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Algorithm that Predicts Deadly Infections is Often Flawed


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Consulting a computer during a medical procedure.

A new study using data from nearly 30,000 patients in University of Michigan hospitals suggests a sepsis early warning system developed by Epic System performs poorly.

Credit: Juan Barreto/Getty Images

A complication of infection known as sepsis is the number one killer in US hospitals. So it's not surprising that more than 100 health systems use an early warning system offered by Epic Systems, the dominant provider of US electronic health records. The system throws up alerts based on a proprietary formula tirelessly watching for signs of the condition in a patient's test results.

But a new study using data from nearly 30,000 patients in University of Michigan hospitals suggests Epic's system performs poorly. The authors say it missed two-thirds of sepsis cases, rarely found cases medical staff did not notice, and frequently issued false alarms.

Karandeep Singh, an assistant professor at University of Michigan who led the study, says the findings illustrate a broader problem with the proprietary algorithms increasingly used in health care. "They're very widely used, and yet there's very little published on these models," Singh says. "To me that's shocking."

The study was published Monday in JAMA Internal Medicine. An Epic spokesperson disputed the study's conclusions, saying the company's system has "helped clinicians save thousands of lives."

From Wired
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