Technology is changing the world faster than ever—but medicine still doesn’t move quickly enough when it comes to adopting innovations that prevent harm and make patients safer.
When the Institute of Medicine in 1999 released a landmark report on just how common medical errors were, patient safety jumped onto the radars of hospitals across the world. Though the report was published 25 years ago, most of the changes hospitals have made haven’t been enough. One recent study showed that 1 in 4 hospitalized patients experience preventable harm.
[time-brightcove not-tgx=”true”]As a new generation of clinicians enters the medical workforce, it is crucial that the system modernizes itself with tools that other industries have been using for years. From AI machine learning to virtual reality, these innovations are starting to be used in medicine. But tech startups and entrepreneurs still have a steep climb to bring their life-saving technologies to the bedside.
The Pitch: Patient Safety’s Next Generation, a new documentary available Sept. 17 on Apple TV and Prime Video, explores how the health care system is wrestling with this. It follows a young entrepreneur on his quest to help reduce the too-high maternal mortality rate in the U.S.; compared to other high-income countries, it’s a relatively dangerous place to be pregnant and give birth, especially for Black women.
Reetam Ganguli, a 22-year-old MD candidate from San Jose, developed a machine-learning algorithm to spot high-risk pregnancies long before traditional tests, measures, and markers would typically be able to detect them. Through his new startup Elythea, the algorithm can alert a woman’s doctor to these warning signs at a stage in her pregnancy when intervention would make the difference between a healthy pregnancy and a potentially fatal one. Such an advance would be impossible without tools like Elythea. And that is exactly where technology can make the biggest difference in medicine.
But even after winning multiple pitch competitions and acquiring funding from high-profile incubators, Ganguli still is trying to convince hospital administrators that Elythea is worth the investment; he’s found the most success by partnering with clinicians directly.
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When hospitals do embrace AI and machine learning, patient care can become safer—in part because it can relieve overworked doctors and understaffed nurses. Command centers, for instance, are popping up in health systems around the world. Inspired by operational centers like NASA or Dell, these rooms—filled with screens of information like bed availability, emergency department capacity, and patient vitals—are the epicenter of decision-making at the hospital. The software collects and translates the incredible amount of data associated with each patient, freeing up providers and quickly alerting them to areas of care that might soon require urgent attention. And if there is nothing to report, nurses will waste less time checking on patients who would benefit more from uninterrupted recovery.
In the documentary, Jeff Terry, former founding CEO & managing principal of command centers at GE HealthCare, explains them as “the ultimate connector of all the data,” allowing health care providers to “apply algorithms to it to predict the future.” Humber River Health, a hospital in Toronto, started using its command center about a decade ago to improve patient safety and has seen a significant reduction in the rate of harm across the hospital.
Some worry about a future like the one we see in the movies, where artificial intelligence replaces and destroys mankind. We should perhaps be more concerned about a future in which we are too afraid to use what can actually save it.
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This type of technology is already revolutionizing safety in other areas of medicine. Dr. James Clarkson, an orthopedic surgeon in East Lansing, Mich., is using virtual reality to replace unnecessary sedation, allowing more of his patients to walk out of the facility immediately after their procedure and reducing the likelihood of infections that often come with an extended hospital stay. A group of epidemiologists at the University of Pittsburgh, led by Dr. Lee Harrison, are using genomic testing to enhance the detection of hospital-associated infections. When combined with machine-learning technology, the Harrison Lab can reduce the amount of time it takes to identify the source of the outbreak. This has saved countless lives, and without the collaboration between technology and medicine, it would never exist.
But these innovative solutions are still too few and far between. The reason is much of the burden of finding answers to the chronic problems in health care has been placed on clinicians. “To really solve a problem and bring in a disruptive innovation, it can’t really be a part-time hobby,” says Ganguli in The Pitch. “A full-time doctor or surgeon or health care administrator whose really important work of dealing with patients all day consumes most of their time is not going to have the flexibility to either leave their job or manage this on the side as well.”
Hospitals must be transparent with the problems they need help solving and create opportunity for entrepreneurs to dedicate themselves to an answer. Innovators like Ganguli are searching for opportunities to make a difference in the world. Their best bet is to collaborate with doctors and nurses who experience the everyday inadequacies of patient care.
It is time for hospitals to open the door to more than just new patients. It is time to open up to new ideas and technologies.
