The Role and Impact of Artificial Intelligence (AI) in Nursing

Is there a spot for artificial intelligence (AI) in nursing? The American Nurses Association (ANA) statement emphasizes that “the appropriate use of AI in nursing practice supports and enhances the profession’s core values ​​and ethical obligations” and that AI doesn’t “replace good nursing care or care provided by other members of the interdisciplinary team. AI augments, supports, and enhances expert clinical practice” (ANA, 2022).

Recent headlines extolling the advantages of AI in healthcare, plus a special feature May 2024 Edition focused on AI, prompted me to delve deeper into the subject and learn the how, what, and why of AI because it pertains to nursing. Here are a number of the things I learned.

How is artificial intelligence currently utilized in nursing?

Some of the consequences of AI include expanding access to high-quality care and improving care delivery, improving electronic health records (EHRs), and improving collaboration, communication, and coordination across healthcare disciplines (Pailaha, 2023). Generative AI tools akin to ChatGPT and BardAI summarize data in text for accelerated information collection and content creation, and are gaining application in clinical and operational settings to “help nursing staff increase productivity and reduce waste by eliminating simple tasks and enabling more informed and efficient clinical decisions” (Carroll, 2023). By automating some processes, AI has the potential to offer physicians more time to interact with patients, thereby improving outcomes (Molyneux, 2023).

Here are specific examples of the usage of AI in nursing (Columbia School of Nursing, 2023; Molyneux, 2023; Hostetler et al., 2024):

• AI-powered clinical decision support tools built into the EHR, akin to alerts and alarms
• AI tools that analyze large amounts of patient data and discover patterns, including patterns of health deterioration; some specific predictive decision support algorithms include those for detecting sepsis, cardiac arrest, and hospital-acquired infections
• Documentation programs for recording and summarizing doctor-patient encounters
• AI-powered medical chatbots answer doctors’ and patients’ questions, summarize tests, organize information and help coordinate care
• Virtual medical assistants to assist with administrative and academic processes
• AI-powered telemedicine for patient visits and distant tracking and evaluation of patient data using wearable sensors
• Content Generation and Plagiarism Detectors in Academia
• Online Learning Platforms and High-Fidelity Virtual Reality Simulators for Nursing Education

What are the concerns in regards to the use of artificial intelligence?

It is significant to do not forget that AI tools and solutions are technologies and should not intended to exchange human judgment, which is critical to making sure accuracy, safety, ethical standards, equity, and fairness (Carroll, 2023). Concerns expressed by nurses include maintaining holistic care, the likelihood that AI may overlook subtle nuances, and protecting the privacy and security of patient data (Rony et al., 2024). Additionally, AI has the potential to embed existing human biases into electronic systems and will exacerbate the pursuit of market-driven efficiency goals, akin to increasing nurses’ tasks or patient volumes (Columbia School of Nursing, 2023).

In 2021, the World Health Organization (WHO) issued a document entitled Here are six ethical principles to underpin the event and use of artificial intelligence technologies in healthcare (Health Ethics & Governance (HEG), 2021):

1. Let’s protect autonomy.
2. Promoting human well-being, security and the general public interest.
3. Ensure clarity, explainability and understandability.
4. Fostering responsibility and accountability.
5. Ensuring inclusiveness and equality.
6. Let’s promote AI that’s responsive and sustainable.

AI is here to remain, and its role in healthcare and nursing will proceed to evolve. As AI impacts nursing’s role in providing patient care, we have to be involved in the event, implementation, and integration of AI tool workflows. It is significant that nurses are a part of the conversation in order that we are able to best advocate for the secure use of AI to tell and support—not replace—nursing care.

ANA Center for Ethics and Human Rights. (2022). 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 WM (2023). Generative artificial intelligence in clinical practice and surgery. , (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., and Li, R. C. (2024). Effectiveness of a synthetic intelligence-assisted intervention in detecting clinical deterioration. , (5), 557–562. https://doi.org/10.1001/jamainternmed.2024.0084

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

Hostetler, T., Owens, J., Waldrop, J., Oermann, M., and Carter-Templeton, H. (2024). Generative AI detectors and accuracy: Implications for nurses. (5), 315–319. https://www.doi.org/10.1097/CIN.0000000000001134

Molyneux J. (2023). Artificial intelligence and nursing: promise and caution. , (10), 17–19. https://doi.org/10.1097/01.NAJ.0000979068.75051.bd

Pailaha AD (2023). Impact and problems with 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., and Parvin, M.R. (2024). Artificial Intelligence in Future Nursing Care: Exploring Nurses’ Perspectives—A Descriptive Qualitative Study. , (4), e25718. https://doi.org/10.1016/j.heliyon.2024.e25718

As the nursing community continues to expand its use and understanding of AI-based research, education, and clinical care, the May 2024 issue offers insight into the event of AI in nursing. Articles include reviews, field tests, feasibility studies, and empirical studies to higher understand the technology. Additionally, the research included on this issue comes from clinical and academic settings.

The article, entitled, provides an evidence of data-centric machine learning in nursing and explores the differences between this method and other approaches, akin to model-centric machine learning. We are pleased to supply skilled development credit to nurses for this selection. Another article on this issue, explores fundamental elements of foundational models, generative AI, and enormous language models that may help readers learn to navigate the emerging role of AI in our field.

This issue on AI also includes the usage of ensemble-based machine learning to develop a predictive model of survival for out-of-hospital cardiac arrest patients; a review of the scope of using AI to discover optimal practice patterns; and a field study of the event of a teaching assistant system for nursing students. We’re excited to share this special edition with you!