Some AI solutions could create new costs or burdens for nurses even if the tools appear efficient on paper, according to researchers at Philadelphia-based University of Pennsylvania.
To successfully attain AI benefits for nurses including reduced paperwork and improved patient monitoring, hospitals and health systems must have clear standards for accountability, bias and validation, the authors wrote in the May-June edition of Nursing Outlook.
“AI implementation can introduce hidden costs and unintended consequences. Systems require training, maintenance, workflow redesign, oversight, cybersecurity protections, and continuous evaluation. In some cases, AI tools may even increase clinicians’ cognitive burden or documentation workload rather than reduce it,” Penn Nursing professors George Demiris, PhD, Antonia Villarruel, PhD, RN, and Connie Ulrich, PhD, RN, said in a May 27 Penn Leonard Davis Institute of Health Economics Q&A.
“There is also the issue of ‘algorithmic drift,’ where performance changes over time as patient populations or workflows evolve. A system that initially appears effective may require substantial ongoing adjustment and monitoring. Efficiency gains are not automatic, and healthcare organizations need realistic expectations about both costs and benefits.”
The researchers suggest teaching AI literacy in nursing school, codeveloping AI with nurses, rigorously testing AI before implementation, analyzing actual financial and workflow costs, and instituting ethical oversight and transparency requirements.
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