Background: The Helicopter Emergency Medical Service (HEMS) is a type of helicopter rescue whose purpose is to optimize health care by operating in parallel and in synergy with the ground network of emergency vehicles to ensure complete coverage of the territory. In Liguria Region, in addition to an established agreement with the Fire Department for a Helicopter Emergency Technical Medical Service (HETMS), from July 2020, a second main helicopter of the private company AirGreen has been introduced. Here, we have carried out an analysis of the activity data on HEMS and medical cars to optimize the cost-effectiveness and highlight the qualitative evolution of the services after the introduction of the second helicopter. Moreover, we have designed a tool to drive the choice of which type of helicopter rescue to use in our Region from time to time. Methods: The data studied, derived from the Medical Priority Dispatch System (MPDS), were provided by the Regional Department of Territorial Health Emergency located at the IRCCS San Martino institute in Genoa. Data were organized into two separate databases, one related to helicopters (1491 rows and 18 columns) and the other related to medical car trips (70130 rows and 21 columns), and then analyzed by using Microsoft Excel software. Results: From the data processing, we have observed a significant increase in helicopter rescue service, which roughly doubled despite the impact of the pandemic, a clear distribution of the service between the Riviera di Ponente (mainly served by the private company AirGreen) and the Riviera del Levante (mainly served by the Fire Department) and a management of 'secondary transport' mostly handled by the private sector. On the other hand, medical-car data are too affected by the impact of the pandemic to be able to highlight a change in service following the introduction of the second helicopter. Focusing on efficiency, we remarked that both services are activated primarily for high severity and priority events. Conclusions: These studies have allowed us to prove graphically and in the regional context the management of helicopter rescue and to hypothesize changes that could optimize the effectiveness and efficiency of the service. In order to achieve this aim, it is considered necessary to create a mathematical model to support decision-making and help to estimate, through objective parameters, which emergency vehicles, between the two main helicopter and the medical cars, should preferentially be activated in case of need.

Helicopter Emergency Medical Service: Analysis and Evaluation of Helicopter Rescue in Liguria

Paoli G.;Scillieri G. S.;Paleari L.;Giacomini M.
2021

Abstract

Background: The Helicopter Emergency Medical Service (HEMS) is a type of helicopter rescue whose purpose is to optimize health care by operating in parallel and in synergy with the ground network of emergency vehicles to ensure complete coverage of the territory. In Liguria Region, in addition to an established agreement with the Fire Department for a Helicopter Emergency Technical Medical Service (HETMS), from July 2020, a second main helicopter of the private company AirGreen has been introduced. Here, we have carried out an analysis of the activity data on HEMS and medical cars to optimize the cost-effectiveness and highlight the qualitative evolution of the services after the introduction of the second helicopter. Moreover, we have designed a tool to drive the choice of which type of helicopter rescue to use in our Region from time to time. Methods: The data studied, derived from the Medical Priority Dispatch System (MPDS), were provided by the Regional Department of Territorial Health Emergency located at the IRCCS San Martino institute in Genoa. Data were organized into two separate databases, one related to helicopters (1491 rows and 18 columns) and the other related to medical car trips (70130 rows and 21 columns), and then analyzed by using Microsoft Excel software. Results: From the data processing, we have observed a significant increase in helicopter rescue service, which roughly doubled despite the impact of the pandemic, a clear distribution of the service between the Riviera di Ponente (mainly served by the private company AirGreen) and the Riviera del Levante (mainly served by the Fire Department) and a management of 'secondary transport' mostly handled by the private sector. On the other hand, medical-car data are too affected by the impact of the pandemic to be able to highlight a change in service following the introduction of the second helicopter. Focusing on efficiency, we remarked that both services are activated primarily for high severity and priority events. Conclusions: These studies have allowed us to prove graphically and in the regional context the management of helicopter rescue and to hypothesize changes that could optimize the effectiveness and efficiency of the service. In order to achieve this aim, it is considered necessary to create a mathematical model to support decision-making and help to estimate, through objective parameters, which emergency vehicles, between the two main helicopter and the medical cars, should preferentially be activated in case of need.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11567/1083038
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact