AI And The Disruption Of Healthcare

Not long ago, if you wanted to explore the intersection of healthcare and artificial intelligence (AI), you’d be confined to the pages of science fiction. Not anymore: In recent years, AI has evolved from what’s possible to what’s practical, and consumers and practitioners alike have been increasingly drawn to the possibilities of how AI can revolutionize healthcare.

While the promise of AI in this field is just starting to be realized, we are already seeing it have a real impact on patients' lives right now. Here are three ways AI is disrupting the practice of healthcare today.

Automation Of Labor-Intensive Tasks

Providing the quality healthcare patients are seeking takes time—something already in short supply in most healthcare facilities. The more practitioners can push labor-intensive or administrative tasks to AI solutions, the more time they can spend with patients. AI can complete those labor-intensive tasks with less (if any) human assistance and even uncover inefficiencies in current practices.

How AI Can Help

While some tasks seem tailor-made for AI-based solutions, like chatbots and schedule reminders, they’re just the tip of the iceberg. For example, automation software company Olive AI recently launched its Autonomous Revenue Cycle solution, which can automatically verify insurance eligibility, identify benefits and ensure claims are processed correctly. Qventus’ Perioperative Solution uses AI and machine learning to address manual operating room scheduling inefficiencies, helping health systems across the country add more OR cases per month, schedule procedures further into the future and increase revenue by more than $10 million per facility.

AI can also be used to analyze and improve current practices. A 2022 UPenn study used AI to analyze the inpatient and outpatient notes for nearly 2 million patients and found that roughly half were duplicated from prior notes—a practice that "casts doubt on the veracity of all information in the medical record."

Virtual Patient Care

It’s easy to see how AI could revolutionize healthcare, even through virtual care alone. It is time-consuming and prohibitively expensive to provide each patient with round-the-clock care. However, emerging virtual care solutions are tapping into AI to alert healthcare practitioners when care is needed and monitor and even influence patient behavior to create better health outcomes.

How AI Can Help

VirtuSense’s wearable technology solutions use AI to prevent injury and even create greater patient quality of life: VSTAlert reduces falls in skilled nursing by 75% and falls with hospitalization by 78%, and VSTBalance can detect deficits in gait and function, increasing resident mobility in assisted living communities by up to 85%. Biofourmis’s virtual care management service uses analytics, AI and wearables to monitor patients’ complex chronic conditions remotely. And facility automation platform care.ai uses AI to monitor in-facility patients for falls, pressure injuries, elopement and protocol adherence.

Diagnosing Medical Issues

The promise of AI in healthcare isn’t only because it’s faster; in many cases, it’s better than its human counterpart. This is perhaps the most exciting aspect of the development of AI—the potential that it can accomplish tasks and achieve results that humans can’t on their own.

How AI Can Help

Though still in its infancy in healthcare, AI is already making incredible inroads in medical diagnoses. Viz.ai’s artificial intelligence software can cross-reference CT images of a patient’s brain with its database of scans to find early signs of large vessel occlusion strokes—and then alert doctors, who can see the images on their phones. The Mayo Clinic’s AI-assisted screening tool "identified people at risk of left ventricular dysfunction 93% of the time. To put that in perspective, a mammogram is accurate 85% of the time."

Digital Diagnostics uses AI to detect diabetic retinopathy and even some types of skin cancer. And a recent study reported in Nature found that a trained neural network (a complex form of machine learning) can classify hip fractures 19% more accurately than even experienced human observers in a clinical setting. Because classification is highly determinative of treatment, an increase in classification accuracy could lead to better treatment, improved patient outcomes and reduced costs.

The Need For Practitioners To Keep Up

For all its promise, though, AI is still facing significant obstacles to widespread development, including cost and proof of effectiveness. But perhaps the biggest impediment lies with healthcare executives themselves: According to a 2022 study by IT services and consulting company Capgemini, “the level of acculturation of C-level executives is lagging, especially for organizations that would need it the most — pharmas, medtechs and hospitals." As healthcare executives, we know that AI is not the future of healthcare but the present, and we need to be leading the way.

Previously published on Forbes.