Improving Healthcare Service Quality: A System Dynamics Approach to Managing Visit Times and Reducing Error Rates

Document Type : Research Article

Authors

• Fatemeh Ghayoor
• Donya Rahmani

Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran.

10.22067/jstinp.2025.91833.1141

Abstract

This study explores the application of system dynamics modelling to enhance service quality in healthcare systems. Healthcare environments are inherently complex, requiring adaptive strategies to address challenges such as fluctuating patient demands, work pressure, reduced visit times, and error generation in physician prescriptions. Through simulation-based analysis, we evaluated the impact of various policies, including adjustments to patient arrival rates and human resource hire/quit rate. Our findings indicate that reducing patient arrival rates effectively stabilises work pressure and minimises error generation, but it may conflict with organisational accessibility goals. Increasing human resources, particularly experienced employees, emerges as a sustainable alternative, enhancing service capacity and reducing errors. A dual strategy combining an increased hire fraction of experienced employees with retention-focused policies preventing the employee quit rate yields the most promising results. This approach improves employee efficiency, reduces error probabilities, aligns visit times with standards, and boosts profitability. The study underscores the importance of balancing workforce optimization with system costs to achieve long-term improvements in service quality. Simulation-based decision-making offers healthcare administrators a robust framework for evaluating the cascading effects of policy changes. By integrating dynamic modelling into management practices, healthcare systems can achieve enhanced operational performance, improved patient satisfaction, and sustainable service quality outcomes..

Keywords

• System Dynamics
• Error Generation
• Visit Time
• Healthcare Service Quality
• Patient Arrival Rate
• Human Resource Efficiency

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