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Aim <p>The use of artificial intelligence in nursing has become increasingly important in recent years. In particular, generative artificial intelligence (GenAI) such as ChatGPT offers the potential to improve care processes, support decision-making, and reduce workload. The aim of this paper is to provide an overview of the current state of research on the use of GenAI in nursing and clinical practice.</p> Subject and methods <p>A systematic literature search was conducted in the PubMed, Embase, CINAHL, and Scopus databases. Studies from the last 5 years (2019–2024) dealing with the use of GenAI in professional nursing and the improvement of nursing skills through AI were included. Studies on machine learning, deep learning, and specific disease contexts were excluded. A total of 13 studies were included in the analysis.</p> Results <p>GenAI in nursing and clinical practice can increase the efficiency of tasks such as scheduling and care planning, but there are currently significant gaps in decision accuracy and reliability. Studies show potential to reduce workload, but also point to the need for further research and technical improvements.</p> Conclusion <p>Although GenAI in nursing is promising, there are still significant limitations. Future developments and regulatory measures are needed to ensure the safe and effective use of GenAI in nursing practice.</p>

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GenAI in nursing and clinical practice: a rapid review of applications and challenges

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年6月5日

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  • Tim Tischendorf,
  • Laura Hinsche,
  • Martina Hasseler,
  • Tom Schaal

摘要

Aim

The use of artificial intelligence in nursing has become increasingly important in recent years. In particular, generative artificial intelligence (GenAI) such as ChatGPT offers the potential to improve care processes, support decision-making, and reduce workload. The aim of this paper is to provide an overview of the current state of research on the use of GenAI in nursing and clinical practice.

Subject and methods

A systematic literature search was conducted in the PubMed, Embase, CINAHL, and Scopus databases. Studies from the last 5 years (2019–2024) dealing with the use of GenAI in professional nursing and the improvement of nursing skills through AI were included. Studies on machine learning, deep learning, and specific disease contexts were excluded. A total of 13 studies were included in the analysis.

Results

GenAI in nursing and clinical practice can increase the efficiency of tasks such as scheduling and care planning, but there are currently significant gaps in decision accuracy and reliability. Studies show potential to reduce workload, but also point to the need for further research and technical improvements.

Conclusion

Although GenAI in nursing is promising, there are still significant limitations. Future developments and regulatory measures are needed to ensure the safe and effective use of GenAI in nursing practice.