Getting Paid for AI – Will It Get Easier?

Reimbursement is one of the major stumbling blocks holding back wider clinical adoption of artificial intelligence. But new legislation was introduced into the U.S. Congress last week that could ease AI’s reimbursement path. 

For AI developers, getting an algorithm approved is just the first step toward commercial acceptance. 

  • Perhaps even more important than FDA clearance is Medicare reimbursement, as healthcare providers are reluctant to use a product they won’t get paid for. 

Reimbursement drives clinical AI adoption, as evidenced by a 2023 analysis listing the top algorithms by CPT claims submitted (HeartFlow Analysis topped the list). 

  • But CMS uses a patchwork system governing reimbursement, from temporary codes like New Technology Add-On Payment codes that expire after 2-3 years to G-codes for procedures that don’t have CPT codes, on up to the holy grail of medical reimbursement: Category I codes. 

The new legislationS.1399 or the Health Tech Investment Act – would simplify the situation by setting up a dedicated Medicare coverage pathway for AI-enabled medical devices approved by the FDA (called “algorithm-based healthcare services”), as follows … 

  • All FDA-approved products would be assigned a Category III New Technology Ambulatory Payment Classification in the HOPPS program.
  • NTAPC codes would last for five years to enable collection of cost data before a permanent payment code is assigned. 
  • Payment classifications will be based on the cost of service as estimated by the manufacturer. 

The bill at present has co-sponsors from both political parties, Sen. Mike Rounds (R-SD) and Sen. Martin Heinrich (D-NM). 

  • The legislation has also drawn support from industry heavyweights like GE HealthCare and Siemens Healthineers, as well as industry groups like AdvaMed and others.

The Takeaway

The new bill sounds like a great idea, but it’s easy to be skeptical about its prospects in today’s highly charged political environment – especially when even bipartisan compromises like the 2025 Medicare fix got scuttled. Still, S.1399’s introduction at least shows that the highest levels of the U.S. government are cognizant of the need to improve clinical AI reimbursement.

FDA Data Show AI Approval Boom

In the previous issue of The Imaging Wire, we discovered how venture capital investment in AI developers is fueling rapid growth in new AI applications for radiologists (despite a slowdown this year). 

This trend was underscored late last week with new data from the FDA showing strong growth in the number of regulatory authorizations of AI and machine learning-enabled devices in calendar 2023 compared to the year before. The findings show:

  • A resurgence of AI/ML authorizations this year, with over 30% growth compared to 14% in 2022 and 15% in 2021 – The last time authorizations grew this fast was in 2020 (+39%)
  • The FDA authorized 171 AI/ML-enabled devices in the past year. Of the total, 155 had final decision dates between August 1, 2022 to July 30, 2023, while 16 were reclassifications from prior periods 
  • Devices intended for radiology made up 79% of the total (122/155), an impressive number but down slightly compared to 87% in 2022 
  • Other medical specialities include cardiology (9%), neurology (5%), and gastroenterology/urology (4%)

One interesting wrinkle in the report was the fact that despite all the buzz around large language models for generative AI, the FDA has yet to authorize a device that uses generative AI or that is powered by LLMs. 

The Takeaway

The FDA’s new report confirms that radiology AI shows no sign of slowing down, despite a drop in AI investment this year. 

The data also offer perspective on a JACR report last week predicting that by 2035 radiology could be seeing 350 new AI/ML product approvals for the year. Product approvals would only have to grow at about a 10% annual rate to hit that number – a figure that seems perfectly achievable given the new FDA report.

Economic Barriers to AI

A new article in JACR highlights the economic barriers that are limiting wider adoption of AI in healthcare in the US. The study paints a picture of how the complex nature of Medicare reimbursement puts the country at risk of falling behind other nations in the quest to implement healthcare AI on a national scale. 

The success of any new medical technology in the US has always been linked to whether physicians can get reimbursed for using it. But there are a variety of paths to reimbursement in the Medicare system, each one with its own rules and idiosyncrasies. 

The establishment of the NTAP program was thought to be a milestone in paying for AI for inpatients, for example, but the JACR authors note that NTAP payments are time-limited for no more than three years. A variety of other factors are limiting AI reimbursement, including … 

  • All of the AI payments approved under the NTAP program have expired, and as such no AI algorithm is being reimbursed under NTAP 
  • Budget-neutral requirements in the Medicare Physician Fee Schedule mean that AI reimbursement is often a zero-sum game. Payments made for one service (such as AI) must be offset by reductions for something else 
  • Only one imaging AI algorithm has successfully navigated CMS to achieve Category I reimbursement in the Physician Fee Schedule, starting in 2024 for fractional flow reserve (FFR) analysis

Standing in stark contrast to the Medicare system is the NHS in the UK, where regulators see AI as an invaluable tool to address chronic workforce shortages in radiology and are taking aggressive action to promote its adoption. Not only has NHS announced a £21M fund to fuel AI adoption, but it is mulling the implementation of a national platform to enable AI algorithms to be accessed within standard radiology workflow. 

The Takeaway

The JACR article illustrates how Medicare’s Byzantine reimbursement structure puts barriers in the path of wider AI adoption. Although there have been some reimbursement victories such as NTAP, these have been temporary, and the fact that only one radiology AI algorithm has achieved a Category I CPT code must be a sobering thought to AI proponents.

Get every issue of The Imaging Wire, delivered right to your inbox.

You might also like..

Select All

You're signed up!

It's great to have you as a reader. Check your inbox for a welcome email.

-- The Imaging Wire team

You're all set!