Needs assessment and development of an EMR-integrated AI system to enhance nursing handover: NurSync

ObjectiveThis study aimed to develop an EMR-integrated, AI-based nursing handover system (NurSync) through a needs assessment and system development process, as a first step toward improving handover efficiency, reducing documentation burden, and enhancing communication accuracy.MethodsA mixed-methods design was used. Surveys and focus group interviews with nine shift-working nurses identified challenges in handovers and EMR use. These findings guided the development of NurSync, a dual web-mobile system based on the PASS-BAR protocol and a large language model trained on 17 nursing record types.ResultsParticipants reported fragmented EMR structures, repetitive manual documentation, and ambiguity in handover scope. NurSync addressed these by automatically classifying nursing data into four structured categories, enabling real-time access and reducing redundancy.ConclusionNurSync was developed as a development and feasibility study integrating AI summarization with EMR data to support handover accuracy, efficiency, and consistency. Its structured design and dual-platform interface show promise for supporting clinical decision-making and communication, pending empirical validation in future studies.