Integrating large language models in nursing practice: Opportunities, challenges, and ethical reflections

Integrating Large Language Models in Nursing Practice

Recent advancements in artificial intelligence, particularly in large language models (LLMs), are reshaping nursing practice by offering innovative solutions to enhance patient care. However, the integration of these technologies presents unique challenges and ethical considerations that must be addressed.

LLMs, such as those developed by OpenAI, can assist nurses in various tasks, including streamlining documentation and providing patient education materials tailored to individual needs, potentially improving health literacy.

However, the adoption of LLMs in nursing faces significant challenges. One concern is the accuracy of information provided by these models, which can vary. This raises questions about the reliability of AI-generated information in critical care scenarios.

Another challenge involves integrating LLMs into existing workflows. Many healthcare facilities have complex systems, and LLMs must align seamlessly with electronic health records (EHRs) and other digital tools. This requires careful planning and training for nursing staff.

Ethical considerations are also crucial. Issues regarding patient privacy, data security, and informed consent are paramount. The use of AI technologies raises concerns about how patient data is handled and whether it adheres to regulatory standards. Ensuring that LLMs are trained on diverse datasets is essential to mitigate bias and disparities in patient care.

Professional organizations, including the American Nurses Association (ANA), are exploring guidelines to navigate the ethical landscape of AI in healthcare, providing a framework for nurses to enhance patient care with technology.