First Test of an Automated Detection Platform to Identify Risk of Decompensation in Elderly Patients
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...
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doaj-60c7a96c343b4a06b47634a34b64a51f2020-12-11T09:40:57ZengSMC MEDIA SRLEuropean Journal of Case Reports in Internal Medicine2284-25942020-12-0110.12890/2020_0021021718First Test of an Automated Detection Platform to Identify Risk of Decompensation in Elderly PatientsAbrar-Ahmad Zulfiqar0Orianne Vaudelle1Mohamed Hajjam2Dominique Letourneau3Jawad Hajjam4Sylvie Ervé5Anna Karen Garate Escamilla6Amir Hajjam7Emmanuel Andrès8Service de Médecine Interne, Diabète et Maladies Métaboliques de la Clinique Médicale B, Hôpitaux Universitaires de Strasbourg and Equipe EA 3072 "Mitochondrie, Stress oxydant et Protection musculaire", Faculté de Médecine, Université de Strasbourg, Strasbourg, France Predimed Technology, Schiltigheim, France Predimed Technology, Schiltigheim, France Fondation de l'Avenir pour la Recherche Médicale Appliquée, Paris, FranceCentre d'Expertise des TIC pour l'autonomie (CenTich) et Mutualité Française Anjou-Mayenne (MFAM) – Angers, Angers, France Centre d'Expertise des TIC pour l'autonomie (CenTich) et Mutualité Française Anjou-Mayenne (MFAM) – Angers, Angers, France Laboratoire IRTES-SeT, Université de Technologie de Belfort-Montbéliard (UTBM), Belfort-Montbéliard, Belfort, FranceLaboratoire IRTES-SeT, Université de Technologie de Belfort-Montbéliard (UTBM), Belfort-Montbéliard, Belfort, FranceService de Médecine Interne, Diabète et Maladies Métaboliques de la Clinique Médicale B, Hôpitaux Universitaires de Strasbourg and Equipe EA 3072 "Mitochondrie, Stress oxydant et Protection musculaire", Faculté de Médecine, Université de Strasbourg, Strasbourg, France 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.https://www.ejcrim.com/index.php/EJCRIM/article/view/2102telemonitoringgeriatric risksmypredie-platformger-e-tec study |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Abrar-Ahmad Zulfiqar Orianne Vaudelle Mohamed Hajjam Dominique Letourneau Jawad Hajjam Sylvie Ervé Anna Karen Garate Escamilla Amir Hajjam Emmanuel Andrès |
spellingShingle |
Abrar-Ahmad Zulfiqar Orianne Vaudelle Mohamed Hajjam Dominique Letourneau Jawad Hajjam Sylvie Ervé Anna Karen Garate Escamilla Amir Hajjam Emmanuel Andrès First Test of an Automated Detection Platform to Identify Risk of Decompensation in Elderly Patients European Journal of Case Reports in Internal Medicine telemonitoring geriatric risks mypredi e-platform ger-e-tec study |
author_facet |
Abrar-Ahmad Zulfiqar Orianne Vaudelle Mohamed Hajjam Dominique Letourneau Jawad Hajjam Sylvie Ervé Anna Karen Garate Escamilla Amir Hajjam Emmanuel Andrès |
author_sort |
Abrar-Ahmad Zulfiqar |
title |
First Test of an Automated Detection Platform to Identify Risk of Decompensation in Elderly Patients |
title_short |
First Test of an Automated Detection Platform to Identify Risk of Decompensation in Elderly Patients |
title_full |
First Test of an Automated Detection Platform to Identify Risk of Decompensation in Elderly Patients |
title_fullStr |
First Test of an Automated Detection Platform to Identify Risk of Decompensation in Elderly Patients |
title_full_unstemmed |
First Test of an Automated Detection Platform to Identify Risk of Decompensation in Elderly Patients |
title_sort |
first test of an automated detection platform to identify risk of decompensation in elderly patients |
publisher |
SMC MEDIA SRL |
series |
European Journal of Case Reports in Internal Medicine |
issn |
2284-2594 |
publishDate |
2020-12-01 |
description |
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. |
topic |
telemonitoring geriatric risks mypredi e-platform ger-e-tec study |
url |
https://www.ejcrim.com/index.php/EJCRIM/article/view/2102 |
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