Wednesday, July 25, 2012

How to Tackle an AR That is Out of Control


Let’s pretend you find that your AR is completely out of control. What do you do? What is the best and fastest way to tackle a major AR problem? I will give you a hint, it is not blindly calling insurance about outstanding claims. That method will get you nowhere fast. Here’s another hint, it is not necessarily calling on the highest dollar claims either. I know that sounds counter intuitive, but it is true. There may be better ways to get more money out of your AR faster. Although, I am not implying that high dollar claims are not worth a attention. What I am saying is you need to look before you leap!

If your AR is completely out of control you have a problem, maybe multiple problems. Blindly calling on individual claims or just looking at big dollar claims does not fix the problem or ensure clean claims in the future. You must search for a root cause. Now, understand I am not implying a blame game. I am talking about starting a large AR project with a thorough analysis of the AR and fixing root problems.

Interestingly, you will find on analysis, you can usually identify a handful of specific problems which can be easily addressed. Addressing those root causes of a huge AR will get dozens of claims paid all at the same time with a single action. Best of all, once you know the root cause, you can make sure it does not happen again in the future. Sound too good to be true? It’s not.. It’s easy! Here’s how.

The first step is to run a detailed AR report from your medical billing software with all outstanding claims equal to or greater than 15 days old (yes, we want relatively new claims too – not just old AR at the same time, don’t include claims that have no chance of even being in the insurance’s adjudication system yet… 14-15 days is about right to make sure the insurance has the claims and they are fresh enough to investigate).

This report should be run for all insurances and include full claim detail including charges, CPT/ICD9 codes, patient name, insurance name, submission dates (if possible)… as many details as you can possibly get about every claim on the AR. Your best bet, is to export the AR to Excel if your billing software can do that. If not, you are in for a more manual process, but it is still possible. I am going to write this post as though you are working on the AR in Excel.  For those that cannot export their AR to Excel, the premise is the same.. just do it manually. But above all, do this before you pick up the phone to call an insurance.

Now that your detailed AR is in Excel, make sure the spreadsheet is organized properly with columns and rows appropriately labeled so the sheet can be sorted without losing or separating information. For example, let’s say that the AR groups claims by insurance company, but does not display the insurance name in each row, like this:



Manually change the contents of the AR report, so the insurance name is listed in each row correctly corresponding with the claim and remove the grouping titles, any redundant headers, and empty rows. After you have added grouping headers to each row, you can quickly remove empty rows and extra headers by sorting the spreadsheet. Make it look like this:



Now that you have a nice clean Excel AR report where rows express the content of each column header and no information is missing in any row where a claim is listed, you can move on. If you are a complete Excel novice and all this is totally lost on you – go learn Excel. There is no more important, versatile, useful software in the entire universe. You can watch tutorials for free on YouTube. You will be glad you did!

Next, we sort, sort, sort, sort… by everything imaginable and look for patterns. I guarantee you, there are patterns. These patterns will lead to the root cause of the AR problem. So…


Sort by CPT: is there one of a few CPT codes that stand out as repeating an awful lot in comparison to other CPT codes?

Sort by insurance: is one insurance massive in comparison to the other insurances?

Sort by ICD-9: is there one of a few ICD-9 codes that stand out as repeating an awful lot in comparison to other ICD-9 codes?

Sort by rendering provider: Does one doctor have more than his/her fair share of the AR?

Sort by submission date: Is there one date (or a few dates) that have massive numbers of unpaid claims

Keep going - sort by everything you can imaging...


I am sure you are starting to see where I am going.  If you see multiple patterns, go after the higher dollar patterns first. If you find a pattern in claims that have minimal value ignore them and look for another pattern. For example, if you find an injectable that generally pays $0.42 is always rejecting… who cares? Ignore it. That kind of claim is not worth wasting the paper the AR is printed on – let alone people time.

So, let’s say the analysis finds that,  regardless of insurance company, there is one CPT code that has dozens of unpaid claims each worth about $100. Now, you call ONE insurance with a recent claim example (maybe two If you really want to double check) and ask why one of these claims was not paid. Guess what… the insurance says that don’t have the claim on file. Hummmm, what to do now? Easy, call the insurance’s EDI department with the recent claim example (submitted within the last 30 days) and find out why the claim never made it to adjudication.

With the insurance’s answer, more than likely, you just learned why ALL of the claims for that CPT weren’t paid. In this type of example, it is likely that the CPT is invalid for the year in which it was billed. Now that you know the CPT is no good, you can correct all 100 problem claims and get them all paid – based on ONE phone call rather than hours of individual calls that just waste time.

Do NOT be deceived. This is NOT the root cause of your AR problem. Yes, we just cleaned up 100 claims in one shot, but a bigger question remains. Ask who, what , when, where, why, and how to find the root cause? Why did this happen? Why did it take so long to find it? Who is responsible for rejections? What processes do we have in place to identify/prevent these problems early? How can we prevent it in the future?

So what is the root cause of this problem? Well, in this example, we called the EDI department and were told that the claim was rejected before adjudication for an invalid code. In other words, you received an EDI report rejecting that claim. Note: codes that are not valid in the year in which the services are rendered are most frequently rejected in EDI reports rather than on EOBs; however, it is possible that the claim will be adjudicated and rejected on an EOB. Either way, the root cause of the problem is that no one looked at the original rejection. Either, the EDI reports are being ignored or denials on EOBs are being overlooked. Now, you have a root cause – address it!

In a nutshell, before blindly calling on individual claims to clean up a massive AR, look for patterns. These patterns will not only allow you to clean up dozens of claims with a single call to insurance, but also help you to find the root cause of the AR problem. Basically, work smarter not harder.



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