Survey details and key findings

For the survey, NNU gathered responses from over 2,300 RNs and members of the organization between Jan. 18 and March 4.

In total, 40% of nurses said their employer had introduced "new devices, gadgets, and changes to the electronic health records" over the last 12 months. Half of respondents also said that their employers used algorithms based on electronic health record (EHR) data to determine patient acuity and need for nursing care.

Among these respondents, 69% said their own assessments differed from the computer-generated acuity metrics, which rely on nurses' ability to chart in real-time. According to surveyed nurses, real-time charting is unrealistic due to patient loads and chronic understaffing. The computer-generated metrics also don't account for the educational, psychosocial, or emotional needs of patients and their families.

"The result of relying on the algorithmically driven acuity measurements is that, on a daily basis, in unit after unit, we have multiple patients whose acuity is underrepresented, which means there are not enough nurses to provide optimal care in a timely manner," said Cathy Kennedy, a VP of NNU and president of the California Nurses Association.

In addition, 12% of respondents said they had seen patient handoffs, which have traditionally been completed directly between nurses, move to computer-generated reports. Among these respondents, 48% said that the automated reports did not align with their personal assessments for patient handoffs.

Twenty-nine percent of nurses in facilities using devices that captured images and sounds from patients reported not being able to change AI-generated assessments or categorizations, such as pain scores or wound assessments. Similarly, 40% of nurses in facilities where automated systems predict patient outcomes, risks for complications, and discharge needs said they were unable to modify these scores to reflect their own clinical judgment.

Overall, 60% of nurses said they don't trust their employer to consider patient safety as the most important factor when implementing AI tools. 

"While our employers argue A.I. will help us, they're using these technologies to erode our ability to practice our clinical judgment," said Aretha Morgan, an RN in emergency pediatrics at New York Presbyterian and a board member of the New York State Nurses Association. "At the core of nursing is assessment of the patient: touching, hearing, seeing, smelling, and showing comfort and compassion to build the bonds of trust. Healing our patients requires time that we are not given by our employers and so A.I. is used to justify the crisis conditions they've made us work under."

Commentary

According to Deborah Burger, president of NNU, "[t]he survey and reports from nurses across the country demonstrate that we need an immediate pause on implementing A.I. in health care settings."

"As patient advocates, it is our duty to assess the evidence in front of us and question the unfounded marketing claims that A.I. will complement our bedside skills or improve the quality of care for our patients," she added.

In addition to the survey, NNU recently published the "Nurses and Patients' Bill of Rights: Guiding Principles for AI Justice in Nursing and Health Care." The document outlines seven rights to ensure "just and safe application" of AI in healthcare settings, including:

• The right to high-quality person-to-person care
• The right to safety
• The right to privacy
• The right to transparency
• The right to exercise professional judgment
• The right to autonomy
• The right to collective advocacy for workers and their patients

"Nurses regularly embrace technology that complements our bedside skills and improves the quality of care for our patients," Burger said. "But this rush to implement untested and unregulated A.I. into care settings threatens our patients' rights to person-to-person care, and their rights to privacy, transparency, and safety."

Michelle Mahon, assistant director of nursing practice at NNU, also stressed that AI cannot replicate human intelligence, even with all the hype surrounding the technology. "AI can recognize patterns in data, but healthcare data are often incomplete or biased ... It takes experience and expertise of a human nurse to understand that data in context, identify what's missing, and holistically assess the needs of individual patients," Mahon said.

"By no means is A.I. a panacea for the systemic issues in our health care system," Burger said. "We desperately need better working conditions to bring back the 1.3 million licensed registered nurses who are choosing not to work, and from what we've seen, A.I. may make working conditions even harder as we respond to false alarms, review A.I. recommendations for errors, and feed data into applications 'learning' from nurses."

Advisory Board AI and nursing resources

For more insights into AI and nursing, check out these Advisory Board resources:

In a recent expert commentary, Advisory Board's Ali Knight outlined three ways organizations can boost nurse involvement in their AI strategy. This includes proactively addressing nurses' concerns about AI, engaging them in identifying opportunities for AI impact, and including them in evaluating and implementing potential AI solutions.

This resource outlines the top 3 concerns staff have about AI and how leaders can address them. Similarly, this expert insight explains what technology can't (or shouldn't) do for clinicians.

To understand how to leverage technology to support your clinical workforce, check out this cheat sheet on clinical workforce technology or this upcoming webinar on the imperative to use technology to empower your clinical workforce. (Firth, MedPage Today, 5/16; Bruce, Becker's Health IT, 5/16; NNU press release, 5/15; NNU Nurses and Patients' Bill of Rights, accessed 5/20)