Nurse Leadership: Leading AI Learning

By Cynthia Plonien DNP, RN, CENP, TONL Communications Committee Chair

Artificial intelligence (AI) is revolutionizing healthcare. AI-powered tools can analyze medical images and detect subtle abnormalities missed by human eyes. AI can personalize and tailor patient treatment plans through the evaluation of multi-source data. Wearable, ingestible, and implantable medical devices can monitor a patient’s health metrics, track conditions, triage and recommend interventions. AI can even perform remote surgery through robotics (5).

AI-powered chatbots and virtual assistants can personalize patient care directly, educating patients on conditions, as well as providing advice and reminders for medications and appointments (5).

Particularly impressive are medical advances resulting from AI 3D printing of organs, skin and bones. Scientists at New Castle University have 3D printed corneas in less than 10 minutes, using a low-cost bioactive printer (3).  Researchers at Yale University have 3D printed skin made of living cells with vasculature (6).  NYU reports the use of 3D printing to create bioactive implantable bone (8).

The Pandemic of 2020 forced organizations to speed up the adoption of AI. Consequentially, administrative efficiencies are becoming streamlined and cutting costs (5). Improved processes range from insurance authorization, coding, billing, scheduling and data input to the closing of communication gaps (5).

Professionally, evidence-based decision making and dissemination of knowledge among practitioners can be enhanced with Natural Language Processing (NLP) algorithms that can extract information from clinical notes, research papers and medical literature (4).

Chat GPT is augmenting medical and nursing expertise by answering questions regarding diagnosis and treatment from reliable sources, generating summary reports from medical records and creating educational materials for patients (4) 

As AI becomes integrated into medical practices, ethical issues are emerging. Identified concerns include public policy, patient privacy, data security, bias in algorithms and the need for human interaction and oversight in decision-making (4). 

Nurse leaders—manager, educator, coach, teacher, mentor—are in unique positions of influence, educating health care providers, patients and policy makers regarding the benefits and limitations of AI.

AI is rapidly evolving, and it is imperative that nurse leaders stay on the forefront of emerging technology by participating in the development and application of AI in health care (2). Multiple professional development opportunities exist for nurse leaders to stay current with the latest developments and trends, including books, articles, podcasts, lectures, conferences, as well as discussions with interdisciplinary colleagues.   

As AI changes all aspects of the healthcare world, in addition to understanding and involvement, nurse leaders need to protect and promote the essence of nursing.

AONL (2) and ANA (1) emphasize that AI cannot replace a nurse’s critical thought, decision making, assessment skills or responsibility. Nor can it replace compassion, trust and caring, the basis of nurse-patient relationships.

The following are Goodreads recommendations on the current AI state-of-affairs, regarding its presence and potential, as well as risks:

• The AI Revolution in Medicine, GPT-4 and beyond. Authors: Lee, Goldberg and Kohane, 2023.
• Deep Tech, Demystifying the Breakthrough Technologies that will Revolutionize Everything, Author: Redmond, 2021. 

References:

 

1. ANA Center for Ethics and Human Rights. Position Statement: The Ethical Use of Artificial 2. Intelligence in Nursing Practice Effective. 2022. nursingworld.org
2. AONL. Artificial Intelligence and the Future of Nursing. https://www.aonl.org/resources/Artificial-Intelligence-and-the-Future-of-Nursing. Accessed 8/31/2023.
3. Isaacson, S, Connon, C., 3D Bioprinting of Corneal Stroma Equivalent. Experimental Eye Research. May 2018. Retrieved from https://europepmc.org/article/med/29772228. Accessed 8/30/23.
4. Lee, P., Goldbert, C. Kohane, I. The AI Revolution in Medicine: GPT-4 and Beyond. Pearson Education, Inc. 2023.
5. Redman, E. Deep Tech. Deep Tech Press (2021)
6. Spero, M. Printing Skin: Generating Multilayered Vascularized Human Skin Graphs. Yale Scientific. March 2020. Retrieved from https://www.yalescientific.org/2020/03/printing-skin-generating-multilayered-vascularized-human-skin-grafts/ Accessed 8/30/23.
7. Topol, E. Deep Medicine. Hatchette Book Group, Inc. 2019.
8. Tovar, N., Lukasz, W., Atria, P., Sobieraj, M., Bowers, M, Lopez, C., Cronstein, & Coelho, P. Form and Functional Repair of Long Bone Using 3D Printed Bioactive Scaffolds. Journal of Tissue Engineering and Regenerative Medicine, 2018; DOI: 10.1002/term.2733