Patient Safety

ECRI has named uncontrolled clinical AI the top patient safety hazard for 2025. This article explains why unchecked algorithms pose real risks at the bedside and what nurses must demand to protect patients, equity, and clinical judgment.

Christmas Eve in the ICU: when AI says 'escalate' and clinical experience says 'wait'. Every day, experienced nurses face moments where algorithms conflict with judgment. These moments of overlap reveal the true nature of human-AI collaboration and why getting them right matters for patient safety during the holidays.

Clinical AI rarely fails with alarms. It fails quietly. Small algorithmic shifts inside routine workflows move risk to the bedside, where nurses detect system drift long before leadership or governance teams notice. This article explains how hidden AI errors reshape clinical decision-making and why nurse vigilance remains the final safety net.

Bias hides in the data that shapes every diagnosis, treatment plan, and algorithm. Nurses are on the front line of spotting these blind spots. From flawed pulse oximeters to inequitable risk scores, biased data can cost lives. This post explores how bias shows up in clinical practice, real-world examples that prove the stakes, and practical steps nurses can take to protect patients and push healthcare toward fairness.