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Related Experiment Video

Updated: May 7, 2026

An R-Based Landscape Validation of a Competing Risk Model
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A queueing theory based model for business continuity in hospitals.

R Miniati, G Cecconi, F Dori

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |October 11, 2013
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces an integrated model using risk analysis and queuing theory to determine optimal device numbers for hospital business continuity. It ensures medical activities are uninterrupted by technology failures.

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    Last Updated: May 7, 2026

    An R-Based Landscape Validation of a Competing Risk Model
    05:37

    An R-Based Landscape Validation of a Competing Risk Model

    Published on: September 16, 2022

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    Area of Science:

    • Operations Research
    • Healthcare Management
    • Reliability Engineering

    Background:

    • Clinical activities involve sequential events with waiting times, influenced by technology.
    • Business continuity management requires more than just matching device numbers to workload.
    • Risk analysis is crucial for identifying necessary interventions and technology purchases.

    Purpose of the Study:

    • To present an integrated model for optimizing device allocation in hospitals.
    • To ensure business continuity management by addressing technological risks.
    • To define the essential number of devices for uninterrupted medical activities.

    Main Methods:

    • Application of Markov models and reliability engineering principles.
    • Integration of a risk analysis approach with a queuing theory model.
    • Case study demonstrating the model's application in a hospital setting.

    Main Results:

    • The proposed integrated model effectively determines the optimal number of devices.
    • Risk assessment identifies critical interventions and necessary technology upgrades.
    • The model supports compliance with business continuity management requirements.

    Conclusions:

    • An integrated risk analysis and queuing theory model is vital for hospital device management.
    • This approach enhances business continuity by proactively addressing technology failures.
    • Optimizing device numbers ensures the uninterrupted flow of essential medical activities.