More than four in ten medical group leaders say their days in accounts receivable held steady or got worse in 2027, even as operating costs kept climbing, according to MGMA’s midyear polling. For a practice evaluating revenue cycle management software, that single fact reframes the search. The problem usually isn’t that payers are slow across the board. It’s a specific, fixable set of upstream mistakes that keeps restarting the clock on claims that should have cleared the first time.
Practices shopping for revenue cycle management software are almost always trying to solve one of two problems: claims that get denials and have to process through reworking, or claims that sit in accounts receivable long after the visit happened. Both problems share the same root cause more often than billing teams expect, which is also why fixing one tends to fix the other.
This guide covers what’s actually slowing payment down right now, the metrics worth tracking instead of a general sense that collections “feel slow,” a practical framework for closing the gap, and what separates the best RCM software from a longer feature list.
1. Key Takeaways
- Denials, not simply slow payers, drive most aging accounts receivable. An MGMA Stat survey report found 48% of practice leaders name denials and appeals as their largest source of revenue leakage, more than double the 23% who cite front-end issues.
- Days in accounts receivable is the clearest early-warning metric, but there’s no single universal healthy number. MGMA’s own polling found a stable days-in-AR figure can still mask faster claim handling offsetting payer delays or growing patient balances underneath it, so the trend against your own baseline matters more than a fixed target.
- The industry has an automation gap, not just a software gap. Only about a quarter of provider organizations currently use AI tools in administrative workflows, per the 2025 CAQH Index, even though the same report found $258 billion in administrative costs avoided last year through automation already in place.
- Front-desk speed matters as much as back-office speed. MGMA’s 2024 data report found practices collected 72% of copayments at time of service but only about 27% of other patient-due balances, so a real share of “slow revenue” never touched a payer claim at all.
2. Why Claims Are Taking Longer to Pay
Denial rates have climbed every year since 2022. Experian Health’s 2025 State of Claims survey of 250 healthcare revenue cycle leaders found that 41% now see at least one in ten claims denied, up from 38% in 2024 and 30% in 2022. The same survey found 54% of respondents agree denials are increasing at their own organization, not just industry-wide.
The survey also traced the cause. The top reasons for denial are missing or inaccurate data, authorization problems, and incomplete patient information, in that order. Twenty-six percent of respondents said inaccurate or incomplete intake data alone accounts for roughly a tenth of their denials.
Sixty-eight percent of the same respondents said submitting a clean claim is harder than it was a year ago. None of this points to payers becoming unpredictable. It points to a data problem sitting upstream of the claim.
3. What “Getting Paid Faster” Actually Measures
“Getting paid faster” is really three separate numbers, and a practice that only watches one of them usually misses where its own problem lives.
Days in accounts receivable divides total outstanding AR by average daily charges, showing how many days pass between service and payment. Denial rate shows what share of claims a payer rejects on first submission. Net collection rate shows what a practice actually collects against what’s truly collectible after contractual write-offs, which is a more honest number than gross collections because it accounts for what the payer contract actually allows.
Days in AR and net collection rate don’t have one universal healthy number. Both depend heavily on payer mix and specialty, so the more useful discipline is tracking each against your own trend rather than a fixed external target. Denial rate and time-of-service collection do have citable industry benchmarks, since they’re measured the same way regardless of specialty.
| Metric | Healthy direction | Warning sign |
| Days in accounts receivable | Flat or falling against your own trend | A steady climb, even if today’s number still looks fine in isolation |
| First-submission denial rate | Under 10%, ideally under 5% | Above 10%, industry-wide for over half of organizations |
| Net collection rate | Flat or rising against your own baseline | Trending down against your own baseline |
| Time-of-service copay collection | Majority of copays collected at check-in | Well under half collected at time of service |
MGMA’s own polling backs up the trend-over-threshold point directly: a stable days-in-AR number can still mask real problems, since faster claim submission and better follow-up on one side can offset payer rework, staffing shortages, or growing patient balances on the other. A practice with an acceptable-looking blended number but a denial rate creeping toward the 10% threshold in that same MGMA report is hiding a claims problem behind slow-but-steady patient collections. Track the numbers together, and against your own history, not as a single blended score.
