If you read nothing else:
There’s no universal “good” patient collection rate. Instead, focus on consistently measuring your own performance over time—with a methodology that reflects the reality of your operations and your population.
“What’s a good patient collection rate?”
It’s the number one question we hear from healthcare revenue cycle leaders, and we get it. In a field chock full of metrics and benchmarks, it’s natural to want to understand where you stand. Especially since patient collections are becoming more and more (and more!) critical to your overall financial health.
But when I hear this question—or worse, when someone claims there’s a “standard” collection rate for the industry—it signals a misunderstanding of just how complex the patient financial experience really is.
Why we don’t benchmark collections
Over the years, we’ve reviewed hundreds—if not thousands—of patient collection rates. And the truth is, there’s significant variation in these numbers, driven by a multitude of factors. Most importantly, the methods used to calculate these rates often differ dramatically.
Even among providers that operate in multiple states with centralized business offices, standardized procedures, and consistent apples-to-apples methodologies, we’ve seen more than 700% variability in collection rates between different states within the same organization.
That kind of gap points to more than just “opportunity.” It underscores the need for deep analytics to understand why patients in different regions resolve their bills at such vastly different rates—and, crucially, what you can do to tailor your engagement strategies.
But before you can act on those insights, you need a reliable, consistent way to measure your collection performance—over time and across all facilities.
Our recommended methodology
After evaluating numerous approaches across many providers, we’ve found one methodology that provides the most reliable and actionable measurement:
Collection rate (%) = posted post-visit payments in month ($) / first statement amounts ($)
Why this works best:
Pro | Benefit |
No maturity period | Enables faster measurement and quicker issue detection |
Clear billing cycle anchor | Uses the first statement date as a reliable starting point—ideal for year-over-year comparisons |
Captures operational impact in real time | Allows for quicker decision making to implement changes |
Eliminates visit-date dependency | Provides consistent measurement regardless of how long it takes patients to receive their first bill, which can vary dramatically |
No data timing pitfalls | No complications tied to the timing of data pulls or dunning cycle completion |
The challenge: The numerator and denominator are not directly correlated (i.e., the amount sent to patients in April may not be paid until July). This can create swings following backlog reduction efforts or due to seasonal fluctuations.
The fix: Aggregate posted payments over a rolling 12-month period to normalize these fluctuations and provide more meaningful trend data.
Alternative methodologies we tested
We’ve considered them all. Some offer useful supplemental views, but most don’t hold up on their own. If you have strong data capabilities, consider layering one or more of these alongside the recommended method:
Method | Best for | Drawback |
Lagged billed amounts 1-2 months | Organizations that want more accuracy without long maturity periods | Creates potential for misinterpretation and fails to address patient payment correlation issue |
Netting out non-bad debt adjustments and discounts | Understanding true collection performance on final patient liability | Adjustments have long maturity periods, delaying insights |
Matching collections to billing month | Analysis of actual performance by billed amount cohort | Takes too long to mature for operational decision-making |
Collections by aging buckets | Quick measurements and tactical interventions | Can mask overall performance (e.g., payment plans may reduce 30-day rates while improving overall collections) |
Bottom line
We all want a clear sign that we’re on the right track. A benchmark to aim for. A number that says “you’re doing great!”
But your collection rate isn’t a grade on a report card. It’s a fingerprint—uniquely yours, shaped by your specific patients, processes, and regional dynamics. The right methodology gives you consistency, and helps you answer the question that really matters:
“Are we getting better at helping our patients pay their bills?”
That’s when your patient collection rate stops being just another metric and starts becoming a tool for meaningful improvement.
Alli Eschbach is Senior Director, Value Analytics at Cedar