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Accounts receivable aging buckets are antiquated. To make sure everybody knows what this is, AR aging buckets are a table that separates the accounts receivable into different aging buckets: 0 to 30, 31 to 60, 61 to 90, 91 to 120, 121+. Sometimes, it’s separated a little more, and it has 180+. It’s grouping accounts receivable claims into buckets by how old they are.
For analytical purposes, it’s tough to look at a table of aging buckets and get a good understanding of what’s happening. I’m very quantitative, and we tend to be very quantitative. Even with that capability, it’s still kind of hard to look at that. Even if it’s broken down by payer, it’s tough to visually look at that and get a good idea of what’s happening. We’re going to compare one period to another and see who’s doing worse or better. If you want to use it for analytical purposes, it might be easier to reduce it to AR days, a single number metric, and compare to each other.
Are accounts receivable useful for analysis?
The point is that accounts receivable aging buckets are not super helpful for analysis. We sometimes convert it to percentages and then try to look at that and do some work off of it. Again, its primary use tends not to be for analytical purposes. The immediate use historically has been to prioritize claim buckets to be worked. So a billing manager or an analyst or somebody like that, typically a billing manager or a supervisor, essentially does an AR aging distribution, puts it into buckets, picks particular buckets, and then decides what to focus the team’s efforts on. They may say, “Okay, for this particular payer, 120+” or “For this particular payer, 90+” or something like that.
One of the most respected analysts in the healthcare practice management world said, and I quote, “The aging pivot table…” Meaning the accounts receivable aging pivot table. It’s somewhat ironic in the sense that if it is an aging pivot table, it’s a little old-school method. “The aging pivot table works well for both billing department managers and staff. Managers may review this pivot table frequently to quickly see the total receivables by aging category, primary, secondary, tertiary balances, provider location, and much more. Billing department staff can use the pivot table daily to make a similar analysis, double-click to show detail, sort the largest balances to the top, and then go to work on the claims.”
Drawbacks of billing systems
The problem is that most billing systems aren’t capable of doing the things that were just articulated. It’s not capable of doing better, and most systems still can’t today. How would you prioritize working individual claims as a department? Maybe, the largest balances first, as was indicated in this area? Perhaps, it’s a combination of factors like large balances over 90 days or for particular payers problematic? This payer over 90 days, large balances. AR aging buckets can’t even really do that. You have to, as indicated here, then pick a payer, hope that there’s a lot of large claims pumped in or something like that, drill down, then sort. Once you’ve got them into the pivot table, double-click, bring up that table, sort again, and then focus somebody on that.
If you had a pivot TablePress with the filter on it that filtered out anything below a certain dollar balance and you only looked at large balances, sure, but the reality is, most billers are not good with pivot tables. They’re unlikely to become quite adept at manipulating these suddenly. More than that, pivot tables get outdated fast. By the time somebody has worked through the first page of balances, it’s outdated. It doesn’t transition well, and it doesn’t communicate back and forth to the billing system very well.
Tracking the billing systems
How do you track what has been worked? Somebody’s going to then work from an Excel sheet. What claims are they going to prioritize? They say, “Okay, work on these claims. Distribute that out to your billers.” Then, you have the billers look at them. They say, “Okay, these are the claims I’m working on today.” And then, what? Manually enter the data into the billing system and not do anything in the Excel spreadsheet? Well, how do you know that they followed what they’re supposed to? How do you then track that? How would you know it’s in Excel, or do they make notes in Excel also? Then, you have duplication of work where you’re losing track of information if you’re not doing that.
There are real problems with this. Because otherwise, this will get to a very long podcast. The net is that accounts receivable aging buckets are outdated, old-school methods of prioritizing and utilizing workflow to deploy resources to tackle and bring in collections effectively.
We’ll do a follow-up on this with the second part of it, so it’s not too long.