1. Implications of estimating road traffic serious injuries from hospital data
- Author
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Heiko Johannsen, Nina Nuyttens, Pete Thomas, Katherine Pérez, Ashleigh J. Filtness, Robert Bauer, Niels Bos, Wendy Weijermars, Léa Pascal, Marta Olabarria, Agència de Salut Pública de Barcelona (ASPB), Institute for Road Safety Research, Transport Safety Research Centre, Loughborough University, Austrian Road Safety Board, Medical University of Hannover, VIAS Institute, Unité Mixte de Recherche Epidémiologique et de Surveillance Transport Travail Environnement (UMRESTTE UMR T9405), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), and CIBER de Epidemiología y Salud Pública (CIBERESP)
- Subjects
EPIDEMIOLOGIE ,ROAD TRAFFIC INJURY ,ACCIDENT DE LA ROUTE ,BLESSURE) ,Human Factors and Ergonomics ,Hospital records ,INJURY SEVERITY ,0502 economics and business ,medicine ,Humans ,BLESSURE ,0501 psychology and cognitive sciences ,Safety, Risk, Reliability and Quality ,Data Linkage ,Road traffic ,050107 human factors ,050210 logistics & transportation ,Descriptive statistics ,Abbreviated Injury Scale ,business.industry ,Data Collection ,05 social sciences ,Accidents, Traffic ,Public Health, Environmental and Occupational Health ,GRAVITE (ACCID ,medicine.disease ,Hospitals ,Weighting ,Europe ,MAIS ,DATA LINKAGE ,External injury ,Case selection ,Wounds and Injuries ,[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie ,Medical emergency ,business - 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.
- Published
- 2018
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