Managing Medical Uncertainty

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2 min read
Doctors in the OR during surgery
Doctors in the OR during Surgery

Hospitals across the United States are relying on AI to keep patients safe.
What’s new: Doctors are using a variety of machine learning systems to assess the risk that a given patient will suffer complications, The Wall Street Journal reported.
How it works: Several facilities are using AI to identify patients who need special attention.

  • Duke University Hospital uses Sepsis Watch to monitor every patient in its emergency room for acute inflammation in response to infection, which is responsible for one in three hospital deaths. Every five minutes, the system analyzes 86 variables and assigns a risk score, alerting nurses only when it passes a certain threshold.
  • Kaiser Permanente deployed Advanced Alert Monitor in 21 of its hospitals after finding that it shortened hospital stays and reduced referrals to intensive care units. The system predicts whether patients will require intensive care within 12 hours based on vital signs, laboratory test results, coexisting conditions, and other factors.
  • Doctors at the University of Maryland Medical System found that a machine learning model outperformed traditional methods at predicting a patient’s risk of returning within 30 days.

Behind the news: Government regulators are beginning to accept machine learning’s potential to transform healthcare.

  • Earlier this month, the European Union approved for clinical use an AI system that scans chest x-rays and automatically writes reports for those with no discernable maladies.
  • In October 2021, regulatory agencies in Canada, the United Kingdom, and the United States jointly issued guiding principles for the use of machine learning in medicine.
  • In November 2020, the U.S. Medicare and Medicaid programs agreed to reimburse doctors who use two AI-powered tools: Viz LVO, which monitors patients for signs of a stroke, and IDx-DR, which helps diagnose a complication of diabetes that can cause blindness. Medicare and Medicaid approval often enables treatments to reach more patients in the U.S.

Why it matters: The Covid-19 pandemic has highlighted tragically underfunded and overworked healthcare workers around the globe. Automated tools could help providers make better use of limited time and resources and help them to focus their attention on the most important cases.
We’re thinking: Many countries face a demographic cliff: The population of younger people is falling precipitously, while the number of elders is growing. It seems likely that AI will be instrumental in helping doctors care for an aging population with a rising life expectancy.

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