Estimating ambulance requirements in Auckland, New Zealand. Henderson, S. & Mason, A. J. In Farrington, P., Black Nembhard, H., Sturrock, D., & Evans, G., editors, Proceedings of the 1999 Winter Simulation Conference, pages 1670–1674, Piscataway NJ, 1999. IEEE. ![Estimating ambulance requirements in Auckland, New Zealand [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper abstract bibtex The St. John Ambulance Service (Auckland Region) in New Zealand (St Johns) supplies ambulance services to Crown Health Enterprises. Current and future contracts specify several minimum performance targets that St Johns must achieve. As the city of Auckland grows, roads become congested, and population demographics change. These changes mean that St. Johns faces a very difficult problem: how many ambulances are needed, and where should they be placed in order to meet the service targets efficiently. A preliminary study using queueing theory established that more ambulances were needed and suggested placements. However, the assumptions required in the queueing model were such that a more realistic modelling approach was deemed necessary to verify and refine the queueing model results. We discuss a simulation and analysis software tool BartSim developed by the authors, that is currently being used to address the issues St. Johns faces. The results obtained from BartSim are used to drive changes to the rostering process for staff at St. Johns.
@inproceedings{henmas99,
abstract = {The St. John Ambulance Service (Auckland Region) in New Zealand (St Johns) supplies ambulance services to Crown Health Enterprises. Current and future contracts specify several minimum performance targets that St Johns must achieve. As the city of Auckland grows, roads become congested, and population demographics change. These changes mean that St. Johns faces a very difficult problem: how many ambulances are needed, and where should they be placed in order to meet the service targets efficiently.
A preliminary study using queueing theory established that more ambulances were needed and suggested placements. However, the assumptions required in the queueing model were such that a more realistic modelling approach was deemed necessary to verify and refine the queueing model results. We discuss a simulation and analysis software tool BartSim developed by the authors, that is currently being used to address the issues St. Johns faces. The results obtained from BartSim are used to drive changes to the rostering process for staff at St. Johns.},
address = {Piscataway NJ},
annote = {pubs/EstimatingAmb99.pdf},
author = {Henderson, S.~G. and A. J. Mason},
booktitle = {Proceedings of the 1999 Winter Simulation Conference},
date-added = {2016-01-10 16:07:54 +0000},
date-modified = {2018-07-16 17:40:46 +0000},
editor = {Farrington, P.~A. and Black Nembhard, H. and Sturrock, D.~T. and Evans, G.~W.},
organization = {IEEE},
pages = {1670--1674},
title = {Estimating ambulance requirements in {A}uckland, {N}ew {Z}ealand},
url_paper = {https://dl.acm.org/authorize?N654072},
year = 1999}
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