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Effect of Centralized Surgical Care on Performance Outcomes Across Multi-hospital Systems: A Systematic Review
Brett A Johnson1,2, Anoosha Moturu1,3, Shelby Eagle1
1Division of Research and Optimal Patient Care, American College of Surgeons, Chicago, IL.
Objective:
To evaluate the effect of centralized surgical care on clinical and operational performance across multi-hospital systems.
Background:
Centralized care is increasingly promoted to enhance surgical value within multi-hospital systems, yet its adoption is inconsistent and its effect across surgical complexity levels remains unclear.
Methods:
A systematic review of PubMed, Embase, and Web of Science (inception-January 30, 2025) identified studies evaluating centralized surgical care at the hospital-level (central vs affiliated hospitals) and system-level (degree of centralization, pre-post redesign) comparisons. Surgical care was classified as complex or non-complex. Findings were synthesized narratively, and certainty of evidence was assessed.
Results:
Of 4737 screened articles, 18 studies (2019-2024) met inclusion criteria. Among the 54 outcomes with statistically significant associations, the certainty of evidence was rated as moderate/high in 12 (22%), low in 13 (24%), and very low in 29 (54%). Centralized delivery of complex surgical care was associated with improvements in mortality (8/10 studies), complication rates (5/7), failure-to-rescue (4/4), long-term survival (4/6), and adherence to evidence-based standards (7/7). Operational benefits included more efficient resource utilization (3/3), shorter hospital stay (2/3), and lower costs (1/2). In contrast, centralizing non-complex care demonstrated limited clinical benefits and was frequently associated with diminished operational efficiency. Studies evaluating deliberate system redesign were limited but reported substantial improvements in performance.
Conclusions:
Findings support a selective, complexity-informed approach to organizing surgical care to enhance system value. Further research is needed to evaluate implementation strategies and determine the scalability of these models across multi-hospital systems.
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