As artificial intelligence and automation transform routine revenue cycle operations, healthcare organizations are restructuring their finance teams around higher-skilled employees who can analyze data, work across functions and drive operational change.

At Becker’s 11th Annual Health IT + Digital Health + RCM Conference, held September 14 in Chicago, three revenue cycle executives discussed what reskilling a finance team looks like after the easiest automation opportunities have been addressed.

Diana Allen, PhD, revenue cycle executive at Springhill Medical Center in Mobile, Alabama, and CEO of healthcare finance technology company SSI Group; Drew von Eschenbach, vice president of enterprise revenue cycle at UW Medicine in Seattle; and Lindsay Myers Bennett, chief revenue officer at Nashville-based Centerstone, shared their experiences with automation, artificial intelligence and workforce transformation.

“WE’RE IN A HEALTHCARE REVENUE CYCLE CRISIS”

Dr. Diana Allen highlighted the growing cost of revenue cycle operations across the U.S. healthcare system.

“We’re in a healthcare revenue cycle crisis,” Dr. Allen said during the panel, moderated by Scott Becker, founder and chief content officer of Becker’s Healthcare.

Allen said she had examined the cost of collecting revenue within her own hospital and found the scale of the expense striking.

Scott Becker noted that the U.S. spends approximately $5.3 trillion annually on healthcare, with nearly 5% of that amount — approximately $220 billion to $250 billion — going toward revenue cycle operations.

Drew von Eschenbach described the fundamental role of revenue cycle teams as converting healthcare services into financial resources that can be reinvested in patient care.

“Our job in revenue cycle is to convert the care that we deliver into cash, so that we can continue the investment and delivery of improving healthcare,” von Eschenbach said.

He added that every dollar spent on revenue cycle represents a dollar that is not directly reaching patient care.

REPLACING 12 POSITIONS WITH 4

At UW Medicine, where von Eschenbach oversees more than 800 revenue cycle employees, the response has not been a straightforward reduction in headcount. Instead, the organization is using employee turnover as an opportunity to redesign positions.

“I’m replacing, say, 12 positions with four, paying them close to equal amounts in terms of overall spend for those 12 into the four, so that we’re hiring a higher-caliber person who understands across the entire continuum of revenue cycle,” he said.

Von Eschenbach compared the transformation to changes in modern military operations, where technology has reduced the need for large numbers of personnel while increasing the importance of specialized capabilities.

He said UW Medicine’s revenue cycle workforce has remained essentially flat even as patient volume has increased.

MOVING BEYOND THE CLAIM-BY-CLAIM QUEUE

At Springhill Medical Center, automation and data analytics are also changing the way teams approach denied claims.

Rather than processing claims individually through a traditional queue, Allen said her team analyzes payer behavior across the organization to identify broader patterns.

“I have taken it upon myself to champion ‘kill the queue,’” she said.

That approach helped the organization identify a pattern involving National Drug Code (NDC) errors that had previously been difficult to detect.

Individual claims were being recorded under different denial reasons, meaning that no single claim appeared to be part of a larger systemic issue.

“When we saw it over 90 days, it was $10 million,” Allen said.

Once the pattern was identified, the organization allocated resources to address and mitigate the problem. According to Allen, such an intervention would not have been possible under the previous claim-by-claim revenue cycle model.

FROM MANUAL WORK TO DATA-DRIVEN DECISIONS

Lindsay Myers Bennett, chief revenue officer at Centerstone, described a similar transition away from manual and transactional work.

“Internal RPA has been working really well,” Bennett said. “We’ve been taking the most painful manual processes and automating that so that our people can focus on more value-added work.”

As automation takes over repetitive processes, the skills required of revenue cycle employees are changing.

“We are shifting away from spending all of our time on compiling data, and we’re shifting forward to using that data,” Bennett said.

She emphasized that employees increasingly need to influence decision-making, communicate with clinical teams and use data to explain problems and opportunities in ways that different parts of the organization can understand.

The objective, she said, is not simply to report numbers but to use data to drive action and improve performance.

THE BIGGEST CHALLENGE: CHANGING HOW PEOPLE WORK

The panelists agreed that implementing technology is only part of the transformation. Getting employees to change established working habits can be more difficult.

Von Eschenbach described the challenge as moving employees beyond their day-to-day comfort zones and encouraging them to think and act differently.

He emphasized the importance of identifying high-performing employees early and supporting them throughout the transformation.

“You’ve got to know who your ‘A’ players are, the people who are high performers, you have high trust in them, and you take care of them,” he said.

Von Eschenbach described these employees as the organization’s “A team” or “SWAT team,” while warning that failing to address performance issues elsewhere in the organization can eventually place excessive pressure on high performers.

SPRINGHILL’S A4 FRAMEWORK

At Springhill Medical Center, Allen developed a structured framework called A4, built around four concepts: agile, automation, AI and architecture.

“I made this up,” Allen said, explaining that she encouraged employees throughout the organization to adopt the framework. Incentives and promotion opportunities were also linked to the transformation.

Full adoption took approximately six months, longer than Allen had initially expected. However, she said the framework ultimately generated a broader transformation than she had anticipated.

One factor she credited for the success was allowing frontline employees to determine how the framework should be applied to their individual roles rather than imposing a single approach from the top.

“Not everyone’s role is the same,” Allen said. “Therefore, their adoption is different. How it solves their problem is different, and they know better than I do where they need to bring that change.”

TECHNOLOGY IS CHANGING THE JOB ITSELF

Bennett said the transformation of revenue cycle operations is changing not only how work is performed but also what organizations expect from their employees.

She stressed that healthcare leaders need to communicate clearly about the scale and urgency of industry-wide change.

“Do all of our team members really realize the urgency and the degree of change across the industry?” Bennett said. “It’s important for us to communicate that, and that inspires people too to keep moving up those levels as the lower levels disappear to technology.”

The discussion at Becker’s conference highlighted how artificial intelligence, automation and robotic process automation are increasingly being used not simply to reduce manual workloads, but to reshape the structure and capabilities of revenue cycle teams.

As routine tasks are increasingly automated, healthcare organizations are placing greater emphasis on employees who can interpret data, understand the revenue cycle across its full continuum, collaborate with clinical teams and translate information into action.

The transformation therefore involves more than adopting new technology. It also requires healthcare organizations to rethink job roles, workforce structures, employee development and the skills needed for the next generation of revenue cycle operations.