Closing RCM Gaps with Next-Gen Laboratory Billing Solutions
Laboratories are dealing with a lot of denied claims, and there’s not one root cause. It’s a combination of issues like outdated laboratory billing solutions, compliance blind spots, and bad data.
Molecular diagnostics has it the worst. For those claims, denial rates are above 32%. RCM teams just can’t work them all. It’s why some laboratories are actually writing off as much as 20% of their earned revenue.
Tony Mancuso, Director of Innovations at Onymos, says, “It is a huge problem for laboratory revenue cycle management, and it doesn’t help that a lot of labs are short-staffed, and they don’t have the bandwidth to manage all of the eligibility checks and prior auths for the volume of claims they’re processing.”
All of this is why a new class of purpose-built technology is emerging, focused on solving upstream workflow challenges that traditional billing software doesn’t (and can’t) address.
Onymos DocKnow validates data at the first touchpoint
The billing process starts at intake. When coding errors, missing documentation, or mismatched data aren’t detected upfront, claims fail downstream. Labs will only discover problems after a denial arrives, weeks later, when recovery is slower and more expensive (or outright impossible).
For these labs, revenue loss is reactive instead of preventable.
DocKnow’s foundation has always been data reconciliation at scale, but our team continues to innovate how data is captured, validated, and analyzed across every laboratory workflow. Today, DocKnow users can automate eligibility checks at the point of intake, instantly generate appeal packets for payers when denials do happen, and much more.
R1’s specialized LLMs optimize payments
One of the biggest sources of revenue leakage in laboratory billing isn’t denied claims themselves. It’s failing to fully understand how payer contracts determine reimbursement in the first place.
Trying to prevent these kinds of losses isn’t just “time-consuming,” it requires specialized expertise in payer contracts and financial modeling.
Or, it did. Until R1 teamed up with Palantir last year to create R37, an applied AI lab for building new technologies that are deployed directly into R1’s RCM solutions. Its “next-generation payer contract analysis” research is finding ways to automate contract analysis for maximizing payments with LLMs.
Waystar’s AltitudePredict transforms claims forecasting
Finding patterns in denials is retrospective by nature. Combined with constantly changing payer requirements, implementing and maintaining process improvements isn’t easy. That’s why Waystar is developing an AI to surface risk identification pre-postmortem.
By applying predictive models to claim data, payer behavior, and reimbursement trends, AltitudePredict helps laboratories identify high-risk claims and potential delays in real time.
Keragon’s orchestration closes the loop
Even when claims are correct and approved, revenue can still slow down or get lost in the handoffs between billing systems, payment gateways, and CRMs.
Keragon’s automation platform specializes in closing those loops by keeping your systems in sync. The moment a payment succeeds, fails, or changes status, Keragon automatically triggers downstream actions and team alerts.
It includes out-of-the-box integrations with over 300 platforms like Docusign, Stripe, and Athenahealth.
The future of laboratory billing is layered, intelligent, and proactive
Laboratories don’t lose revenue in one place.
Preventing that revenue loss means rethinking the processes around the entire lifecycle of a claim, not just at the claim submission itself.
In the short term, solutions like these will be a competitive advantage for the labs that implement them and treat lab billing holistically. In the long-term, they’ll be operational table stakes.
If your team is evaluating ways to close revenue gaps, the Onymos team can help you assess where automation and intelligent document processing can have the biggest impacts.