International group calls for more nursing in healthcare AI—and vice versa

The profession of nursing is something of a sleeping giant within the global village of healthcare AI, according to an interdisciplinary collaborative of health workers from North America and Europe.

Or, as the group puts it in a paper published online May 18 in the Journal of Advanced Nursing, “There is a substantial untapped and unexplored potential for nursing to contribute to the development of AI technologies for global health and humanitarian efforts.”

From that inarguable premise, lead author Charlene Esteban Ronquillo, PhD, RN, of Ryerson University in Toronto, senior author Maxim Topaz, PhD, RN, of Columbia University and 17 co-authors make a compelling case for increasing nurses’ involvement with AI.

The group’s roll call alone may be enough to render its positions influential, as the lineup reflects expertise in not only nursing practice and various aspects of AI but also biomedical ethics, implementation science, healthcare informatics and patient advocacy.

Also contributing as a co-author is Thomas Weigand, PhD, chair of the global focus group on healthcare AI convened in 2018 by the International Telecommunication Union with the WHO.

The group, named NAIL for Nursing and Artificial Intelligence Leadership Collaborative, names three top priorities guiding its vision and recommends action steps for each across four spheres—education, practice, research and leadership.

The priorities are as follows, with sample steps: 

1. Nurses must understand the relationship between data they collect and AI technology they may use.

  • Education sample step: “Nursing educational programs and continuing education should prioritize recruiting faculty with expertise in health informatics and technology development.”
  • Practice: “Nursing stakeholders need to create structures that promote a continuous discussion of the implications of AI technologies in nursing on all levels.”
  • Research: “Nursing researchers should focus on the use and impact of AI in nursing and the impacts related to workforce, clinical and patient health outcomes as well as making the AI lifecycle explainable, from AI conception to implementation.”
  • Leadership: “Nursing leaders need to have an understanding of AI technologies to be able to lead the implementation of these technologies and support clinical teams on its use.”

2. Nurses must be involved in all stages of AI, from development to implementation.

  • Education: “Nursing educators should develop advanced educational training for nurses who are interested in taking on more active and hands-on roles in the development and implementation of AI technologies in health systems.
  • Practice: “Nurses should play an active role in AI technology development and deployment in clinical settings to ensure that technology is integrated into the clinical workflows, patient and caregiver perspectives are addressed and potential unintended consequences are forecasted.”
  • Research: “Research entities and funding mechanisms needed to support the development of AI or related technologies that target nursing practice and establish programs of research in this underdeveloped field.”
  • Leadership: “Leaders should build organizational structures to afford nurses opportunities to be involved in all stages of AI creation.”

3. AI must be used to help nurses be better at what they do.

  • Education: “Nursing education programs can use virtual environments and/or simulations mirroring real case studies to study AI implications. These would focus on the provision of patient-centered and relational care while using AI technologies; assessment of patients' digital literacy and digital privacy and security as part of the informed consent process; understanding the impacts of AI technology use on practice.”
  • Practice: “All stakeholders need to ensure that AI technology should be used to help nurses allocate more time for providing preventative health recommendations to patients and patient populations.”
  • Research: “Nursing researchers need to study what types of AI technologies are needed to augment nursing critical-thinking and care skills.”
  • Leadership: “Health systems leaders and nursing leadership need to ensure that achieving economic efficiencies is not the sole driver of AI implementation; AI technologies can be used to help nurses with specific skill-based tasks to afford more time for higher-order cognitive tasks and critical thinking.”

The authors conclude:

AI technologies will change the profession of nursing. AI technologies can serve as important tools to support the contribution of nurses towards higher level aims of evolving the nursing profession and improving population and global health. … AI has the potential to enhance and extend nursing capabilities. In return, nursing has much to contribute to the development of AI systems that leverage nurses' strengths and expertise in relational practice and patient advocacy, toward the development of AI that considers patients with a more holistic view.

The paper is available in full for free.

Dave Pearson

Dave P. has worked in journalism, marketing and public relations for more than 30 years, frequently concentrating on hospitals, healthcare technology and Catholic communications. He has also specialized in fundraising communications, ghostwriting for CEOs of local, national and global charities, nonprofits and foundations.

Around the web

The tirzepatide shortage that first began in 2022 has been resolved. Drug companies distributing compounded versions of the popular drug now have two to three more months to distribute their remaining supply.

The 24 members of the House Task Force on AI—12 reps from each party—have posted a 253-page report detailing their bipartisan vision for encouraging innovation while minimizing risks. 

Merck sent Hansoh Pharma, a Chinese biopharmaceutical company, an upfront payment of $112 million to license a new investigational GLP-1 receptor agonist. There could be many more payments to come if certain milestones are met.