As healthcare leaders assess the forces reshaping the revenue cycle workforce, connecting with younger employees is an increasingly valuable skill set. Some of those employees, as Mayo Clinic’s Nikki Harper pointed out during Becker’s IT + Revenue Cycle Conference, are unfamiliar with typewriters — previously a key RCM tool.
“Those early careerists, they don’t want to do anything that’s manual,” said Ms. Harper, chair of revenue cycle, AI/automation, analytics and diversified revenue at the Rochester, Minn.-based system. “They have grown up in a world in which everything is on their smartphone in front of them, and they’re almost scared to make a phone call. They don’t want to make a phone call to an insurance company. They don’t want anything to do with paper, and they certainly don’t want to do anything where they are going to log into a website, look at something, copy the status, put it back in and put it into the EHR system.”
Ms. Harper and two other leaders on a Sept. 17 panel at the event shared who health systems look for, where they look and how they train them once hired.
Dan Angel, vice president of revenue cycle and managed care contracting at Pensacola, Fla.-based Baptist Health Care, said tenure and technical background matter less than before.
“I don’t think you need necessarily someone to come in with 20 years of customer service experience or billing experience,” he said. “Individuals who can adapt to change, can adapt to technological change, are curious and think outside the box [are valuable]. Analytical skills, I think, are going to be very important in the workforce of the future.”
On where to find that talent, Ms. Harper said Mayo Clinic has largely stopped recruiting for entry-level, manual data-entry roles altogether.
“It’s going to be harder and harder to find the talent if we don’t evolve through automation and AI and using our EHR the way it’s designed,” she said. “So for us to be able to recruit, we have to make it something that they’re interested in.”
In practice, she said, that has meant building fellowship and internship programs and a “citizen developer” track that puts early career hires to work on prompt engineering and data storytelling rather than claim status lookups.
Training looks different depending on which segment of the workforce is involved. For existing staff, Ms. Harper described splitting teams by career stage: early career employees drawn to the AI and analytics work already underway, a midcareer group she said faces the steepest pressure to adapt or risk being left behind, and staff nearing retirement whose institutional knowledge is often “not written down on paper” and at risk of exiting with them.
For that last group, Mayo’s approach is to have them help translate their workflows into training material for the automation replacing parts of their job. For everyone else, Ms. Harper said Mayo built a Citizen Champion program with a self-directed structure.
“You’re going to pick your path,” she said the program tells employees. “You’re going to power your progress forward, and you’re going to make a choice here.”
Mr. Angel said his system’s approach leans on career ladders rather than the certificate programs revenue cycle departments have traditionally built with community colleges. As automation takes over more transactional work, he said, it opens room for more analyst-level and exception-handling roles, which he expects to help with retention.
“I don’t think automation is going to take over the talent or replace the talent,” he said. “You still need a good, engaged team.”
Ankit Rohatgi, MD, vice president of physician advisory and utilization management at Cincinnati-based UC Health, described a parallel shift specific to physician advisers, who review medical necessity determinations. As payers lean more heavily on AI to flag or deny claims, Dr. Rohatgi said the physicians reviewing those decisions need enough technical fluency to challenge an algorithm’s output, not just clinical experience.
“They don’t need to be [data] scientists, but they need to understand the dashboard, the clinical workflows and also challenge the recommendations” made by AI tools, he said.
