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通过灵活使用床位容量优化急性脑卒中救治流程:一项计算机建模研究。

Optimising acute stroke pathways through flexible use of bed capacity: a computer modelling study.

机构信息

Bristol, North Somerset and South Gloucestershire ICB, National Health Service, South Plaza, Marlborough St, BS1 3NX, Bristol, United Kingdom.

School of Management, University of Bath, Claverton Down, BA2 7AY, Bath, United Kingdom.

出版信息

BMC Health Serv Res. 2022 Aug 20;22(1):1068. doi: 10.1186/s12913-022-08433-0.

Abstract

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.

摘要

背景

优化临床路径的容量对于避免医院压力过大、确保最佳患者治疗效果和财务可持续性至关重要。然而,仅使用平均到达率和平均住院时间的典型方法,已知会低估所需的床位数量。本研究旨在调查通过稳健评估额外的“弹性容量”需求,在需求高峰期使用,来补充基于平均值的估计的程度。

方法

研究地点是英国一个拥有 100 万居民的大型医疗保健系统,该系统正在向集中化的中风路径发展。开发了一个计算机模拟程序来模拟患者沿着拟议的中风路径的流动情况,考虑了患者到达、住院时间和转移过程时间的可变性。主要的结果衡量标准是模拟期间的弹性容量利用率。

结果

对于超急性、急性和康复病房,分别需要比基于平均值的计算高出 45%、45%和 36%的弹性容量,以确保只有 1%的中风患者发现超急性病房已满且需要等待。对于每个病房,大约需要 30%、20%和 18%的时间来提供一定数量的弹性容量。

结论

本研究证明了在容量计划中适当捕捉变异性的重要性,并提供了一种实用且经济的方法,可以补充常用的基于平均值的方法。本研究的结果直接为医疗保健系统中风服务的新配置提供了信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b3b/9392305/16f70ba13a49/12913_2022_8433_Fig1_HTML.jpg

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