High-volume dental healthcare settings face capacity challenges governed by the rigid coupling constraint between dentists and dental chairs. This study aims to analyze these complex resource interdependencies and evaluate the long-term impacts of capacity management strategies on medical revenue, resource investment, dentist workload and service quality.
A system dynamics modeling approach was applied to capture the non-linear dynamics and feedback delays. The model was constructed integrating qualitative causal loop diagrams with quantitative stock-flow modeling based on operational data from 2023 to 2025 collected at a large-scale stomatological center in China. Validation was conducted using historical data, achieving a mean absolute percentage error of 2.19% for outpatient visits and 3.09% for medical revenue.
Simulation results reveal that capacity expansion alone is insufficient to resolve the supply-demand gap. Aggressive expansion leads to diminishing financial returns and underutilized assets due to high fixed costs. In contrast, an internal optimization strategy satisfies demand earlier, generates the highest net surplus and stabilizes workforce stress more effectively.
The study provides a practical decision-support tool enabling healthcare administrators to transition from experience-based static planning to data-driven dynamic management. It suggests that improving coordination efficiency of coupled resources yields a higher return on investment than simple scale expansion.
This research conceptualizes dentist-chair coupling as a dynamic binding constraint within a system dynamics framework and models the interplay between resource constraints and operational feedback loops that drive the long-term capacity, financial performance, and workforce sustainability of dental healthcare organizations.
