If you build it, they will come: Experts believe reimbursement will follow AI implementation

If you implement AI, will reimbursement come? Just like Kevin Costner’s character in the 1989 hit "Field of Dreams," many imaging stakeholders are mulling whether their efforts will reap any sort of benefits.

This was the question that was debated during a panel discussion at the annual meeting of the Society for Imaging Informatics in Medicine’s annual conference. 

The panel, stacked with experts in the field of imaging and informatics, unanimously agreed—if you build it, they will, in fact, come. Tasked with cracking the code to the issue of implementing AI in medicine alongside dwindling reimbursement rates, every member of the panel pointed to history to back their take. 

“Historical analysis is important. In history, billing came later,” said Saurabh Jha, MBBS, MS, associate professor of radiology at Penn Medicine, who pointed to the previous integration of PACS software, which quickly became a mainstay as the use of film images faded. 

When PACS systems first emerged, radiologists adopted the technology because it improved their workflows and made them more efficient long before it became standard practice. It took a few years, but reimbursement for the technology eventually followed and PACS became a staple in nearly all imaging departments.  

Jha believes that AI is likely on the same path. 

Lots of products, few payments 

The U.S. Food and Drug Administration includes nearly 900 products on its list of approved artificial intelligence- and machine learning-enabled medical devices, the majority of which are tailored to radiology. Despite this, AI algorithms are still not a mainstay within radiology departments. 

This could be, in part, due to the lack of reimbursement for such technology and decreasing payments to the specialty in general. After adjusting for inflation, the American College of Radiology estimates that Medicare reimbursement to radiologists has plummeted nearly 32% since 2005. What's more, the Centers for Medicare & Medicaid Services (CMS) has assigned payment for just around 10 of the AI/ML devices that are currently approved. 

How can stakeholders advocate for reimbursement? 

During the panel discussion, Jha said that if AI makes radiologists better at their jobs, it should be adopted without getting too deep into return-on-investment (ROI) calculations because the return will be felt in other ways.

Joseph Cavallo, MD, MBA, an assistant professor of radiology and biomedical imaging at Yale School of Medicine, agreed, noting that the current absence of reimbursement should not deter stakeholders from exploring how AI can improve their practices. Reimbursement for the use of AI will be the exception more than the rule, he said. 

“Some CPT codes have been created, but AI as a whole is going to have to be like PACS was for radiology for a while. Improving workflow and efficiency for radiologists now will result in ROI and gains in the future,” Cavallo suggested. 

For those hoping to implement algorithms into their practice, Eliot Siegel, MD, chief of imaging services at the University of Maryland School of Medicine, said that conversations related to payments for AI-based tools are increasing at the federal level. 

Like Jha, Siegel, believes that AI algorithms are on a similar path as PACS. 

“It took a small number of years, but eventually people realized film wasn't practical anymore. The same will happen with AI,” he said. 

Read more about commercially available AI products at work below.

Hannah murhphy headshot

In addition to her background in journalism, Hannah also has patient-facing experience in clinical settings, having spent more than 12 years working as a registered rad tech. She joined Innovate Healthcare in 2021 and has since put her unique expertise to use in her editorial role with Health Imaging.

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