4. Where the Time Actually Goes
Most of the delay in a claim’s life happens before it processes through submission, which is exactly why chasing already-denied claims harder rarely fixes the underlying rate. The recurring causes, in the order billing teams report seeing them:
- Intake and eligibility errors. Wrong member ID, lapsed coverage, or a plan change nobody caught before the appointment.
- Authorization gaps. A procedure that needed prior authorization that either wasn’t requested or wasn’t confirmed before the visit.
- Coding and documentation mismatches. The clinical note doesn’t fully support the billed code, or a modifier is missing.
- Slow claim submission. Encounters that sit unclosed for days before a claim is even generated. It adds time before the payer clock has even started.
- Weak denial follow-up. A denied claim that isn’t triaged by dollar value and appeal deadline gets reworked whenever staff has a spare hour. It is often after the appeal window has narrowed.
Each denied claim doesn’t just delay itself. Because a denial is resolved against the original date of service, it retroactively ages the whole claim. As a result, pushing it into an older receivables bucket even though the rework may only take a few days.
5. A Practical Framework for Closing the Gap
Three actions, done consistently, address nearly everything on that list above.
Prevent. Verify eligibility and authorization before the appointment, not after the claim bounces. Build claim scrubbing into the workflow. So, obvious errors, mismatched codes, and missing modifiers are caught before submission. Instead, a payer catches them for you afterwards.
Track. Segment accounts receivable by payer and by age, not just as one blended number. A payer that’s consistently slow needs a different conversation, and possibly a different contract-negotiation approach, than one that’s simply behind this month.
Escalate. Work denials daily, starting with the highest dollar value and the nearest appeal deadline. Furthermore, it also reviews the five most common denial codes each month for a preventable pattern. A denial that keeps recurring for the same reason is a process fix waiting-to-happen, not a one-off to resubmit and forget.
If you’re mapping your own aging report against the benchmarks above and finding the gap larger than expected. Such as, a system that flags denial risk before a claim goes out, with your team still reviewing and approving every flag. As a result, this usually shows where the leak is within a single billing cycle rather than a full quarter.
6. What the Best Revenue Cycle Management Software Actually Fixes
CureAR, for example, doesn’t just move the same manual process onto a screen. It closes the loop between the three actions above so they happen by default instead of depending on someone remembering to do them.
A built-in claim scrubber checks accuracy and completeness before submission, catching missing or mismatched data that Experian Health’s survey identified as the leading cause of denials. Real-time eligibility verification confirms coverage before the appointment instead of after the claim rejection. A denial and accounts receivable dashboard that groups claims by payer, aging bucket, and denial code turns “collections feel slow” into a specific, actionable list, which is the tracking half of the framework above.
Where artificial intelligence adds real value is denial risk scoring. It analyzes a claim against historical approval and denial patterns before you submit and flagging the ones likely to bounce. The distinction that matters here is who acts on that flag.
With CureAR, AI surfaces the risk; your billing team still reviews it, decides whether to correct or hold the claim, and approves what goes out the door. That review step isn’t a limitation bolted-on for compliance. It’s what makes the flag trustworthy to a billing manager who is ultimately accountable for what gets submitted under the practice’s name.
That’s also the practical difference between evaluating software with an AI feature and evaluating revenue cycle management software for a specific practice. The real question is whether the automation makes your team faster at the judgment calls. Mostly the ones which they still make on claims and reimbursement, rather than simply adding another feature to the workflow.
7. Common Misconceptions About Speeding Up Collections
Common misconception: Hiring another biller to work the AR queue harder will fix a rising denial rate.
What is actually true: MGMA’s polling on revenue leakage found denials and appeals accounting for more than twice the leakage of front-end issues. Adding staff to rework denials treats the symptom. It doesn’t touch the intake and authorization errors that caused the denial in the first place.
