Decision-making model for hospital selection in the emergency medical system

Abstract

We designed a decision model for hospital selection in the emergency medical system, which integrates its actors, such as the dispatch center, emergency medical services (EMS), and emergency departments (ED). We designed and simulated the model using colored Petri nets to evaluate two policies: the nearest hospital policy (in time) and the proposed policy that integrates the proximity criteria and ED congestion. The simulation results for the Massachusetts Region 3 case study indicate that the proposed policy that considers the shortest transfer times (travel time + wait time) appropriately allocates ambulance patients to EDs. In addition, the proposed improves and balances indicators, such as average patient waiting times per ESI, physician utilization, and average patient queues, in each ED. For example, the proposed policy best scenario that adds a physician to all hospital EDs would reduce waiting times for ESI 2 and 3 patients between (26.16%–71.65%) and (74.69%–88.84%), respectively, and improve the patient queue and the allocation of ambulance patients. Finally, the proposed decision policy allows the planning of medical staff in EDs and scenario analysis using performance indicators focused on the timeliness of patient care. This approach would avoid problems such as overcrowding, delayed discharge, retention, and diversion of ambulances, putting patient health and life at risk.

Keywords:

• Decision making
• ambulance allocation
• emergency medical services
• healthcare management
• discrete event simulation
• emergency department

Disclosure statement

No potential conflict of interest was reported by the author(s).

Consent and approval statement

This study does not require approval from an institutional review board (IRB) as it used de-identified secondary data collected by a public agency.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.