arXiv subjects

Massimo Roma

Publications and source records attributed to Massimo Roma.

3 recordsLinked to original sources

arXiv2026

A Realistic Discrete Event Simulation model for Ambulance Location and Deployment within a regional Emergency Medical Service

The objective of Emergency Medical Services (EMSs) is to promptly respond to calls from citizens for first aid, providing pre-hospital care and, if necessary, to transfer patients to an appropriate Emergency Department (ED) by ambulance. The efficiency of such a system strongly depends on the deployment of ambulance home bases, i.e., locations where ambulances and their crews are strategically positioned, ready to respond to emergency calls. This paper presents a general Discrete Event Simulation (DES) model designed to capture the stochastic behaviour and workflow of regional ambulance emergency systems. The proposed model incorporates and integrates information collected from different sources, reproducing very accurately the operation of the ambulance system, thus allowing a more comprehensive and realistic analysis. To show the applicability and reliability of the proposed general model, a case study provided by the Azienda Regionale Emergenza Sanitaria - ARES 118 (an Italian Regional Emergency Medical Services Authority - ARES~118}) is presented. It concerns a territory within the Lazio region of Italy, including a medium-size city along with sparsely populated areas. The reported results about scenario analyses highlight how the model we propose can be fruitfully used by the managers to improve effectiveness and quickness of the entire regional EMS system.

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arXiv2023

A Simulation--Based Optimization approach for analyzing the ambulance diversion phenomenon in an Emergency-Department network

Ambulance Diversion (AD) is one of the possible strategies for relieving the worldwide phenomenon of Emergency Department (ED) overcrowding. It can be carried out when an ED is overloaded and consists of redirecting incoming by ambulance patients to neighboring EDs. Properly implemented, AD should result in reducing delays of patient treatment, ensuring safety and rescue of life-threatening patients. From an operational point of view, AD corresponds to a resource pooling policy among EDs in a network. In this paper we propose a novel model for studying the effectiveness of AD strategies, based on the Simulation-Based Optimization (SBO) approach. In particular, we developed a discrete event simulation model for reproducing the ED network operation. Then, for each AD policy considered, we formulate and solve an optimal resources allocation problem consisting of a bi-objective SBO problem where the target is the minimization of the non-value added time spent by patients and the overall cost incurred by the ED network. A set of optimal points belonging to the Pareto frontier is obtained for each policy. To show the reliability of the proposed approach, a real case study consisting of six large EDs in the Lazio region of Italy is considered, analyzing the effects of adopting different AD policies.

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arXiv2021

A Simulation-Based Optimization approach for analyzing the ambulance diversion phenomenon in an Emergency Department network

Most of the studies dealing with the increasing and well-known problem of Emergency Department (ED) overcrowding usually mainly focus on modeling the patient flow within a single ED, without considering the possibilities offered by the cooperation among EDs. Instead, it is important to analyze the overcrowding phenomenon considering an ED network rather than a single ED. In this paper, the Simulation-Based Optimization approach is adopted for studying an ED network under different conditions, by means of Discrete Event Simulation models. In particular we consider the so called Ambulance Diversion problem, analyzing different diversion policies. Such models are carried out from real data collected from six big EDs in the Lazio region of Italy. The aim is to optimize the performances of the entire network, in order to provide the best service to the patients without sustaining too high costs. The obtained experimental results show which are the best diversion policies both in terms of patient waiting time and costs for the service providers.

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