(A175) Traffic Injury Severity Prediction by Algorithm of Automatic Crash Notification System

Abstract

Introduction

Since 2009 automatic crash notification system(ACNS) using event data recorder(EDR) and mobile communication have been developed for early detection of traffic accident and prediction of physical injury of victims for increase of survival rate via early medical treatment. For adequate prediction of injury, authors developed the guideline and algorithm from parameters related to accident and medical situation. Methods: Expert survey was done about the adequate parameters related to accident and medical situation. Medical record of traffic accident admission was analyzed in a trauma center of a university hospital in Seoul, Korea. Additionally epidemiology of traffic accident death in a region was done. Afterwards data of medical record was linked to data of traffic accident insurance companies.

Results

The important parameters for prediction of physical injury of victims were as follows: Intercept, deltav, belt, age, intrus, sex, multiple, roll, ejection, narrow, height, weight, steering defect, track loc.

Conclusions

Prediction of physical injury severity of victims on traffic accident spot and immediate transfer of related information to adequate medical institution by automatic mobile communication can help the traffic accident victims and upgrade the trauma care system of traffic accident.