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A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic
This study presents two simulation modelling tools to support the organisation of networks of dialysis services during the COVID-19 pandemic. These tools were developed to support renal services in the South of England (the Wessex region caring for 650 dialysis patients), but are applicable elsewher...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7425906/ https://www.ncbi.nlm.nih.gov/pubmed/32790773 http://dx.doi.org/10.1371/journal.pone.0237628 |
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author | Allen, Michael Bhanji, Amir Willemsen, Jonas Dudfield, Steven Logan, Stuart Monks, Thomas |
author_facet | Allen, Michael Bhanji, Amir Willemsen, Jonas Dudfield, Steven Logan, Stuart Monks, Thomas |
author_sort | Allen, Michael |
collection | PubMed |
description | This study presents two simulation modelling tools to support the organisation of networks of dialysis services during the COVID-19 pandemic. These tools were developed to support renal services in the South of England (the Wessex region caring for 650 dialysis patients), but are applicable elsewhere. A discrete-event simulation was used to model a worst case spread of COVID-19, to stress-test plans for dialysis provision throughout the COVID-19 outbreak. We investigated the ability of the system to manage the mix of COVID-19 positive and negative patients, the likely effects on patients, outpatient workloads across all units, and inpatient workload at the centralised COVID-positive inpatient unit. A second Monte-Carlo vehicle routing model estimated the feasibility of patient transport plans. If current outpatient capacity is maintained there is sufficient capacity in the South of England to keep COVID-19 negative/recovered and positive patients in separate sessions, but rapid reallocation of patients may be needed. Outpatient COVID-19 cases will spillover to a secondary site while other sites will experience a reduction in workload. The primary site chosen to manage infected patients will experience a significant increase in outpatients and inpatients. At the peak of infection, it is predicted there will be up to 140 COVID-19 positive patients with 40 to 90 of these as inpatients, likely breaching current inpatient capacity. Patient transport services will also come under considerable pressure. If patient transport operates on a policy of one positive patient at a time, and two-way transport is needed, a likely scenario estimates 80 ambulance drive time hours per day (not including fixed drop-off and ambulance cleaning times). Relaxing policies on individual patient transport to 2-4 patients per trip can save 40-60% of drive time. In mixed urban/rural geographies steps may need to be taken to temporarily accommodate renal COVID-19 positive patients closer to treatment facilities. |
format | Online Article Text |
id | pubmed-7425906 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-74259062020-08-20 A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic Allen, Michael Bhanji, Amir Willemsen, Jonas Dudfield, Steven Logan, Stuart Monks, Thomas PLoS One Research Article This study presents two simulation modelling tools to support the organisation of networks of dialysis services during the COVID-19 pandemic. These tools were developed to support renal services in the South of England (the Wessex region caring for 650 dialysis patients), but are applicable elsewhere. A discrete-event simulation was used to model a worst case spread of COVID-19, to stress-test plans for dialysis provision throughout the COVID-19 outbreak. We investigated the ability of the system to manage the mix of COVID-19 positive and negative patients, the likely effects on patients, outpatient workloads across all units, and inpatient workload at the centralised COVID-positive inpatient unit. A second Monte-Carlo vehicle routing model estimated the feasibility of patient transport plans. If current outpatient capacity is maintained there is sufficient capacity in the South of England to keep COVID-19 negative/recovered and positive patients in separate sessions, but rapid reallocation of patients may be needed. Outpatient COVID-19 cases will spillover to a secondary site while other sites will experience a reduction in workload. The primary site chosen to manage infected patients will experience a significant increase in outpatients and inpatients. At the peak of infection, it is predicted there will be up to 140 COVID-19 positive patients with 40 to 90 of these as inpatients, likely breaching current inpatient capacity. Patient transport services will also come under considerable pressure. If patient transport operates on a policy of one positive patient at a time, and two-way transport is needed, a likely scenario estimates 80 ambulance drive time hours per day (not including fixed drop-off and ambulance cleaning times). Relaxing policies on individual patient transport to 2-4 patients per trip can save 40-60% of drive time. In mixed urban/rural geographies steps may need to be taken to temporarily accommodate renal COVID-19 positive patients closer to treatment facilities. Public Library of Science 2020-08-13 /pmc/articles/PMC7425906/ /pubmed/32790773 http://dx.doi.org/10.1371/journal.pone.0237628 Text en © 2020 Allen et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Allen, Michael Bhanji, Amir Willemsen, Jonas Dudfield, Steven Logan, Stuart Monks, Thomas A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic |
title | A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic |
title_full | A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic |
title_fullStr | A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic |
title_full_unstemmed | A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic |
title_short | A simulation modelling toolkit for organising outpatient dialysis services during the COVID-19 pandemic |
title_sort | simulation modelling toolkit for organising outpatient dialysis services during the covid-19 pandemic |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7425906/ https://www.ncbi.nlm.nih.gov/pubmed/32790773 http://dx.doi.org/10.1371/journal.pone.0237628 |
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