Artificial Intelligence Positioned To Disrupt $5 Trillion Industry

Globally, healthcare is a colossal industry. In the U.S. alone, healthcare spending exceeds $5 trillion annually. Everyone at some point is touched by this vast, complex infrastructure of providers and solutions. Steady progress in drug discovery, new surgical techniques, and knowledge has meant better outcomes and increased quality of life for those needing medical attention.

However, significant gaps have remained in healthcare's ability to produce innovative leaps that radically reshape what's possible in treating disease. Now, AI is emerging as a profound industry disruptor. The impact isn’t anticipated to be subtle. Moreover, with the help of AI-driven hardware and software, patients and providers alike are about to experience a healthcare revolution.

AI Begins Delivering Real Clinical Impact

AI has played a role in medicine for decades, supporting areas such as drug discovery, surgical robotics, knowledge management, training, and decision-making.

What has changed more recently is a confluence of meaningfully improved technologies that include deep learning-based AI, cloud computing, data analytics, automation, and processing speed. Individually, any one of these technologies are impactful, but together they have the capacity to deeply accelerate possibilities.

Healthcare is one of the most difficult industries to transform because mistakes carry enormous consequences. New technologies must not only work, they must demonstrate clinical efficacy, satisfy regulators, integrate into existing workflows, and earn physician trust. That makes successful AI deployments particularly noteworthy.

That a new day has arrived in what medicine can achieve for patients is not lost on Dr. David Stoffel, a physician and business leader with many years in medical innovation. His experience has included working on some of the most important new technologies in healthcare, notably da Vinci robotics, which have played a large role in surgical automation.

What drives Stoffel as a healthcare professional is an interest in changing clinical horizons. That’s an industry term that means better long-term patient outcomes. It’s more than just increasing survivability of an illness or accident but also ensuring a good post-intervention quality of life.

With AI, Stoffel believes new, positive clinical horizons will arrive in abundance. It’s why he joined his latest healthcare company.

A Breakthrough In Stroke Management Opens The Door

Today, Stoffel is the Chief Business Officer of Rapid AI, a recognized healthcare player in around 100 countries and 2500 hospitals, including presence in 75 percent of comprehensive stroke centers in the US. The company, which emerged out of Stanford University didn’t start as an AI company 11 years ago, but today it’s one of the world’s largest clinical system providers utilizing AI in its product suite.

One of the many challenges the company sought to improve were outcomes in the removal of blood clots in blocked arteries and veins related to serious strokes.

In one particular approach called a mechanical thrombectomy, a device inserted into the body is used to suck out the clot. It’s an intervention that has a historically high failure rate.

One of Rapid AI’s breakthroughs was developing its own AI model to analyze imaging of the clot locality and determining whether the patient was a good candidate for the invasive procedure.

The results were substantial. In addition, to significantly reduced mortality rates, many patient outcomes improved dramatically. According to Stoffel, some patients who might previously have faced severe disability were able to return to normal activities.

The development of this deep clinical AI didn’t happen overnight and was the culmination of several years of research and the availability of a new generation of sophisticated algorithms—what Stoffel calls “algorithms on steroids”--and powerful processors.

As case after case of trials delivered impressive results, stroke guidelines were changed in just 30 days versus the more common years-long process.

Encouraged by the results, Stoffel and his colleagues began exploring whether the same approach could be applied to other medical conditions. Soon they saw positive results in tackling high demand areas such as aneurisms and pulmonary embolisms. For example, Stoffel cited a study where AI was able to identify 23 percent more aneurysms when compared to humans alone.

Today, their AI-driven scanning analysis technology can be applied to many diseases anywhere in the human body.

AI Alone Doesn’t Get The Job Done

It might sound like AI alone is the hero, but that’s only part of the story. What’s really happening is that a combination of AI-driven enhanced capabilities such as accuracy, speed, visualization, data, and predictions, are enabling much higher confidence in practitioner decision-making.

Rather than removing the doctor from the equation, AI is augmenting their ability to make the best decisions for the most favorable outcomes.

Instead of slowing the physician down with false positives and unnecessary investigation, they get high quality information quickly. In addition, standard workflows reduce unnecessary friction.

The lesson emerging from healthcare's most successful AI deployments is that AI itself is rarely the entire solution. Clinical impact appears when advanced algorithms are combined with high-quality data, workflow integration, collaboration tools, and physician expertise.

Digital collaboration is another ingredient that enhances the delivery of medical support to the patient. In a configurations where different systems are used and may not be integrated, an initial scan may take time to reach all the necessary medical stakeholders and gathering input becomes overly burdensome.

It’s not unusual, for example, for a team of radiologists, doctors, nurses, and other medical professionals to be engaged in treating a patient. Rapid AI and similar systems are now designed to easily socialize a new scan, collect insights, provide decision-support, and organize the results into an approved and coordinated treatment plan.

A common digital platform ties all functions together and AI is embedded throughout to act as a success catalyst. Medical practitioners also see reduced cognitive overload since the tools and process makes many parts of everyone’s jobs easier.

Healthcare's AI Revolution Is Just Beginning

Exploring a successful AI solution such as Rapid AI, one where results are obvious and profound, is a good news story in a current environment where too many AI offerings either over-promise or fail to deliver. Stoffel shared details of a study of 100 AI solutions that suggested 88 percent of them had no clinical impact.

But it’s also a story that reminds us that AI alone will often be insufficient. What’s becomes clear is that humans continue to play a role as does a wide range of other supporting technologies.

Innovation in healthcare is also a sobering topic because it reminds us how complex the human body is, how many diseases still exist to be solved, and how insufficient many of the solutions available are today. Optimists will acknowledge that all of this presents remarkable opportunity ahead, particularly with AI in the toolkit.

Stoffel is optimistic about the role AI and other emerging technologies will play in the future of healthcare. At Rapid AI he sees that future clearly. It’s about smart, integrated systems that manage a patients journey including monitoring changes over time and ensuring that essential follow-up requirements are met.

As a doctor he’s encouraged by greater accuracy and decision-making that is vastly enhanced, and communication and collaboration that is seamless between stakeholders. Stoffel sees agentic AI being instrumental in helping both practitioners and patients navigate complex systems, treatment and follow-up plans. It’s obvious to anyone today that much work is needed in this area.

The healthcare industry's future is unlikely to be defined by AI replacing clinicians. Instead, it will be shaped by intelligent systems that help physicians make better decisions, collaborate more effectively, and intervene earlier. If the results being achieved in stroke care are any indication, healthcare's next major advances may come not from AI alone, but from the combination of human expertise and machine intelligence working together.