A black SUV crashed into a silver sedan. (Photo istock/Thomas Eckstadt)

OnStar is enhancing its core safety focus.

In coordination with the GM Foundation, OnStar is providing a grant of $500,000 to the International Center for Automotive Medicine at the University of Michigan Health System for research related to the prediction of injury severity level after a crash. This grant, along with three years of actual OnStar crash data, will enable OnStar and the University of Michigan Health System to link crash data to actual physical injuries sustained in vehicle crashes. The revolutionary research, conducted over approximately 18 months, will look at 1,000 incidents and ultimately will allow OnStar to predict not only the severity of a crash, but assist emergency care providers by providing the probability of certain types of injuries sustained by crash victims.

Also, OnStar, in coordination with the GM Foundation, is providing $100,000 to the CDC Foundation to allow the Centers for Disease Control and Prevention to convene an expert panel to develop a multi-site study design in various states. The study’s purpose will be to assess the correlation of real-time injury predictions sent directly from crash data with actual injury severity. The study will set the stage for broad collaborative research directed at optimizing the potential for automatic crash notification technologies to save lives.

Recently, OnStar also unveiled First Assist, an enhancement of its existing emergency services. The First Assist service allows certified Emergency Advisors to obtain critical information and provide important instructions to subscribers until first responders arrive. Emergency situations can include the aftermath of a car crash or the birth of a child. After determining the nature of the situation, Advisors can provide rapid guidance, which may result in potentially lifesaving actions. This service, available at no additional cost to active OnStar subscribers, will complement the efforts of public safety professionals.

All of this comes on the heels of another project that resulted in the publication of report on advanced automatic collision notification and triage of the injured patient prepared by the Centers for Disease Control and Prevention, National Center for Injury Prevention and Control, Division of Injury Response, as reported in the May 2010 issue of Public Safety Communications:

“With a grant from the GM Foundation and OnStar, the Centers for Disease Control and Prevention (CDC) formed an interdisciplinary panel of experts to investigate the potential impact of the use of Advanced Automatic Collision Notification data on the outcome of medical situations resulting from automotive collisions. The report from the panel identified specific data elements to include in an urgency algorithm, which could generate an estimation of the likelihood that vehicle occupants have sustained severe injuries as a result of the crash. OnStar calls this estimation the injury severity prediction. The complete CDC report, titled Recommendations from the Expert Panel: Advanced Automatic Collision Notification and Triage of the Injured Patient, can be viewed on the CDC Web site.”

Author John Hunt, public policy manager for OnStar and an APCO member since 1987, said, “For many years, some American automobile manufacturers have been able to remotely detect the deployment of an air bag. This capability was originally called Automatic Collision Notification, but with the advent of new vehicle sensors, additional vehicle and collision data can now be monitored and analyzed. This incremental data, which General Motors (GM) began using in 2004 in some vehicles, is called Advanced Automatic Collision Notification, and can include the following types of vehicle data: Delta velocity (change in velocity); principle direction of force (where the impacts occurred); whether multiple impacts occurred; air-bag deployment; rollover status; and vehicle make and model.”

All of these factors can be used by EMS and medical professionals to predict the severity of injury and help determine what facility would be the most appropriate destination.