A study of operating room scheduling that integrates multiple quantitative and qualitative objectives

Area of Science:

• Healthcare Management
• Operations Research
• Medical Informatics

Background:

• Traditional operating room (OR) scheduling relies on experience and heuristics, leading to inefficiencies.
• Current methods often result in excessive personnel overtime and suboptimal resource utilization.

Purpose of the Study:

• To develop and evaluate an integrated OR scheduling performance evaluation model (IOSPEM).
• The model aims to improve OR scheduling quality by incorporating quantitative and qualitative objectives.

Main Methods:

• Fuzzy Delphi method to determine weights for time, cost, and risk factors.
• Fuzzy set theory to quantify qualitative risk measures.
• Desirability function to integrate factors into the IOSPEM.
• Simulated annealing algorithm for system development and performance testing.

Main Results:

• The IOSPEM successfully unified quantitative and qualitative indices into a single metric.
• The model, combined with simulated annealing, achieved optimal OR schedules.
• Demonstrated reduction in costs and fatigue risks associated with OR scheduling.

Conclusions:

• Implementing the IOSPEM promotes objective and efficient OR scheduling by considering cost, fatigue risk, and other factors.
• Practical application requires setting appropriate cost coefficients and may benefit from including OR overtime costs and nurse fatigue risks.
• The developed methodology provides a foundation for more advanced OR scheduling systems.