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One of the things that’s clear is that there are a billion different ways to analyze something and look at different metrics. I’m continually surprised at the different lenses that we can use to calculate things.

We’re doing a denials analysis program for a client at the moment, and we’re trying to distill down all of these calculations. When you’re doing a ton of different metrics, there are so many different things you’re looking at. You often don’t get into the hierarchy of which are the most critical metrics.

In this particular situation, we’ve been trying to distill down what we’re doing to the smallest number of KPIs: just one, two, three…some minimal number of metrics that are the most important when it comes to denials. As we were going through that process and trying to figure out, “Okay, this one versus this one,” we ran into something interesting.

Primary Misleading Metric

First of all, the number one metric that most providers and billing companies look at is the number of denials.  This is usually done on an encounter basis, in other words, “how many denials did we receive,” or on a dollar basis “how much got denied in charges”? They may even look at that trend month-by-month over time. That’s the most common metric we see far and away from what everybody looks at, which is “How many denials are you getting month over month?”

We can categorically say without doubt that this is nowhere near the number one most important metric. Not number one, not number two, not number three. I almost don’t consider it to be an important metric at all. Sound like heresy?  The reason why I say that is because it’s so problematic in so many different ways. So many things can be hidden by it that it can be incredibly misleading, and it doesn’t even tell you much.

I’ll give you a straightforward example. If your volume of encounters is increasing (which is a good thing) and you’re seeing a problem in denials you might reasonably react when looking just a denials, “Oh, my gosh! My denials are increasing month over month at an alarming and consistent rate,” when they SHOULD be increasing month over month. If your volume of patient encounters is increasing, that doesn’t mean that you’re moving backward. It doesn’t mean you have a problem with denials any more than you did last month or the month before. Looking at that isn’t particularly helpful.

We don’t like data or metrics just for the sake of metrics. If you’re looking at numbers, if you’re outputting some number, you should be able to do something with it. It should tell you something, allow you to conclude that you can then act upon that will allow you to make more money. We don’t like denials count, whether it’s by volume of denials or dollar charge volume or denials trend over time. Spoiler alert: Not a great metric. Not number one, not number two, not number three, not top at all.

Don’t Mix Metrics

One of the metrics that we have often analyzed for clients is percentage of denials paid. There are many different iterations of this, but we’re trying to zero in on the percentage of denials that get paid after getting denied. If you think about where claims are falling out of the revenue cycle and not getting paid as a result of denials, a key thing to look is “What’s your net? How many claims are getting kicked out and staying out?” If they get denied, they don’t get paid. Suppose you look at the percentage of claims that get paid after a denial. Forget denial days and all kinds of other metrics because there are many nuances around that denial payment cycle. If you look at the percentage of denials that end up getting paid, that’s a pretty critical metric. 

While we thought about putting at the top of the denials KPIs, we concluded that there’s a better metric. But we’ll get to that in just a moment.  First, some clarification on denials paid percent.  There are multiple ways to calculate this with the two most common being on a units of denials basis or a dollar charge basis.  But first of all, let me note one really critical thing about how not to calculate, absolutely not to calculate, the denials paid percent, which is – do not calculate collections over charges.  While this might seem perfectly natural since this parallels other similar calculations that take payments over charges to get a percent like gross collection rate, it is a complete disaster for a KPI.

We hate gross collection rate as a metric anyways. And in a different article I can articulate and I’ll go off on that some other day in the near future again with why it is so useless. But for now suffice it to say that gross collections is a garbage metric, really useless, both internally to use over time and for comparison benchmarking against other organizations. So – don’t mix that in! You effectively are mixing denials rate and gross collection rate in this case, which is a going to fail.

Let’s take a hypothetical example for clarification. If we collected $100,000 in payments from charges that had NOT been denied on a million dollars in denials of charges, you would calculate a gross collection rate of 10%. Now if we have a million dollars in denials and appeal and receive $100,000, that would generate a 10% success rate by that calculation.  However, that’s extraordinarily misleading because you shouldn’t expect to collect 100% of your charges anyway. You’re effectively blending two different metrics: a percentage of denials collected and a gross collection calculation.

Real Denials Percent KPI

When you’re essentially trying to quantify the performance of appeals or quantify your revenue cycle management department’s performance or billing company in terms of how successful they are at overturning denials, the real metric you want to use is the percentage of denials subsequently allowed. This can be either on an encounter level basis or charges.  We suggest charges since there is a positive correlation between charges and collections.  To illustrate, let’s say take that prior example of $100k collection on $1m in charges.  Let’s now say that this $100k collected represents $400k in charges.  SECRET: You would then take $400k in the numerator and $1m in the denominator to generate a 40% success rate in this example.

SUPER SECRET TIP: It’s also so critical that you use “allowed” rather than “paid” because, otherwise, you’re conflating two different things. You’re conflating the patient revenue cycle management process and the denials management/appeals process. Suppose you want to isolate and look at how successful your denial appeals are or your patient collections department, or whatever the title for that group is in your organization. In that case, you don’t want to mix in the patient revenue cycle. You want to look at “Did you overturn that denial where the allowed amount went from 0 to a positive number?” not “Did it get paid by the insurance company?” Because there are going to be a significant number of claims where you did not get paid by the insurance company, but it did get allowed because the patient deductible or something like that consumed the entire claim.  That is still success on the part of the medical billing team overturning that denial and if it fails at the patient collection level you want to track that separately.

A key thing: look at percentage denials allowed for how successful your denials management program is. Overall, in terms of denials, there are two hypercritical metrics and we have just laid out one of them. The second one, we won’t give that to you tonight. We’ll do that another day. You’ll have to come to talk to us. Have a good night!

 

 

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