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

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.

Differences in urban and rural accident characteristics and medical service utilization for traffic fatalities in less-motorized societies.

Introduction: Fatalities from traffic accidents in less-motorized societies are an important global issue. We aimed to characterize the geographic differences of fatalities in such societies to facilitate the development of targeted interventions.

Method: This study linked police reports, hospital data, and vital registration data from Taiwan with special reference to accident factors in pre-hospital deaths and medical care in hospital deaths.

Mortality burden from motor vehicle accidents in Taiwan.

Objective: To examine the risk factors contributing to the mortality burden due to road traffic accidents (RTA) in Taiwan.

Design: We compared RTA years of life lost (YLL) rates of Taiwan with those of the surrounding region. We also investigated the risk factors described by the police in a Linked Database combined from police-reported accident data and vital registration data.

Using data linkage to generate 30-day crash-fatality adjustment factors for Taiwan.

Different countries have their own police reporting time standards for counting the number of fatalities in reported crashes. A rapid estimation method (such as adjustment factor) for the comparison is important. The data-linkage technique was used to combine police-reported crash data and vital registration data, in order to generate 30-day fatality adjustment factors for various reporting time standards, which could also shed light on the fatal injury trend over time.