England, Tracey, Harper, Paul ORCID: https://orcid.org/0000-0001-7894-4907, Crosby, Tom, Gartner, Daniel ORCID: https://orcid.org/0000-0003-4361-8559, Arruda, Edilson F., Foley, Kieran and Williamson, Ian 2023. Modelling lung cancer diagnostic pathways using discrete event simulation. Journal of Simulation 17 (1) , pp. 94-104. 10.1080/17477778.2021.1956866 |
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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 model has 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 of patients receiving treatment within the Welsh Government set target of 62 days.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Mathematics |
Subjects: | Q Science > QA Mathematics R Medicine > R Medicine (General) |
Additional Information: | This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Publisher: | OR Society |
ISSN: | 1747-7778 |
Funders: | This work was supported by a Cancer Research UK grant “Analysis and Modelling of a Single Cancer Pathway Diagnostics” (Early Diagnosis Project Award A27882). |
Date of First Compliant Deposit: | 20 August 2021 |
Date of Acceptance: | 12 July 2021 |
Last Modified: | 15 Aug 2023 11:43 |
URI: | https://orca.cardiff.ac.uk/id/eprint/143533 |
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