How many times have you run into an issue about difficult claims not getting collected? Whether that’s with an in-house billing team or whether it’s an outside billing company, the old issue of hard to collect claims not getting collected and easy to collect claims are getting collected is pervasive and perennial.

What is Pareto concept?

I’m sure you are familiar with the Pareto concept. Most people think of it as the 80-20 rule. To be clear, since we’re data junkies here, it isn’t an 80-20 rule. The concept is that 80% of the output comes from 20% of the work. And the remaining 20% output requires 80% work. That’s, at least in theory, what people say.

The reality is Pareto’s got all kinds of different slopes. Just because people use a rule of thumb to explain a concept doesn’t mean that that’s correct.

Within healthcare specifically and revenue cycle management, it depends on the type of provider you are since some providers have a much harder time getting claims paid. A GP that’s doing mostly E&Ms and basic kinds of things… I’m not denigrating in any way those practices, so please don’t take it that way.

Claim Percentages

There will be a smaller percentage of claims that are challenging at a very far end of the spectrum. It might be something like an out-of-network laboratory where to get the remaining 40% paid. If that ever can happen, requires 95% of the work. It’s an extraordinary problem. If you take out the ones that are never going to be collectible, the remaining 10 or 20% that you can affect change upon might be 95% of the workload. That Pareto does vary quite a bit.

Now that we’ve gotten out of way of the minutia of dealing with that because we get stuck on that kind of stuff ; let’s look at the microeconomics of work with respect to hard claims and easy claims.

Hard claims or Easy claims

An individual biller or collector can, in theory, work hard claims or easy claims. There’s a whole range of activities that they could be doing that we’ve discussed in some of the podcasts, like doing write-offs or checking status. Again, it depends on how you’re sort of structured internally. We’re doing appeals or investigating and identifying widespread issues that might include pulling data or other things.

You can imagine that a harder thing takes more time, obviously, and you get less done per unit time. If somebody works ten easy claims and gets all ten paid, and let’s say you get $100 on average per encounter or claim, you’ve collected $1,000. However, if somebody works one hard claim, and it takes the same amount of time, and they collect $100, that’s not only bad for the collector, but it’s bad for the practice.

It isn’t necessarily bad that somebody is working the quote low-hanging fruit. It would be, in that case, good for the provider to have somebody work ten easy claims, get ten collected rather than one collected. All the other things are being equal.

Claim collection challenges

The challenge is that, of course, it often isn’t that way. It may be that one hard to collect claim might be a $2,000 surgery or $2,000 expected reimbursement surgery. In that case, if it takes same amount of time to collect $2,000 as it does to collect $1,000 claims. You’re better off having them work one claim in that unit of time and getting one collect.

That is where data is needed since it’s virtually impossible for billers or collectors swimming in the data to take a step back and identify what their unit-level productivity is or dollar-level productivity to determine what is better to do.

Incentives can play a role in this, obviously, but as we’ve talked about in other podcasts, that can get complicated and ugly and create some perverse effects.

Tracking claim status

Most tracking of productivity around really psychometric relates to units like worked a hundred claims. Billers will typically work the easiest stuff, even if there isn’t an incentive structure simply because if somebody’s tracking or checking things, that may look better on paper.

If we dive into the sort of psychology from a biller’s standpoint, if you work ten easy claims and get them paid for $1,000 or work one hard claim and have a 50/50 chance of getting that $2,000 claim paid, statistically, those are precisely the same for the practice, which is in one case, you got ten by $100 paid as $1,000. On the other, you got a 50/50 chance, which means you have an expected value of $1,000 and not $2,000. If half of them paid, over time, you work half of them, you get to collect $1,000 on those.

The problem is from a human’s psychology, do you want to work something that may not succeed, where you’ve got a 50/50 chance? We naturally are risk-averse, which means we will work ten easy things rather than one harder thing that has a lower probability of success. They’re just not going to get work. Even if you say, “Well, there’s a 60% chance.” Therefore, the expected value is $1,200 for the hard to collect claim; odds are most collectors would probably want to do the easier ones, not just because it looks better in terms of getting ten rather than one done, but only in terms of risk tolerance.

Collect the hard claims

There’s another nuance that comes into play here, which is a skillset. You have to be very skill to get hard claims collect, including analytical capabilities like pulling data, analyzing data, or problem-solving skills.

Some billers are very good at that. Some are not, including billing managers who are effectively billers who grew up in the business and often did not get enough external training to grow into that role. Suppose a biller cannot do that sort of analysis and figure out or identify, get to the root cause, and solve the problem. There’s a wide variance in that capability. It’s better for that person to say that claim is not collectible rather than saying individually were not capable. It’s much easier to defer the blame to something else or “Hey! The payer screwed this up!” or whatever it might be.

Another aspect involves sort of that Pareto concept, which is there may often be diminishing returns on things. If you work ten easy claims, then the next set is a little bit harder. And the next set is a little harder until you get to the hard to collect claims. Doing things in sort of that cascading, descending order may be good. However, you may quickly run into a problem where they don’t realize that they’ve gone off that cliff. They started down a good path of working sort of easy to collect claims, and then suddenly, those $100 claims are harder to collect. They are not working the $1,000 claim that should be not that different in terms of probability but dramatically better in terms of expected value.


Low-hanging fruit is an apt metaphor since going after the easiest stuff is typically beneficial for the practice when there’s a limited amount of resources. This is a crucial point. If you have a fixed number of resources and they are capped out, they’re wholly maxed. There is the stuff that’s falling off the plate virtually, where things are not getting done every month, then you want to maximize the output, which is collections, by doing the easiest to collect first. Simplification, of course, of some things. What I mean by the easiest is the greatest dollar collection per unit time. That’s being the definition of “the easiest first.”

You want collectors to work the low-hanging fruit but that assumes limited resources, which is the critical assumption.

I think you want to be able to identify, “Is the limited issue resources? Would it be worthwhile to add additional resources, whether in an in-house billing department to increase collections? If you had a little more time, would they work the harder to collect stuff. The more resources to then dedicate towards the hard to collect stuff that would generate significant revenue and be a positive return on investment?” That’s the critical question, which I’m identifying. Again, all comes back to data on having those things to determine the right decisions to make in this arena.

That’s our rant on low-hanging fruit, but that’s virtually why typically hard to collect claims are not collect. It’s because there is a resource limitation, naturally, and that means people go after the easiest stuff first, and then there are those other factors as well.


For more information from Please subscribe to our blog. Enter the details below and click on "Subscribe" button