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dc.contributor.authorSilvina, Agastya
dc.contributor.authorRedeker, Guilherme Alfredo
dc.contributor.authorWebber, Thais
dc.contributor.authorKuster Filipe Bowles, Juliana
dc.contributor.editorBowles, Juliana
dc.contributor.editorBroccia, Giovanna
dc.contributor.editorNanni, Mirco
dc.identifier.citationSilvina , A , Redeker , G A , Webber , T & Kuster Filipe Bowles , J 2021 , A simulation-based approach for the behavioural analysis of cancer pathways . in J Bowles , G Broccia & M Nanni (eds) , From data to models and back : 9th International symposium, DataMod 2020, virtual event, October 20, 2020, revised selected papers . Lecture notes in computer science , vol. 12611 , Springer , Cham , pp. 57-71 .
dc.identifier.otherORCID: /0000-0002-8091-6021/work/86538459
dc.identifier.otherORCID: /0000-0002-5918-9114/work/86538469
dc.identifier.otherORCID: /0000-0002-8722-2559/work/137494602
dc.descriptionFunding: This research is partially supported by the DataLab.en
dc.description.abstractCancer pathway is the name given to a patient’s journey from initial suspicion of cancer through to a confirmed diagnosis and, if applicable, the definition of a treatment plan. Typically, a cancer patient will undergo a series of procedures, which we designate as events, during their cancer care. The initial stage of the pathway, from suspected diagnosis to confirmed diagnosis and start of a treatment is called cancer waiting time (CWT). This paper focuses on the modelling and analysis of the CWT. Health boards are under pressure to ensure that the duration of CWT satisfies predefined targets. In this paper, we first create the visual representation of the pathway obtained from real patient data at a given health board, and then compare it with the standardised pathway considered by the board to find and flag a deviation in the execution of the cancer pathway. Next, we devise a discrete event simulation model for the cancer waiting time pathway. The input data is obtained from historical records of patients. The outcomes from this analysis highlight the pathway bottlenecks and transition times which maybe used to reveal potential improvements for CWT in the future.
dc.relation.ispartofFrom data to models and backen
dc.relation.ispartofseriesLecture notes in computer scienceen
dc.subjectCancer pathwayen
dc.subjectCancer waiting timeen
dc.subjectDiscrete event simulationen
dc.subjectProcess modellingen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectRC0254 Neoplasms. Tumors. Oncology (including Cancer)en
dc.subjectSDG 3 - Good Health and Well-beingen
dc.titleA simulation-based approach for the behavioural analysis of cancer pathwaysen
dc.typeConference itemen
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen

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