ArticleBMJ open2026
Implementation determinants and outcomes of artificial intelligence in surgical healthcare: a systematic review protocol.
Article in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
11 authors.
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Abstract
introductionArtificial intelligence (AI) is increasingly being integrated into surgical healthcare to enhance perioperative risk assessment, improve diagnostic accuracy, refine clinical workflows, support intraoperative decision-making and reduce postoperative complications. AI applications including machine learning-based predictive analytics, computer vision, robotic assistance and clinical decision support systems have shown promising clinical performance across surgical specialties. However, knowledge on real-world implementation, barriers, facilitators and system-level outcomes in surgical healthcare remains fragmented with limited synthesis of implementation determinants. This systematic review aims to identify, categorise and synthesise global evidence on implementation strategies, barriers, facilitators, adoption outcomes and reported impacts of AI applications in surgical healthcare settings. METHODS AND ANALYSIS: This protocol is reported in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) 2015 guidelines and has been registered with PROSPERO (CRD420261305972). A systematic search will be conducted across PubMed/Medline, CINAHL (EBSCO), Web of Science, Scopus, Global Index Medicus, medRxiv, IEEE Xplore and ACM Digital Library for studies published between January 2000 and December 2025. Study designs include interventional (randomised controlled trials), observational, implementation, qualitative and mixed-methods studies and programme evaluations. The primary outcome is barriers and facilitators to AI implementation, and synthesised using framework synthesis (Carroll ETHICS AND DISSEMINATION: Ethical approval is not needed, and the results will be disseminated via peer-reviewed publication and presentation at conferences relevant to this field.
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