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Using a genetic algorithm to solve a non-linear location allocation problem for specialised children's ambulances in England and Wales.
Kung, Enoch; Seaton, Sarah E; Ramnarayan, Padmanabhan; Pagel, Christina.
Afiliación
  • Kung E; Department of Mathematics, UCL Clinical Operational Research Unit, University College London, London, UK.
  • Seaton SE; Department of Health Sciences, University of Leicester, Leicester, UK.
  • Ramnarayan P; Children's Acute Transport Service (CATS), London, UK.
  • Pagel C; Department of Mathematics, UCL Clinical Operational Research Unit, University College London, London, UK.
Health Syst (Basingstoke) ; 11(3): 161-171, 2022.
Article en En | MEDLINE | ID: mdl-36147554
Since 1997, special paediatric intensive care retrieval teams (PICRTs) based in 11 locations across England and Wales have been used to transport sick children from district general hospitals to one of 24 paediatric intensive care units. We develop a location allocation optimisation framework to help inform decisions on the optimal number of locations for each PICRT, where those locations should be, which local hospital each location serves and how many teams should station each location. Our framework allows for stochastic journey times, differential weights for each journey leg and incorporates queuing theory by considering the time spent waiting for a PICRT to become available. We examine the average waiting time and the average time to bedside under different number of operational PICRT stations, different number of teams per station and different levels of demand. We show that consolidating the teams into fewer stations for higher availability leads to better performance.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Health Syst (Basingstoke) Año: 2022 Tipo del documento: Article Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Health Syst (Basingstoke) Año: 2022 Tipo del documento: Article Pais de publicación: Reino Unido