One of the world’s most prominent hospitals is testing how AI can revolutionize health care

CNN, MAYO CLINIC, SCALE, GETTY IMAGES

By Clare Duffy, CNN

Rochester, Minn. (CNN) — Preparing to meet with a patient can require Mayo Clinic internal medicine physician Dr. Alexander Ryu to sort through dozens, or even hundreds, of pages of medical records.

Many patients visit the renowned clinic looking for a third or fourth opinion, carting with them unsorted documents from external health systems. A new artificial intelligence tool is helping clinicians parse through records faster — generating relevant patient summaries, organizing documents in chronological order and making them easier to search.

Ryu said the tool, called Record Time, can save him between five and 30 minutes of preparation per visit, depending on the complexity of the case. That’s time he can instead spend face-to-face with the patient. And Record Time helps ensure that he doesn’t miss important details that might be buried in the file that could drive treatment and testing recommendations.

“We receive a huge volume of these records, tens of millions of pages every year, and we needed a way to find important information in that,” said Ryu, who also serves as vice chair of innovation for the Mayo Clinic Department of Medicine.

Health-related applications are considered among the most promising areas of innovation for AI. Google, OpenAI, Anthropic and others have rolled out health assistant chatbot features — and tens of millions of people are turning to AI for medical-related questions. Leaders in Silicon Valley also frequently make bold promises about AI curing cancer and other diseases, although those statements often sound more like marketing pitches given the big industry players are largely focused on other consumer and business applications.

But Record Time is just one way that Mayo Clinic, one of the world’s most well-known hospital systems, is using AI in hopes of improving patient care and, ultimately, saving lives. The hospital is partnering with firms like Microsoft and Scale AI to use its huge volume of patient records and research to develop AI tools.

There are now around 150 AI models deployed within the hospital, according to Dr. Matthew Callstrom, a radiologist and medical director of Mayo Clinic’s generative AI program.

The use of AI in healthcare settings is not without controversy, raising big questions about accuracy and patient privacy.

Mayo Clinic’s former Director of Research Operations Traci Tamiko Eto sued the hospital earlier this month, alleging she was retaliated against for raising privacy and oversight concerns around some Mayo AI systems.

Mayo Clinic spokesperson Andrea Kalmanovitz said the hospital doesn’t comment on ongoing litigation but noted it is “committed to the responsible development and deployment of AI, with privacy, security, transparency and compliance embedded throughout our processes.”

“Our research and clinical innovation are conducted in accordance with applicable laws and regulations and we remain steadfast in upholding the trust patients place in us and respecting their privacy,” Kalmanovitz said in a statement.

‘Potentially life changing’

Part of what makes AI so useful in health and medicine is that the technology excels at identifying trends in large swaths of data, said Jason Droege, CEO of Scale AI, which worked with Mayo Clinic to develop Record Time.

“AI can step in and do a lot of the tedious work that very specialized doctors or medical professionals do to speed up that process — get to more accurate diagnoses, faster so you can treat more people,” he said. “This is an industry where a lot of what doctors are doing, and nurses and others, is pattern recognition.”

Callstrom told CNN he was convinced of AI’s potential back in 2016, when he saw how AI could help radiologists identify subtle, early cancer warning signs in imaging.

Mayo Clinic is now running a clinical trial to test whether AI can help identify patients at risk of or with early-stage pancreatic cancer — an application the hospital has said could detect the disease years earlier than the typical diagnosis. Currently, patients often aren’t diagnosed with pancreatic cancer until it is regionally spread or metastatic, when the five-year survival rate hovers around 9%, Callstrom said.

The hospital has also successfully used AI to analyze patients’ heart rhythms to tell whether someone could develop atrial fibrillation, a condition that can cause blood clots and strokes.

“For those patients where you actually find it and identify it, it’s potentially life changing,” Callstrom said.

Balancing speed and trust

To build AI tools, Mayo Clinic pairs tech experts with doctors or clinicians to decide which medical problems need tackling. A big part of Callstrom’s job is ensuring that Mayo Clinic’s AI tools are accurate and trusted by both patients and doctors.

AI tools go through the same process as a clinical trial, he said. First, it’s tested with a small group of patients with doctor oversight. The performance is measured, and then testing expands to a wider population.

Once a tool is rolled out broadly, Mayo Clinic continues to monitor how well it works.

“On the physician side … we’re skeptical a lot,” Callstrom said. “We give them the option to try (a new AI tool) and if they like it, they use it. If they don’t want to use it, they don’t have to. And the best measure of how well we’re doing is the adoption rate.”

Callstrom also gets frequent questions from staff about what AI tools will mean for jobs. So far, he said, jobs aren’t going away. But they are changing.

The hospital’s nursing team, for example, helped to develop an AI system that listens and takes notes during patient visits. That potentially cuts in half the more than an hour per day they spend typing up those visits.

“What it’s doing is letting them spend more time talking to patients,” Callstrom said.

Scale’s Droege believes the health care industry is only at the beginning of realizing AI’s full potential — but that speed of adoption shouldn’t necessarily be the top priority.

“These predictions where everything is going to be fixed in a year or two, I think that’s wildly ambitious,” he said. “Quality of care is the bar, and then speed … in healthcare, you want to get it right, as fast as possible.”

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