Thursday, June 20, 2024

When AI predicts trouble, doctors take note

The ideas and innovators shaping health care
Jun 20, 2024 View in browser
 
Future Pulse

By Gregory Svirnovskiy, Erin Schumaker, Daniel Payne and Ruth Reader

EXAM ROOM

Dr. Laurie Margolies demonstrates the Koios DS Smart Ultrasound software, Wednesday, May 8, 2024, at Mount Sinai hospital in New York. The breast imaging AI is used to get a second opinion on mammography ultrasounds. “I will tell patients, ‘I looked at it, and the computer looked at it, and we both agree,’” Margolies said. “Hearing me say that we both agree, I think that gives the patient an even greater level   of confidence.” (AP Photo/Mary Altaffer)

Artificial intelligence could warn doctors when their patients' health is deteriorating, a new study found. | AP

AI-powered alerts that warn doctors when their patients’ conditions are in danger of deteriorating could save lives, according to researchers at Mount Sinai Hospital in New York City.

How so? Researchers divided 2,740 Mount Sinai medical-surgical unit patients into two groups, one with artificial intelligence alerts sent live to health care workers and another that monitored patients’ conditions without the benefit of AI. Patients in the AI intervention group were 43 percent more likely to receive a more rapid response and care, including medicine to support their hearts and blood circulation, and were less likely to die within 30 days compared with the control group.

Mt. Sinai uses the AI algorithm in its so-called stepdown units, where stable patients still need close monitoring.

What they’re saying: “These models are accurate and timely aids to clinical decision-making that help us bring the right team to the right patient at the right time,” Dr. David Reich, president of Mount Sinai Hospital and one of the study’s authors, said in a press release. “We think of these as ‘augmented intelligence’ tools that speed in-person clinical evaluations.”

Why it matters: These days, doctors rely on early warning systems that often aren’t helpful and require significant manual input to work.

The study findings were published in Critical Care Medicine. The research was conducted at a single center, so outcomes might differ in another setting.

 

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This is where we explore the ideas and innovators shaping health care.

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Share any thoughts, news, tips and feedback with Carmen Paun at cpaun@politico.com, Daniel Payne at dpayne@politico.com, Ruth Reader at rreader@politico.com, Erin Schumaker at eschumaker@politico.com, or Toni Odejimi at aodejimi@politico.com.

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SAFETY CHECK

SAN FRANCISCO - AUGUST 18:  Eighteen-year-old cancer patient Patrick McGill looks at a rack holding bags of chemotherapy while receiving treatment for a rare form of cancer at the UCSF Comprehensive Cancer Center Childrens Hospital August 18, 2005 in San Francisco, California. The UCSF Comprehensive Cancer Center continues to use the latest research and technology to battle cancer and was   recently rated 16th best cancer center in the nation by US News and World Report.  (Photo by Justin Sullivan/Getty Images)

CAR T-cell therapy remains a good option for people with blood cancer, despite some risks, a study found. | Getty Images

Despite a Food and Drug Administration warning this year, the risk of getting secondary blood cancer after receiving CAR T-cell therapy, a cell-based cancer treatment, is low, according to a Stanford Medicine study.

How’s that? Of the 724 people treated with CAR T-cell therapy at Stanford Health Care between 2016 and 2024, roughly 6.5 percent developed secondary blood cancers within three years, researchers found, similar to secondary cancer rates seen among patients who receive stem cell transplant cancer treatments.

Secondary cancer is when cancer cells spread, or metastasize, in the body.

Why it matters: The FDA told several drugmakers in January to add a boxed label, the agency’s highest safety warning, to CAR T-cell therapy because of the therapy’s risk for triggering secondary cancers.

The FDA did the right thing by issuing the warning, according to Dr. David Miklos, a co-author of the study and a professor of medicine and chief of bone marrow transplantation and cellular therapy at Stanford Health Care.

“There is a lot of oversight occurring,” Miklos told Erin. “Doctors and the government are stewarding what is a relatively new therapy.”

The FDA approved the first CAR T-cell therapies in 2017. Since the treatment is new, it’s important for researchers and the government to track its long-term safety by looking for warning signs that might occur one, five or even 10 years after treatment.

“That work is being done,” Miklos said.

The bottom line: The risk of developing second cancers pales in comparison to the risk of foregoing treatment.

“Patients who are fortunate enough to get the therapy are then at risk for more risks,” Miklos said. “If you didn’t get the therapy, unfortunately, with this disease, you die — you die within three to six months.”

The National Institutes of Health-backed research was published this month in The New England Journal of Medicine. The research was conducted at a single center, so outcomes might differ in another setting.

 

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FORWARD THINKING

A doctor speaks with a patient.

AI could help doctors determine who's eligible for clinical trials, a study found. | Joe Raedle/Getty Images

Advanced AI could help screen patients for clinical trial eligibility, according to new research out of Brigham and Women’s Hospital and Harvard Medical School.

How so? The AI system the researchers vetted drew on clinical patient notes and came to the correct conclusion about eligibility more than 90 percent of the time.

AI systems like the one in the study also have the potential to reduce costs, the authors wrote.

Even so: Concerns remain about bias in AI systems, particularly those trained on data that isn’t representative of the wider population. Those worries could grow should AI systems become more integrated in that data creation.

The study authors suggested that health systems should consider the potential hazards of AI systems and safeguards to ensure a clinician reviews the systems’ work.

 

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