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Optimising acute stroke pathways through flexible use of bed capacity: a computer modelling study
BACKGROUND: Optimising capacity along clinical pathways is essential to avoid severe hospital pressure and help ensure best patient outcomes and financial sustainability. Yet, typical approaches, using only average arrival rate and average lengths of stay, are known to underestimate the number of be...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392305/ https://www.ncbi.nlm.nih.gov/pubmed/35987642 http://dx.doi.org/10.1186/s12913-022-08433-0 |
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author | Wood, Richard M. Moss, Simon J. Murch, Ben J. Vasilakis, Christos Clatworthy, Philip L. |
author_facet | Wood, Richard M. Moss, Simon J. Murch, Ben J. Vasilakis, Christos Clatworthy, Philip L. |
author_sort | Wood, Richard M. |
collection | PubMed |
description | BACKGROUND: Optimising capacity along clinical pathways is essential to avoid severe hospital pressure and help ensure best patient outcomes and financial sustainability. Yet, typical approaches, using only average arrival rate and average lengths of stay, are known to underestimate the number of beds required. This study investigates the extent to which averages-based estimates can be complemented by a robust assessment of additional ‘flex capacity’ requirements, to be used at times of peak demand. METHODS: The setting was a major one million resident healthcare system in England, moving towards a centralised stroke pathway. A computer simulation was developed for modelling patient flow along the proposed stroke pathway, accounting for variability in patient arrivals, lengths of stay, and the time taken for transfer processes. The primary outcome measure was flex capacity utilisation over the simulation period. RESULTS: For the hyper-acute, acute, and rehabilitation units respectively, flex capacities of 45%, 45%, and 36% above the averages-based calculation would be required to ensure that only 1% of stroke presentations find the hyper-acute unit full and have to wait. For each unit some amount of flex capacity would be required approximately 30%, 20%, and 18% of the time respectively. CONCLUSIONS: This study demonstrates the importance of appropriately capturing variability within capacity plans, and provides a practical and economical approach which can complement commonly-used averages-based methods. Results of this study have directly informed the healthcare system’s new configuration of stroke services. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-08433-0. |
format | Online Article Text |
id | pubmed-9392305 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-93923052022-08-21 Optimising acute stroke pathways through flexible use of bed capacity: a computer modelling study Wood, Richard M. Moss, Simon J. Murch, Ben J. Vasilakis, Christos Clatworthy, Philip L. BMC Health Serv Res Research BACKGROUND: Optimising capacity along clinical pathways is essential to avoid severe hospital pressure and help ensure best patient outcomes and financial sustainability. Yet, typical approaches, using only average arrival rate and average lengths of stay, are known to underestimate the number of beds required. This study investigates the extent to which averages-based estimates can be complemented by a robust assessment of additional ‘flex capacity’ requirements, to be used at times of peak demand. METHODS: The setting was a major one million resident healthcare system in England, moving towards a centralised stroke pathway. A computer simulation was developed for modelling patient flow along the proposed stroke pathway, accounting for variability in patient arrivals, lengths of stay, and the time taken for transfer processes. The primary outcome measure was flex capacity utilisation over the simulation period. RESULTS: For the hyper-acute, acute, and rehabilitation units respectively, flex capacities of 45%, 45%, and 36% above the averages-based calculation would be required to ensure that only 1% of stroke presentations find the hyper-acute unit full and have to wait. For each unit some amount of flex capacity would be required approximately 30%, 20%, and 18% of the time respectively. CONCLUSIONS: This study demonstrates the importance of appropriately capturing variability within capacity plans, and provides a practical and economical approach which can complement commonly-used averages-based methods. Results of this study have directly informed the healthcare system’s new configuration of stroke services. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-022-08433-0. BioMed Central 2022-08-20 /pmc/articles/PMC9392305/ /pubmed/35987642 http://dx.doi.org/10.1186/s12913-022-08433-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Wood, Richard M. Moss, Simon J. Murch, Ben J. Vasilakis, Christos Clatworthy, Philip L. Optimising acute stroke pathways through flexible use of bed capacity: a computer modelling study |
title | Optimising acute stroke pathways through flexible use of bed capacity: a computer modelling study |
title_full | Optimising acute stroke pathways through flexible use of bed capacity: a computer modelling study |
title_fullStr | Optimising acute stroke pathways through flexible use of bed capacity: a computer modelling study |
title_full_unstemmed | Optimising acute stroke pathways through flexible use of bed capacity: a computer modelling study |
title_short | Optimising acute stroke pathways through flexible use of bed capacity: a computer modelling study |
title_sort | optimising acute stroke pathways through flexible use of bed capacity: a computer modelling study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392305/ https://www.ncbi.nlm.nih.gov/pubmed/35987642 http://dx.doi.org/10.1186/s12913-022-08433-0 |
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