Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Leading with AI in critical care nursing: challenges, opportunities, and the human factor
50
Zitationen
2
Autoren
2024
Jahr
Abstract
INTRODUCTION: The integration of artificial intelligence (AI) in intensive care units (ICUs) presents both opportunities and challenges for critical care nurses. This study delves into the human factor, exploring how nurses with leadership roles perceive the impact of AI on their professional practice. OBJECTIVE: To investigate how nurses perceive the impact of AI on their professional identity, ethical considerations surrounding its use, and the shared meanings they attribute to trust, collaboration, and communication when working with AI systems. METHODS: An interpretive phenomenological analysis was used to capture the lived experiences of critical care nurses leading with AI. Ten nurses with leadership roles in various ICU specializations were interviewed through purposive sampling. Semi-structured interviews explored nurses' experiences with AI, challenges, and opportunities. Thematic analysis identified recurring themes related to the human factor in leading with AI. FINDINGS: Thematic analysis revealed two key themes which are leading with AI: making sense of challenges and opportunities and the human factor in leading with AI. The two main themes have six subthemes which revealed that AI offered benefits like task automation, but concerns existed about overreliance and the need for ongoing training. New challenges emerged, including adapting to new workflows and managing potential bias. Clear communication and collaboration were crucial for successful AI integration. Building trust in AI hinged on transparency, and collaboration allowed nurses to focus on human-centered care while AI supported data analysis. Ethical considerations included maintaining patient autonomy and ensuring accountability in AI-driven decisions. CONCLUSION: While AI presents opportunities for automation and data analysis, successful integration hinges on addressing concerns about overreliance, workflow adaptation, and potential bias. Building trust and fostering collaboration are fundamentals for AI integration. Transparency in AI systems allows nurses to confidently delegate tasks, while collaboration empowers them to focus on human-centered care with AI support. Ultimately, dealing with the ethical concerns of AI in ICU care requires prioritizing patient autonomy and ensuring accountability in AI-driven decisions.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.697 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.602 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 8.127 Zit.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
2019 · 6.872 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.