At a panel at LSI USA '24, industry leaders convened to discuss the transformative potential of the adoption of AI in healthcare and the path to true adoption in clinical workflows. Moderated by Natasha Allen from Foley & Lardner, the panel featured Sascha Berger of TVM Capital Life Science, Rob Krummen of Vector Medical, and Daniel Hawkins of Vista.ai. Their conversation highlighted how AI is reshaping the medtech landscape by enhancing diagnostic accuracy, reducing costs, alleviating staff burnout, ensuring data quality, overcoming resistance, and collaborating with regulators.

Enhancing Diagnostic Accuracy and Efficiency

One of the most significant advantages of the adoption of AI in healthcare is its ability to improve diagnostic accuracy and efficiency. AI's superior capability to analyze medical images can surpass human expertise, leading to more precise and consistent diagnostic outcomes.

Daniel Hawkins emphasized this point: "Humans have certain limitations, and artificial intelligence can overcome those limitations and create consistency in what is produced. That then generates higher diagnostic yield, changing the clinical pathways that follow from there. Artificial intelligence has the benefit of the expertise of the best minds and best experience, but it’s digitized."

Rob Krummen added, "AI can look at images and see deflections, modulations, and differences that beginners can't see but also a little better than the experts can see. Doctors get to spend a little less time looking at the ECG and a little more time looking at the heart and how to treat their patient."

Reducing Healthcare Costs and Increasing Efficiency

AI's role in healthcare also extends to cost reduction and enhanced efficiency. By streamlining procedures and improving resource utilization, AI can lead to significant cost savings for healthcare providers.

"We found a 25% reduction in procedure time," shared Rob Krummen. "In an eight-hour procedure, if you can cut 25% out of that, the cath lab cost is reduced significantly, and you can treat more patients."

Alleviating Staff Burnout

AI's ability to handle routine and repetitive tasks helps alleviate the burden on healthcare professionals, reducing burnout and improving job satisfaction.

Daniel Hawkins highlighted this benefit: "Technicians suffer burnout working 12-hour days—and they’re forced to move faster and faster all the time, so they make mistakes. AI helps reduce their workload and improve the quality of their work."

Rob Krummen pointed out the positive impact on staff retention: "At one VA, staff haven't had overtime since we were introduced. The nurses have not left because they like the improved work conditions."

Ensuring Data Quality and Validation

The successful adoption of AI in healthcare relies heavily on the quality of the data used to train algorithms and the validation of these algorithms through rigorous clinical studies. Ensuring high-quality data and robust validation processes is crucial for effective AI implementation.

"You have to have real fidelity to the training sets you're creating, the amount of data you’re getting, and how you’re using it. Validation and verification of your data are crucial," emphasized Rob Krummen.

Sascha Berger added, "If we're looking at software, what's the background? How do these companies get their models trained? What's the source of data, and how unique is that?"

Overcoming Resistance to AI Integration

Integrating AI into existing clinical workflows can face resistance, primarily due to concerns about job loss and skepticism regarding AI's capabilities. Building trust through demonstration and validation is essential to overcoming this resistance.

Daniel Hawkins explained, "AI is scary in healthcare because it's making a diagnosis or suggesting a diagnosis. In our case, there's resistance from staff, but once they see the benefits and overcome the fear, the resistance reduces."

Rob Krummen noted, "One of the big buy-in moments for us was when doctors started helping us make the case to their admins that they need the technology. That's when we know we've done something really special."

Collaborating with Regulators

Close collaboration with regulatory bodies like the FDA is vital for successfully approving and integrating AI technologies in healthcare. This partnership ensures that AI solutions meet stringent safety and efficacy standards.

"It’s controversial, but we over-disclose with the FDA. We want to be a trusted partner with them. I try to communicate with them on a regular basis," said Rob Krummen.

Sascha Berger added, "The FDA is much more receptive to these changes now. When I speak to companies who are in frequent exchange with the FDA, it’s becoming much smoother these days."

Adoption of AI in Healthcare

The full recording of the panel can be found in LSI’s resource hub at the link below:

• Advent of AI: What Will it Take to Drive True Adoption in Clinical Workflows

The panel discussions underscored the transformative impact of the adoption of AI in healthcare. By enhancing diagnostic accuracy, reducing costs, alleviating staff burnout, ensuring data quality, overcoming resistance, and collaborating with regulators, AI is set to reshape the medtech market. As Natasha Allen concluded, "AI will change the way we interact with patients, our healthcare system, and our health professionals." Medical device investors are keenly observing these developments, recognizing the vast opportunities that AI presents in shaping the future of healthcare.