How will radiology providers be reimbursed for investing in AI?
Countless studies have explored the colossal impact artificial intelligence (AI) will have—and, in many ways, is already having—on radiology. But who is ultimately going to pay for it?
Kurt Schoppe, MD, of Radiology Associates of North Texas in Fort Worth, Texas, explored this very question in a new commentary published in the Journal of the American College of Radiology.
“We cannot know when AI will arrive commercially, how we will use it precisely, what it will do for us, or how it will ultimately affect radiologists and patients,” he wrote. “Research grants and investor dollars will only go so far. Unless the business of healthcare changes rapidly in the next few years, someone will have to pay for all of these AI tools as numerous companies create them.”
Schoppe noted that practices seeing reimbursements through CPT codes anytime in the near future codes may be difficult due to the peer-reviewed research and widespread use typically required to get such a code created. If AI tools do get CPT codes, he added, it would then need to be valued by the Relative Value Scale Update Committee (RUC) so that RVUs could be assigned.
“When this new CPT code for an AI tool comes to the RUC, the first question will be whether there is any physician work involved,” Schoppe wrote. “The RUC values the professional component of a medical procedure based upon the work of a physician. The primary components of physician work include the time it takes to perform the service, the level of technical skill required, and the mental effort and judgment necessary. For most AI tools I have seen, there is minimal to no physician work.”
Some AI work could end up receiving a value similar to computer-aided detection, he added. But for many AI applications, “there is no physician work to value.”
Another factor working against radiologists being properly reimbursed for AI investments is the way RVUs are calculated for direct and indirect practice expenses. Medicare, for example, only recognizes computer monitors and the CPU tower that runs the software as direct expenses related to operating a PACS. Everything else gets treated as indirect expenses. AI applications, Schoppe explained, could very well end up being “bureaucratically mischaracterized” just like PACS.
The Hospital Outpatient Prospective Payment System (HOPPS) doesn’t offer the specialty a ton of hope that it will be properly reimbursed either. The way that HOPPS payment rates are calculated could lead to the costs associated with AI being significantly diluted.
At the end of the day, Schoppe concluded, investing in AI may just become “a cost of doing business like other operational expenses.” And if that’s the case, it could have serious implications on how quickly facilities throw their money behind AI technologies.
“If AI is an unreimbursed business expense, it changes the potential return on investment for all of the outside money that continues to pour into companies creating products using AI,” Schoppe concluded. “When even the troglodytes of radiology see a future with AI benefiting both patients and the specialty, we should perhaps temper our enthusiasm because of these financial realities. The barriers to entry for new products and services in health care are high, and for good reason. But without the promise of governmental largesse or large inflows of reimbursements from private payers, vendors may take a pass on investing resources in radiology or health care-specific applications for AI.”
Michael has more than 18 years of experience as a professional writer and editor. He has written at length about cardiology, radiology, artificial intelligence and other key healthcare topics.