Improving timeliness and accuracy of data on road traffic injury severity in an emerging economy setting

Road traffic accidents (RTAs) are among the leading causes of injury and fatality worldwide. Currently, the casualty of RTAs is continuously increasing in Taiwan; however, because of the lack of an advanced method to classify data regarding the injury severity in RTAs and the fragmentation of the original sources of these data, the road traffic safety authorities encounter difficulties in analyzing the epidemiology of injury patterns and mechanisms of RTAs as well as the effects on the victims, their families, and national resources. These difficulties may lead to blind spots during policy making. Our study reports the current situation of RTA data collection in Taiwan and the sources of domestic RTA injury data. After reviewing the classification methods of RTA injury severity applied in developed countries, we analyzed the difficulties of injury prevention that are caused by a lack of effective classification of RTA injury severity in Taiwan. We also examined the fragmentation of sources of domestic RTA injury data and its influences. We then proposed a method for classifying injury severity and a potential model for the timely collection and integration of these data. Finally a comparison among different models for collecting RTA injury data was completed.