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Examining the diagnostic pathway for lung cancer patients in Wales using discrete event simulation

Examining the diagnostic pathway for lung cancer patients in Wales using discrete event simulation
Examining the diagnostic pathway for lung cancer patients in Wales using discrete event simulation
Background: UK’s National Health Service (NHS) has one of the poorest lung cancer survival rates in Europe. To improve patient outcomes, a single cancer pathway was introduced in the NHS. In this study, a Discrete Event Simulation was developed to understand bottlenecks during lung cancer treatment.

Methods: this study focused on the lung cancer diagnostic pathways at two Welsh hospitals. Discrete Event Simulation is a computer-based method that has been effectively used in demand and capacity planning. In this study, simulation models were developed for the current and proposed single cancer pathways. The validated models were used to provide Key Performance Indicators. Several “what-if” scenarios were considered for the current and proposed pathways.

Results: under the current diagnostic pathway, the mean time to treatment for a surgery patient was 68 days at the Royal Glamorgan Hospital and 79 days at Prince Charles Hospital. For chemotherapy patients, the mean time to treatment was 52 days at the Royal Glamorgan Hospital and 57 days at Prince Charles Hospital. For radiotherapy patients, the mean time to treatment was 44 days at Royal Glamorgan Hospital and 54 days at Prince Charles Hospital. Ensuring that the patient attends their first outpatient appointment within 7 days and streamlining the diagnostic tests would have the potential to remove approximately 20 days from the current lung cancer pathway resulting in a 20-25% increase of patients receiving treatment within 62 days. Ensuring that patients begin their treatment within 21 days of diagnosis sees almost all patients comply with the 62-day target.

Conclusions: discrete Event Simulation coupled with a detailed statistical analysis provides a useful decision support tool which can be used to examine the current and proposed lung cancer pathways in terms of time spent on the pathway.
Diagnostics, Lung cancer, Optimal pathway, Simulation models
2226-4477
1368-1382
England, Tracey J.
8f99b32a-1670-4e20-b6c6-30ae96940ca2
Harper, Paul R.
8cba8a2d-4088-4112-abc9-da6100e414b9
Crosby, Tom
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Gartner, Daniel
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Arruda, Edilson F.
8eb3bd83-e883-4bf3-bfbc-7887c5daa911
Foley, Kieran G.
d9d17bd6-415a-48b2-ab23-6cc819e34368
Williamson, Ian J.
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England, Tracey J.
8f99b32a-1670-4e20-b6c6-30ae96940ca2
Harper, Paul R.
8cba8a2d-4088-4112-abc9-da6100e414b9
Crosby, Tom
d641cb6d-efc6-45ae-b083-a21c599a032c
Gartner, Daniel
fbe94ad1-bea5-441c-89aa-c5327e450f4b
Arruda, Edilson F.
8eb3bd83-e883-4bf3-bfbc-7887c5daa911
Foley, Kieran G.
d9d17bd6-415a-48b2-ab23-6cc819e34368
Williamson, Ian J.
12381296-edbf-4ac5-969b-dcb559c22f27

England, Tracey J., Harper, Paul R., Crosby, Tom, Gartner, Daniel, Arruda, Edilson F., Foley, Kieran G. and Williamson, Ian J. (2021) Examining the diagnostic pathway for lung cancer patients in Wales using discrete event simulation. Translational Lung Cancer Research, 10 (3), 1368-1382. (doi:10.21037/tlcr-20-919).

Record type: Article

Abstract

Background: UK’s National Health Service (NHS) has one of the poorest lung cancer survival rates in Europe. To improve patient outcomes, a single cancer pathway was introduced in the NHS. In this study, a Discrete Event Simulation was developed to understand bottlenecks during lung cancer treatment.

Methods: this study focused on the lung cancer diagnostic pathways at two Welsh hospitals. Discrete Event Simulation is a computer-based method that has been effectively used in demand and capacity planning. In this study, simulation models were developed for the current and proposed single cancer pathways. The validated models were used to provide Key Performance Indicators. Several “what-if” scenarios were considered for the current and proposed pathways.

Results: under the current diagnostic pathway, the mean time to treatment for a surgery patient was 68 days at the Royal Glamorgan Hospital and 79 days at Prince Charles Hospital. For chemotherapy patients, the mean time to treatment was 52 days at the Royal Glamorgan Hospital and 57 days at Prince Charles Hospital. For radiotherapy patients, the mean time to treatment was 44 days at Royal Glamorgan Hospital and 54 days at Prince Charles Hospital. Ensuring that the patient attends their first outpatient appointment within 7 days and streamlining the diagnostic tests would have the potential to remove approximately 20 days from the current lung cancer pathway resulting in a 20-25% increase of patients receiving treatment within 62 days. Ensuring that patients begin their treatment within 21 days of diagnosis sees almost all patients comply with the 62-day target.

Conclusions: discrete Event Simulation coupled with a detailed statistical analysis provides a useful decision support tool which can be used to examine the current and proposed lung cancer pathways in terms of time spent on the pathway.

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More information

Accepted/In Press date: 23 December 2020
Published date: 31 March 2021
Additional Information: Funding Information: We would like to take this opportunity to thank all those staff in Cwm Taf Morgannwg University Health Board, Aneurin Bevan University Health Board, and Velindre Cancer Centre, who have supported this work through their clinical advice and supply of data. We would like to thank Sinan Eccles and Alexander Brown who provided expert knowledge of the current diagnostic pathways in their hospitals. This work was supported by a Cancer Research UK grant 'Analysis and Modelling of a Single Cancer Pathway Diagnostics' (Early Diagnosis Project Award A27882). Funding Information: We would like to take this opportunity to thank all those staff in Cwm Taf Morgannwg University Health Board, Aneurin Bevan University Health Board, and Velindre Cancer Centre, who have supported this work through their clinical advice and supply of data. We would like to thank Sinan Eccles and Alexander Brown who provided expert knowledge of the current diagnostic pathways in their hospitals. Funding: This work was supported by a Cancer Research UK grant ‘Analysis and Modelling of a Single Cancer Pathway Diagnostics’ (Early Diagnosis Project Award A27882). Publisher Copyright: © 2021 AME Publishing Company. All rights reserved. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
Keywords: Diagnostics, Lung cancer, Optimal pathway, Simulation models

Identifiers

Local EPrints ID: 448436
URI: http://eprints.soton.ac.uk/id/eprint/448436
ISSN: 2226-4477
PURE UUID: 08c62073-1e61-4947-8c65-4dcfb7670b5b
ORCID for Edilson F. Arruda: ORCID iD orcid.org/0000-0002-9835-352X

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Date deposited: 22 Apr 2021 16:40
Last modified: 28 Apr 2022 02:31

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Contributors

Author: Paul R. Harper
Author: Tom Crosby
Author: Daniel Gartner
Author: Kieran G. Foley

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