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

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Sara Ferreira
Antonio Couto
Marco Amorim

Besides fatalities, road traffic crashes also cause a large number of nonfatal injuries with a high impact on 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 OECD working group proposal, the European Commission adopted the maximum abbreviated injury scale (MAIS) classification. This injury severity classification is based on medical diagnosis, which is reported by the international classification of diseases (ICD). Therefore, the adoption of MAIS classification 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 named diagnosis-related group (DRG), which is a system codification usually used as a reimbursement mechanism as well as to perform comparisons across hospitals. Tools and methods to easily use this clinical metrics to traffic injury analysis are critical to advance safety knowledge. In this study, we seek to explore the most used clinical metrics that are ICD and DRG to describe the diagnosis and the medical treatment, respectively. The ICD is converted to abbreviated injury scale (AIS), which in time provides the MAIS, i.e., the severity of the injury but also the anatomical description such as the type of body region and anatomical structure. On the other hand, DRG is used to estimate the health care costs (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 on the type of response variable, i.e. discrete or continuous. Due to an evident correlation between body region and MAIS, we firstly analyse the relationship between both variables. Also, the combination of body region and type of anatomical structure is set as other alternative variable. The ordinal logit model is applied, showing that for instance, head is the region of the body associated with high severity, particularly regarding loss of consciousness. Secondly, the relationship between HCC and MAIS, and HCC and body region were analysed separately by using a log link and gamma distribution GLM. The results clearly show that increasing severity, the HCC increase with an evident leap between score 2 to 3 and between score 4 to 5. The head is the body region associated to higher medical treatment costs. Because LHS is still widely used has a measure of injury severity, we apply the same model to the LHS as response variable. Despite the type of relationship was found to be more or less the same, differences were found between LHS model and HCC model. Finally, a discussion is presented 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.

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