As patients increasingly turn to AI tools to interpret their health data, nurses are encountering new challenges at the bedside, according to a March case study in Nursing Outlook.
The paper describes a chemotherapy patient who used ChatGPT to interpret her lab results before an infusion appointment, creating confusion when the AI-generated explanation conflicted with clinical evidence.
To guide these interactions, the authors propose nurse-led communication protocols, including a patient-level framework — Ask, Balance, Clarify, Document — to help clinicians address AI-derived information during care discussions. The study emphasizes the need for stronger AI literacy among nurses and greater transparency around algorithmic outputs used by patients.
The researchers — from Plainsboro Township, N.J.-based Penn Medicine Princeton Medical Center and Durham, N.C.-based Duke University School of Nursing — also call for health systems and nursing programs to integrate AI ethics, bias mitigation and governance into education and organizational policies.
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