ArticleAORN journal2026
Leveraging Artificial Intelligence to Improve Perioperative Staffing Consistency: A Quality Improvement Initiative at a Large Academic Medical Center.
Article in AORN journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A large academic medical center in the Pacific Northwest addressed perioperative staffing challenges by implementing a workflow with application of AI assistance to optimize daily assignments. The initiative integrated real-time and historical data to support consistent matching of staff competencies and procedure experience with scheduled procedures and surgeons. The workflow streamlined processes and saved service line coordinators 20 hours per week and nurse leaders 5 hours per week. Surgical staffing consistency improved by 30 percentage points, from 50% to 80%, and staff and surgeon sentiment improved. By enhancing visibility into documented competencies and procedure history and reducing reliance on manual assignments, the initiative improved the reliability and efficiency of daily staffing decisions while reinforcing safe alignment of skills with procedure complexity. Implementation success was supported by multidisciplinary collaboration and iterative workflow refinement. This article outlines the implementation approach, observed outcomes, and key operational considerations for health systems pursuing similar innovations.
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Registered trials
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