Modelling methods-Repurposing a discrete event simulation model to include covid 19 workflow changes in a computed tomography department

Mary Conlon, Owen Molloy

    Research output: Chapter in Book or Conference Publication/ProceedingConference Publicationpeer-review

    1 Citation (Scopus)

    Abstract

    The importance of infection control has taken centre stage with the arrival of Covid-19, and radiology staff must take precautions to limit contamination. This paper identified the changes required to an existing discrete event simulation model of a CT service to repurpose it for post COVID-19. Methods: Radiology workflow was mapped using Microsoft Visio to capture changes to roles, tasks and communications. Task and delay times were observed. Interviews with cleaning and clinical staff verified observational findings. Rich picture diagramming was used to include staff perceptions. In partnership with decision makers a culturally desirable and feasible scenario was identified and the increase in the consumed staff time post COVID-19 demonstrated. Conclusion: While CT throughput has decreased, the individual inpatient workload in terms of staff resource utilisation has increased. Separate inpatient and outpatient services are recommended to increase throughput and efficiency.

    Original languageEnglish
    Title of host publicationOperational Research Society 10th Simulation Workshop, SW 2021 - Proceedings
    EditorsMasoud Fakhimi, Tom Boness, Duncan Robertson
    PublisherOperational Research Society
    Pages210-220
    Number of pages11
    ISBN (Electronic)9780903440660
    DOIs
    Publication statusPublished - 2021
    Event10th Operational Research Society Simulation Workshop, SW 2021 - Virtual, Online
    Duration: 22 Mar 202126 Mar 2021

    Publication series

    NameOperational Research Society 10th Simulation Workshop, SW 2021 - Proceedings

    Conference

    Conference10th Operational Research Society Simulation Workshop, SW 2021
    CityVirtual, Online
    Period22/03/2126/03/21

    Keywords

    • Computed tomography
    • Covid-19
    • Discrete event modelling
    • Rich picture

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