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HOROPLAN: computer-assisted nurse scheduling using constraint-based programming

S J Darmoni1, A Fajner, N Mahé

  • 1Rouen University Hospital, France.

Journal of the Society for Health Systems
|January 1, 1995
PubMed
Summary
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This study introduces Horoplan, an artificial intelligence-driven nurse scheduling system. It efficiently manages nurse shifts using a flexible, constraint-based approach, optimizing hospital operations.

Area of Science:

  • Artificial Intelligence
  • Operations Research
  • Healthcare Management

Background:

  • Nurse scheduling is complex, demanding significant time and effort.
  • Balancing hospital requirements with nurse preferences is challenging.
  • Existing methods often lack flexibility and efficiency.

Purpose of the Study:

  • To develop and evaluate an AI-powered system for optimizing nurse scheduling.
  • To address the complexities of creating fair and efficient nurse rosters.
  • To improve the balance between operational needs and nurse well-being.

Main Methods:

  • A constraint-based artificial intelligence approach was employed.
  • A prototype system, Horoplan, was developed using the Charme language.

Related Experiment Videos

  • Non-cyclical scheduling with heuristics and four constraint levels was implemented.

    • Main Results:

    • The Horoplan system demonstrated effective nurse scheduling at Rouen University Hospital.
    • The constraint-based approach allowed for flexibility in meeting diverse requirements.
    • The system supports rescheduling to accommodate unforeseen absences.

    Conclusions:

    • Constraint-based AI offers a powerful solution for complex nurse scheduling problems.
    • Horoplan provides a flexible and efficient tool for hospital workforce management.
    • This approach can significantly improve the scheduling process, benefiting both institutions and staff.