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Potential uses of AI for perioperative nursing handoffs: a qualitative study.

Objective: Situational awareness and anticipatory guidance for nurses receiving a patient after surgery are key to patient safety. Little work has defined the role of artificial intelligence (AI) to support these functions during nursing handoff communication or patient assessment. We used interviews and direct observations to better understand how AI could work in this context. Materials and Methods: 58 handoffs were observed of patients entering and leaving the post-anesthesia care unit at a single center. 11 nurses participated in semi-structured interviews. Mixed inductive-deductive thematic analysis extracted major themes and subthemes around roles for AI supporting postoperative nursing. Results: Four themes emerged from the interviews: (1) Nurse understanding of patient condition guides care decisions, (2) Handoffs are important to nurse situational awareness; problem focus and information transfer may be improved by AI, (3) AI may augment nurse care decision making and team communication, (4) User experience and information overload are likely barriers to using AI. Key subthemes included that AI-identified problems would be discussed at handoff and team communications, that AI-estimated elevated risks would trigger patient re-evaluation, and that AI-identified important data may be a valuable addition to nursing assessment. Discussion and Conclusion: Most research on postoperative handoff communication relies on structured checklists. Our results suggest that properly designed AI tools might facilitate postoperative handoff communication for nurses by identifying elevated risks faced by a specific patient, triggering discussion on those topics.