Implications of estimating road traffic serious injuries from hospital data
Pérez, Catherine (Agència de Salut Pública de Barcelona)
Weijermars, Wendy (Institute for Road Safety Research (SWOV))
Bos, Niels M. (Institute for Road Safety Research (SWOV))
Filtness, Ashleigh J. (Transport Safety Research Centre. Loughborough University (LOUGH))
Bauer, Robert (Austrian Road Safety Board (KFV))
Johannsen, Heiko (Medical University of Hannover (MHH))
Nuyttens, Nina (Vias institute)
Pascal, L. (French Institute of Science and Technology for Transport)
Thomas, P. (Loughborough University (LOUGH))
Olabarria Saenz de Viguera, Marta (Institut d'Investigació Biomèdica Sant Pau)
Universitat Autònoma de Barcelona

Data:	2019
Resum:	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.
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Data linkage ; Injury severity ; MAIS ; Road traffic injury
Publicat a:	Accident analysis and prevention, Vol. 130 (september 2019) , p. 125-135, ISSN 0001-4575

DOI: 10.1016/j.aap.2018.04.005
PMID: 29680154

11 p, 405.0 KB

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