Analytic queueing model for ambulance services

TL;DR

This paper develops an analytic queueing model to predict ambulance requirements based on demand, differentiating between emergency and non-urgent calls, and analyzes both stationary and nonstationary regimes for performance assessment.

Contribution

It introduces a comprehensive analytic framework for ambulance service modeling, incorporating nonstationary and stationary regimes with detailed probabilistic analysis.

Findings

Effective prediction of ambulance staffing needs

Insights into emergency vs. non-urgent call handling

Performance metrics for ambulance service efficiency

Abstract

We present predictive tools to calculate the number of ambulances needed according to demand of entrance calls and time of service. Our analysis discriminates between emergency and non-urgent calls. First, we consider the nonstationary regime where we apply previous results of first-passage time of one dimensional random walks. Then, we reconsider the stationary regime with a detailed discussion of the conditional probabilities and we discuss the key performance indicators.