The University of Southampton
University of Southampton Institutional Repository

Modelling lung cancer diagnostic pathways using discrete event simulation

Modelling lung cancer diagnostic pathways using discrete event simulation
Modelling lung cancer diagnostic pathways using discrete event simulation

The United Kingdom has one of the poorest lung cancer survival rates in Europe. In this study, to help design and evaluate a single lung cancer pathway (SCP) for Wales, existing diagnostic pathways and processes have been mapped and then modelled with a discrete event simulation. The validated models have been used to provide key performance indicators and to examine different diagnostic testing strategies. Under the current diagnostic pathways, the mean time to treatment was 72 days for surgery patients, 56 days for chemotherapy patients, and 61 days for radiotherapy patients. Our research demonstrated that by ensuring that the patient attends their first outpatient appointment within 7 days and streamlining the diagnostic tests would have the potential to remove approximately 11 days from the current lung cancer pathway resulting in a 21% increase in patients receiving treatment within the Welsh Government set target of 62 days.

Diagnostic pathway, cancer, discrete event simulation, performance indicators
1747-7778
England, Tracey
8f99b32a-1670-4e20-b6c6-30ae96940ca2
Harper, Paul
ca5e539f-4d8c-483c-a3f1-2beedeaacd49
Crosby, Tom
d641cb6d-efc6-45ae-b083-a21c599a032c
Gartner, Daniel
fbe94ad1-bea5-441c-89aa-c5327e450f4b
Arruda, Edilson F.
8eb3bd83-e883-4bf3-bfbc-7887c5daa911
Foley, Kieran
ba5b6b0c-35de-4b9f-8bcf-aafd42603504
Williamson, Ian
12381296-edbf-4ac5-969b-dcb559c22f27
England, Tracey
8f99b32a-1670-4e20-b6c6-30ae96940ca2
Harper, Paul
ca5e539f-4d8c-483c-a3f1-2beedeaacd49
Crosby, Tom
d641cb6d-efc6-45ae-b083-a21c599a032c
Gartner, Daniel
fbe94ad1-bea5-441c-89aa-c5327e450f4b
Arruda, Edilson F.
8eb3bd83-e883-4bf3-bfbc-7887c5daa911
Foley, Kieran
ba5b6b0c-35de-4b9f-8bcf-aafd42603504
Williamson, Ian
12381296-edbf-4ac5-969b-dcb559c22f27

England, Tracey, Harper, Paul, Crosby, Tom, Gartner, Daniel, Arruda, Edilson F., Foley, Kieran and Williamson, Ian (2021) Modelling lung cancer diagnostic pathways using discrete event simulation. Journal of Simulation. (doi:10.1080/17477778.2021.1956866).

Record type: Article

Abstract

The United Kingdom has one of the poorest lung cancer survival rates in Europe. In this study, to help design and evaluate a single lung cancer pathway (SCP) for Wales, existing diagnostic pathways and processes have been mapped and then modelled with a discrete event simulation. The validated models have been used to provide key performance indicators and to examine different diagnostic testing strategies. Under the current diagnostic pathways, the mean time to treatment was 72 days for surgery patients, 56 days for chemotherapy patients, and 61 days for radiotherapy patients. Our research demonstrated that by ensuring that the patient attends their first outpatient appointment within 7 days and streamlining the diagnostic tests would have the potential to remove approximately 11 days from the current lung cancer pathway resulting in a 21% increase in patients receiving treatment within the Welsh Government set target of 62 days.

Text
JOS(2021) - Version of Record
Available under License Creative Commons Attribution.
Download (1MB)

More information

Accepted/In Press date: 12 July 2021
e-pub ahead of print date: 5 August 2021
Additional Information: Publisher Copyright: © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Keywords: Diagnostic pathway, cancer, discrete event simulation, performance indicators

Identifiers

Local EPrints ID: 450424
URI: http://eprints.soton.ac.uk/id/eprint/450424
ISSN: 1747-7778
PURE UUID: 024fa694-d82f-4630-99e9-9c13ed47e510
ORCID for Edilson F. Arruda: ORCID iD orcid.org/0000-0002-9835-352X

Catalogue record

Date deposited: 28 Jul 2021 16:30
Last modified: 29 Nov 2022 02:59

Export record

Altmetrics

Contributors

Author: Tracey England
Author: Paul Harper
Author: Tom Crosby
Author: Daniel Gartner
Author: Kieran Foley
Author: Ian Williamson

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×