Evaluating the clinical reasoning of generative AI in palliative care: A comparison with five years of pharmacy learners

Evaluating the clinical reasoning of generative AI in palliative care: A comparison with five years of pharmacy learners 
Journal of Palliative Medicine; by Mikaila T Lane, Toluwalase A Ajayi, Kyle P Edmonds, Rabia S Atayee; 9/9/25
Context: Artificial intelligence (AI), particularly large language models (LLMs), offers the potential to augment clinical decision-making, including in palliative care pharmacy, where personalized treatment and assessments are important. 
Conclusions: While LLMs [large language models] show potential for augmenting clinical decision-making, their limitations in patient-centered care highlight the necessity of human oversight and reinforce that they cannot replace human expertise in palliative care. 
Guest Editor's Note, Drew Mihalyo, PharmD: 
Takeaway: LLMs can mimic expert-style reasoning under uncertainty, but that’s not the same as safe, compassionate bedside decisions by clinicians.
Caveat: The study bypassed some default safety guardrails; real-world use must keep protections on.
Next steps: Pilot pharmacist-in-the-loop workflows with guardrails intact; track concrete outcomes (time-to-analgesia, deprescribing quality, error interception) and require audit logs, source traceability, and bias/shift monitoring.
Bottom line: Promising adjunct, not a replacement and human oversight remains essential. Adoption at the bedside may come sooner than many expect.
I invite conversation with anyone that wants to learn more about this topic. My LinkedIn information is www.linkedin.com/in/drewmihalyo.