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The subject of net collections seems to be in the ether these days. (For the purposes of this discussion, I’m referring to net collections as the amount your practice is ultimately reimbursed for services it provides, i.e., your net reimbursement after adjustments or credits.) Though it’s long been a staple metric, its usefulness in our high-deductible environment may be in doubt.

Since net collections measures how much of what you’re entitled to has actually been paid, an accurate calculation of it can be invaluable. But therein lies the rub. An accurate calculation of this “simple” metric is increasingly hard to come by.

Practice management systems have gotten much better at tracking multiple fee schedules and comparing them against what we’ve actually been paid–this isn’t the problem. The problem is that more of our reimbursement must now come from patients, so it may take months for any service to be fully reimbursed. If you run a report on net collections for a recent time period, this lag in reimbursement will suppress the average net collected for all your payers.

If you’re running the report primarily to keep an eye on your payers, this lag is enough to make the aggregate data all but useless for that purpose. The report will almost always “show” that your payers haven’t reimbursed as promised, even when the reason is simply that it takes more time to bill patients and for them to pay.

An executive at one of the larger groups we’ve worked at confessed to me that “we don’t even bother with net collections reports anymore. Entering the fee schedules is a waste of time.”

While I can understand the frustration, I think there’s a risk of throwing the baby out with the bathwater. There’s a lot of value in calculating net collections. We want to know–no, we need to know–if payers are reimbursing as agreed. And when slow patient collections drag down the net collections figures, that information is also important to understand. What if patient bad debt is starting to climb? Net collections analysis can help you spot this and take action.

My view is that it’s better to use the aggregate net collections data your system can produce as just a starting point. Recognize what it can tell you and what it can’t. Learn how to interpret the fuzzy signals it’s able to send, and dig into the details manually for clearer understanding.

Here are a few suggestions about how you might do this:

  • Use net collections reports for trend analysis. You probably can’t rely on last month’s net collections as an accurate indication of whether any one payer is complying with your contract. But you can look at last month’s compared to prior months to spot any unexplained change in the collection rate that requires further analysis.
  • Look at lagged data to get a clearer picture. Running net collections reports for, say, the previous year will allow time for patient collections to catch up. If your practice management system reports allow you to run your reports by billing or service date, use these settings to try to capture only claims that should reasonably be paid by now. And if results show a disparity, look at individual patient accounts to figure out whether the issue is slow payment from patients or underpayment from payers. (Then roll those calculations up to see if there are any trends by payer to address, such as if patients from a health plan are more likely to pay slowly or not pay at all.)
  • Use custom fee schedules to check allowed amounts when posting ERAs. Entering fee schedules into the system can do more for you than allowing you to run a net collections report by payer. Your billers should be able to use this data to check if ERAs they’re about to post reflect the agreed-upon fees. Your practice management system vendor may even be able to add a field to posting screens to make this easier for your billers. Or, you may be able to capture this data with a custom report that can be scanned monthly for errors.

Even as our practice management systems get better at tracking data, changes in our environment make the dream of simple metrics to take the pulse of the business elusive. Yet despite this annoying irony, our systems do permit more custom reporting and slicing-and-dicing of data than ever before. We still might not have the dashboards we dream of, with a few metrics that reassure us in seconds that our business is doing fine, but we do get a little bit closer over time. And we do have the capacity, at least, to look at our businesses in more detail, with more objectivity than ever before, as long as we’re willing to put in the time and energy.

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