Device designers and engineers of AI-enabled medical technology must focus on reimbursement early in the development process for widespread adoption.

By Tim Fonte and Cara Santillo, HeartFlow

Artificial intelligence (AI) has been increasingly adopted in healthcare. Many of these improvements are related to medical transcription, digital communications and diagnostics. Despite innovation, few AI enhancements and offerings receive additional reimbursements from federal or private insurance payors.

Some AI improvements add incremental value or efficiency to existing medical products or services. That’s a useful benefit for the facility and staff, but does not correlate to higher reimbursement like a distinctly new product or service would. For example, an algorithm that helps a physician more efficiently perform an existing service like interpreting an x-ray can be valuable, but would most likely require payment from a hospital budget and not be eligible for independent reimbursement.

If AI-enabled medical technologies that offer new products and services are to be widely adopted, they need to achieve broad coverage and reimbursement. Product designers and developers should consider reimbursement at each stage of the development process.

Design plays a pivotal role in reimbursement from the start

Bringing new AI-enabled medical technology to market is not a matter of launching a new product and expecting immediate commercial viability, even for compelling products. Pursuing the reimbursement process and ensuring broad access and payment for patients is a multi-year journey that requires patience and grit.

Don’t wait for a new technology to be cleared by the FDA before addressing how it fits existing reimbursement codes or if new codes need to be developed. How the clinical value of a new technology is studied and how the indication is submitted to the FDA have implications for achieving reimbursement.

Here are tips to help guide new AI-enabled medical technology through development while positioning it well to achieve reimbursement.

1. Determine what problem the new technology solves

In order to be reimbursed, the new technology must offer independent clinical value, such as informing diagnosis or treatment decisions for patients in a way not possible with existing methods. Creating a distinctly new product or service that generates useful information can change how physicians or staff care for patients. Ideally, the new technology should offer operational or financial value as well. During the development process, it’s important to ask what unmet need the technology addresses, and is the impact compelling enough that it could be demonstrated?

2. Bring in reimbursement advisors early on

Once there is proof-of-concept for the new technology, ask for the help of reimbursement or market access advisors. These experts can help assess how the new technology could be used and how it could be classified and paid for under the existing reimbursement system — or if new reimbursement codes need to be developed. Later on, these experts can help payers understand the technology and how it benefits patients.

3. Commit to getting clinical data to show the technology provides a benefit

All too often, AI-enabled medical technologies do not have the clinical data to back up their claims, or the data only answers some of the key clinical questions. For example, demonstrating the accuracy of a diagnostic test is important, but you need a plan for evidence to also show how it impacts decision-making and patient care. Defining these needs early is important because it could affect the design of the product or regulatory claims, and many studies take significant time to enroll and complete, sometimes as long or longer than the development process itself. Consider clinical evidence jointly with your overall technology development plans.

For example, HeartFlow’s Fractional Flow Reserve – Computed Tomography (FFRCT) Analysis is a noninvasive procedure that provides a 3D model of a patient’s coronary arteries to identify potential blockages. We wanted to show from the outset that it creates novel information and addresses a need. To do this, we obtained clinical data throughout the development process to build, validate and prove the new technology. This clinical evidence showed that the product was accurate, helped physicians make decisions, improved patient outcomes, and was of economic benefit to the healthcare providers. All of these elements are essential for reimbursement.

We are continuing to leverage this expertise and proven success to create new AI reimbursement categories in the development of additional products like HeartFlow Plaque Analysis, a product that quantifies and characterizes plaque type and volume enabling physicians to accurately assess a patient’s risk and optimize treatment for coronary artery disease.

4. Prove the new technology’s value with physician advocates

It is important to show from the start that the new technology addresses an unmet need. It is also important to identify physician advocates for the new innovation. This is key as new technologies rarely achieve reimbursement without physicians standing behind them.

Designers and marketing teams should work together to summarize what the new technology will do in a simple, compelling way for physicians. Once physicians use the new technology, develop the experience and data to show it creates value for them and that they need it for patient care.

Keep in mind that the new technology should not require physicians to perform additional work for which they are not paid. First, design the new technology to be as accessible, interpretable and as efficient as possible. Second, ensure physicians get reimbursed for additional time spent using the new information.

5. Establish pricing

A particular challenge for AI-enabled technology is that, unlike most healthcare products, it doesn’t often fit existing codes. Medicare has not often valued or priced AI technologies, and there are varying perceptions about what AI does. While some AI simply runs one algorithm alone, other products like HeartFlow use multiple algorithms on large datasets incorporated in a service that includes human quality review and verification on every patient’s analysis.

It is important to look at healthcare economics and consider the overall net savings to the healthcare system, including savings for patients, providers and insurers. Additionally, benchmarking your technology against other technologies can help you to better understand the market.

Product and technology design can play a pivotal role in achieving reimbursement for AI-enabled medical technology. By keeping reimbursement in mind as an end goal from the start, designers and developers can ensure adoption of breakthrough technologies that help physicians care for their patients.

Tim Fonte is chief technology officer at HeartFlow Inc., a leader in noninvasive integrated AI heart care solutions. Fonte has 18 years of experience leading the development and market introduction of innovative healthcare technologies.

Cara Santillo, HeartFlow SVP of market access and reimbursement, is responsible for reimbursement strategy across the device developer’s product portfolio and pipeline. Most recently, Santillo helped establish a reimbursement pathway for the HeartFlow Fractional Flow Reserve – Computed Tomography (FFRCT) Analysis.

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The opinions expressed in this blog post are the author’s only and do not necessarily reflect those of Medical Design & Outsourcing or its employees.