Matter for Discussion: The evolution of AI in health care

Whilst its application in health care is relatively new, the concept of artificial intelligence (AI) dates back to the 1950s. Concepts such as machine learning (ML) e.g. facial recognition on mobile phones and natural language processing (NLP) e.g. predictive text, emerged more recently in the 1990s(O’Connor et al., 2023)

Although AI such as internet search engines, intelligent navigation systems and personal assistants (Alexa, Siri) are now common in modern daily life, there is still a fear around its application in health care. This may be a fear of causing patient harm or that new technology will make roles redundant (Aronson, 2022).

However, with the right application, AI has the potential to support the nursing workforce by providing real-time decision support, reducing time spent on administrative tasks, optimising workflows and improving patient outcomes. (Martinez-Ortigosa et al., 2023). In a report by The Health Foundation (Hardie et al., 2021), it was identified that nurses who had more exposure and understanding of AI and its applications had a more positive impression of how this technology can benefit modern health care.

The aim of this discussion is to get the nursing workforce debating AI and how it will impact our work. The Moravec Paradox theory, whereby tasks that are easy for humans yet difficult for machines (such as empathy), and tasks that are difficult for humans yet easy for machines (such as large-scale data analysis) (Arora, 2023) can demonstrate what AI use could mean in practice, and how we can aim to alleviate fears and identify opportunities.

This discussion will also touch on the ethics and sustainability benefits of AI and the role that nursing plays in policy development and preparing patients and society for the change.

AI is only as good as the quality of data that it is provided with, and nurses play a vital role in collecting data for this purpose. Nurses are also best placed to advocate for patients and scrutinise how AI will impact on patient safety such as clinical decision support (Johnson et al., 2023). Thus, putting nursing front and centre for making AI a success transformation.

“By embracing AI, nurses, and health care institutions can harness its potential to enhance nursing practice, improve patient care, and shape the future of healthcare.” (Rony et al., 2023)

The reading list for this debate is available here.

References 

Aronson, J K (2022) When I use a word.... Too much healthcare—technology, BMJ, 378. doi.org/10.1136/bmj.o2102.

Arora, A (2023) Moravec’s paradox and the fear of Job Automation in health care, The Lancet, 402(10397), pp. 180–181. doi:10.1016/s0140-6736(23)01129-7.

Hardie T, Horton T, Willis M, Warburton W (2021) Switched on: How do we get the best out of automation and AI in health care?. Available at: https://www.health.org.uk/publications/reports/switched-on

Johnson, E A, Dudding, K M and Carrington, J M (2023) When to ERR is inhuman: An examination of the influence of artificial intelligence‐driven nursing care on patient safety, Nursing Inquiry, 31(1). doi:10.1111/nin.12583.

Martinez-Ortigosa, A et al. (2023) Applications of artificial intelligence in nursing care: A systematic review, Journal of Nursing Management, 2023, pp. 1–12. doi.org/10.1155/2023/3219127.

O’Connor S (2023) Realising the benefits of artificial intelligence for nursing practice. Nursing Times; 119: 10, 18-22.

Rony, M K, Parvin, Mst R. and Ferdousi, S (2023) Advancing Nursing Practice with Artificial Intelligence: Enhancing Preparedness for the Future, Nursing Open, 11(1). Doi.org/10.1002/nop2.2070.