Is there a place for artificial intelligence (AI) in nursing? The position statement from the American Nurses Association (ANA) emphasizes that “the appropriate use of AI in nursing practice supports and enhances the core values and ethical obligations of the profession” and “AI does not replace good nursing care or the care provided by other members of the interprofessional team. AI augments, supports, and streamlines expert clinical practice” (ANA, 2022).

Recent headlines touting the benefits of AI in healthcare, plus a special May 2024 issue of Computers Informatics Nursing focused on AI, prompted me to dive deeper into this topic and learn the how, what, and why of AI as it pertains to nursing. Here are some things I learned.

How is AI currently being used in nursing?

Some of the impacts of AI include expanding access to high-quality medical care and improving care delivery, improving the electronic health record (EHR), and improving collaboration, communication, and coordination between healthcare disciplines (Pailaha, 2023). Generative AI tools, such as ChatGPT and BardAI, summarize data into text for expedited information-gathering and content creation, and are gaining use in clinical and operations settings to “help nursing staff improve productivity and decrease waste by eliminating menial tasks and enabling more informed and efficient clinical decisions” (Carroll, 2023). By automating certain processes, AI has the potential to give clinicians more time for patient interaction, thereby improving outcomes (Molyneux, 2023).

Specific examples of how AI is being used in nursing include (Columbia School of Nursing, 2023; Molyneux, 2023; Hostetler et al., 2024):

• AI-based clinical decision support tools built into the EHR, such as alerts and alarms
• AI tools that analyze large quantities of patient data and identify patterns, including patterns of deterioration; some specific predictive decision support algorithms include those to detect sepsis, cardiac arrest, and hospital acquired infections
• Documentation software programs to record and summarize clinician-patient encounters
• AI-powered medical chatbots to answer clinicians' or patients' questions, summarize research, organize information, and help coordinate care
• Virtual health assistants to help with administrative and educational processes
• AI-powered telehealth for patient visits and to remotely track and analyze data from patients with wearable sensors
• Content generation and plagiarism detectors in academia
• Online learning platforms, as well as high-fidelity and virtual reality simulators, in nursing education

What are some concerns related to AI use?

It’s important to remember that AI tools and solutions are assistive technologies, and not meant to replace human judgment which is critical to ensure accuracy, safety, ethical standards, equity, and fairness (Carroll, 2023). Concerns voiced by nurses include preserving holistic care, the possibility that AI might overlook subtle nuances, and safeguarding patient data privacy and security (Rony et al., 2024). Also, AI can potentially embed existing human biases into electronic systems and can exacerbate a push towards market-driven goals of efficiency, such as increasing nurses’ tasks or volume of patients (Columbia School of Nursing, 2023).

In 2021, the World Health Organization (WHO) issued Ethics and Governance of Artificial Intelligence for Health. Here are the six ethical principles identified to guide the development and use of AI technology for health (Health Ethics & Governance (HEG), 2021):

1. Protect autonomy.
2. Promote human well-being, human safety, and the public interest.
3. Ensure transparency, explainability, and intelligibility.
4. Foster responsibility and accountability.
5. Ensure inclusiveness and equity.
6. Promote AI that is responsive and sustainable.

AI is here to stay and its role in healthcare and nursing will continue to evolve. As AI impacts the role of nursing in patient care delivery, we must be involved in the development, implementation, and workflow integration of AI tools. It’s important for nurses to be part of the discussion so we can best advocate for safe use of AI to inform and support – not replace – nursing care.

References:

ANA Center for Ethics and Human Rights. (2022). The Ethical Use of Artificial Intelligence in Nursing Practice. American Nurses Association.  https://www.nursingworld.org/~48f653/globalassets/practiceandpolicy/nursing-excellence/ana-position-statements/the-ethical-use-of-artificial-intelligence-in-nursing-practice_bod-approved-12_20_22.pdf

Carroll W. M. (2023). Generative AI in clinical practice and operations. Nursing management, 54(10), 56. https://doi.org/10.1097/nmg.0000000000000056

Columbia School of Nursing (2021, July 13). Q&A: Artificial Intelligence and Nursing https://www.nursing.columbia.edu/news/q-artificial-intelligence-and-nursing

Gallo, R. J., Shieh, L., Smith, M., Marafino, B. J., Geldsetzer, P., Asch, S. M., Shum, K., Lin, S., Westphal, J., Hong, G., & Li, R. C. (2024). Effectiveness of an Artificial Intelligence-Enabled Intervention for Detecting Clinical Deterioration. JAMA internal medicine, 184(5), 557–562. https://doi.org/10.1001/jamainternmed.2024.0084

Health Ethics & Governance (HEG). (2021, June 28). Ethics & Governance of Artificial Intelligence for Health. World Health Organization. https://www.who.int/publications/i/item/9789240029200

Hostetler, T., Owens, J., Waldrop, J., Oermann, M., & Carter-Templeton, H. (2024). Generative Artificial Intelligence Detectors and Accuracy: Implications for Nurses. CIN: Computers, Informatics, Nursing 42(5), 315–319. https://www.doi.org/10.1097/CIN.0000000000001134

Molyneux J. (2023). Artificial Intelligence and Nursing: Promise and Precaution. The American journal of nursing, 123(10), 17–19. https://doi.org/10.1097/01.NAJ.0000979068.75051.bd

Pailaha A. D. (2023). The Impact and Issues of Artificial Intelligence in Nursing Science and Healthcare Settings. SAGE open nursing, 9, 23779608231196847. https://doi.org/10.1177/23779608231196847

Rony, M. K. K., Kayesh, I., Bala, S. D., Akter, F., & Parvin, M. R. (2024). Artificial intelligence in future nursing care: Exploring perspectives of nursing professionals - A descriptive qualitative study. Heliyon, 10(4), e25718. https://doi.org/10.1016/j.heliyon.2024.e25718

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As the nursing community continues to expand its use and understanding of AI-driven research, education, and clinical care, the May 2024 issue of Computers Informatics Nursing (CIN) offers insight into the growth of AI in nursing. The articles cover reviews, field tests, feasibility studies, and empirical research to further understand this technology. Furthermore, studies included in this issue are from the clinical and educational settings.

The article titled Data-Centric Machine Learning in Nursing: A Concept Clarification, provides explanation on data-centric machine learning in nursing, and explores the distinction of this method compared to other approaches such as model-centric machine learning. We are happy to offer nursing professional development credits for this selection. Another article in the issue, Foundation Models, Generative AI, and Large Language Models: Essentials to Nursing, investigates fundamental aspects of foundation models, generative AI, and large language models which may assist readers as they learn to navigate the emerging role of AI in our field.

This AI-focused issue also includes the use of ensemble-based machine learning to develop a predictive model for survival in patients with cardiac arrest outside of a hospital; a scoping review related to use of AI to identify optimal practice patterns; and a field-testing study related to developing a teaching assistant system for undergraduate nursing students. We are excited to share this special issue with you!

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COLLECTION	AI RESOURCES	JOURNAL
Informatics	Wolters Kluwer AI	Computers Informatics Nursing