In order to allow a deep knowledge of the nonfatal injuries, recently the European Commission adopted the maximum abbreviated injury scale classification which is based on medical diagnosis. This classification will open the door to a new source of information based on international hospital data such as diagnosis-related group and international classification of diseases. In this study, we seek to explore these clinical metrics, which are used to describe the diagnosis and the medical treatment, and to infer consequences of crashes mainly through the costs and severity. Therefore, statistical analyses were applied using generalized linear models selected depending on the type of response variable, i.e. discrete or continuous. Relationships between these metrics were identified revealing for instance that head is the region of the body associated with high severity as well as to higher health care costs. Additionally, a discussion is presented regarding study results and future developments of clinical metrics are pointed out.
Keywords: Traffic injury; diagnosis-related group; health care cost; length of hospital stay; maximum abbreviated injury scale.