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A simple method to optimize hospital beds capacity.

J M Nguyen1, P Six, D Antonioli

  • 1Laboratory of Medical Statistics and Informatics, 1 rue Gaston Veil, 44035 Nantes Cedex 01, France. jmnguyen@chu-nantes.fr

International Journal of Medical Informatics
|January 1, 2005
PubMed
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This study introduces a novel method for determining hospital bed capacity, offering a robust alternative to traditional ratio-based approaches. The new method balances simplicity with effectiveness, ensuring optimal resource allocation for patient care.

Area of Science:

  • Health Services Research
  • Hospital Management
  • Operations Research

Background:

  • Current methods for determining acute hospital bed numbers rely on ratios or target occupancy rates, failing to account for demand variability.
  • Sophisticated models often require expert input, limiting their accessibility for routine bed management.

Purpose of the Study:

  • To develop a new method for hospital bed capacity planning that is as user-friendly as ratio-based methods.
  • To minimize the limitations of existing approaches by incorporating demand variability and reducing reliance on expert judgment.

Main Methods:

  • A novel scoring system was developed using three parameters: transfers due to lack of space, days with no unscheduled admissions, and days with unoccupied beds.
  • The optimal number of beds was identified as the point where both the mean and standard deviation of this score are minimized.

Related Experiment Videos

  • The method was validated by comparing its results with traditional ratio methods in internal medicine and urological surgery departments.

    • Main Results:

    • The proposed method yielded bed number recommendations intermediate to local and national length-of-stay ratio methods.
    • The method demonstrated robustness when simulating significant increases in admission requests.
    • The developed tool provides a practical alternative to conventional bed planning techniques.

    Conclusions:

    • The new method offers a viable and user-friendly alternative to traditional ratio-based hospital bed capacity planning.
    • A software implementation of this method is available, facilitating its adoption in clinical practice.