Show and Tell: AI Gives Revenue Cycle Leaders a Chance to Make Healthcare Better

In this week's The Winning Edge webinar, sponsored by FinThrive, panelists discussed how revenue cycle teams are using Ai across the enterprise, reducing administrative inefficiency and opening up opportunities to improve clinical care.

Health systems and hospitals are scoring some early and significant wins in applying AI to revenue cycle management. Executives hope to continue that momentum as they apply the technology to clinical and payer relations.

Stephen Rinaldi, SVP and Chief Revenue Officer at UNC Health, says the North Carolina-based health system is leveraging AI across the RCM spectrum, including appointment and referral matching, patient financial eligibility and verification, and coding. They're also training the technology on denials and prior authorizations.

In short, AI is giving executives an opportunity to show just what goes into the revenue cycle management process.

"A lot of people think of revenue cycle as [just] being billing, even though it's the smallest piece of what happens in the revenue cycle," he says. "You have to take a step back and realize that it's [also] patient access and registration, as well as clinical documentation improvement, or utilization management and review, and partnership with providers, which is part of revenue cycle. It's at the elbow and it's side by side."

Rinaldi took part in this week’s The Winning Edge webinar, titled “Revolutionizing Revenue Cycle Management With AI" and sponsored by FinThrive. He and John Landy, FinThrive’s Chief Technology Officer, discussed how AI – particularly generative and agentic tools – is addressing key pain points in RCM and opening the door to new strategies.

Together, Rinaldi and Landy outlined five key areas in which AI is now being used:

1. Reviewing payer-provider and managed care contracts. Many of those contracts are thousands of pages long and revised often, making it difficult for healthcare leaders to stay on top of those programs. Providers are now using AI to review those contracts and point out everything from deliverables to discrepancies.
2. Prior authorizations. A process often fraught with back-and-forth phone calls and e-mails is ripe for improvement. AI can be used to identify when and where prior authorizations are required, help clinicians with the information needed for prior auths and even draft the correspondence to the payer.
3. Denials and underpayments. A key pain point in healthcare, according to Rinaldi. Providers can use AI to anticipate and address denials and underpayments, working with clinicians to improve care processes and reduce any opportunities for denials. In addition, AI can be used to track payer trends to better understand when and why denials and underpayments are issued, again in hopes of avoiding them.
4. Cash flow forecasts. RCM executives need to be able to determine cash flow over key time periods, such as 30, 60 and 90 days in advance, to react quickly in the event of an emergency and to chart the organization's financial health. Some are now using AI to analyze and chart that data, giving leadership more insight at a time when economic uncertainty is a daily concern.
5. Patient financial forecasting. Both Rinaldi and Landy pointed to this as an area for future growth. RCM departments are using AI now to analyze a patient's financial health, ranging from insurance coverage to ability to pay. Rinaldi points out these tools could help RCM staff work with patients to better identify when they might qualify for financial assistance or medical debt forgiveness.

Both Rinaldi and Landy see Ai helping to improve collaboration between the RCM team and clinicians, especially as the technology is used to plot disease identification and diagnosis and care pathways. Adding RCM to that process, they said, can help predict and address payer interventions and pinpoint opportunities for reimbursement.  

"We've got to have the positions at the table, our tech partners and our revenue cycle leaders, in order to drive the organization forward," Rinaldi says.

But Rinaldi also says the increased availability and use of AI by consumers will drive RCM strategies. Patients will use AI, he says, to shop around for care, comparing prices and data on provider quality and reviews. Healthcare organizations will not only need to beef up their transparency and patient portals, but be prepared to have some delicate conversations around cost of care.

"We have to recognize that often that first person that a patient interacts with is a revenue cycle person, whether it's coming up to the ED, calling for an appointment, or showing up for an ambulatory test," he says. "We'll have to balance the sensitivities that are occurring around that."