Revenue cycle leaders discussed practical applications for AI during this week's HealthLeaders Revenue Cycle NOW webinar, highlighting tangible ROI in denial appeals and emphasizing the need for cultural readiness and upskilling staff rather than replacing them.
While many revenue cycle leaders are still determining the best use cases for AI, the technology is already delivering meaningful results in key areas.
During this week’s HealthLeaders Revenue Cycle NOW webinar, sponsored by Waystar, revenue cycle leaders shared their practical strategies for moving AI from a concept to a core part of their operational toolkits.
The discussion, featuring Bill Arneson, Director of Business Operational Transformation at Moffitt Cancer Center; Keisha Downes, Vice President of Mid-Revenue Cycle at Beth Israel Lahey Health; and Christine Fontaine, Solution Strategist at Waystar, focused on where AI is making an immediate impact.
Denial Prevention and Appeals
A primary goal for revenue cycle leaders is denial prevention, and both panelists emphasized that AI is changing the approach from reactive to proactive.
AI helps to "stabilize how we're approaching" coding and documentation, according to Downes. "An account that I code on a Monday is going to get a different type of energy from me that will get on a Friday at 3 p.m.,"
By using AI to flag unspecified diagnoses or documentation gaps, Beth Israel Lahey Health teams can fix claims before they go out the door rather than just reacting when the denial comes back.
Meanwhile, AI has allowed Moffitt to pursue appeals for low-dollar claims that were previously written off by reducing the cost to collect from $50 to $5 per appeal for medical necessity denials, according to Arneson.
"We have had this new AI product in place for not even quite a year – it really went live in January – and we've already seen $500,000 that we were able to collect that we would have written off before,” Arneson said.
The Workforce and Culture Shift
Panelists agreed that AI will allow health systems to upskill staff rather than replace them.
“AI is not replacing revenue cycle teams,” Downes declared. “It's not going to happen."
Instead, she said Beth Israel Lahey Health is moving staff from data entry and validation to roles that require more strategic problem solving.
At Moffitt, whenever a task is automated, staff are moved to more complex work, such as moving from eligibility checks to handling authorization denials.
“AI is here. It’s not going to replace any person,” Arneson said. “It is to amplify the people that do embrace AI.”
Challenges and First Steps
When implementing new AI, panelists warned that the biggest roadblock is not the technology, but the people.
“It always comes down to the culture,” Arneson said. “Does the organization have the will and flexibility to do it or not?”
For organizations just beginning their AI journey, the advice was unanimous: Start small. Chasing massive savings and “implementing too broadly to begin with” can be a mistake that prevents revenue cycle teams from becoming comfortable with a new tool and extracting the most value from its functionality, Downes said.
Arneson agreed: “Just start pushing that snowball down the hill, right? And it can gain speed down the road.”
Luke Gale is the revenue cycle editor for HealthLeaders.
KEY TAKEAWAYS
AI is delivering tangible ROI in denial management, with Moffitt Cancer Center reducing the cost to appeal medical necessity denials from $50 to $5 and recovering $500,000 in previously written-off claims.
Despite fears that AI may replace staff, the technology is allowing health systems to repurpose employees for more complex work rather than mundane tasks.
For health systems just getting started with AI, panelists say that organizational culture is critical and suggest that the jounrey should begin with small steps.