Day surgery appointment scheduling with patient preferences and stochastic operation duration

Area of Science:

• Healthcare Operations Research
• Medical Informatics
• Surgical Workflow Optimization

Background:

• Day surgery is increasingly vital due to its efficiency and high patient throughput.
• Effective scheduling is crucial for managing demand and supply pressures in healthcare systems.
• Optimizing day surgery processes can significantly alleviate resource constraints.

Purpose of the Study:

• To address the day surgery scheduling problem by integrating patient preferences and limited operating room availability.
• To enhance operational efficiency and reduce surgical costs within day surgery settings.
• To develop a robust scheduling model that benefits both patients and healthcare providers.

Main Methods:

• A multi-objective stochastic programming model was developed to balance competing objectives.
• A multi-objective genetic algorithm was employed to solve the complex scheduling model.
• The model's effectiveness was validated using various scenarios of different scales.

Main Results:

• The proposed model and algorithm successfully identified feasible solutions for day surgery scheduling.
• The approach maximizes surgeon preferences while optimizing operating room utilization.
• The results demonstrate the model's capability to handle complex scheduling requirements.

Conclusions:

• Incorporating patient preferences into day surgery scheduling is a key finding.
• Considering the variability of surgery durations leads to more realistic and satisfactory scheduling schemes.
• The developed approach aligns better with actual hospital operational conditions and patient needs.