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Balancing scarce hospital resources during the COVID-19 pandemic using discrete-event simulation.
Melman, G J; Parlikad, A K; Cameron, E A B.
  • Melman GJ; Institute for Manufacturing, Department of Engineering, University of Cambridge, 17 Charles Babbage Rd, Cambridge, CB3 0FS, UK. gj.melman@gmail.com.
  • Parlikad AK; Modelling Support, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK. gj.melman@gmail.com.
  • Cameron EAB; Industrial Engineering & Innovation Sciences, Eindhoven University of Technology, Eindhoven, Netherlands. gj.melman@gmail.com.
Health Care Manag Sci ; 24(2): 356-374, 2021 Jun.
Artículo en Inglés | MEDLINE | ID: covidwho-1173953
ABSTRACT
COVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke's hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.
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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Eficiencia Organizacional / Asignación de Recursos / Equipos y Suministros de Hospitales / Pandemias / COVID-19 / Hospitales Tipo de estudio: Estudio experimental / Estudio pronóstico Límite: Humanos País/Región como asunto: Europa Idioma: Inglés Revista: Health Care Manag Sci Asunto de la revista: Servicios de Salud Año: 2021 Tipo del documento: Artículo País de afiliación: S10729-021-09548-2

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Eficiencia Organizacional / Asignación de Recursos / Equipos y Suministros de Hospitales / Pandemias / COVID-19 / Hospitales Tipo de estudio: Estudio experimental / Estudio pronóstico Límite: Humanos País/Región como asunto: Europa Idioma: Inglés Revista: Health Care Manag Sci Asunto de la revista: Servicios de Salud Año: 2021 Tipo del documento: Artículo País de afiliación: S10729-021-09548-2