INTELLIGENT DIGITAL FLOW: TRIAGE, PATIENT PORTAL, AND REMOTE MONITORING IN EMERGENCY AND URGENT CARE

Abstract

Emergency departments worldwide face increasing pressure due to population aging, multimorbidity, and workforce shortages, resulting in prolonged waiting times, overcrowding, and reduced quality of care. This study evaluates the impact of implementing an intelligent digital flow in emergency care, integrating AI-based digital triage, active patient communication portals, and post-discharge remote monitoring. The methodology consisted of a narrative literature review and analysis of real-world implementation cases. Findings indicate that digital triage systems achieve 88.5% specificity for predicting low-risk patients and 88.5% sensitivity for high-acuity cases, demonstrating superior accuracy compared with traditional triage. The Virtual Queue powered by predictive AI reduced patient length of stay in emergency departments by 60%. Furthermore, the integration of AI and 5G technology enables real-time data sharing between ambulances and hospital teams, supporting immediate clinical decision-making before patient arrival. Remote patient monitoring has the potential to reduce hospital readmissions by up to 76%, strengthening continuity of care. Additionally, the integration of health information systems and standardized referral and counter-referral protocols improves operational efficiency and communication across services.