“You can’t manage what you can’t measure”
– Peter Drucker
Business guru (legend?) Peter Drucker is famously quoted as having said this. If you’ve ever heard this quote, then at one point you probably thought, “Hey! This is really spot on.”
I’ll be brutally honest – I’m tired of hearing this.
And if it seems odd or even sacrilegious that the leader of a healthcare analytics company would utter these words, then you’re not wrong. I can’t tell you how many times I hear consultants and journalists and other random individuals say something similar to this or quote Drucker in their presentation or article, and then suggest measuring something in healthcare finance.
However, they miss the point entirely. They are typically suggesting that people measure something/anything, just so that they can say they are measuring, rather than using data to solve real business problems. It becomes upsetting after a while to hear this advice get so perverted and cheapened when it is coming from somebody who doesn’t know what they’re talking about, or worse is peddling bad information and something that isn’t going to help anyone.
We should be able to measure an extraordinary array of things in healthcare finance. Finance is by its nature a data business, especially since everything is electronic finally in healthcare. We’re dealing in numbers and data, so we’re swimming in massive amounts of it. And we are capturing all of this information. In theory, measuring should not be a problem. The reality is that the massive amounts of information we are collecting is not being utilized well, or often not even at all.
Every time you go to a conference, or you read some advice article in a healthcare journal there is someone peddling bad advice or their own services. The reverence is such that it is almost suggesting that we all need to bow down to worship data. Remember that we are IN THE DATA BUSINESS, so I’m not knocking the concept or the value of data. However, there is almost an infatuation with the panacea of analytics when in fact most provider organizations are not using them very much.
There is often pressure within a provider or department to quantify performance. Co-workers within the organization, consultants, top management, and others might say “Oh, we’ve got to measure stuff. We’ve got a benchmark. We’ve got to improve. Use data.” Analytics is a buzzword now. Just as the internet boom of the late 90s caused people to invest huge amounts of money into companies like pets.com just because “internet” was hot, many are now investing in bad metrics and analytics because of pressure to do so.
The King of Medical Billing KPIs
The #1 garbage metric is accounts receivable days. It’s not that there is no value to it, but it’s the gold standard and it needs. To come down off of its pedestal. There are other similar kinds of metrics, things as the percentage of AR over 120 days, AR aging distribution, AR days on hand, or AR days. There are many different ways to measure accounts receivable outstanding.
AR Days is one of the most common and is measured as follows:
Outstanding AR x Days outstanding
This gives you a measurement in days like 37, 54, or 146. This is a measure of how old the receivables are that are on the books.
Advantages of AR Days
There are some advantages to this metric, so it is understandable why it has become the gold standard. For one, it’s pretty easy to measure. It’s a simple mathematical equation that any 12-year-old can do. A second benefit is that everyone has access to these data. Every provider no matter how poor their reporting has access. To accounts receivable detail report that includes a DOS and charge amount. Even if it does not include a submit date or a first submission date. And that means anyone and everyone has the underlying data to be able to calculate this. A third benefit is that it measures the speed of resolution of claims, and therefore is not entirely useless.
The benefit of measuring the speed of resolution of claims is that one could detect a significant change. In theory, rapid AR changes could signal a problem in revenue cycle management. For example, a sudden and dramatic increase in AR days for one payer might suggest a contracting or another issue that needs addressing, or if all payers experience this there might be a clearinghouse or EDI problem. This assumes that you have isolated and accounted for any change in volume that would drive that change in receivables.
The last benefit is that accounts receivable days are a universally recognized benchmark. Everybody measures it and everybody uses it. Which makes it the top and one of the few metrics that providers benchmark.
The problems with AR days as a metric are massive. Can you compare Anthem to Medicare? Obviously not. And yet AR days is usually expressed for an entire practice or provider. Orthopedic surgery is a radically different beast than primary care and an E&M compared to surgery also performs extremely differently in RCM. Payer matters. Payer type matters. Specialty matters. Even subspecialties get treated differently.
One example that illustrates the differences that are not accounted for in a simple and often misleading metric like AR days is radiology. Professional radiology read of a chest CT is treated very differently by health insurers than a technical component for the same CT study for an imaging center. A professional component for CT is reimbursed in the mid-two figures; call it $50 for simplicity. The technical component is paid in the mid-3-figures; call it $500. It depends on where you are in the country and which payers you are dealing with, as well as other factors. But one CPT or procedure is reimbursed at a rate that is an order of magnitude higher.
They are treated radically differently by payers in terms of whether or not they’re paid. The frequency of denials and the speed of payments is very different on average for those two. We see this within orthopedic, as well, where the E&Ms get paid more easily than the surgeries. If you have been in this business for any period of time you will likely have noticed the significant differences in ease of payment for lower-priced procedures compared to more expensive ones.
