Will AI help or hurt ASCs?

Artificial intelligence exploded in healthcare over the last 12 months, and surgery center leaders are watching its impact closely. Will AI make surgery centers more efficient or too complex?

"At this point, the jury is out on the full use case in many settings that we work today," said Andrew Lovewell, CEO of Columbia (Mo.) Orthopaedic Group. "There is a lot of excitement and discussion about the future of medicine and the way it will look given this technological boom that we are experiencing. However, I don't look for things to change as rapidly as some are predicting."

Healthcare traditionally is slow to adopt new technologies because the stakes are high. Healthcare is one of the most regulated industries and slim margins mean every technology investment is highly scrutinized.

"If we could find a way to bend the cost curve on cutting-edge technologies, I would expect the deployment and use of AI and large language models to increase exponentially," said Mr. Lovewell. "In fact, as more companies develop AI, machine learning and LLM, I do believe we will see the cost burden lessen as things become more of a commodity in our space."

Brian Curtin, MD, an orthopedic surgeon at OrthoCarolina in Charlotte, N.C., thinks AI is moving the needle in healthcare despite the slower pace of integration, and providers are adjusting accordingly.

"Healthcare trends that have potential to really change the way we do our jobs on a daily basis include the integration of AI and quantum computing into decision-making as well as more individualized specific patient care," he said.

Sap Sinha, COO of Allied Digestive Health in West Long Beach, N.J., said the advent of more AI across healthcare in the operational areas like machine learning in billing or conversational AI with patients and physician support for documenting in the EHR.

"It is just a fast-paced world and organizations have to be vigilant and up-to-date on these topics, including hiring differentiated talent," said Mr. Sinha.

But there are roadblocks. The inconsistent data gathering and reporting across systems, coupled with years of sparse data collection, means AI and machine learning can only take surgeons so far.

"The truth is that AI is not 'intelligent.' It is simply a very fast and efficient and powerful way to search and apply data," said Nikhil Verma, MD, professor and director of the division of sports medicine at Midwest Orthopaedics at Rush in Chicago. "The problem is, if you put bad data in, you will get bad data out. What we are missing in healthcare is large amounts of outcome-driven data in large populations."

Surgeons may track certain populations for research, but not all patients report outcomes.

"This is a huge limitation no one is talking about," Dr. Verma said.

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