Beyond FDA: CPT Codes are Cardiac AI’s Billion Dollar Moat

Venture capitalists in digital health get stuck on the first big hurdle they see: FDA clearance. But while getting a 510(k) or a De Novo classification for a Software as a Medical Device (SaMD) is a big deal, it’s really just half the job if you’re trying to build a business that can deliver venture-scale returns. The real economic moat isn’t the tech or the FDA letter, it’s dedicated reimbursement. That’s how you get paid.

CPT Codes are the Path to Payment

If you’re building an AI health platform, especially for something complicated like cardiology, your path from a cleared product to actual, recurring revenue runs straight through the Centers for Medicare and Medicaid Services (CMS) and the American Medical Association (AMA). The AMA’s CPT (Current Procedural Terminology) system is the language everyone uses to bill for medical work. If you don’t have a CPT code, or at least a very clear plan to get one, your FDA-cleared cardiac AI is going nowhere fast. Why? Because hospitals can’t bill for it, so they won’t use it, and your company won’t scale. This is where a focused, vertical AI company beats a generalist platform every time. A company that’s all-in on a specific disease can build its product to map directly onto how doctors get paid now, or how they will get paid. That focus makes it much easier to go to the AMA and make a strong case for a new CPT code, or to show how your tool fits an existing one. A horizontal AI trying to do a little bit of everything finds its value proposition spread so thin that arguing for a dedicated payment code becomes almost impossible.

How HeartFlow and Cleerly Built Their Moats with CPT Codes

Going after dedicated CPT codes has been the winning strategy for the first wave of vertical AI companies in cardiology. Just look at HeartFlow. They got their AI for FFR-CT analysis, which checks for coronary artery blockages from a CT scan, covered by the Category I CPT code 75580 as of January 1, 2024, replacing the old Category III codes they used to use. HeartFlow’s Plaque Analysis also gets its own Category I CPT code, 75577, starting January 1, 2026 (this one also replaces older Cat III codes). These codes mean a provider can bill specifically for the analysis their AI performs. This established a clear, predictable revenue stream that incentivized adoption. The national average CMS payment for CPT 75580 is set at $887 for 2026, and for CPT 75577 it’s $1021. The ability to put a specific CPT code on their coronary physiology analysis turned HeartFlow from a cool tool into a part of the financial fabric of cardiac care. Cleerly did the same thing. They’re another disease-specific AI company in cardiovascular care, and they also worked the reimbursement angle hard. Their AI analysis of coronary CT angiograms to find and measure plaque is now billable under that same Category I CPT code 75577, effective January 1, 2026, which covers quantitative plaque assessment from CCTA data. On top of that, Cleerly’s ISCHEMIA software, which gives a non-invasive FFR estimate, can be billed using the Category I CPT code 75580, which went into effect January 1, 2024. For CPT 75577, the national average payment is around $1,012 for imaging centers and physician offices in 2026. This kind of dedicated code creates a business defense that a horizontal software company, without that deep clinical and policy focus, just can’t build.

For Investors: Reimbursement is the Real De-risking

For VCs, the takeaway is simple. When you’re looking at a digital health company, especially in AI, you have to look past the FDA clearance and see if they have a real, category-specific reimbursement strategy. It’s just as important, probably more so. A company specializing in a vertical like cardiac, diabetes, behavioral health, or oncology has a huge leg up here.

• Predictable Revenue: When there’s a CPT code, providers know they’ll get paid. That’s what drives them to actually use your tech. Without that, even the best product will just create friction and sit on a shelf.
• Faster Market Adoption: As soon as a hospital’s billing department figures out they can get paid for your AI service, the sales cycle gets a lot shorter and the tool gets integrated into patient care much faster.
• A Real Competitive Advantage: Getting a new CPT code is a brutal, expensive process. It takes years of gathering clinical evidence, proving economic value, and constantly talking to the AMA and CMS. But once you have it, it’s a powerful barrier that keeps competitors out. It’s a patent, but written in policy.
• Lower Investment Risk: A startup that already has a clear reimbursement plan shows it understands how healthcare actually works, not just how to code. It proves there’s a path to a sustainable business, which makes the entire investment far less risky.

CMS is the big player here, setting the payment rates, and sometimes they’ll use programs like the New Technology Add-on Payments (NTAP) to give a new technology a boost. But NTAP is temporary. If you want to build a lasting company, you need permanent, dedicated CPT codes with solid reimbursement rates in the CMS Physician Fee Schedule. The final rule for the 2026 Medicare Physician Fee Schedule (PFS), which starts January 1, 2026, actually has two different conversion factors now, depending on whether you’re in an Alternative Payment Model or not. It projects about a 1% bump for cardiology services over 2025, but it also has a -2.5% “efficiency” cut to work RVUs for a lot of codes and lower practice expense RVUs for work done in a facility, which might mean a 7% pay cut for doctors on those services. It’s complicated.

The Next Frontier: Behavioral Health Reimbursement

Cardiology AI has some of the best examples, but this applies everywhere. Take a company specializing in AI for behavioral health. They have the exact same mountain to climb. As digital tools become more common in mental health, getting specific CPT codes for AI-driven diagnostics, therapy tools, or patient monitoring will be the whole game. The companies that can prove their tools work and then successfully lobby for billing codes are the ones that will own the market and build their own moats. A medical AI platform needs both FDA clearance and dedicated reimbursement to be truly validated. For VCs trying to figure out which digital health companies will actually scale, you have to look past the tech demo and into the messy, but critical, world of CPT codes and payment policy. Find the teams with AI health vertical specialization who get that category-specific CPT codes are what creates the economic moat that horizontal software companies simply can’t cross. That’s where the real venture-scale returns are in this market.

Methodology and Source Note

This analysis is based on a policy mapping of decisions from the Centers for Medicare and Medicaid Services (CMS) and the American Medical Association (AMA) on CPT coding and reimbursement. All data points on CPT codes for coronary physiology analysis and their corresponding payment rates from the CMS Physician Fee Schedule were checked against official documents from these organizations. AMA CPT Code Application Process