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Planning the capacity of hospital lifts for a new ambulatory block

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

In a regional acute general public hospital, a new multi-storey ambulatory care block is under construction to accommodate specialty out-patient clinics to meet future growth in patient demand. Hospital lifts play a key role in vertical transportation and are an expensive long-term investment. The building design includes several lift groups each serving different floors and targeting user groups in the new ambulatory block. The main objective of this study is to decide on the capacity in terms of number of lifts needed in each group. Statistical forecasting provides demand estimates for comparison with projected figures from staff. A simulation model is developed to study the performance of different capacities under three demand scenarios to find the right level of service in terms of lift waiting time performance. Sensitivity analysis of the capacities has provided comprehensive information for multiple stakeholders, including the Hospital Authority Head Office, hospital management and the building contractor, to finalize the capacity decision which would have a long-term impact on service quality and cost. © ORLab Analytics Inc. All rights reserved.
Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Applied Operational Research
EditorsKaveh Sheibani, Tomas Eric Nordlander, Roberto Montemanni
Place of PublicationCanada
PublisherORLab Analytics Inc.
Pages78-85
Publication statusPublished - 28 Jun 2016
Event8th International Conference on Applied Operational Research (ICAOR 2016) - Rotterdam, Netherlands
Duration: 28 Jun 201630 Jun 2016

Publication series

NameLecture Notes in Management Science
Volume8
ISSN (Print)2008-0050
ISSN (Electronic)1927-0097

Conference

Conference8th International Conference on Applied Operational Research (ICAOR 2016)
PlaceNetherlands
CityRotterdam
Period28/06/1630/06/16

Research Keywords

  • Demand partitioning
  • Forecasting
  • Healthcare
  • Hospital lifts
  • Sensitivity analysis
  • Simulation

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