Exploring the clinical metrics to assess the health cost impact of traffic injuries

Abstract

Besides fatalities, road traffic crashes also cause a large number of nonfatal injuries with a high impacton economic and human costs to society. In order to allow a deep knowledge of the nonfatal injuries,efforts have been made to improve injury severity classification. Recently, and in line with the OECDworking group proposal, the European Commission adopted the maximum abbreviated injury scale(MAIS) classification. This injury severity classification is based on medical diagnosis, which isreported by the international classification of diseases (ICD). Therefore, the adoption of MAISclassification will open the door to a new source of information based on hospital data. Furthermore,the type of medical treatment is commonly described using the international classification nameddiagnosis-related group (DRG), which is a system codification usually used as a reimbursementmechanism as well as to perform comparisons across hospitals. Tools and methods to easily use thisclinical metrics to traffic injury analysis are critical to advance safety knowledge. In this study, weseek to explore the most used clinical metrics that are ICD and DRG to describe the diagnosis and themedical treatment, respectively. The ICD is converted to abbreviated injury scale (AIS), which in timeprovides the MAIS, i.e., the severity of the injury but also the anatomical description such as the typeof body region and anatomical structure. On the other hand, DRG is used to estimate the health carecosts (HCC) applying a national standard methodology. Together with the length of hospital stay(LHS), statistical analyses are applied using generalized linear models (GLM) selected depending onthe type of response variable, i.e. discrete or continuous. Due to an evident correlation between bodyregion and MAIS, we firstly analyse the relationship between both variables. Also, the combination ofbody region and type of anatomical structure is set as other alternative variable. The ordinal logitmodel is applied, showing that for instance, head is the region of the body associated with highseverity, particularly regarding loss of consciousness. Secondly, the relationship between HCC andMAIS, and HCC and body region were analysed separately by using a log link and gamma distributionGLM. The results clearly show that increasing severity, the HCC increase with an evident leapbetween score 2 to 3 and between score 4 to 5. The head is the body region associated to highermedical treatment costs. Because LHS is still widely used has a measure of injury severity, we applythe same model to the LHS as response variable. Despite the type of relationship was found to be moreor less the same, differences were found between LHS model and HCC model. Finally, a discussion ispresented with reference to the long term costs estimated by disability-adjusted life-year (DALY),identifying the future needs to a huge implementation of this metric to traffic injuries.