that they have a quality control process where they go through systematically and analyze all transactions to determine whether or not the payment was correct. This meas they have the capability to do contract compliance and enure payments are correct. 

That small percentage of claims that were overpaid, they come back and take back the money. It is not possible to only analyze the claims that were overpaid.  That is statistically impossible.  They must analyze all claims in order to identify which were overpaid.

That means if they’re identifying all incorrect payments, they can identify whether all of those that were underpaid, as well. They are not contacting you and paying you when they underpay, which means there is clear intent to underpay providers.  Even if one includes all the overpayments which result in refunds into the data distribution, it is still nowhere near a normal distribution.

Insurance companies are intentionally systematically underpaying or at the very least they are knowingly underpaying, and then they’re deliberately catching the overpayments and making sure they get those back and not notifying you of underpayment.

 

The data very clearly shows that there’s intent to defraud providers. We are not in a criminal law case, but if anyone brought a fraud case against health insurers, this data would support intent.  However, it is a fairly sophisticated concept for a judge or jury to accept so it might be hard to convict even though we can accept without a reasonable doubt that payers are crooked.

 

Action Plan Required

 

What do you do with that information? I think the important thing is recognizing why we want to know whether it is intentional or unintentional. If it were unintentional, then you would expect a random or normal distribution. You would expect the overpayments and underpayments roughly balance and that the payer would come back and pay you for the underpayments, just as they would find and recover the overpayments. It would basically all even out, and you shouldn’t have a problem. Therefore there would be nothing to do as a provider in order to ensure financial health and complete reimbursement.

 

Once you know for sure that it is intentional and that they’re doing it willfully, then that means you need to make sure you have a program in place to catch the underpayments because they’re not going to do it for you. There’s going to be a lot of them with some payers, for example, Anthem is notorious for this. It would help you financially if you did something about this. That’s the net effect.

 

If you don’t have a contract compliance program in place, it’s worth investing in one, although that’s the subject of another article.  Stay tuned.

 

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