摘要：Background: The ability to quickly and effectively receive medical treatment in the event of an automobile collision is one of the most important aspects in emergency medical services (EMS). Emergency medical service providers are the first to respond and manage cases related to trauma, emergency surgery, and critically injured patients. Response time for emergency medical services vehicles is especially important for areas, where travel distances are often much larger, compared to more urban areas. The importance of the present data and analysis procedures are their applicability to multiple environments, including urban settings. Methods: The present study is focused on optimization of analysis tools, and understanding the influences of different traffic-related variables, related to hospital EMS transport times for Pickens County, a county in west Alabama. Optimization of associated analysis tools is important for optimal trauma patient survivability, and as such, is directly relevant to the management of care for severely injured surgical patients. Of particular interest are the effects of variables, such as travel time, time of the day, day of the week, weather, lighting conditions, and crash severity, on the EMS response time (ERT), which are analyzed using two types of advanced regression analysis: geographically weighted regression (GWR) and global regression analysis (GRA). Results: For GWR analysis, the accuracy of the approach is improved by employing an adaptive bi-square kernel weighting function. The GWR approach is also unique because geographic location variations are quantified for local independent variables, as their effects are included. Magnitudes of variable coefficients, and variable t-statistic values provide information on the relative influences and impacts of different variables, and different variable combinations, as they are considered in pairs, triplets, and different combinations. Conclusion: The resulting effects and alterations to optimal EMS response time are provided for a wide range of travel conditions and travel time periods.
