Using a queueing model to help plan bed allocation in a department of geriatric medicine

Area of Science:

• Healthcare Operations Research
• Geriatric Medicine
• Mathematical Modeling

Background:

• Geriatric medicine departments face challenges in managing patient flow, bed occupancy, and rejection rates.
• Efficient resource allocation and patient throughput are critical for maintaining service quality and controlling costs.

Purpose of the Study:

• To develop and apply a mathematical model integrating queuing theory and compartmental flow models to analyze geriatric medicine department performance.
• To investigate the impact of admission rates, length of stay, and bed allocation on key performance indicators.
• To evaluate the potential benefits of incorporating unstaffed backup beds for improving service responsiveness and cost-effectiveness.

Main Methods:

• Integration of queuing theory with compartmental models to simulate patient flow dynamics.
• Analysis of variables including admission rates, length of stay, and bed allocation strategies.
• Extension of the model to incorporate waiting beds and unstaffed backup beds.

Main Results:

• Demonstrated that 10-15% bed emptiness is essential for maintaining optimal service efficiency.
• Showcased how adjusting admission rates, length of stay, and bed allocation significantly influences bed occupancy, emptiness, and rejection.
• Indicated that the addition of unstaffed backup beds can enhance departmental performance and cost control.

Conclusions:

• The developed model provides a framework for optimizing geriatric medicine department operations across various parameters.
• Unstaffed backup beds offer a cost-effective solution for improving service responsiveness and managing patient flow.
• Further research is recommended to validate the model's applicability and real-world performance.