Simulation-based optimization to improve hospital patient assignment to physicians and clinical units

Area of Science:

• Healthcare Operations Research
• Hospital Management Systems
• Clinical Informatics

Background:

• Patient assignment is crucial for hospital operations, impacting efficiency and care quality.
• Overflow patient assignment, used when capacity is limited, can negatively affect care quality and length of stay.
• Existing capacity-based overflow strategies may not optimize hospital resources or patient outcomes.

Purpose of the Study:

• To develop and evaluate discrete-event simulation models for hospital patient assignment strategies.
• To heuristically optimize assignment strategies considering profit, care quality, and patient waiting times.
• To compare optimized overflow strategies against traditional capacity-based methods.

Main Methods:

• Development of a discrete-event simulation model for patient assignment.
• Application of simulation-based optimization to evaluate various assignment strategies.
• Utilizing data from the University of Chicago Medical Center for model validation.

Main Results:

• Heuristically optimized overflow services and units increased expected profit compared to capacity-based strategies.
• A strategy incorporating optimized overflow and a holding unit showed further performance improvements.
• Demonstrated impact of strategies on patient concentration, waiting times, and overall outcomes.

Conclusions:

• Optimized overflow designation in patient assignment enhances hospital profitability.
• Integrated strategies with holding units offer superior performance in patient flow and resource utilization.
• Simulation-based optimization provides a powerful tool for improving hospital operational efficiency and patient care.