Loughborough University
Browse
Perez_1-s2.0-S000145751830143X-main.pdf (405.04 kB)

Implications of estimating road traffic serious injuries from hospital data

Download (405.04 kB)
journal contribution
posted on 2018-05-08, 14:48 authored by Katherine Perez, Wendy Weijermars, Niels Bos, Ashleigh FiltnessAshleigh Filtness, Robert Bauer, Heiko Johannsen, Nina Nuyttens, Lea Pascal, Pete Thomas, M. Olabarria, Working group of WP7
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.

Funding

This work has been funded by the SafetyCube (Safety CaUsation, Benefits and Efficiency) (H2020 N.633485).

History

School

  • Design

Published in

Accident Analysis and Prevention

Volume

130

Pages

125-135

Citation

PEREZ, K. ...et al., 2018. Implications of estimating road traffic serious injuries from hospital data. Accident Analysis and Prevention, 130, pp. 125-135.

Publisher

Elsevier

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2018-01-17

Publication date

2018-04-19

Copyright date

2018

Notes

This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND). Full details of this licence are available at: http://creativecommons.org/licenses/by-nc-nd/4.0/

ISSN

1879-2057

Language

  • en

Usage metrics

    Loughborough Publications

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC