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Research Reports |
| Title: | Improving Rural Emergency Medical Services (EMS) through Transportation System Enhancements Phase II |
| Authors: | Xiao Qin, Zhaoxiang He, and Haifa Samra |
| University: | South Dakota State University |
| Publication Date: | Dec 2015 |
| Report #: | MPC-15-301 |
| Project #: | MPC-442 |
| TRID #: | 01594128 |
| Keywords: | emergency medical services, geographic information systems, optimization, performance measures, regression analysis, rural transportation |
| Type: | Research Report – MPC Publications |
Providing acute medical care outside of the hospital, Emergency Medical Services (EMS) is crucial in rural environments where hospitals are not close by and are difficult to access. This study used the National EMS Information System (NEMSIS) South Dakota data to exemplify the establishment of data-driven performance measures for each rural EMS provider. The two measures – timely service and service coverage – are both dependent on mobility and the accessibility of the transportation network. If the service by the current EMS provider is not sufficient, the stations can either be relocated or augmented to increase the service coverage and quality. The bi-objective of maximizing ambulance coverage area and minimizing en route time has been explored under given constraints and solved by the genetic algorithm for tactically locating EMS stations.
Moreover, the factors contributing to en route time were thoroughly reviewed and 13 key variables were identified, including six variables that are specific to the 911 call and seven variables that characterize the service provider. Among several regression models developed and evaluated, the Geographically Weighted Regression (GWR) model was found to produce the best statistical goodness-of-fit and provide additional insights into the particular spatial patterns of coefficient estimates that can be used to explore the influence of unobserved heterogeneity among EMS providers. The findings can be used by the decision-makers to establish performance measures, quantify and monitor service quality over time, identify provider-specific or case-specific contributing factors that may hinder service efficiency, and optimize limited resource to continuously provide effective EMS.
Qin, Xiao, Zhaoxiang He, and Haifa Samra. Improving Rural Emergency Medical Services (EMS) through Transportation System Enhancements Phase II, MPC-15-301. North Dakota State University - Upper Great Plains Transportation Institute, Fargo: Mountain-Plains Consortium, 2015.
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