{"title":"Ambulance dispatching and relocation problem considering overcrowding of emergency departments","authors":"M. Yavari, R. Maihami, Mahdis Esmaeili","doi":"10.1080/24725579.2022.2064008","DOIUrl":null,"url":null,"abstract":"Abstract An important issue in emergency medical services (EMS) is ambulance dispatching and relocation. EMS response time is usually measured by the response time of an ambulance (RTA), the time between receiving a call and the ambulance's arrival at the scene. EMS's success also depends on response time to the patient (RTP), the time between receiving a call and starting the service to the patient in a hospital. This study aims to use RTP to decide about ambulance dispatching and relocation. RTP is affected by the distance of the patient to the chosen hospital and the crowding in the hospital. Thus, this study integrates ambulance dispatching and relocation with hospital selection to better provide both RTA and RTP along with coverage while considering an overcrowded emergency department (ED). A mixed-integer linear programming model is developed to solve the proposed problem. The model's performance and the impact of the ED overcrowding factor have been examined in the context of a real case study from Utrecht, Netherlands. Findings reveal that considering RTP in joint ambulance dispatching and relocation has a 39% positive impact on the patient's average response time. Further, considering ED crowding with RTP results in 91% and 9% improvement in RTP and RTA with the same demand coverage, compared to typical ambulance dispatching and relocation problems, respectively.","PeriodicalId":37744,"journal":{"name":"IISE Transactions on Healthcare Systems Engineering","volume":"12 1","pages":"263 - 274"},"PeriodicalIF":1.5000,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IISE Transactions on Healthcare Systems Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/24725579.2022.2064008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 1
Abstract
Abstract An important issue in emergency medical services (EMS) is ambulance dispatching and relocation. EMS response time is usually measured by the response time of an ambulance (RTA), the time between receiving a call and the ambulance's arrival at the scene. EMS's success also depends on response time to the patient (RTP), the time between receiving a call and starting the service to the patient in a hospital. This study aims to use RTP to decide about ambulance dispatching and relocation. RTP is affected by the distance of the patient to the chosen hospital and the crowding in the hospital. Thus, this study integrates ambulance dispatching and relocation with hospital selection to better provide both RTA and RTP along with coverage while considering an overcrowded emergency department (ED). A mixed-integer linear programming model is developed to solve the proposed problem. The model's performance and the impact of the ED overcrowding factor have been examined in the context of a real case study from Utrecht, Netherlands. Findings reveal that considering RTP in joint ambulance dispatching and relocation has a 39% positive impact on the patient's average response time. Further, considering ED crowding with RTP results in 91% and 9% improvement in RTP and RTA with the same demand coverage, compared to typical ambulance dispatching and relocation problems, respectively.
期刊介绍:
IISE Transactions on Healthcare Systems Engineering aims to foster the healthcare systems community by publishing high quality papers that have a strong methodological focus and direct applicability to healthcare systems. Published quarterly, the journal supports research that explores: · Healthcare Operations Management · Medical Decision Making · Socio-Technical Systems Analysis related to healthcare · Quality Engineering · Healthcare Informatics · Healthcare Policy We are looking forward to accepting submissions that document the development and use of industrial and systems engineering tools and techniques including: · Healthcare operations research · Healthcare statistics · Healthcare information systems · Healthcare work measurement · Human factors/ergonomics applied to healthcare systems Research that explores the integration of these tools and techniques with those from other engineering and medical disciplines are also featured. We encourage the submission of clinical notes, or practice notes, to show the impact of contributions that will be published. We also encourage authors to collect an impact statement from their clinical partners to show the impact of research in the clinical practices.