An optimization based on simulation approach to the patient admission scheduling problem using a linear programing...

Area of Science:

• Health Services Management
• Operations Research
• Medical Informatics

Background:

• Increasing patient waiting list lengths necessitate novel management strategies.
• Current strategies involving private sector partnerships are insufficient to meet demand.
• Balancing cost, quality, and efficiency in healthcare delivery is a critical challenge.

Purpose of the Study:

• To present a simulation-based optimization approach for the Patient Admission Scheduling Problem.
• To optimize patient flow within a diagnostic imaging department.
• To minimize patient length of stay while controlling costs and maintaining care quality.

Main Methods:

• Utilized modeling tools and simulation techniques for healthcare service optimization.
• Applied a simulation-based optimization approach to the Patient Admission Scheduling Problem.
• Employed a simulated annealing algorithm to optimize patient admission sequences.

Main Results:

• The simulation effectively evaluated diagnostic imaging workflows.
• Optimized patient admission sequences led to reduced total completion and waiting times.
• Achieved average reductions of 5% in total completion time and 38% in total patient waiting time.

Conclusions:

• Simulation-based optimization is effective for improving healthcare operational efficiency.
• The proposed methods successfully reduced patient waiting times in diagnostic imaging.
• This approach offers a viable strategy for managing healthcare resources and patient flow.