Improving the timeliness and accuracy of injury severity data in road traffic accidents in an emerging economy setting

Carlos Lam, Chang-I Chen, Chia-Chang Chuang, Chia-Chieh Wu, Shih-Hsiang Yu, Kai-Kuo Chang, Wen-Ta Chiu

研究成果: 雜誌貢獻文章

摘要

Road traffic injuries (RTIs) are among the leading causes of injury and fatality worldwide. RTI casualties are continually increasing in Taiwan; however, because of a lack of an advanced method for classifying RTI severity data, as well as the fragmentation of data sources, road traffic safety and health agencies encounter difficulties in analyzing RTIs and their burden on the healthcare system and national resources. These difficulties lead to blind spots during policy-making for RTI prevention and control. After compiling classifications applied in various countries, we summarized data sources for RTI severity in Taiwan, through which we identified data fragmentation. Accordingly, we proposed a practical classification for RTI severity, as well as a feasible model for collecting and integrating these data nationwide. This model can provide timely relevant data recorded by medical professionals and is valuable to healthcare providers. The proposed model’s pros and cons are also compared to those of other current models.
原文繁體中文
頁(從 - 到)mzy115-mzy115
期刊International Journal for Quality in Health Care
31
發行號2
DOIs
出版狀態已發佈 - 2019

引用此文

Improving the timeliness and accuracy of injury severity data in road traffic accidents in an emerging economy setting. / Lam, Carlos; Chen, Chang-I; Chuang, Chia-Chang; Wu, Chia-Chieh; Yu, Shih-Hsiang; Chang, Kai-Kuo; Chiu, Wen-Ta.

於: International Journal for Quality in Health Care, 卷 31, 編號 2, 2019, p. mzy115-mzy115.

研究成果: 雜誌貢獻文章

@article{f9e9ee611f8d4c1cbb2ce6e7fe3dc418,
title = "Improving the timeliness and accuracy of injury severity data in road traffic accidents in an emerging economy setting",
abstract = "Road traffic injuries (RTIs) are among the leading causes of injury and fatality worldwide. RTI casualties are continually increasing in Taiwan; however, because of a lack of an advanced method for classifying RTI severity data, as well as the fragmentation of data sources, road traffic safety and health agencies encounter difficulties in analyzing RTIs and their burden on the healthcare system and national resources. These difficulties lead to blind spots during policy-making for RTI prevention and control. After compiling classifications applied in various countries, we summarized data sources for RTI severity in Taiwan, through which we identified data fragmentation. Accordingly, we proposed a practical classification for RTI severity, as well as a feasible model for collecting and integrating these data nationwide. This model can provide timely relevant data recorded by medical professionals and is valuable to healthcare providers. The proposed model’s pros and cons are also compared to those of other current models.",
author = "Carlos Lam and Chang-I Chen and Chia-Chang Chuang and Chia-Chieh Wu and Shih-Hsiang Yu and Kai-Kuo Chang and Wen-Ta Chiu",
note = "10.1093/intqhc/mzy115",
year = "2019",
doi = "10.1093/intqhc/mzy115",
language = "繁體中文",
volume = "31",
pages = "mzy115--mzy115",
journal = "International Journal for Quality in Health Care",
issn = "1353-4505",
publisher = "Oxford University Press",
number = "2",

}

TY - JOUR

T1 - Improving the timeliness and accuracy of injury severity data in road traffic accidents in an emerging economy setting

AU - Lam, Carlos

AU - Chen, Chang-I

AU - Chuang, Chia-Chang

AU - Wu, Chia-Chieh

AU - Yu, Shih-Hsiang

AU - Chang, Kai-Kuo

AU - Chiu, Wen-Ta

N1 - 10.1093/intqhc/mzy115

PY - 2019

Y1 - 2019

N2 - Road traffic injuries (RTIs) are among the leading causes of injury and fatality worldwide. RTI casualties are continually increasing in Taiwan; however, because of a lack of an advanced method for classifying RTI severity data, as well as the fragmentation of data sources, road traffic safety and health agencies encounter difficulties in analyzing RTIs and their burden on the healthcare system and national resources. These difficulties lead to blind spots during policy-making for RTI prevention and control. After compiling classifications applied in various countries, we summarized data sources for RTI severity in Taiwan, through which we identified data fragmentation. Accordingly, we proposed a practical classification for RTI severity, as well as a feasible model for collecting and integrating these data nationwide. This model can provide timely relevant data recorded by medical professionals and is valuable to healthcare providers. The proposed model’s pros and cons are also compared to those of other current models.

AB - Road traffic injuries (RTIs) are among the leading causes of injury and fatality worldwide. RTI casualties are continually increasing in Taiwan; however, because of a lack of an advanced method for classifying RTI severity data, as well as the fragmentation of data sources, road traffic safety and health agencies encounter difficulties in analyzing RTIs and their burden on the healthcare system and national resources. These difficulties lead to blind spots during policy-making for RTI prevention and control. After compiling classifications applied in various countries, we summarized data sources for RTI severity in Taiwan, through which we identified data fragmentation. Accordingly, we proposed a practical classification for RTI severity, as well as a feasible model for collecting and integrating these data nationwide. This model can provide timely relevant data recorded by medical professionals and is valuable to healthcare providers. The proposed model’s pros and cons are also compared to those of other current models.

U2 - 10.1093/intqhc/mzy115

DO - 10.1093/intqhc/mzy115

M3 - 文章

VL - 31

SP - mzy115-mzy115

JO - International Journal for Quality in Health Care

JF - International Journal for Quality in Health Care

SN - 1353-4505

IS - 2

ER -