How does the hospital make a safe and stable elective surgery plan during COVID-19 pandemic?

Area of Science:

• Operations Research in Healthcare
• Healthcare Management
• Optimization Theory

Background:

• The COVID-19 pandemic caused hospital overcrowding, delaying elective surgeries and impacting patient health and hospital revenue.
• Uncertainties in surgery duration, patient length of stay, emergency arrivals, and infection status complicate hospital resource allocation.
• Effective management of these uncertainties is crucial for maintaining healthcare system functionality.

Purpose of the Study:

• To develop a robust bed configuration and planning model for elective surgery scheduling amidst healthcare uncertainties.
• To integrate robust optimization and fuzzy set theory for handling diverse uncertainty types within a single healthcare system.
• To address the complexity of surgical scheduling, which is often NP-hard.

Main Methods:

• Proposed a novel bed configuration strategy to shield elective surgeries from non-elective patient disruptions.
• Developed a planning model using robust optimization and fuzzy set theory to manage various uncertainties.
• Introduced a hybrid algorithm (GA-VNS-H) combining genetic algorithm, variable neighborhood search, and heuristics for efficient problem-solving.
• Implemented an adaptive mechanism to reduce algorithm solution time.

Main Results:

• The proposed model effectively copes with the uncertain healthcare environment exacerbated by COVID-19.
• The hybrid algorithm (GA-VNS-H) demonstrated superior calculation efficiency and solution accuracy compared to traditional methods.
• The new bed configuration ensures elective surgeries are minimally impacted by unpredictable events.

Conclusions:

• The developed planning model and bed configuration offer a robust solution for elective surgery scheduling under uncertainty.
• The hybrid algorithm provides an efficient and accurate approach to solving complex healthcare optimization problems.
• This research provides a framework for enhancing hospital resilience and operational efficiency in crisis situations.