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    Rights statement: This is an Accepted Manuscript of an article published by Taylor & Francis in Health Systems on 27/07/2020, available online:  https://www.tandfonline.com/doi/full/10.1080/20476965.2020.1796530

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Constructing operating theatre schedules using partitioned graph colouring techniques

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Constructing operating theatre schedules using partitioned graph colouring techniques. / Kheiri, Ahmed; Lewis, Rhyd; Thompson, Jonathan et al.
In: Health Systems, Vol. 10, No. 4, 31.10.2021, p. 286-297.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Kheiri A, Lewis R, Thompson J, Harper P. Constructing operating theatre schedules using partitioned graph colouring techniques. Health Systems. 2021 Oct 31;10(4):286-297. Epub 2020 Jul 27. doi: 10.1080/20476965.2020.1796530

Author

Kheiri, Ahmed ; Lewis, Rhyd ; Thompson, Jonathan et al. / Constructing operating theatre schedules using partitioned graph colouring techniques. In: Health Systems. 2021 ; Vol. 10, No. 4. pp. 286-297.

Bibtex

@article{1ec6b15a636e4c2084ef7b40e0691823,
title = "Constructing operating theatre schedules using partitioned graph colouring techniques",
abstract = "In hospitals, scheduled operations can often be cancelled in large numbers due to the unavailability of beds for post-operation recovery. Operating theatre scheduling is known to be an (Formula presented.) -hard optimisation problem. Previous studies have shown that the correct scheduling of surgical procedures can have a positive impact on the availability of beds in hospital wards, thereby allowing a reduction in number of elective operation cancellations. This study proposes an exact technique based on the partitioned graph colouring problem for constructing optimal master surgery schedules, with the goal of minimising the number of cancellations. The resultant schedules are then simulated in order to measure how well they cope with the stochastic nature of patient arrivals. Our results show that the utilisation of post-operative beds can be increased, whilst the number of cancellations can be decreased, which may ultimately lead to greater patient throughput and reduced waiting times. A scenario-based model has also been employed to integrate the stochastic-nature associated with the bed requirements into the optimisation process. The results indicate that the proposed model can lead to more robust solutions.",
keywords = "OR in health services, optimisation, scheduling, graph colouring, Integer programming",
author = "Ahmed Kheiri and Rhyd Lewis and Jonathan Thompson and Paul Harper",
note = "This is an Accepted Manuscript of an article published by Taylor & Francis in Health Systems on 27/07/2020, available online:  https://www.tandfonline.com/doi/full/10.1080/20476965.2020.1796530",
year = "2021",
month = oct,
day = "31",
doi = "10.1080/20476965.2020.1796530",
language = "English",
volume = "10",
pages = "286--297",
journal = "Health Systems",
issn = "2047-6973",
publisher = "Palgrave Macmillan",
number = "4",

}

RIS

TY - JOUR

T1 - Constructing operating theatre schedules using partitioned graph colouring techniques

AU - Kheiri, Ahmed

AU - Lewis, Rhyd

AU - Thompson, Jonathan

AU - Harper, Paul

N1 - This is an Accepted Manuscript of an article published by Taylor & Francis in Health Systems on 27/07/2020, available online:  https://www.tandfonline.com/doi/full/10.1080/20476965.2020.1796530

PY - 2021/10/31

Y1 - 2021/10/31

N2 - In hospitals, scheduled operations can often be cancelled in large numbers due to the unavailability of beds for post-operation recovery. Operating theatre scheduling is known to be an (Formula presented.) -hard optimisation problem. Previous studies have shown that the correct scheduling of surgical procedures can have a positive impact on the availability of beds in hospital wards, thereby allowing a reduction in number of elective operation cancellations. This study proposes an exact technique based on the partitioned graph colouring problem for constructing optimal master surgery schedules, with the goal of minimising the number of cancellations. The resultant schedules are then simulated in order to measure how well they cope with the stochastic nature of patient arrivals. Our results show that the utilisation of post-operative beds can be increased, whilst the number of cancellations can be decreased, which may ultimately lead to greater patient throughput and reduced waiting times. A scenario-based model has also been employed to integrate the stochastic-nature associated with the bed requirements into the optimisation process. The results indicate that the proposed model can lead to more robust solutions.

AB - In hospitals, scheduled operations can often be cancelled in large numbers due to the unavailability of beds for post-operation recovery. Operating theatre scheduling is known to be an (Formula presented.) -hard optimisation problem. Previous studies have shown that the correct scheduling of surgical procedures can have a positive impact on the availability of beds in hospital wards, thereby allowing a reduction in number of elective operation cancellations. This study proposes an exact technique based on the partitioned graph colouring problem for constructing optimal master surgery schedules, with the goal of minimising the number of cancellations. The resultant schedules are then simulated in order to measure how well they cope with the stochastic nature of patient arrivals. Our results show that the utilisation of post-operative beds can be increased, whilst the number of cancellations can be decreased, which may ultimately lead to greater patient throughput and reduced waiting times. A scenario-based model has also been employed to integrate the stochastic-nature associated with the bed requirements into the optimisation process. The results indicate that the proposed model can lead to more robust solutions.

KW - OR in health services

KW - optimisation

KW - scheduling

KW - graph colouring

KW - Integer programming

U2 - 10.1080/20476965.2020.1796530

DO - 10.1080/20476965.2020.1796530

M3 - Journal article

VL - 10

SP - 286

EP - 297

JO - Health Systems

JF - Health Systems

SN - 2047-6973

IS - 4

ER -