OnStar’s Injury Severity Prediction analyzes crash information like force of impact and direction of impact to determine the probability of severe injury to the vehicle occupants. OnStar advisors then relay the Injury Severity Prediction rating to 9-1-1 centers, which may choose to adjust the level and priority of response dispatched to a crash scene.
OnStar’s Injury Severity Prediction service is accurately predicting the severity of crash victims’ injuries, allowing for improved on-scene treatment, according to findings of a recent study.
Injury Severity Prediction (ISP) is an algorithm that OnStar uses in properly equipped Chevrolet, Buick, GMC and Cadillac vehicles in the U.S. and Canada to provide additional information to first responders following a vehicle crash.
The algorithm analyzes crash information like force of impact and direction of impact to determine the probability of severe injury to the vehicle occupants.
OnStar Advisors then relay the Injury Severity Prediction rating to 9-1-1 centers, which may choose to adjust the level and priority of response dispatched to a crash scene.
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Over the past four years, General Motors, OnStar and the University of Michigan’s International Center for Automotive Medicine (ICAM), led by Dr. Stewart Wang, conducted research that illustrates how crash data can assist first responders.
This was the first known study to match real-life injury outcomes with crash telemetry data.
Now that the algorithm for predicting severe injuries has been validated, the next step is educating the emergency response community so it can adjust training and protocols.
Pilot programs will be held in early summer.
Taking input from the pilot sessions, the training will be adjusted and rolled out to all first responders in the fall.
OnStar Injury Severity Prediction is part of OnStar’s Automatic Crash Response service, available as part of the OnStar Protection, Security and Guidance plans.
OnStar responds to more than 5,000 vehicle crashes every month.
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