Open Access Repository

A stochastic model for the patient-bed assignment problem with random arrivals and departures

Heydar, M ORCID: 0000-0001-9277-9370, O'Reilly, MM ORCID: 0000-0003-3898-3957, Trainer, E, Fackrell, M, Taylor, PG and Tirdad, A 2021 , 'A stochastic model for the patient-bed assignment problem with random arrivals and departures' , Annals of Operations Research , doi: 10.1007/s10479-021-03982-9.

Full text not available from this repository.

Abstract

We consider the patient-to-bed assignment problem that arises in hospitals. Both emergency patients who require hospital admission and elective patients who have had surgery need to be found a bed in the most appropriate ward. The patient-to-bed assignment problem arises when a bed request is made, but a bed in the most appropriate ward is unavailable. In this case, the next-best decision out of a many alternatives has to be made, according to some suitable decision making algorithm. We construct a Markov chain to model this problem in which we consider the effect on the length of stay of a patient whose treatment and recovery consists of several stages, and can be affected by stays in or transfers to less suitable wards. We formulate a dynamic program recursion to optimise an objective function and calculate the optimal decision variables, and discuss simulation techniques that are useful when the size of the problem is too large. We illustrate the theory with some numerical examples.

Item Type: Article
Authors/Creators:Heydar, M and O'Reilly, MM and Trainer, E and Fackrell, M and Taylor, PG and Tirdad, A
Keywords: modelling healthcare, optimisation, markovian decision processes, patient-bed assignment problem, emergency department, health care modelling, Markov chain, dynamic programming, approximate dynamic programming, simulation
Journal or Publication Title: Annals of Operations Research
Publisher: Kluwer Academic Publ
ISSN: 0254-5330
DOI / ID Number: 10.1007/s10479-021-03982-9
Copyright Information:

Copyright 2021 The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature

Related URLs:
Item Statistics: View statistics for this item

Actions (login required)

Item Control Page Item Control Page
TOP