2134/32863
Katherine Perez
Katherine
Perez
Wendy Weijermars
Wendy
Weijermars
Niels Bos
Niels
Bos
Ashleigh Filtness
Ashleigh
Filtness
Robert Bauer
Robert
Bauer
Heiko Johannsen
Heiko
Johannsen
Nina Nuyttens
Nina
Nuyttens
Lea Pascal
Lea
Pascal
Pete Thomas
Pete
Thomas
M. Olabarria
M.
Olabarria
Working group of WP7
Working
group of WP7
Implications of estimating road traffic serious injuries from hospital data
Loughborough University
2018
Road traffic injury
MAIS
Data linkage
Injury severity
Design Practice and Management not elsewhere classified
2018-05-08 14:48:40
Journal contribution
https://repository.lboro.ac.uk/articles/journal_contribution/Implications_of_estimating_road_traffic_serious_injuries_from_hospital_data/9346037
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.