AI can predict when we’ll die—here’s why that’s a good thing

Feb. 8, 2018

Artificial intelligence is proving to be a revolutionary tool across many industries, but the technology is having a particularly big impact when it comes to healthcare. Researchers are using AI to combat the flu, by building improved seasonal forecasts that inform the development of influenza vaccines, and the technology is already helping to diagnose rare diseases so that patients can get the treatments they need.

Now, scientists have found a new medical application for AI: Predicting when a seriously ill patient admitted to the hospital will likely die.

In hospitals, palliative care teams are charged with improving the quality of life of gravely ill patients and making sure their final wishes are carried out. But clinicians sometimes don’t refer their patients to these specialists because they believe their patients are better off than they really are.

Research shows that less than half of the 8% of hospital admissions who need palliative care actually receive it, says Kenneth Jung, a research scientist at Stanford University School of Medicine who helped develop the new AI algorithm.

This can have terrible consequences if the patient’s health suddenly plummets, causing some people to spend their final days receiving aggressive treatments to extend life a few weeks when they’d rather spend that time with family. Studies have shown that approximately 80% of Americans say they would prefer to die at home, but 60% die in acute care hospitals, according to Stanford.

The new algorithm can predict if a hospital inpatient will die within 3 to 12 months (a window during which palliative care is thought to be most useful) with over 90% accuracy.

In the near future, health records of all hospital admissions could be screened by the AI, which would then flag palliative care teams about patients who may be near death. The specialists would review the records of those people and discuss with clinicians whether they could indeed benefit from palliative care.

In effect, the AI would help ensure that most severely ill patients are as comfortable as possible in their final months and receive the care that best reflects their preferences.

In this case, Stanford researchers used AI to parse the medical records of 160,000 deceased patients of Stanford Health Care and Lucile Packard Children’s Hospital who had varying illnesses (ranging from cancer to organ failure to neurological issues), medical histories, and disease severities.

Knowing the exact date of each patient’s death, the AI searched the records for patterns indicative of advanced illness and encroaching death and assigned weights to the various pieces of medical information.

When tested on the records of another 40,000 patients whose deaths were withheld, the algorithm was able to correctly determine if the patient died within a 3- to 12-month window from a specific date nine times out of 10.

NBC News has the full story

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