UChicago Medicine is using automation to move revenue cycle staff away from routine insurance and prior authorization tasks and into more complex cases that require human judgment.
Matthew Kennedy, director of patient access and financial clearance at UChicago Medicine, discussed the health system’s strategy during a panel at Becker’s 11th Annual Health IT + Digital Health + RCM Conference and said the system had significant amounts of manual work tied to insurance verification, prior authorization, imaging and routine procedures.
“We didn’t have anything broken so much as we had a lot of manual work,” Mr. Kennedy said.
UChicago Medicine partnered with a vendor to automate portions of that workload through Epic-integrated workflows. Routine cases can now be checked automatically, while exceptions are routed to staff for further review.
Now the health system is clearing about 95% of certain cases up to 28 days before the scheduled service — roughly 12 days earlier than before.
“It really helped take care of a lot of the imaging work, a lot of those simpler surgeries,” he said.
The technology is best suited for more predictable cases, according to Mr. Kennedy, who said more complex procedures still require experienced employees to review clinical documentation, payer requirements and other details.
“AI is not going to know the clinicals that you’re going to pull,” he said. “It’s not going to know the information to help get that verification or that authorization.”
UChicago Medicine has not reduced headcount as a result of the automation. Instead, employees have been reassigned to more complicated work.
“AI does not mean that you’re going to lose staff,” Mr. Kennedy said. “Your colleagues aren’t going anywhere. They have this depth of knowledge. But we were able to move them to those more difficult things.”
That expertise is being redirected toward areas such as complex surgeries, labor plans, payer follow-up and cases where prior authorization or predetermination requirements are unclear.
Mr. Kennedy also cautioned against treating AI as a fully autonomous solution.
“AI automation is a really cool tool, but it’s just a tool,” he said. “You shouldn’t rely solely on it.”
He said UChicago Medicine maintains teams that review automation results and monitor payer changes rather than simply accepting what technology or vendors return.
“I love skeptics,” Mr. Kennedy said. “AI is not a ‘set it and forget it’ thing. AI is going to make mistakes.”
Those employees can help identify changes in payer rules, portal requirements or documentation standards before they create larger problems.
Mr. Kennedy said successful automation also depends on adoption by employees.
“Implementation and adoption — those are two different things,” he said. “Just because you have that tool, it doesn’t mean that it’s being used appropriately. It doesn’t mean it’s being used correctly.”
For UChicago Medicine, the goal is not to automate every revenue cycle task, but to use technology where it can reliably handle routine work and preserve employee expertise for cases that require more judgment.
“It’s better to put them towards those exceptions, those difficult cases,” Mr. Kennedy said.
