Scheduling Patients' Appointments: Allocation of Healthcare Service Using Simulation Optimization

Area of Science:

• Healthcare Management
• Operations Research
• Health Services Research

Background:

• Appointment scheduling in the service industry, particularly healthcare, faces challenges due to variable patient demand and service times.
• Inefficient scheduling impacts patient waiting times, resource idleness, and overall operational costs and profits.
• Optimizing scheduling is crucial for enhancing efficiency and patient satisfaction in medical departments.

Purpose of the Study:

• To implement and simulate four distinct appointment scheduling policies within a hospital's ultrasound department.
• To determine optimal or near-optimal solutions for key scheduling parameters like patient arrival rates and time slot allocation.
• To evaluate the performance of different scheduling policies using three objective functions.

Main Methods:

• Simulation modeling of four appointment scheduling policies: constant, mixed, three-section pattern, and irregular arrival.
• Optimization procedures applied to simulated data to identify best-fit parameters for patient flow.
• Analysis of simulation outcomes based on three defined objective functions.

Main Results:

• Simulation identified optimal or near-optimal scheduling parameters for patient arrivals and time slot allocation under different policies.
• Performance variations were observed across the four scheduling policies, highlighting their respective strengths and weaknesses.
• The study provides quantitative data on the impact of each policy on efficiency metrics.

Conclusions:

• The findings offer practical insights for hospital managers to enhance healthcare service capacity allocation.
• Implementing optimized scheduling policies can lead to reduced patient wait times and improved resource utilization.
• This research contributes to the field of healthcare operations management by providing evidence-based scheduling strategies.