What to do instead: Put the same effort into the prevent step of the framework above. A practice that reduces its first-submission denial rate needs less rework capacity overall, which is a better use of a billing team’s time than a growing queue of appeals.
8. A Composite Example: Cutting AR Days in a Multi-Provider Practice
The following is a composite scenario built from patterns reported across MGMA’s practice polling, not a specific client result. A multi-provider practice has days in accounts receivable sitting near 55 and still climbing. Tracing the cause turns up two things: eligibility checks that only happened for new patients, and a denial queue worked in whatever order claims arrived rather than by dollar value or deadline.
The practice adds eligibility verification for every scheduled visit and starts triaging denials by value and appeal window, without adding headcount. That combination matches the kind of operational change MGMA’s own poll respondents described when their days in A/R improved.
Unlike the illustrative practice above, this next figure is a real. According to specific data point: one respondent in that same MGMA poll separately reported an A/R overhaul. It took their own days in A/R from 67 to under 34. The mechanism is the same one which we described in the framework above. It prevents what’s preventable, track what’s outstanding by payer, and escalate what’s already denied before the appeal window closes.
Conclusion
Getting paid faster is rarely about chasing individual claims harder. It’s about preventing the errors that cause denials, tracking accounts receivable by payer instead of as one number, and escalating what’s already denied before the appeal window closes. The practices closing the gap in 2027 are the ones treating denial prevention and front-desk collection as connected parts of the same revenue cycle, and evaluating revenue cycle management software on how well it supports all three.
For practices looking to strengthen that workflow, CureAR provides AI-powered practice management with end-to-end RCM software, supporting the journey from appointments and eligibility through claims, denials, accounts receivable, and collections.
CTA
If your days in accounts receivable or first-submission denial rate look closer to the warning column than the healthy one, it may be worth understanding what is driving those numbers before adding more people to work the queue. That is the thinking behind CureAR, an AI-infused practice management and predictive RCM platform designed to connect the appointment-to-payment journey without requiring multiple clearinghouse logins. Its AI-assisted denial risk scoring helps teams identify potential problems before claims are submitted, while keeping the final decision with the people responsible for the claim.
Frequently Asked Questions (FAQs)
polling found that even a stable days-in-AR figure can mask faster claim handling offsetting payer delays or growing patient balances underneath it. Track it monthly against your own baseline, and treat a steady climb as the real warning sign, not just a single threshold.
Industry benchmarking reports put under 10% as the general threshold, with best-in-class practices operating under 5%. MGMA's benchmarking report shows more than half of organizations currently sit above 10%, and first-submission denials have held at 7% to 8% industry-wide across the past several years.
Both, depending on the platform. Tracking alone helps a billing team prioritize, but the bigger gain comes from prevention features like real-time eligibility verification and built-in claim scrubbing that catch the errors before a payer ever sees the claim.
AI-driven denial risk scoring flags a claim by comparing it against historical approval and denial patterns, and your team reviews each flag before deciding whether to correct or hold it. That review step matters because the team, not the software, is accountable for what's ultimately submitted.
A meaningful share. Eligibility errors and incomplete intake information are consistently cited as leading denial causes, and time-of-service collection data shows a large gap between how reliably practices collect copays versus other patient balances, which points to registration and check-in as a real point of leverage.
Reducing denials first. Every denied claim restarts against the original date of service, so it ages the account even if the appeal is resolved quickly. Preventing the denial avoids that aging entirely, while a faster appeal only limits the damage after it's already happened.
Monthly at minimum for the blended number, but high-performing practices review aging by payer weekly for their slowest payers, since a single problem payer can distort an otherwise healthy overall average.
Yes. Time-of-service copay collection already runs well ahead of other patient-balance collection at most practices, and closing even part of that gap reduces the volume of balances that age into statements, calls, and eventually write-offs.
Look for real-time eligibility verification, built-in claim scrubbing before submission, a denial and AR dashboard segmented by payer and aging bucket, and AI-assisted risk scoring that your team reviews and approves rather than software that submits or resolves claims on its own.
