GM OnStar Adds ‘Injury Severity Protection’ Technology

GM OnStar Adds ‘Injury Severity Protection’ Technology

General Motors has used a study to prove how effective its latest OnStar technology is.

OnStar’s Injury Severity Protection is a new feature that can accurately predict the severity of crash victims’ injuries, helping improve on-scene treatment, according to the American automaker. By using an algorithm that analyzes crash information like force of impact and direction of impact, Injury Severity Protection is able to determine the probability of severe injury to the vehicle occupants. When an accident occurs, OnStar Advisors are able to relay that predicted rating to 9-1-1 centers, which may choose to adjust the level and priority of response dispatched to the crash scene.

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Over the past four years, the American automaker has worked with OnStar and the University of Michigan’s International Center for Automotive Medicine (ICAM) to conduct research that illustrates how crash data can assist first responders. Led by Dr. Stewart Wang, the team matched each Injury Severity Protection rating with the corresponding police report, medical records, EMS data and computerized tomography (CT) scan data, with the goal of seeing if the predicted injury rating accurately matched the confirmed injuries. The result of the study validated the algorithm that the system uses and pilot programs will commence this summer to educate the emergency response community so that it can adjust training and protocols.

The technology can be found in properly equipped Chevrolet, Buick, GMC and Cadillac models in the U.S. and Canada.

“This past April we added injury severity prediction criteria to our trauma transport protocols,” said Cory Richter, battalion chief, Indian River County (Fla.) Fire Rescue. “It has been proven that crash victims with a severe injury have a better chance of survival when they’re transported to a trauma center instead of a local hospital. Resources like OnStar’s Injury Severity Prediction give us a better chance of identifying those victims early on.”

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