Current Urban Studies, 2021, 9, 581-596 https://www.scirp.org/journal/cus ISSN Online: 2328-4919 ISSN Print: 2328-4900 DOI: 10.4236/cus.2021.93035 Sep. 22, 2021 581 Current Urban Studies EMS Response Time for Patients Critically-Injured from Automobile Accidents Using Regression Analysis Sneha R. Vanga, Phillip M. Ligrani, Mehrnaz Doustmohammadi, Michael Anderson Department of Mechanical and Aerospace Engineering, Department of Civil & Environmental Engineering, The University of Alabama in Huntsville, Huntsville, AL, USA Abstract 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, in- cluding urban settings. Methods: The present study is focused on optimiza- tion 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 im- portant for optimal trauma patient survivability, and as such, is directly rele- vant to the management of care for severely injured surgical patients. Of par- ticular 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 regres- sion analysis: geographically weighted regression (GWR) and global regres- sion 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. Mag- nitudes of variable coefficients, and variable t-statistic values provide informa- tion 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 How to cite this paper: Vanga, S. R., Li- grani, P. M., Doustmohammadi, M., & An- derson, M. (2021). EMS Response Time for Patients Critically-Injured from Automobile Accidents Using Regression Analysis. Cur- rent Urban Studies, 9, 581-596. https://doi.org/10.4236/cus.2021.93035 Received: August 8, 2021 Accepted: September 19, 2021 Published: September 22, 2021 Copyright © 2021 by author(s) and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/ Open Access