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I have a question. Why does everybody estimate average denials or average denials range? Why is it that nobody gives a specific number? How many times have you seen a supposed expert, a consultant, even somebody who should have all this information say something like, “The average medical billing denials rate is between 5% and 10%”?

Medical billing denials

The reason why this popped up recently was that I saw an article from Change Healthcare. The title was “Medical Billing Denials are Avoidable.” And then, there was a subtitle. But the main thrust of it was that there was a relatively high percentage of denials. There’s something you can do about it. For instance, they broke it down a little bit. Also, they quoted a 5-to-10% range for the average. An average is a specific number, not a range by definition. In addition, a range is a range.

Further, an average is an average. That’s a number, not a degree. They quoted 5% to 10% of the spectrum.

Where is the standard?

First of all, that’s a pretty statistically small range. So if they’re saying the entire range is 5% to 10%, that’s patently wrong. We know that because we’ve seen tons above and below that. Again, if they’re saying the average is a range, that doesn’t make any sense. But if they’re saying they believe the standard is somewhere in that range, again, that’s not very helpful information.

More importantly, why didn’t they say something specific like, “The average is 7% or 8.3% or whatever the number is,” or “Hey, the top quartile is 4% and below,” or “The bottom quartile is 13% and above or 17% and above or whatever the number is”? I mean, those numbers, 5% to 10%, are remarkably round. It’s like somebody was estimating instead of using accurate data.

Consider the references 

When we dive in and look at the references to that article, they have many connections, which is fantastic. I love it when reports reference where they found their source information.

One of the first things we looked at was that the better practices were under 4% in that Change Healthcare article. First of all, we don’t know what “better” means. Does that mean above average, so 51st percentile? Does that mean the 75th percentile? Does that mean the 95th percentile? What does “better” mean? So, first of all, it’s extraordinarily vague.

When we dive in and look at the reference, we see, “Okay, where does that 4% come from?”

Sorry, I have a big truck coming by. I’m sitting outside an airport waiting for somebody while I record this podcast.

The link is nonfunctioning when we dive in to see where that reference for 4% comes from. We can’t get to the source material, that article. If we click on another reference link that supposedly purports to give you the 5% to 10% rate, it takes us to an article with no data. That article references another article as its source material. So we’re being daisy-chained along from one article to the following article to the next piece without ever actually finding a legitimate source for where the data comes from.

Deep dive 

As we try to dig (and I dig and dig and dig) and figure out where the numbers come from, it seems as though somebody got this number from the AAFP (the American Academy of Family Practice Physicians). But I can’t find that. So I google because the links don’t work, or you can’t get to the source material. So I google AAFP 5%-to-10% denials, and I find a source article. That source article doesn’t have any data. It’s just somebody coming up with an estimate.

We have somebody estimating, and then somebody else referring to that. Then somebody else refers to that article that refers to that. Then somebody else refers to the report that refers to the article that relates to somebody else making an estimate. When you say it that way, it sounds ludicrous. But this is common. Everyone daisy-chains estimates referring to somebody else without anybody providing any accurate data.

Why does everybody make up numbers? I think it’s to give it some false sense of credibility by referencing somebody else. If you wanted to run a scam of this type to generate legitimacy where there wasn’t any, you would refer to somebody that seemed natural, who referred to somebody else in a never-ending chain that obfuscated it sufficiently that nobody bothered to dig deep enough to figure out that these are all made up numbers. It’s effectively a scam. It’s a scam to generate credibility, in my opinion.

Use the data accurately

The bizarre thing is, Change Healthcare of all organizations doesn’t need to do this. They have all the data they need to develop an actual number. It’s the largest clearinghouse in the country. That means they have all of the data. They know the denials because they handed them out, they passed them out, they routed through them, and they can count them if they want to. That’s the crazy thing.

They must have billions of transactions that they can use to quantify and come up with a number, and it would be statistically significant. It’s improbable that even if there are some biases where some types of organizations don’t use Change Healthcare, it will better or worsen because they are so large, they have such a dominant market share. They probably have the data. They don’t even offer sample data. Yet, they have the data.

Final thought

Why don’t they give real numbers? Moreover, why don’t they provide an average, a specific number? Also, why is this such a big secret? Why are they, of all people giving a range referenced from somebody else, daisy-chained out from somebody making up several developing a supposed range? I haven’t answered that. We’ll talk about it in another podcast.