Has AI Reimbursement in Healthcare Entered a New Era?


Economics of AI

The significance of an AI company securing an NTAP is more than just press-release hype. Until now, the business case for most imaging AI companies relied on increased efficiencies and optimistic estimates of clinical benefit. The lack of adequate reimbursement has long been a barrier to widespread AI adoption, and the potential for AI applications to be considered revenue generators would indeed be groundbreaking.

What is the NTAP and what potential opportunities does this pathway present for AI reimbursement?

In 2000, Congress enacted the Medicare, Medicaid, and State Children's Health Insurance Program Benefits Improvement and Protection Act, which included a provision mandating an additional payment to “recognize the costs of new medical services and technologies under the [inpatient] payment system.” Lawmakers wanted to ensure that Medicare beneficiaries would have timely access to breakthrough technologies that, absent any additional payments, would be inadequately reimbursed under the existing Diagnosis Related Groups (DRG) payment. Under the ruling, the NTAP reimbursement would continue until CMS had sufficient inpatient claims data to set DRG rates that reflected the added costs of the new technology. In 2001, CMS issued regulations specifying a process and criteria for granting NTAPs.

Currently, a technology must meet three criteria to be eligible for an NTAP:

• The technology must be new, which CMS generally defines as within two to three years of FDA approval or market introduction. As part of the newness criteria, the technology cannot be “substantially similar” to existing technologies.
• The existing DRG payment for the service must be inadequate: that means the average standardized charge for inpatient cases receiving the technology must be shown to exceed the cost thresholds calculated annually by CMS.
• The new technology must be a substantial clinical improvement over existing services.

How is reimbursement determined?

For technologies that meet the eligibility criteria and receive CMS approval, the amount of the NTAP is based on the cost to hospitals to provide the new technology. The NTAP amount is calculated individually for each eligible patient discharge that includes the technology, and NTAPs are only made when the estimated cost of the case exceeds the payment the hospital would otherwise receive.

The NTAP amount is equal to the lesser of 65% of the amount by which the total covered costs of the case exceed the DRG payment, or 65% of the costs of the new technology.

This formula requires Medicare and hospitals to share in the financial risk of providing costly new technologies. The maximum NTAP amount is linked to the price of the technology as reported by manufacturers in their application and published by CMS in the Inpatient Prospective Payment System annual final rule.

What does the future hold for AI reimbursement? Many questions remain as the landscape of AI reimbursement evolves. NTAPs are self-limited by definition and expire after a maximum of three years. In the past, CMS has steeply reduced the NTAP amounts within the first few years, returning vendors back to the reimbursement starting line. The extent to which the NTAP pathway would be applicable to other AI products is unknown, especially given the criteria to prove there is no “substantially similar” technology. Nonetheless, this decision by CMS to reimburse providers for Viz’s LVO AI technology will no doubt be cited as precedent.

Join me to talk more about these and other new developments in AI reimbursement and payment policy at ACR’s Virtual 2020 Imaging Informatics Summit on October 27-28.

Gregory N. Nicola, MD, FACR | Chair ACR Commission on Economics | Executive leadership Hackensack Radiology Group

Has AI Reimbursement in Healthcare Entered a New Era?

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