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Virtual A to E Simulation Platform

ARTIFICIAL INTELLIGENCE · SIMULATION TRAINING · WEB & APP Virtual A to E Simulation Platform AI-powered ABCDE clinical simulation · Imperial London PATIENT MONITOR LIVE HR 99 bpm SpO2 89% NIBP 138 / 82 A Assessment Question 1 of 7 On approaching the patient, what is your first assessment in the A-to-E approach? A. Check blood pressure immediately B. Assess the airway

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Artificial Intelligence · Simulation Training · Web & App

Virtual A to E Simulation Platform

Prototype developed February 2026 · Imperial London, Faculty of Medicine

Overview

The Virtual A to E Simulation Platform is an AI-powered browser-based clinical simulation tool designed to help medical students practise the ABCDE (Airway, Breathing, Circulation, Disability, Exposure) assessment approach. Developed as a proof-of-concept for the ACE Simulation Programme module beginning in the 2025–26 academic year at Imperial London, the platform immerses students in realistic ward scenarios where they must assess and manage acutely unwell patients. The simulation features SBAR handover from a nurse, interactive bedside assessment, a dynamic patient monitor with live waveforms, and an AI-powered debrief on completion.

Project at a Glance

Status Proof of Concept — Prototype (February 2026)
Module ACE Simulation Programme, Faculty of Medicine, Imperial London
Platform interactive-sim.vercel.app
Technology React, TypeScript, Vercel, Claude AI (Anthropic), OpenAI API
Scenarios Chest Pain / ACS (POC); 6 additional scenarios planned
Partners Imperial London · Imperial Healthcare NHS Trust · Croydon NHS

Technology & Approach

The simulation opens with a nurse delivering a structured SBAR (Situation, Background, Assessment, Recommendation) handover, giving students the clinical context before they approach the patient. Students then work through each element of the ABCDE assessment, answering multiple-choice questions and making clinical decisions at each stage. A dynamic patient monitor displays live ECG and SpO₂ waveforms that respond to the student’s actions, reinforcing the connection between clinical decisions and patient outcome. On completion, an AI-driven debrief reviews the student’s performance and provides targeted feedback.

“The nurse-to-doctor SBAR handover at the start felt authentic and worked really well.”

— Teaching Fellow feedback, February 2026

Partners & Collaborators

Imperial — Adrian Cowell (Innovation Lead, Faculty of Medicine) and Emma Blyth (ACE Programme Lead). Clinical Lead — Dr Omid Halse (Imperial Healthcare NHS Trust), who led clinical scenario design and review throughout the pilot. Additional clinical input was provided during early development by two clinicians who have since moved on from their respective posts. The project was developed as a rapid prototype to test the feasibility of AI-driven simulation for undergraduate clinical skills training.

Impact & Next Steps

The proof-of-concept was demonstrated to teaching fellows in February 2026 and received positive feedback on realism, particularly around the SBAR handover, the dynamic patient monitor, and the AI debrief. The initial pilot has now concluded. The platform received encouraging feedback and demonstrated clear feasibility. Should there be further interest from faculty or the wider programme, the project could be developed further — expanding clinical scenarios, refining the UX, and running a broader cohort evaluation.

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