Abstract
Cancer 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 may be used to reveal potential improvements for CWT in the future.
This research is partially supported by the DataLab.
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More information on simulation framework can be found on https://www.salabim.org/.
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Silvina, A., Redeker, G., Webber, T., Bowles, J. (2021). A Simulation-Based Approach for the Behavioural Analysis of Cancer Pathways. In: Bowles, J., Broccia, G., Nanni, M. (eds) From Data to Models and Back. DataMod 2020. Lecture Notes in Computer Science(), vol 12611. Springer, Cham. https://doi.org/10.1007/978-3-030-70650-0_4
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