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Waiting for the doctor.

E I Marshall

    British Medical Journal (Clinical Research Ed.)
    |April 12, 1986
    PubMed
    Summary
    This summary is machine-generated.

    This study developed a computer model to find the optimal appointment intervals in general practice surgeries. The model helps reduce patient waiting times by simulating patient arrivals and consultation durations.

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    Area of Science:

    • General Practice
    • Operations Research
    • Health Services Research

    Background:

    • Optimizing appointment scheduling is crucial for efficient general practice operations.
    • Patient waiting times in primary care settings are a significant concern for both patients and providers.
    • Existing appointment systems may not effectively account for variations in patient arrival and consultation durations.

    Purpose of the Study:

    • To determine the optimal time interval between patient appointments in general practice.
    • To develop a flexible mathematical model for simulating surgery appointment systems.
    • To assess the potential for reducing patient waiting times through optimized scheduling.

    Main Methods:

    • Construction of a rapid computer-based mathematical model simulating patient arrivals and consultations.

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  • The model requires only observed patient arrival and consultation times from 10 surgeries as input.
  • Application of the model to general practitioner surgeries with established appointment systems.

    • Main Results:

    • The developed model accurately simulates patient flow within a general practice setting.
    • The model provides a method for identifying ideal appointment time intervals.
    • Demonstrated potential for significant reduction in patient waiting times in a case study practice.

    Conclusions:

    • The mathematical model offers a practical tool for optimizing appointment scheduling in primary care.
    • Implementing optimized appointment intervals can lead to improved efficiency and reduced patient wait times.
    • The model's adaptability makes it suitable for diverse general practice environments.