Hospital Bed Allocation using Three-Stage Weighted Optimization Method for Government Hospital in Pulau Pinang
Ineffective bed allocation across hospital departments leads to the imbalance between patients’ needs and resource capacity. This study aims to simulate patients’ arrivals, to measure the departments’ importance and to design a mathematical model for allocating beds which will be realized by the pro...
Published in: | Journal of Advanced Research in Applied Sciences and Engineering Technology |
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Penerbit Akademia Baru
2023
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2-s2.0-85163684462 Halim K.M.; Khadijah W. Hospital Bed Allocation using Three-Stage Weighted Optimization Method for Government Hospital in Pulau Pinang 2023 Journal of Advanced Research in Applied Sciences and Engineering Technology 31 1 10.37934/araset.31.1.9098 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163684462&doi=10.37934%2faraset.31.1.9098&partnerID=40&md5=4ebc9e5287fc4f5d51b048a59626b8f3 Ineffective bed allocation across hospital departments leads to the imbalance between patients’ needs and resource capacity. This study aims to simulate patients’ arrivals, to measure the departments’ importance and to design a mathematical model for allocating beds which will be realized by the proposed three-stage weighted optimization model. The stages consist of data simulation in ARENA software, weight evaluation based on bed occupancy rate patients’ arrival rates, bed occupancy rate (BOR), patients’ average length of stay (ALOS) and bed operation cost (BOC), and weighted optimization using goal programming (GP) model. The goals to be achieved in this study consists of minimizing the idle beds in departments and the hospital and minimizing the total BOC. The result of the study shows that obstetrics and orthopaedics wards obtained the biggest number of beds while dengue and paediatrics surgery wards obtained the least number. The statistical analysis made to the results shows that patients’ arrival rate is the most influential factor in allocating the beds as its Pearson correlation value to the bed numbers is 0.789, which indicates strong correlation. © 2023, Penerbit Akademia Baru. All rights reserved. Penerbit Akademia Baru 24621943 English Article All Open Access; Hybrid Gold Open Access |
author |
Halim K.M.; Khadijah W. |
spellingShingle |
Halim K.M.; Khadijah W. Hospital Bed Allocation using Three-Stage Weighted Optimization Method for Government Hospital in Pulau Pinang |
author_facet |
Halim K.M.; Khadijah W. |
author_sort |
Halim K.M.; Khadijah W. |
title |
Hospital Bed Allocation using Three-Stage Weighted Optimization Method for Government Hospital in Pulau Pinang |
title_short |
Hospital Bed Allocation using Three-Stage Weighted Optimization Method for Government Hospital in Pulau Pinang |
title_full |
Hospital Bed Allocation using Three-Stage Weighted Optimization Method for Government Hospital in Pulau Pinang |
title_fullStr |
Hospital Bed Allocation using Three-Stage Weighted Optimization Method for Government Hospital in Pulau Pinang |
title_full_unstemmed |
Hospital Bed Allocation using Three-Stage Weighted Optimization Method for Government Hospital in Pulau Pinang |
title_sort |
Hospital Bed Allocation using Three-Stage Weighted Optimization Method for Government Hospital in Pulau Pinang |
publishDate |
2023 |
container_title |
Journal of Advanced Research in Applied Sciences and Engineering Technology |
container_volume |
31 |
container_issue |
1 |
doi_str_mv |
10.37934/araset.31.1.9098 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163684462&doi=10.37934%2faraset.31.1.9098&partnerID=40&md5=4ebc9e5287fc4f5d51b048a59626b8f3 |
description |
Ineffective bed allocation across hospital departments leads to the imbalance between patients’ needs and resource capacity. This study aims to simulate patients’ arrivals, to measure the departments’ importance and to design a mathematical model for allocating beds which will be realized by the proposed three-stage weighted optimization model. The stages consist of data simulation in ARENA software, weight evaluation based on bed occupancy rate patients’ arrival rates, bed occupancy rate (BOR), patients’ average length of stay (ALOS) and bed operation cost (BOC), and weighted optimization using goal programming (GP) model. The goals to be achieved in this study consists of minimizing the idle beds in departments and the hospital and minimizing the total BOC. The result of the study shows that obstetrics and orthopaedics wards obtained the biggest number of beds while dengue and paediatrics surgery wards obtained the least number. The statistical analysis made to the results shows that patients’ arrival rate is the most influential factor in allocating the beds as its Pearson correlation value to the bed numbers is 0.789, which indicates strong correlation. © 2023, Penerbit Akademia Baru. All rights reserved. |
publisher |
Penerbit Akademia Baru |
issn |
24621943 |
language |
English |
format |
Article |
accesstype |
All Open Access; Hybrid Gold Open Access |
record_format |
scopus |
collection |
Scopus |
_version_ |
1809677582027718656 |