In brief: A not-for-profit health system in the South partnered with Aspirion to improve complex clinical denial recovery without adding significant IT burden. It went live in 45 days, overturned 94% of its complex clinical denials within 30 days, and recovered more than $2.5 million in 11 months, all without a significant IT lift.
Every revenue cycle leader knows the squeeze. Denials keep climbing, and the clinical ones are the hardest to win, often requiring a deep dive into the medical record and an appeal that can stand up to payer scrutiny. Meanwhile, the teams and systems that would normally absorb that work are already at capacity.
Aspirion is a revenue cycle recovery partner that helps hospitals and health systems overturn denials and recover underpaid or unpaid claims, combining AI-assisted record review with experienced clinical specialists.
The short answer: Most health systems can reduce clinical denials without adding IT burden by handing complex appeals to a partner that needs little integration, pairing AI-assisted record review with experienced clinical specialists, and using denial data to fix root causes upstream.
That’s what one not-for-profit health system in the South did with Aspirion. It went live in 45 days, overturned 94% of its complex clinical denials within 30 days, and recovered more than $2.5 million in 11 months.
The health system runs three hospitals, with specialty care spanning trauma, cardiology, and cancer. Like many revenue cycle teams, it was caught in a familiar squeeze. Here’s how it played out, and what other health systems can learn from it.
What challenges were driving this health system’s denials?
The challenge wasn’t a single issue. It was three at once:
- Denials draining revenue. Growing denial volume was cutting into revenue, and leaders needed results without a long ramp-up.
- Stretched IT resources. Hospital IT was already managing multiple vendor integrations, with little capacity left for another implementation.
- Complex clinical appeals. The clinical denials exceeded the in-house team’s appeals expertise and capacity.
It’s a familiar combination. As we’ve discussed before, you can’t hire your way out of denials, and asking an already stretched team to learn yet another platform rarely helps.
Why are clinical denials so hard to win?
A clinical denial is one where the payer disputes the care itself: whether it was medically necessary, billed at the right level of care, or coded to the right diagnosis-related group (DRG). Unlike a technical denial, which can often be fixed by correcting and resubmitting the claim, a clinical denial has to be argued from the medical record.
That makes them slow and expensive to work, and payers are raising the stakes. Many now use AI to flag and deny claims faster than hospital teams can respond, especially DRG and level-of-care downgrades.
How can hospitals recover revenue without increasing staff workload?
Hospitals can reduce the burden on internal revenue cycle teams by partnering with specialized recovery organizations that manage complex denial appeals, use AI to accelerate medical record review, and provide clinical expertise without requiring significant additional IT resources. This allows internal teams to focus on core revenue cycle operations while pursuing previously unrecovered revenue.
How long does it take to go live with a denials management partner?
Timelines vary by partner and integration model, but a partner-led approach that requires little IT work can go live in roughly 6-10 weeks. In this case, the health system was live 45 days after kickoff, with Aspirion leading onboarding and implementation. IT demand was minimal, operations continued without disruption, and staff didn’t have to learn a new system.
That speed matters more than it might seem. Every week spent in implementation is another week of denials aging toward filing deadlines and potential write-offs. A partner that goes live quickly, and carries the work rather than handing it back to your staff, starts recovering revenue sooner.
How do AI and clinical specialists build stronger appeals?
AI reads the medical record at scale and drafts the appeal, and a clinical specialist reviews every appeal before it goes out. That pairing gives payers evidence-backed arguments that hold up under scrutiny. At this health system, Aspirion’s specialists used DocIQ, its proprietary AI platform, to extract the facts that answer each payer’s specific denial reason and draft cited clinical evidence for the appeal.
Payers are using AI to deny claims; this approach uses AI, guided by experts, to overturn them. The AI handles the volume, and the specialist makes sure each appeal stands up to payer scrutiny. It’s a pairing of automation and expertise, not a choice between them.
What results did the health system achieve?
Within 30 days, 94% of the health system’s complex clinical denials were overturned. Over 11 months, Aspirion recovered more than $2.5 million in overturned denials.
Speed and precision reinforced each other. Well-supported appeals resolved faster, and faster resolutions put cash back in the health system’s hands sooner.
Can older unpaid claims still be recovered?
Often, yes. In this case, a one-time review of the health system’s older unpaid claims produced $632,000 of the $2.5 million recovered, about a quarter of the total.
It’s a useful reminder that older, unresolved accounts can still hold recoverable revenue. If your team has a backlog it hasn’t had the capacity to revisit, a cleanup review is worth considering before those claims age past their filing deadlines.
How can denials data help prevent future denials?
Breaking denials out by payer and by denial reason shows where documentation gaps and process breakdowns are causing them, so teams can fix the cause instead of re-appealing the same issue. Aspirion used ClinIQ, its clinical intelligence platform, to share these trends with the health system. The health system’s clinical documentation integrity (CDI) and utilization management (UM) teams then used the patterns to target root causes upstream.
The partnership kept growing from there. The health system’s System Director of Revenue Cycle called Aspirion’s implementation team “responsive, easy to partner with,” and the denials results were strong enough to expand the work into out-of-network recovery and zero-balance review.
What can other health systems learn from this?
Key lessons for revenue cycle teams:
- A fast, partner-led implementation protects both revenue and your IT team’s bandwidth
- Clinical denials need automation for scale and human expertise for accuracy
- A one-time review of unpaid claims can surface revenue that’s been sitting untouched
- Payer- and reason-level denial data helps CDI and UM teams stop denials before they start
Denials aren’t slowing down, but your team’s workload doesn’t have to grow with them. Ready to see what’s possible for your organization? Let’s talk denials, or start with a free assessment.
