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AI-Augmented Clinical Handoff Systems: Enhancing Safety and Continuity in Healthcare Transitions
0
Zitationen
1
Autoren
2025
Jahr
Abstract
Clinical handoff transitions among healthcare professionals represent high-risk points where breakdowns in communication often lead to harmful medical mistakes and patient harm. Standard handover routines exhibit high levels of variability, are not standardized, and are loaded with high cognitive burdens for clinicians who are working with complex patient groups in high-acuity areas. The convergence of artificial intelligence technologies with electronic health record systems holds transformative promise for improving handoff quality through automated multimodal patient data synthesis, structured communication summarization based on established guidelines, and knowledge-based identification of clinical risks that need to be addressed immediately. AI-facilitated handoff structures use natural language processing algorithms to cull applicable information from narrative scientific records, predictive analytics to signal deterioration styles and protection problems, and interoperability requirements to facilitate unfettered deployment within numerous healthcare data technology infrastructures. Effective implementation requires human-focused design concepts that situate artificial intelligence as assistive support and not as individual choice-making authority, retaining clinician judgment and minimizing documentation burden and information synthesis complexity. Governance models want to fulfill transparency wishes, ensure privacy protections, ensure audit trails, and cope with algorithmic bias in order to provide honest overall performance across patient populations. Combining sophisticated machine learning capabilities with systematic clinical verbal exchange protocols is a primary breakthrough for patient protection infrastructure, offering measurable gains in data completeness, handoff quality, and provider confidence at handoff factors without sacrificing human components of medical judgment and interpersonal communication.
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