First test of an automated detection platform to identify risk of decompensation in elderly patients

Abstract

Introduction: We tested the MyPrediTM e-platform which is dedicated to the automated, intelligent detection of situations posing a risk of decompensation in geriatric patients. Objective: The goal was to validate the technological choices, to consolidate the system and to test the robustness of the MyPrediTM e-platform through daily use. Results: The telemedicine solution took 3,552 measurements for a hospitalized patient during her stay, with an average of 237 measurements per day, and issued 32 alerts, with an average of 2 alerts per day. The main risk was heart failure which generated the most alerts (n=13). The platform had 100% sensitivity for all geriatric risks, and had very satisfactory positive and negative predictive values. Conclusion: The present experiment validates the technological choices, the tools and the solutions developed.