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Background: Prolonged surgical waiting lists are a persistentchallenge in publicly funded health systems. In Brazil's Unified Health System(SUS), managing elective surgical demand involves complex organizationalpressures and competing stakeholder priorities. Soft Systems Methodology (SSM)offers a framework for addressing such situations, yet its application inresource-constrained public health systems in low- and middle-income countriesremains limited. This study used SSM to examine the organizational complexitiesof elective surgical waiting list management at a federal orthopedic hospitalin Brazil and to identify systemically desirable and culturally feasibleimprovements. Methods: A qualitative case study based on SSM was conducted at theNational Institute of Traumatology and Orthopedics (INTO). Data were collectedbetween March and October 2024 through 22 semi-structured interviews, documentanalysis, and field observations. The six-stage SSM process was used to explorethe problem situation, develop conceptual models, and identify feasibleimprovements. Results: Three dominant worldviews shaped waiting list management:INTO as a Surgical Executor, focused on productivity and waiting-timereduction; as a SUS Network Actor, concerned with equity and federativecoordination; and as a Center of Excellence, committed to research, teaching,and high-complexity care. The interaction of these institutional logicsgenerated tensions in prioritization, governance, and care pathways. Anintegrated conceptual model comprising eleven interdependent activities wasdeveloped to reconcile these perspectives by linking demand management,prioritization, network coordination, operational performance, and academicobjectives. Conclusions: Surgical waiting list management in large public orthopedic hospitals is a complex organizational problem shaped by competinginstitutional logics and federative governance constraints, rather thanoperational bottlenecks alone. SSM made these tensions explicit and supportedstrategic decision-making by identifying systemically desirable and culturallyfeasible improvements. The integrated model provides a foundation for futuredecision-support tools and quantitative modeling, highlighting the value ofqualitative systems approaches in resource-constrained health systems.
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Blanco et al. (2026) studied this question.
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