Optimization of Markov Queuing Model in Hospital Bed Resource Allocation.

Area of Science:

• Healthcare Management
• Operations Research
• Queuing Theory

Background:

• Efficient hospital bed resource management is crucial for optimal healthcare delivery.
• Current systems often face challenges in balancing resource utilization with patient needs.
• Scientific management and advanced models are needed to improve healthcare system efficiency.

Purpose of the Study:

• To analyze existing queuing theory models in medical services.
• To develop and evaluate a novel Markov queuing strategy for hospital bed resource allocation.
• To measure the performance of the proposed model using key indicators like resource utilization and patient waiting times.

Main Methods:

• Literature review of queuing theory in medical services.
• Development of a mathematical queuing model based on Markov service.
• Construction of a queuing network model for bed resource allocation.
• Comparative analysis using simulation experiments.

Main Results:

• The proposed Markov queuing strategy significantly improves hospital bed resource utilization.
• Patient satisfaction is enhanced through more reasonable queue management and reduced average waiting times.
• The model effectively addresses individual patient needs and optimizes overall healthcare resource allocation.

Conclusions:

• The Markov-based queuing strategy offers a practical and effective solution for hospital bed resource management.
• This approach provides a theoretical and empirical reference for optimizing healthcare resource allocation.
• Implementing this strategy can lead to substantial improvements in hospital operational efficiency and patient care.