REVIEW article
Front. Bioeng. Biotechnol.
Sec. Biosafety and Biosecurity
Artificial Intelligence and Precision Nursing in the Operating Room: Transforming Perioperative Safety and Surgical Outcomes
Provisionally accepted
- The Ninth Medical Center of Chinese PLA General Hospital, 739621, Beijing, China
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Background The operating room represents a high-risk clinical environment where perioperative nurses play a critical role in patient safety, workflow coordination, and surgical outcomes. Recent advances in artificial intelligence (AI) and precision health technologies offer new opportunities to enhance perioperative nursing practice; however, the scope, maturity, and clinical relevance of these applications remain heterogeneous. Objective This scoping review aimed to map the existing evidence on the integration of AI and precision nursing in perioperative and operating room settings, with a focus on nursing roles, clinical applications, outcomes, and implementation challenges. Methods A scoping review was conducted in accordance with the PRISMA-ScR guidelines. A systematic search of PubMed/MEDLINE, Scopus, Web of Science, and CINAHL was performed for studies published between January 2010 and March 2025. Eligible studies examined AI-enabled or data-driven technologies relevant to perioperative nursing practice across preoperative, intraoperative, and postoperative phases. Data were charted and synthesized descriptively to identify key application domains, evidence levels, and research gaps. Results Seventy-two studies met the inclusion criteria. Identified AI applications included predictive analytics for perioperative risk stratification, real-time intraoperative monitoring and decision support, computer vision–based workflow and sterility surveillance, automated documentation, robotic assistance, and postoperative remote monitoring. Evidence suggests potential benefits in early complication detection, workflow efficiency, and support for nursing decision-making. However, most studies were pilot or observational in nature, with limited large-scale clinical validation. Ethical considerations, data governance, workforce readiness, and integration into nursing workflows emerged as recurring challenges. Conclusion AI-enabled precision nursing represents a promising approach to enhancing perioperative safety and surgical outcomes. Current evidence supports AI as a complementary tool that augments—rather than replaces—clinical judgment and nursing expertise. Further high-quality nursing-focused research, standardized evaluation frameworks, and ethically grounded implementation strategies are required to support safe and sustainable integration into perioperative practice.
Keywords: artificial intelligence, digital transformation, Perioperative Nursing, predictive analytics, Simulation-based education
Received: 19 Nov 2025; Accepted: 31 Jan 2026.
Copyright: © 2026 Gong, Zhao and Zong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Huana Zong
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