A Simulation-Optimisation approach for hospital beds allocation.

Area of Science:

• Healthcare Management
• Operations Research
• Computational Science

Background:

• Hospital bed planning is a complex, debated issue in healthcare.
• Existing methods often fail to sustain improvements, leading to high costs and patient refusals.
• The problem involves stochastic elements and conflicting optimization criteria.

Purpose of the Study:

• To propose and evaluate a Simulation-Optimisation approach for hospital bed planning.
• To address the challenges of conflicting criteria and stochasticity in resource allocation.
• To provide an alternative to current empirical methods used in Brazil.

Main Methods:

• Utilizing an Evolutionary Algorithm, specifically NSGA-II, to drive the optimization process.
• Employing Discrete Event Simulation for validating and evaluating the generated solutions.
• Applying the approach to a real-world case in a Brazilian health region.

Main Results:

• The Simulation-Optimisation approach successfully identified efficient and feasible solutions.
• The method demonstrated effectiveness in optimizing hospital bed allocation.
• The application in Minas Gerais, Brazil, showed promising results for the public health system.

Conclusions:

• The proposed Simulation-Optimisation approach is a viable alternative to traditional empirical methods for hospital bed allocation.
• This approach offers a robust framework for improving healthcare service planning and resource management.
• It has the potential to enhance efficiency and reduce costs in public health systems.