European Journal of Case Reports in Internal Medicine (Dec 2020)

First Test of an Automated Detection Platform to Identify Risk of Decompensation in Elderly Patients

  • Abrar-Ahmad Zulfiqar,
  • Orianne Vaudelle,
  • Mohamed Hajjam,
  • Dominique Letourneau,
  • Jawad Hajjam,
  • Sylvie Ervé,
  • Anna Karen Garate Escamilla,
  • Amir Hajjam,
  • Emmanuel Andrès

DOI
https://doi.org/10.12890/2020_002102

Abstract

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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.

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