Responsible for more than 270,000 annual deaths in the U.S., sepsis claims a life in this country every two minutes. The condition, which arises from the body’s inflammatory response to infection, costs over $27 billion in hospitalizations each year.
Despite advancements in understanding and managing sepsis, the fight is far from over. This is why an evolved strategy using predictive technology is critical.
By leveraging patient data, artificial intelligence is helping healthcare organizations identify patients in the early stages of sepsis. With the help of machine learning, custom dashboards to display risk scores and automatic alerts that notify caregivers of potential trouble, an AI-guided approach allows clinicians to get in front of the condition and even predict an adverse event.
Since introducing a sepsis warning system in 2017, Fishersville, Va.-based Augusta Health has witnessed a decrease in mortality rates from sepsis, saving an estimated 282 lives as a result. This drop in mortality rates is promising news and could prompt wider deployment of the tools.
Augusta’s warning system is able to examine patients’ vital signs via their electronic health records, recognize familiar warning signs of sepsis onset and alert clinicians and staff if abnormalities arise.
A number of healthcare organizations are doing the same by adopting or building upon existing AI models to help combat sepsis. Here’s a look at some notable recent efforts.
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