In an interactive session at the 8th Annual Becker's Health IT + Digital Health + RCM Meeting, Bradford Kuntscher, head of strategic growth at Iodine Software, a machine learning and artificial intelligence technology company, discussed the potential of AI in healthcare.
Mr. Kuntscher highlighted the importance of AI in improving efficiency and productivity, particularly in the middle of the revenue cycle where complex clinical workflows are required. He also emphasized the need for AI to be able to explain its predictions to ensure trust and widespread adoption, as well as its potential to reduce labor costs and increase top-line growth. Session participants also shared their questions and comments, expressing varying levels of optimism about the future of AI in healthcare.
Editor's note: Quotes have been edited for length and clarity.
Key takeaways:
1: AI technology in healthcare can help optimize financial resiliency — and internal teams — by removing unproductive work, improving documentation accuracy and reducing denials.
Bradford Kuntscher: "The middle of the revenue cycle is where things get interesting because that's where you've got seasoned clinical nurses, for example, who every day are painstakingly doing clinical reviews to make sure we're getting paid appropriately and quality metrics are maximized … How can we take a team of 10 and help them operate as if they're a team of 30? It's more about supercharging and augmenting the people we have as opposed to replacing them."
2: Before engaging in partnerships, healthcare organizations should apply a critical eye to technology companies.
BK: "Push them on those questions: What are your results? Who are you serving? How mature is the model? It takes time ... It took us a decade to get to this point. There's no silver bullet or shortcut for this. And so I would recommend asking those tough questions."
3: AI should be applied to the revenue cycle strategically to maximize efficiency and help healthcare organizations do more with less.
BK: "For many of the people in this room who may be pushing out your technology to what we say are the front- and back-end revenue cycle — those are the easy ones, the scheduling, registration, back-end billing, claims status authorization. A lot of that is stuff Epic can build rules in, and you can do on your own. But the areas of the revenue cycle where clinical workflows are more complex, that is truly where AI needs to be, so it can affect the backend."