Seth Katz of University Health KC says healthcare organizations should train their staff to take ownership of their AI programs and understand what the technology can and cannot do.
Seth Katz fears that misconceptions about AI could harm its adoption.
Katz, vice president of revenue cycle and health information management at University Health KC and a participant in the HealthLeaders Mastermind program on AI in revenue cycle and financial operations, says most current applications of the technology address a few critical pain points.
“If we can automate (redundant tasks), that’s still a win,” he says. “I want them to spend more time negotiating with a payer about an issue, not pulling information out of the electronic health record.”
But not everyone understands how to use AI correctly.
One misconception, he says, is that once a process is automated, you can just leave it as it is. Regardless of their capabilities, these solutions still require accountability and control.
“This is not about reducing headcount. In a way, it’s about avoiding future expenses,” he explained. “It’s about avoiding the costs of increasing headcount in the future.”
Another misconception, he says, is that AI will eventually replace all staff. And that presents an opportunity that could benefit both the organization and individual employees.
As more companies implement these solutions into their revenue cycle, the employees who work with them will be empowered to adopt the technology, Katz says. With this strategy, companies no longer rely as heavily on outside support, and employees can increase their marketability with their knowledge and experience.
“The great thing about this (technological) revolution we’re experiencing is that there are no real experts,” Katz said. “That makes the workforce absolutely marketable.”
Leaders should also build their knowledge of Rev-Tech as they evolve and expand their skills, he says, so they can proactively develop strategies and a governance structure for future implementation and support of future solutions.
However, companies should not rush into automating a process just to achieve this. These solutions are meant to complement the processes already in place, and if those processes don’t work, the investment will have been wasted.
As more and more providers enter the market, Katz believes responsibility should be a priority for all companies.
“(Vendors) need to take some level of responsibility for what happens with their AI or automation,” he says.
“There has to be someone who is responsible at the end of the day if (the solution) causes problems, if it does something wrong, if there are rejections; and that should be the provider.”
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