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An interactive simulation in the health service.

R M Davies

    The Journal of the Operational Research Society
    |June 9, 1985
    PubMed
    Summary
    This summary is machine-generated.

    This study developed a computer model to optimize kidney failure treatments, especially for older adults. The model helps manage resources and prioritize treatments to meet patient demand effectively.

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    Area of Science:

    • Nephrology
    • Health Services Research
    • Computational Modeling

    Background:

    • Irreversible kidney failure presents a significant unmet treatment demand, particularly affecting older populations.
    • Current treatment systems face challenges in resource allocation and prioritizing available therapies.

    Purpose of the Study:

    • To develop and validate a discrete event simulation model for the kidney failure treatment system.
    • To explore the implications of meeting treatment demand by adjusting treatment priorities and the balance between home and hospital care.

    Main Methods:

    • A discrete event simulation model was developed using Pascal on an Apple II computer.
    • The model realistically incorporates resource constraints, organ availability for transplantation, and donor-recipient matching.

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  • Shadow entities were employed to simulate patient survival across different treatment modalities.

    • Main Results:

    • The model was validated using techniques including real-time tabular displays during simulation.
    • The simulation demonstrated robustness to varying data inputs and significant policy shifts.
    • The developed modeling techniques are adaptable for broader applications within the healthcare system.

    Conclusions:

    • The developed simulation model provides a valuable tool for understanding and optimizing kidney failure treatment systems.
    • The model's flexibility and robustness support its use in policy analysis and resource management for renal replacement therapy.
    • The techniques offer a transferable methodology for health service modeling and strategic planning.