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Implications of estimating road traffic serious injuries from hospital data
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 injur...
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| Main Authors: | , , , , , , , , , , |
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| Format: | Default Article |
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2018
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| Online Access: | https://hdl.handle.net/2134/32863 |
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| _version_ | 1818169737241165824 |
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| author | Katherine Perez Wendy Weijermars Niels Bos Ashleigh Filtness Robert Bauer Heiko Johannsen Nina Nuyttens Lea Pascal Pete Thomas M. Olabarria Working group of WP7 |
| author_facet | Katherine Perez Wendy Weijermars Niels Bos Ashleigh Filtness Robert Bauer Heiko Johannsen Nina Nuyttens Lea Pascal Pete Thomas M. Olabarria Working group of WP7 |
| author_sort | Katherine Perez (7149641) |
| collection | Figshare |
| description | 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. |
| format | Default Article |
| id | rr-article-9346037 |
| institution | Loughborough University |
| publishDate | 2018 |
| record_format | Figshare |
| spelling | rr-article-93460372018-04-19T00:00:00Z Implications of estimating road traffic serious injuries from hospital data Katherine Perez (7149641) Wendy Weijermars (7149656) Niels Bos (7149644) Ashleigh Filtness (1384968) Robert Bauer (230088) Heiko Johannsen (7152353) Nina Nuyttens (7149650) Lea Pascal (7152356) Pete Thomas (1249617) M. Olabarria (7152359) Working group of WP7 (7152362) Design not elsewhere classified Road traffic injury MAIS Data linkage Injury severity Design Practice and Management not elsewhere classified 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. 2018-04-19T00:00:00Z Text Journal contribution 2134/32863 https://figshare.com/articles/journal_contribution/Implications_of_estimating_road_traffic_serious_injuries_from_hospital_data/9346037 CC BY-NC-ND 4.0 |
| spellingShingle | Design not elsewhere classified Road traffic injury MAIS Data linkage Injury severity Design Practice and Management not elsewhere classified Katherine Perez Wendy Weijermars Niels Bos Ashleigh Filtness Robert Bauer Heiko Johannsen Nina Nuyttens Lea Pascal Pete Thomas M. Olabarria Working group of WP7 Implications of estimating road traffic serious injuries from hospital data |
| title | Implications of estimating road traffic serious injuries from hospital data |
| title_full | Implications of estimating road traffic serious injuries from hospital data |
| title_fullStr | Implications of estimating road traffic serious injuries from hospital data |
| title_full_unstemmed | Implications of estimating road traffic serious injuries from hospital data |
| title_short | Implications of estimating road traffic serious injuries from hospital data |
| title_sort | implications of estimating road traffic serious injuries from hospital data |
| topic | Design not elsewhere classified Road traffic injury MAIS Data linkage Injury severity Design Practice and Management not elsewhere classified |
| url | https://hdl.handle.net/2134/32863 |