Effective nurse handover is crucial in high-pressure environments like Intensive Care Units (ICUs), where accurate communication of patient-specific information directly shapes patient care and clinical decision-making. We conducted seven interviews with ICU nurses to understand current handover practices. Preliminary findings reveal significant challenges, including high cognitive load from fragmented EMR data, the risk of technology hindering interpersonal rapport, and the loss of nuanced data during shift transitions. These issues lead to cognitive overload and information omission, particularly during fast-paced shift transitions when staff fatigue is prevalent. We explore the potential for in-situ Augmented Reality (AR) overlays and Artificial Intelligence (AI) agents to support ICU nurse handover by enabling hands-free information access, procedure guidance and documentation assistance.
Li, Mengxing, Phoebe Zhang, Jiazhou Liu, Agnes Haryanto, Kadek Ananta Satriadi, Trung Nguyen, Deval Mehta, Zerina Lokmic-Tomkins, and Tim Dwyer. 'HandovAR: Towards AR and AI Support for ICU Nurse Handover.' Paper presented at the CHI 2026 Workshop on XR for Challenging Environments: Enabling Human Performance and Agency under Stress, 2026.