In injuries reducing ambulance response time (time from injury to hospital arrival) is an important factor for saving people’s lives. Helicopter emergency medical services can reduce out-of-hospital transport times b...In injuries reducing ambulance response time (time from injury to hospital arrival) is an important factor for saving people’s lives. Helicopter emergency medical services can reduce out-of-hospital transport times because of their high speed and their ability to travel in straight paths?unlike ground ambulance which are restricted to road network paths, as well as the ability toaccess rural or remote area injuries that are difficult to reach by ground ambulance. GIS technology aids air ambulance movement planning to reduce out-of-hospital response time based on mathematical and geographic models to support decision making which is necessary from out-of-hospital care providers. The goal of this study is to use GIS to develop an efficient DSS to outline where air ambulance can reduce response times, by using spatial analysis tools to create Euclidean distance and direction zones around receiving hospitals. The study concludes that GIS technology can be used to develop an efficient DSS to outline where air ambulance can reduce response times, by creating surfaces of Euclidean allocation, direction, and distance that can be used to improve initial response times for the civil defense air rescue and air ambulance services.展开更多
Emergency ambulance services in the UK are tasked with providing pre-hospital patient care and clinical services with a target response time between call connect to on-scene attendance.In 2017,NHS England introduced f...Emergency ambulance services in the UK are tasked with providing pre-hospital patient care and clinical services with a target response time between call connect to on-scene attendance.In 2017,NHS England introduced four new response time categories based on patient needs.The most challenging is to be on-scene for a life-threatening situation within seven minutes of the call being connected when such calls are random in terms of time and place throughout a large territory.Recent evidence indicates emergency ambulance services regularly fall short of achieving the target ambulance response times set by the National Health Service(NHS).To achieve these targets,they need to undertake transformational change and apply statistical,operations research and artificial intelligence techniques in the form of five separate modules covering demand forecasting,plus locate,allocate,dispatch,monitoring and re-deployment of resources.These modules should be linked in real-time employing a data warehouse to minimise computational data and generate accurate,meaningful and timely decisions ensuring patients receive an appropriate and timely response.A simulation covering a limited geographical area,time and operational data concluded that this form of integration of the five modules provides accurate and timely data upon which to make decisions that effectively improve ambulance response times.展开更多
文摘In injuries reducing ambulance response time (time from injury to hospital arrival) is an important factor for saving people’s lives. Helicopter emergency medical services can reduce out-of-hospital transport times because of their high speed and their ability to travel in straight paths?unlike ground ambulance which are restricted to road network paths, as well as the ability toaccess rural or remote area injuries that are difficult to reach by ground ambulance. GIS technology aids air ambulance movement planning to reduce out-of-hospital response time based on mathematical and geographic models to support decision making which is necessary from out-of-hospital care providers. The goal of this study is to use GIS to develop an efficient DSS to outline where air ambulance can reduce response times, by using spatial analysis tools to create Euclidean distance and direction zones around receiving hospitals. The study concludes that GIS technology can be used to develop an efficient DSS to outline where air ambulance can reduce response times, by creating surfaces of Euclidean allocation, direction, and distance that can be used to improve initial response times for the civil defense air rescue and air ambulance services.
文摘Emergency ambulance services in the UK are tasked with providing pre-hospital patient care and clinical services with a target response time between call connect to on-scene attendance.In 2017,NHS England introduced four new response time categories based on patient needs.The most challenging is to be on-scene for a life-threatening situation within seven minutes of the call being connected when such calls are random in terms of time and place throughout a large territory.Recent evidence indicates emergency ambulance services regularly fall short of achieving the target ambulance response times set by the National Health Service(NHS).To achieve these targets,they need to undertake transformational change and apply statistical,operations research and artificial intelligence techniques in the form of five separate modules covering demand forecasting,plus locate,allocate,dispatch,monitoring and re-deployment of resources.These modules should be linked in real-time employing a data warehouse to minimise computational data and generate accurate,meaningful and timely decisions ensuring patients receive an appropriate and timely response.A simulation covering a limited geographical area,time and operational data concluded that this form of integration of the five modules provides accurate and timely data upon which to make decisions that effectively improve ambulance response times.
