Master Surgical Scheduling as a Complex Feedback System: A Systems Thinking and System Dynamics Perspective

Articles in Press

Document Type : Research Article

Authors

Mohammad Ebrahimi ¹

Ramezan Khosravi ²

¹ Department of Management, Faculty of Humanities, University of Gonabad, Gonabad, Iran

² Department of Industrial Engineering, Faculty of Engineering, University of Gonabad, Gonabad, Iran

10.22067/jstinp.2026.99579.1214

Abstract

Master Surgical Scheduling is a tactical planning problem that determines how operating room capacity is allocated to meet surgical demand. Existing research has relied on optimization-based approaches that focus on capacity allocation, resource utilization, and schedule feasibility. Although these approaches provide valuable decision-support tools, they offer limited insight into the feedback mechanisms and dynamic interactions that shape long-term surgical system performance. This study adopts a System Dynamics perspective to investigate Master Surgical Scheduling as a complex feedback system. A causal loop diagram was developed through literature synthesis and validated through a two-round Fuzzy Delphi process involving 12 multidisciplinary experts to capture interactions among elective and emergency demand, specialty block allocation, effective capacity, downstream bed constraints, workforce conditions, treatment quality, patient satisfaction, hospital reputation, and financial resources. Across the two rounds, 44 of 47 candidate variables and 67 of 71 candidate causal relationships met the predefined retention criteria. The analysis identifies eighteen feedback loops - seven reinforcing and eleven balancing - organized around the original four mechanisms and an additional MSS-specific block-allocation and coordination mechanism; fifteen delayed effects are explicitly mapped. The structural analysis suggests that surgical scheduling performance is shaped by the interaction between balancing mechanisms that seek to align demand and capacity and reinforcing mechanisms that intensify system pressure through patient deterioration, workforce burnout, and quality-related effects. These findings represent structurally plausible dynamic tendencies rather than quantified behavioral trajectories. The resulting CLD complements optimization-oriented MSS research and provides a transparent foundation for subsequent stock-and-flow simulation and policy testing.

Keywords

Master Surgical Scheduling

System Dynamics

Systems Thinking

Hospital Operations Management

Causal Loop Diagram

Capacity Management

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