Implications of estimating road traffic serious injuries from hospital data. (September 2019) - Pérez, K.; Weijermars, W.; Bos, N.; Filtness, A.J.; Bauer, R.; Johannsen, H.; Nuyttens, N.; Pascal, L.; Thomas, P.; Olabarria, M.; ,
Highlights: It is essential to use a common definition to compare serious road traffic injury rates. For estimating the number of serious injuries, at some point it is always necessary to use hospital records. This paper explores the implications for in/exclusion criteria applied to case selection and. Provides a methodological approach for converting ICD to MAIS codes. Weighting factors could be used to correct data deviations and make more real estimations. Abstract: To determine accurately the number of serious injuries at EU level and to compare serious injury rates between different countries it is essential to use a common definition. In January 2013, the High Level Group on Road Safety established the definition of serious injuries as patients with an injury level of MAIS3+(Maximum Abbreviated Injury Scale). Whatever the method used for estimating the number or serious injuries, at some point it is always necessary to use hospital records. The aim of this paper is to understand the implications for (1) in/exclusion criteria applied to case selection and (2) a methodological approach for converting ICD (International Classification of Diseases/Injuries) to MAIS codes, when estimating the number of road traffic serious injuries from hospital data. A descriptive analysis with hospital data from Spain and the Netherlands was carried out to examine the effect of certain choices concerning in- and exclusion criteria based on codes of the ICD9-CM and ICD10. The main parameters explored were: deaths before and after 30 days, readmissions, and external injury causes. Additionally, an analysis was done to explore the impact of using different conversion tools to derive MAIS3 + using data from Austria, Belgium, France, Germany, Netherlands, and Spain. Recommendations are given regarding the in/exclusion criteria and when there is incomplete data to ascertain a road injury, weighting factors could be used to correct data deviations and make more real estimations.