Bed allocation to reduce overflow

Hospital emergency department boarding time, i.e. the duration between the patient bed request time and the patient admission time to inpatient wards, is a key performance in many hospitals. In order to avoid this waiting time to exceed certain level, some hospitals including the one under study in...

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Main Authors: Xie, J., CHOU, M.C., ANG, Marcus, Yao, D.D.
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Language:English
Published: Institutional Knowledge at Singapore Management University 2005
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Online Access:https://ink.library.smu.edu.sg/lkcsb_research/4480
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spelling sg-smu-ink.lkcsb_research-54792015-03-26T03:36:06Z Bed allocation to reduce overflow Xie, J. CHOU, M.C. ANG, Marcus Yao, D.D. Hospital emergency department boarding time, i.e. the duration between the patient bed request time and the patient admission time to inpatient wards, is a key performance in many hospitals. In order to avoid this waiting time to exceed certain level, some hospitals including the one under study in this paper may set a maximum boarding time (e.g. 6 hours) beyond which patients will be assigned to any available beds in the inpatient wards despite the medical specialties required. As a result, patients may be overflowed all over the hospital, causing physicians wasting their time on the way to visit their patients. High overflow rates also cause many other problems such as worse patient outcomes and more complicated bed allocation process. To address the overflow issue, we build an analytical model and propose two easy-to-compute bed allocation polices. We use the real data from the only university hospital in Singapore and a simulation model to evaluate the effectiveness of our proposed polices against the base case provided by the empirical study of the hospital. Through the simulation study, we show that the proposed policies can reduce the overflow rate from 18.91% to about 4.5% without sacrificing other performance measures. More surprisingly, our simulation studies suggest that the existing capacity actually can accommodate 50% more elective patients while keeping the overflow rate at a level of less than 10%. 2005-07-03T07:00:00Z text https://ink.library.smu.edu.sg/lkcsb_research/4480 Research Collection Lee Kong Chian School Of Business eng Institutional Knowledge at Singapore Management University bed allocation patient overflow M/M/c optimization discrete event simulation Business
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic bed allocation
patient overflow
M/M/c
optimization
discrete event simulation
Business
spellingShingle bed allocation
patient overflow
M/M/c
optimization
discrete event simulation
Business
Xie, J.
CHOU, M.C.
ANG, Marcus
Yao, D.D.
Bed allocation to reduce overflow
description Hospital emergency department boarding time, i.e. the duration between the patient bed request time and the patient admission time to inpatient wards, is a key performance in many hospitals. In order to avoid this waiting time to exceed certain level, some hospitals including the one under study in this paper may set a maximum boarding time (e.g. 6 hours) beyond which patients will be assigned to any available beds in the inpatient wards despite the medical specialties required. As a result, patients may be overflowed all over the hospital, causing physicians wasting their time on the way to visit their patients. High overflow rates also cause many other problems such as worse patient outcomes and more complicated bed allocation process. To address the overflow issue, we build an analytical model and propose two easy-to-compute bed allocation polices. We use the real data from the only university hospital in Singapore and a simulation model to evaluate the effectiveness of our proposed polices against the base case provided by the empirical study of the hospital. Through the simulation study, we show that the proposed policies can reduce the overflow rate from 18.91% to about 4.5% without sacrificing other performance measures. More surprisingly, our simulation studies suggest that the existing capacity actually can accommodate 50% more elective patients while keeping the overflow rate at a level of less than 10%.
format text
author Xie, J.
CHOU, M.C.
ANG, Marcus
Yao, D.D.
author_facet Xie, J.
CHOU, M.C.
ANG, Marcus
Yao, D.D.
author_sort Xie, J.
title Bed allocation to reduce overflow
title_short Bed allocation to reduce overflow
title_full Bed allocation to reduce overflow
title_fullStr Bed allocation to reduce overflow
title_full_unstemmed Bed allocation to reduce overflow
title_sort bed allocation to reduce overflow
publisher Institutional Knowledge at Singapore Management University
publishDate 2005
url https://ink.library.smu.edu.sg/lkcsb_research/4480
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