ArticleBMC nursing2026
How do dialysis nurses and AI reason clinically? A scenario-based comparative study.
Article in BMC nursing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Evaluating the potential of ChatGPT as an educational decision-support tool for hemodialysis decision-making in nephrology training.Frontiers in medicine · 2026Article
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3 authors.
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Abstract
backgroundDialysis nurses routinely make high-stakes clinical decisions under conditions of uncertainty, balancing protocol-based guidelines with contextual and experiential judgment. Recent advances in artificial intelligence (AI) raise questions regarding its potential role in supporting nursing clinical reasoning.
aimTo compare clinical reasoning performance across experienced dialysis nurses, a general-purpose large language model (ChatGPT-4), and an agent-based AI system (MAI-DxO) using real-world nephrology scenarios, and to explore patterns of human nursing decision-making.
designA comparative, scenario-based study.
methodsOne hundred and ten dialysis nurses and two AI systems independently responded to four validated hemodialysis scenarios reflecting common clinical dilemmas. Responses were evaluated by senior nephrology nursing experts for diagnostic accuracy, appropriateness, and quality of clinical reasoning.
resultsThe agent-based AI system achieved higher mean scenario scores than both ChatGPT-4 and nurses, particularly in structured justification and differential diagnosis. Nurses demonstrated greater variability, with strengths in contextual interpretation and recognition of dialysis-specific complications. Cluster analysis identified three distinct nursing reasoning profiles: protocol-driven, holistic-explanatory, and minimalist.
conclusionWhile AI systems can provide structured and guideline-consistent clinical reasoning, experienced dialysis nurses contribute contextual judgment and practical insight that remain essential to safe patient care. These findings support a complementary, rather than substitutive, role for AI in nursing clinical decision-making.
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