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I’m going to let you in on a secret denials analysis tip. Most people don’t realize that frequently, there are formatting differences between payers on their denial codes. That means it might be a CO-119, a CO 119, a CO119, all in one string, maybe just a 119. It might even be buried in a note text string somewhere in the middle with carrots surrounding or perhaps not any carrots and just a bunch of letters around it.
This means parsing out these codes for the systems that are doing it, whether it’s a billing system or a clearinghouse or whoever it might be, or sometimes it’s both of those because it comes through a clearinghouse. Then it gets routed, and then it has some work done by the billing system or a denials management system. That parsing process is very complicated, and often, it does not work correctly.
This can be challenging for something like a COD6 versus a CO6 because if it strips off and identifies the 6, those are two completely different denial reasons even though they’re both a 6, and they both start with CO.
Where’s the code?
Sometimes, you can even run into a situation where there is no code at all. There’s just a written description: “Claim not on file.” It wouldn’t be “Claim not on file.” That would not happen. “Medical records required” or something like that or “A patient termed” or whatever it might be, but there’s no code at all.
Why does all this matter, and why do you need to know? It’s because, in a word, duplicates. Suppose you’re doing an analysis and looking at the top denial reasons in descending order. In that case, you may not realize that hidden somewhere below or several other lines in combination below are batches of the same denials. You might see a thousand on line 4, and you might see 312 on line 26, and then another one further down below that has some number of denials.
What about duplicates?
I remember the first time I ran into this. I didn’t even realize that I had seen duplicates. When scanning down the list of denials, we had a denial code and a reason, description, and several denials. I will tell you that I saw a code once, a whole bunch of other codes, and then I saw the same code again, and it didn’t even occur to me that this was a duplicate.
It said CO27, and then down below it repeated CO27. It didn’t even say CO-27 or some other funky thing. It just said the same denial code on a different line item, with another group of them, hundreds of them. I didn’t pick it up.
If you’re good with data and you may remember seeing a bunch of codes, you’re not going to remember, “Oh, I’ve seen CO27 before!” because you’ve seen it so many times in your life that it’s not going to register as something novel. So to see it again, it isn’t necessary to look at the register. You’re not going to catalog all the ones you’ve seen in that list so far because there are a hundred of them or hundreds.
Seeing the same data repeatedly
It just so happened that at some point, I was there scanning a list of multipliers and went, “Wait a minute! I thought I saw that before. Did I see some before?” I don’t remember exactly, but I had to go back and look and then take the data, export it into Excel, run a duplicate check, and sure enough. I was like, “Oh, my gosh! There’s a ton of them. Wow!”
If you don’t pick up on these duplicates or your system doesn’t group them all correctly, you will miss prioritizing what to work on. If you’ve been in this business a long time, anyone who will ask you to tell you everything that you know, you could never possibly explain everything you always know. That’s an unaided recall.
Without a prompt, you may not remember, “Oh, you know, I know these things are under these things.” We can’t possibly remember all that we know until we’re prompted. That’s the reason why this came up.
Get it right the first time around
This came up recently, just the other day, when we ran into this with a client. We had all denial information and stuff like that. Once we regrouped them and consolidated all of those duplicates, the number 2 denial reason changed. That’s how big of an impact it was. It wasn’t like number 34 became number 37. Number 2 in descending order changed.
We’ve seen situations where a number 1 changed and several of the top 5 or 10 changed in order and sometimes quite dramatically. Something that was outside the top 10 suddenly shot up into the top 3.
Eliminate the duplicates
Eliminating duplicates and understanding what’s going on there is vital for prioritization. It’s essential to understand your denials management system, the analysis tools you’re using, the clearinghouse, all these things so that you can root out duplicates or make sure there are no duplicates. If there are, root them out, consolidate them to get a better idea of the top problems to prioritize.
Prioritization means you’re going to make the most effective use of limited time and resources because none of us has unlimited resources. This is important in terms of maximizing how much money is recaptured for the provider. It also means that you will solve a more significant number of problem claims at one time if you group correctly.
Even if you have the prioritization correct, you may solve 500 when you should have solved 800. How? Well, by making a similar problem, if you identify all of the payers and all of the claims with that particular problem and then go out and solve that problem all in one giant batch.
It also means that you will be able to track improvements and the results of rebills and appeals. You’ll be able to show more success, whether that’s to a superior within the organization or to a colleague or simply because you want to track the efficacy of your team’s work so that you know what your return on investment is for allocation of resources or investment. It’s essential to be able to show the results of your work and then quantify the improvement.
That’s our secret tip on denials analysis. Happy hunting!