Estimating demand for emergency transportation

Area of Science:

• Emergency Medical Services
• Health Services Research
• Transportation Planning

Background:

• Current emergency transportation services face increasing demand.
• Accurate estimation of demand is crucial for resource allocation and service optimization.
• Understanding utilization patterns is key to improving efficiency.

Purpose of the Study:

• To estimate current and future demands for emergency transportation services.
• To define correct and incorrect utilization based on response levels and severity.
• To develop predictive models for future demand.

Main Methods:

• Defined correct/incorrect utilization by matching response types (MICU, BEA, etc.) to severity levels (Life-threat, Urgent, etc.).
• Calculated demand and need using data from emergency facilities.
• Developed multiple regression models to estimate future demand, validated with rural county data.

Main Results:

• Five significant variables were identified as key predictors of demand.
• These variables explained over 90% of the variation in the number of emergency transportation calls.
• Predictive equations were developed using these variables.

Conclusions:

• The developed models provide a robust method for estimating emergency transportation demand.
• Accurate demand prediction can lead to improved resource allocation and service delivery.
• Identifying key predictive variables enhances the efficiency of emergency medical services.