Policy-making

Injury Prediction Algorithms

In 2007, Stewart Wang, the Director of the International Center of Automotive Medicine, was a member of a CDC-convened expert panel of more than 20 of the nation's leading emergency medical physicians, public safety and vehicle safety experts to review real-time crash data to determine how it can be used to further improve the emergency transport and treatment of crash victims.

Thanks to the findings of this panel, our team worked with GM and OnStar to develop an important new tool to assist emergency responders in anticipating the seriousness of a crash. This new technology called Injury Severity Prediction utilizes Automatic Collison Notification data to predict if a crash is likely to have caused severe injury to passengers. Each crash is given an Injury Severity Prediction of either "normal" or "high," helping first responders better determine what level of care is required and what medical facility is most appropriate for transport. In an MVC, seconds are precious following a traumatic injury and complications can result from the delayed treatment of injuries. With this new tool, when a medical professional responds to a crash scene, we've equipped them with information that makes them better prepared to treat crash victims and, ultimately, save more lives.