Case study: Tend uses Amperos’ AI agents to accelerate cash while reducing cost to collect
by Amperos Health
Fast growth can put substantial stress on, or even break, a provider group’s RCM operations. Adding locations increases claim volumes, which in turn can lead even a top-notch in-house RCM team to fall behind. As AR starts to grow and age, the risk of write-off grows, and for a fast-growing dental service organization (DSO), that cash is needed as soon as possible to fuel growth.
Tend Dental faced this exact problem, and they turned to Amperos to help solve it.
The challenge
Tend’s clinical footprint was growing fast, with new clinics opening in major cities across the country. This growth led to a massive backlog of claims. As new locations opened, outstanding claims grew faster than their in-house RCM team could work them, leading to a growing AR balance.
Then came the problem of the claims themselves. Many of the outstanding claims carried small balances, or required relatively simple follow-up work – not the kind of work that is the best use of time of a tenured, onshore RCM specialist’s time. Paying experienced staff to work these claims is an expensive way to run a collections operation, and at scale, can drive cost to collect to start eating into margins.
For a growing clinic – regardless of whether that growth is organic or the product of M&A – collecting cash on time provides the capital needed to keep expanding. Delayed collections always means less capital to grow the business, and if unaddressed for too long, they can become write-offs that impact both top-line and margin.
Given Tend’s rapid growth, their RCM team saw a need to modernize their AR follow-up and denial management operations to rapidly scale claims worked, while also decreasing cost per claim worked and maintaining quality.
The solution
Tend partnered with Amperos to deploy our AI co-sourcing solution across first-touch denials and AR follow-up.
Amperos worked their outstanding claims end-to-end by calling payors, navigating payor portals, submitting appeals and resubmissions, and more. In turn, claims that required provider input (e.g., for medical records or narratives) were routed back to the local clinic. In turn, that allowed Tend’s in-house RCM team to focus on older and more complex claims, where their team’s experience made the biggest difference. That translated into a lower cost to collect for lower complexity claims, allowing the RCM team to use resources more efficiently as they scaled to support Tend’s overall growth.
The results
“Our clinical footprint was growing on a monthly basis, so we knew our existing in-house RCM approach was not scalable. Using Amperos, we first worked through 30+ day AR and reduced that by 42%, and then shifted ongoing claims to Amperos, reducing our cost to collect by 60%.”
– Joanna Fritz, Director of RCM, Tend
Tend achieved three key results through their partnership with Amperos:
42% reduction in 30+ day AR. Amperos helped Tend clear the existing backlog quickly, preventing claims from being written off and accelerating cash flow into the business.
60% lower cost to collect. Tend shifted its ongoing claims volume to Amperos, lowering cost to collect for those claims.
98% QA score. Amperos followed Tend's SOPs at a level of accuracy in line with – or exceeding – that of many AR specialists. Lower cost did not mean lower quality.
What other growing practices can learn from Tend
Historically, doubling your team’s clinical footprint meant you had to simultaneously manage a growing AR backlog and hire more RCM specialists – which can take months.
With Amperos’ AI co-sourcing solution, a digital workforce can work claims end-to-end, following your SOPs, at a fraction of the cost.
That means you can have your staff focus on the most complex claims while routine and ongoing denials or AR follow-up goes to Amperos.
RCM capacity is a growth constraint for many multi-site practices. It doesn’t have to be.
Learn how Amperos can help you recover outstanding claims five times faster, at half the cost. Book a demo today.
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