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What is a denial recovery rate? Denial recovery rate is a metric. By the way, this is going to be one of those rants, podcasts again. Denial recovery rate is a metric that many hospitals and provider organizations use to quantify how well they’re doing to overcome denials effectively.
Understand what denial recovery means
The definition of denial recovery rate effectively is the collections or the dollar collections as the numerator divided by the denominator, which is charges of denied claims. In other words, you take the total number of denied charges in dollars in the denominator, and you take how much money you collect from those claims that were denied and put that in the numerator, and you get a ratio, a percentage.
Why is this a flawed metric? Why is this so poor even though it’s pretty standard in the industry? Well, the main reason is that you’re effectively combining two different metrics. The first is the denial success rate. In other words, how do the denials get overturned effectively and collected upon? And the second is a gross collection rate. We’ve railed on the gross collection rate before.
So, in this case, yes, a gross collection rate is terrible, but I think the more significant issue is that you’re mixing two different metrics. That makes things very confusing and not at all illuminating.
Does anyone know what a good rate means?
For example, is 20% good? Is 40% good? Is 60% good? I have no idea, and neither does anybody else. You can’t know whether or not a number is good because it’s not absolute. It’s not comparable to other organizations. It’s not on a 0-to-100 scale.
What should you target?
Again, should you be going for 30%, 40%, 50%, 60%? In theory, you should be targeting 100%. Because that’s the whole round number, that would make sense linearly approach and target 100%. But the answer is nope. Again, because you’re combining two different metrics. When you do that, then you no longer have 100% as the target. If it’s not 100% as a target, what should be the target? Again, no idea.
Compare and contrast
The other part, of course, is, since you have this fundamental problem, you can’t compare this metric to other providers. You can’t benchmark it against other providers. If you can’t compare it and benchmark it, again, what’s the value? You don’t even know what you’re shooting for? You don’t know how to compare it to anybody else.
Why do people use this metric? First of all, and we’ve talked about some other metrics very similar to this in some other podcasts, it’s essential to have a metric that says how well your revenue cycle management team is performing in dealing with the denials that come in. So you have the “How bad are we?” in terms of “How many denials are we getting?” And then, we have the “How good are we at fixing the problems that either the payers created, or the clinicians created, or that we somehow created?
What about denials?
However they are created, are we able to fix the problems that were created?” So it makes sense to have a metric in that arena that shoots towards, “Okay, how are we doing on denials?”, not just the creation of denials, but overcoming denials.
Why this metric precisely, in any case? Why would somebody use this denial recovery rate metric or KPI to accomplish that goal? From what we’ve seen, the first is that there is generally a bias towards dollar metrics rather than count metrics in healthcare revenue cycle management. That means rather than somebody saying, “Oh, 36 or 2,412,” we want to know 1 million, 7 million, 12.4 million.
Show them the money
People like to see dollars because they want to translate the count into an impact. That makes sense. I get that. Wherever possible, it does make sense to convert a count or percentage or something else into dollar metrics because then you are quantifying the impact of this, and that’s great. So there is that general bias. That’s one of the reasons why it leads towards this.
The second, I think, is the more prominent reason, and this is the problem. If people have calculated their denial rate, not denial recovery but the denial rate, on a dollar basis, meaning, “How much do we have in denials? We had 3 million in denials last month. We had 7 million in denials,” whatever the dollar amount was, then we need to calculate the denial recovery rate on a dollar basis to be consistent.
Okay, I follow that logic. But a famous person once said, “A foolish consistency is the hobgoblin of many small minds.” We shouldn’t lock ourselves into consistency when it hobbles us when it causes more problems than it helps.
Indeed, we should keep that perspective and say, “Hey, all other things being equal, or if it works, great, let’s do that. But if not, abandon it and use what works more effectively.”
How to approach unpaid denials
The more significant thing is, this misses the goal. If you’re trying to eliminate unpaid denials, effectively getting those denials all paid or prevented, you should have something that gears you towards 100% or all of them or something that allows you to figure out, “Okay, yeah, it’s working,” or “It’s not working,” or “We have some target, a quantitative target,” whatever it might be.
Again, and we stressed this many times before, you have to start with the question that you’re trying to answer and move forward from there, not just follow through with some consistency, “Okay, we’re going to do this metric because it’s consistent with other metrics we’re doing, and somehow we should be.” And then, is anybody using that metric? I mean, what are we doing with that metric then?
There should be some action taken from that. That means it should be understandable by everybody. It should have easily understood targets. We should be able to compare it across providers to be efficacious. That’s my rant on why a denial recovery rate is a lousy metric.