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A dynamic ambulance management model for rural areas

Overview of attention for article published in Health Care Management Science, October 2015
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Title
A dynamic ambulance management model for rural areas
Published in
Health Care Management Science, October 2015
DOI 10.1007/s10729-015-9341-3
Pubmed ID
Authors

T. C. van Barneveld, S. Bhulai, R. D. van der Mei

Abstract

We study the Dynamic Ambulance Management (DAM) problem in which one tries to retain the ability to respond to possible future requests quickly when ambulances become busy. To this end, we need models for relocation actions for idle ambulances that incorporate different performance measures related to response times. We focus on rural regions with a limited number of ambulances. We model the region of interest as an equidistant graph and we take into account the current status of both the system and the ambulances in a state. We do not require ambulances to return to a base station: they are allowed to idle at any node. This brings forth a high degree of complexity of the state space. Therefore, we present a heuristic approach to compute redeployment actions. We construct several scenarios that may occur one time-step later and combine these scenarios with each feasible action to obtain a classification of actions. We show that on most performance indicators, the heuristic policy significantly outperforms the classical compliance table policy often used in practice.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Korea, Republic of 1 3%
Unknown 30 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 16%
Student > Master 5 16%
Student > Doctoral Student 4 13%
Student > Bachelor 3 9%
Professor 2 6%
Other 8 25%
Unknown 5 16%
Readers by discipline Count As %
Engineering 10 31%
Medicine and Dentistry 5 16%
Computer Science 2 6%
Mathematics 2 6%
Social Sciences 2 6%
Other 4 13%
Unknown 7 22%