Other factors also come into play. Like whether a provider is contracted with that payer. There are even some payers and plans or plan types who categorically will not pay out of network. Some even have explicitly stated policies to obstruct claim payment, where they may slow it down by stipulating a much longer adjudication cycle, while others have crazy policies that they won’t take an electronic claim submission or send an ERA or EFT. In order to get paid by these payers, you may have to send the claim on paper or via Pony Express. Others have differing timely filing limits for contracted compared to out of network.
Presumably the purpose of calculating AR days is to do one of several things including benchmarking to other providers, across different payers, or something similar in order to take some action based off of that information.
But if one asks, “How worthwhile is accounts receivable days as a benchmark to compare to other providers?”, you may find that it is suspect at best. Most data that you get is broad, comparing a single number like 37 days to another provider. A few organizations may break down this number into groups of provider types so that orthopedic surgeons can compare to others. Even if you could compare it to somebody else who has the same specialty as you, it isn’t very useful at all.
You’re saying, “Okay! BCBS Alabama for orthopedic surgery billing is all the same.” Can you find other providers? That is the same specialty and the same payer and get that data and compare? First of all, you’re not going to be able to get that kind of granulated data. Can you get data that drills down by specialty, subspecialty, payer, and other factors that really matter? Effectively no.
Even if you do, you’re probably still not going to be able to drill down and get useful information. That particular BCBS might be a Medicaid plan, or it might be a PPO, or it might be a Medicare plan, or a Medicaid MCO plan. Those are all radically different in getting paid. And it is still not accounting for other factors, some of which were already mentioned but might even include nuances like getting paid for MRIs within the orthopedic practice different from PT or DME. If you can’t isolate down to all of those variants and compare by CPT, by payer, by plan type, by specialty, by subspecialty, then you are comparing apples to oranges. It’s beyond not helpful, it actually can be very misleading. There’s virtually no value in that data as a benchmarking tool.
A Perverse Incentive
Worse, when it comes to accounts receivable days, it only measures speed to resolution. While I said this isn’t completely without value; it does not measure speed to payment, rate of payment, or anything we really care about.
While an excellent medical billing company or billing department might have fantastic AR days, they are not always causal. A really bad medical billing company or department may also have really good AR days because they write off things quickly. There is a perverse incentive to write off a 9-month-old claim that has some chance of getting paid. It makes billing look bad rather than hang on for another 3, 6, or even 8 months while continuing to fight to get the claim paid. This is especially the case for those problematic payers or procedures that take a lot of work to get reimbursed.
If low AR Days could either mean a really good medical billing team or a really bad one, what value does this metric have? The answer is none. If someone can game the metric so easily, then it serves no purpose.
Growing AR Days – A Warning Sign?
We mentioned earlier that a sudden change in AR Days could signal a problem in the revenue cycle management process. If one an strip out and normalize for any changes in volume and other factors like payer mix, procedure mix, and so on, then this could be a good signal that something is wrong.
However, even if you haven’t had a variance in a volume that accounts for the change in AR, it is possible there was some variance in the speed of claim entry or submission. Imagine a scenario in which there was a slowdown in submissions for some reason and then they got caught up. Perhaps they were short-staffed for some months and then added resources to catch up. That catch-up spike would actually drop your AR days because a large number of claims that had just been submitted would suddenly be weighing down the average and might hide a real AR problem. In an odd analytical feature, your AR would spike up but your AR days would spike down.
Measurements Of Accounts Receivable
The net is AR days, and similar other measurements of accounts receivable are not worthwhile. They certainly shouldn’t be the gold standard. It doesn’t mean you should never look at AR or metrics surrounding medical accounts receivable. However, it is not something you can benchmark against other providers and derive any value. It really should just be one of the relatively small tools that you have in your toolkit and say, “Hey! Can we look at this occasion and see if there’s some problem?” Or put in place ideally a sophisticated early warning system that looks for radical changes in AR, while normalizing for other variables like changes in volume and mix, and sends out a notification to somebody to say, “There has been a significant change in AR. Go check and make sure there isn’t a problem here.”
Performance in Revenue Cycle Management
I think part of why people have looked for and utilized accounts receivable days is because they are desperate to measure something.
Phrenology and phrenologists were once considered to be part of real legitimate science. There were courses and clinical textbooks on this subject in prominent universities. Phenology was the study of the measurement of cranial size in order to measure intelligence. This is patently ridiculous to anyone today, however, it was not always so. There was a time when, since we didn’t have a good way to measure intellectual capacity, we measured the size of people’s heads in order to figure out how intelligent they were.
This is how I would categorize the current state of the revenue cycle management industry – we are desperate to measure something…anything! Absent a really good set of metrics and KPIs that actually matter and are agreed upon, most people will attempt to find a something to measure since we want to understand, measure, compare, and improve medical billing performance.
The king is dead (or at least should be).
If you want better metrics, talk to us, check out our blog, or attend a conference where we are presenting, or take one of our courses. There are far better metrics than AR days.