From Near Miss to Collective Learning: Team-Based Learning as a Structured Debriefing Tool for Expert Nurses

Abstract

Introduction. Near misses are intercepted adverse events offering critical opportunities for organizational learning. Although nurses identify approximately 41% of near misses, reporting rates remain low (52.4%) due to fear of consequences, punitive culture, and excessive workload. Structured clinical debriefing is essential to transform these events into shared learning and to support nurses affected by the second victim phenomenon.

Methods. A TBL-based debriefing model was designed for teams of 5–7 expert nurses, structured in five phases: (1) pre-session preparation with real clinical cases; (2) individual and team Readiness Assurance Testing (iRAT/tRAT); (3) mini-lecture targeting identified knowledge gaps; (4) application activity (tAPP following the 4S principles), in which teams reconstruct event chronology, identify contributing factors, analyze error-intercepting barriers, process emotional responses, and define corrective actions; (5) structured peer evaluation to foster accountability.

Results. The model is expected to promote greater active participation, more effective identification of systemic causes, and reduced psychological impact on second victims, compared to unstructured debriefing.

Discussion. Reframing post-event debriefing through TBL logic represents an innovative strategy integrating patient safety, organizational learning, and professional well-being. Empirical validation in high-complexity hospital settings is warranted.