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Modeling the Clinical Reasoning Workflow: A Dynamic, Time-Aware CDSS for the Emergency Department
Chaeyeon Park1, Sanga Ahn1, Hansol Chang1,2
1Dept. of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea.
Abstract:
Emergency Departments (ED) require rapid differentiation of time-sensitive critical conditions. We present a dynamic Clinical Decision Support System (CDSS) utilizing a Time-Aware Retrieval-Augmented Generation (RAG) framework. In a retrospective pilot study of 70 cases (Aortic Dissection, MI, Stroke, and Trauma Controls), the system's Top-1 diagnostic accuracy significantly improved from 69.5% (triage) to 86.7% (discharge). This validates the system's capability to integrate evolving FHIR data with clinical guidelines to reduce the diagnostic uncertainty.
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