Solving patient referral problems by using bat algorithm

Area of Science:

• Healthcare Operations Research
• Medical Systems Engineering
• Health Informatics

Background:

• Addresses the challenge of optimizing patient referral volumes between two hospitals.
• Evaluates if current referral numbers are suboptimal, impacting patient care.

Purpose of the Study:

• Develops a simulation-based optimization algorithm to determine ideal patient referral rates.
• Aims to find optimal daily referral policies for inter-hospital patient transfers.

Main Methods:

• Employs system simulation combined with a bat algorithm (BA) for optimization.
• Constructs a simulation model reflecting the specific conditions of the two hospitals.

Main Results:

• Demonstrates algorithm stability across 20 test instances.
• Achieved a 50% reduction in average magnetic resonance imaging (MRI) patient wait time (from 16 to 8 days).
• Identified an optimal strategy: increase average total monthly MRI referrals to 370 with a daily limit of 25 patients.

Conclusions:

• Successfully investigated and modeled two-hospital patient referral dynamics.
• The simulation model improved the case hospital's operational efficiency and medical care quality.
• Findings are generalizable to other hospital departments and healthcare facilities.