Maestría en Diseño y Gestión de Procesos · 2026

Diseño de un modelo de gemelo digital para predecir la experiencia del paciente en la ruta de atención de urgencias de la Clínica Universidad de La Sabana

Emergency departments face congestion and delays that negatively affect patient experience and operational efficiency. In response to this challenge, this thesis presents the implementation of a Digital Twin (DT) for the emergency care pathway at Clínica Universidad de La Sabana, aimed at monitoring in real time the stages of the care process and supporting the prediction of compliance with the institutional standard of care time = 120 minutes for adult patients classified as Triage III. The proposed framework is based on a hybrid architecture that integrates Internet of Things (IoT) technologies, Edge Computing (EC), discrete-event simulation platforms, and Machine Learning (ML), ensuring operational synchronization between the physical environment and its digital representation. The physical sensing system consists of three fixed stations (STA1–STA3) and a wearable device (BAND), equipped with RAK19007 (base), RAK13801 (UWB), and RAK4631 (MCU + BLE) modules. The stations receive UWB signals emitted by the BAND, while ESP32 devices act as BLE–MQTT gateways to a Jetson Nano operating as an edge node and MQTT broker.