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What Should Be Simple

Calculating denials might seem like something relatively simple. For clarification, we don’t mean, “How do you add, subtract, multiply, and divide?” but “What counts as a denial? How do you figure out what to use? What is the right way to calculate this?” Most would assume that your primary goal is that you’re essentially looking to see if denials are going up or going down. For this, you need to filter out the noise. For things that you don’t want to pay attention to that might distract you and give you an incorrect perception of what’s happening. We recently ran into this scenario where a provider was trying to calculate their denial rate and wanted to use something like transaction ID from the clearinghouse, but there were some challenges.

If you count the number of transaction IDs that isn’t going to give you a good idea because:

1) It may not include any denials; it might just be payments and allowed amounts and other transaction information;

2) It may be that a single record (single claim or single patient encounter) has a whole bunch of denials, or you could receive five denials for five separate patient encounters in one single remittance.

What To Use To Calculate Denial Rate?

So how do you figure out exactly what to use if you’re going to be doing this? And how do you do a reverse engineering check to see whether or not you’re getting the right information? Do you have something from your clearinghouse or your billing system or something like that identifies these, and uniquely?

Most of the time, I think the majority of billers, billing companies, and billing departments are just looking at these at a transaction level, which is, “Oh, I get a denial! I have got to fix that problem claim” or “I don’t have to worry about that one. Next!”

That’s at a micro-level because you can see the granularity, and you can say, “Okay, if I get this particular code, then I do this thing.” But that doesn’t give you the 30,000-foot level picture of “are we getting better?” or “are we getting worse?” If you’re adding additional resources or there is some effort to improve your denials rate, then you need to see if any of these are are having any success, if it’s getting better or worse, or just stagnating – there is no effect.

One provider that we evaluated recently used the patient ID as the unique identifier for the number of denials. We mentioned that some remittances might not be denials, but more importantly, you can have multiple denials in a single month for the same patient or even for the same encounter. And there’s not always a one-one relationship…there may be a one-to-many or many-to-one.  There can be all sorts of problems where you could have multiple patient encounters that have denials in a single month and if you use the date received for the denial you might get two different denials on the same date for two different encounters for the same patient. That’s because the doctor saw them twice in a month, and the payer effectively batched those denials and it might seem like you only got one denial when in fact you got two. This would artificially suppress the number of denials counted.  

Issues You Will Face

Another scenario frequently encountered is where you received a denial early in the month, then somebody did something to resubmit it or modify the claim or to appeal. Later in the same month you receive another denial back three or four weeks later. And so you would see two different denials for the same claim for the same single patient encounter in one month.  This can wreak havoc on people trying to count denials effectively to analyze medical billing performance.

So there clearly are some real challenges in figuring out how to do this at a granular level. And then you run into some additional nuances, like what if it’s a single patient encounter where one claim has two different denials. That is to say, not just for other line items in the same encounter because you would frequently get three, four, or five different line items with five different corresponding CPT codes, and they all received the same denial. A more complex issue is when encounter a fairly common situation where you get two different denials for the same line item, i.e you have multiple problems listed for one CPT.  On the same claim like you might get a CO 18 and a CO 109, where one of those indicates it is not covered by the payer, and one that it is considered a duplicate. Are those two denials or one? Now, you got two denial codes, but effectively, the claim got denied once and the line item denied just once, it just got denied for two different reasons. So again is that two denials or one?

Since the transactions (remittances) from a clearinghouse can include payments, allowed amounts, denials, etc. and not all of these are denials, you will also have to filter through all of these to make sure you are only counting actual denials.  Transaction type is the most common way to look at this, so RRC codes.  If you want to simply filter for RRC codes using transaction type, it may work. However, depending upon how the clearinghouse sets up the remittances or your system displays them, you may or may not see the transaction type or worse, it doesn’t show RRC in that field, so you can’t just use those. It shows the ANSI X12 remittance code like a CO 45 or a CO 119 in the transaction type itself, which means you can’t just filter for the RRCs.

So the other thing you can run into is that not all remittance codes are denials. So if you said, “Okay, we’re going to assume that all the RRCs are denials,” that may or may not be the case. And how can you figure it out? You essentially need to add an additional filter to only include denial codes.  Now some of this comes down to what’s the definition of a denial? Is a CO 45 a denial, where the charge exceeds the allowable? I think everyone would agree not.  What about a CO 253, the sequestration? I’m sure you will not be able to get out of that cut to your payment because pretty much everybody gets a reduction in payment when the government does that, or at least that should be the case.

Set Clear Goals

But I think what we generally counsel people to do is take a step back and say, “What’s the purpose of looking at denials?” Why are you doing denials analysis or denials management? And the goal, presumably for everybody, should be to identify problems so that you can diagnose and solve those problems to collect more money. So if that’s the goal, it isn’t reporting for the sake of reporting or just seeing what’s going up and what’s going down? It’s really – “What can we do differently to make more money?” What we might suggest is filtering and including denials that you can do something about. It could be in terms of resubmission or fixing some problem with a claim or an appeal, or it could be something further up the line related to the prevention of the problem.

Some solutions are reactive, but some could be proactive, where it’s not possible to solve the problem after the fact once you’ve submitted the claim. Let’s say, for example, you get a timely filing limit denial. You’re probably unlikely to be able to overturn that unless you’ve got some excellent documentation that shows you did submit it before the timely filing limit. But again, if you missed that, then you’re not going to be able to overcome that, but you should be able to prevent that in the future. So you want to track those and see those and put in place some process to avoid it. 

What constitutes denials?

So sequestration is not going to fall into that category. Contractual adjustments are not going to fall into that category. But suppose you have a diagnosis that doesn’t support a procedure code like a CO 11. In that case, whether there is documentation, results, or can you look through the notes and try to come up with a diagnosis code from the documentation?

Even if you cannot solve that individual claim after the fact, you should still be able to prevent that problem even if it means that you have to go even further upstream to “How do you get physicians to document better?” so that they include more information that allows you to get more claims paid. Or even if you go even further upstream, that provides counseling physicians on what to order or what type of clinical care they should get to ensure you’re not providing unreimbursable care. Now, that’s really far upstream, and you may find resistance on the clinical side to doing some of these kinds of things. While acceptance or resistance to this depends on your organization and many other things, it IS preventable. So you do want to track those kinds of remittances as denials.

Anything that falls into the category of “you should be able to solve it and get it paid or prevent it so that those claims get paid so you don’t do unreimbursed care” should count as denials. Decide what that list of codes is for denials as an organization and make that documentation available to everybody. You can modify it over time, but use that to filter through, “Okay, these are ones we’re going to track. We’re going to see whether it gets better or worse. And then we’re going to put some resources towards it to improve it and reduce denials consistently.”

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