Abstract

Introduction: Telemedicine is believed to be helpful in managing patients suffering from chronic diseases, in particular elderly patients with numerous accompanying conditions. This was the basis for the “GERIATRICS and e-Technology (GER-e-TEC) study”, which was an experiment involving the use of the smart MyPredi™ e-platform to automatically detect the exacerbation of geriatric syndromes. Methods: The MyPredi™ platform is connected to a medical analysis system that receives physiological data from medical sensors in real time and analyzes this data to generate (when necessary) alerts. These alerts are issued in the event that the health of a patient deteriorates due to an exacerbation of their chronic diseases. An experiment was conducted between 24 September 2019 and 24 November 2019 to test this alert system. During this time, the platform was used on patients being monitored in an internal medicine unit at the University Hospital of Strasbourg. The alerts were compiled and analyzed in terms of sensitivity, specificity, and positive and negative predictive values with respect to clinical data. The results of the experiment are provided below. Results: A total of 36 patients were monitored remotely, 21 of whom were male. The mean age of the patients was 81.4 years. The patients used the telemedicine solution for an average of 22.1 days. The telemedicine solution took a total of 147,703 measurements while monitoring the geriatric risks of the entire patient group. An average of 226 measurements were taken per patient per day. The telemedicine solution generated a total of 1611 alerts while assessing the geriatric risks of the entire patient group. For each geriatric risk, an average of 45 alerts were emitted per patient, with 16 of these alerts classified as “low”, 12 classified as “medium”, and 20 classified as “critical”. In terms of sensitivity, the results were 100% for all geriatric risks and extremely satisfactory in terms of positive and negative predictive values. In terms of survival analysis, the number of alerts had an impact on the duration of hospitalization due to decompensated heart failure, a deterioration in the general condition, and other reasons. Conclusion: The MyPredi™ telemedicine system allows the generation of automatic, non-intrusive alerts when the health of a patient deteriorates due to risks associated with geriatric syndromes.

Highlights

  • Telemedicine is believed to be helpful in managing patients suffering from chronic diseases, in particular elderly patients with numerous accompanying conditions

  • During the GER-e-TEC project, a pilot study was conducted in a hospital setting to evaluate the use of the MyPrediTM remote monitoring platform, to monitor the chronic diseases of elderly patients (hypertension, heart failure, diabetes, kidney failure, chronic obstructive pulmonary disease (COPD), etc.) and to detect the risks and disorders associated with these syndromes

  • Any patient over 65 years of age admitted to the hospital or emergency room with one or more chronic diseases was eligible for the GER-e-TEC study

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Summary

Introduction

According to the INSEE (Institut National de la Statistique et des Etudes Economiques, Paris, France) [1], 25.6% of people in France are aged 60 and over. The risks associated with the geriatric syndromes of elderly patients must be taken into consideration [3] These risks include pain, falls, constipation, dehydration, confusion, iatrogenesis, malnutrition, heart failure (HF), hypertension, diabetes, infections, bedsores, psychobehavioral disorders, etc. As far as we know, no telemedicine project to date has allowed for the monitoring and detection of all these risks In this context, we tested the MyPrediTM e-platform in an internal medicine unit. We present the results of a pilot study involving 36 elderly patients who were hospitalized with an acute disease To our knowledge, this is the very first study to use a remote monitoring platform to detect and monitor geriatric syndromes

Objective
Patients
Study Outline
Experimental Protocol
Atypical behaviors
The Remote Monitoring Platform
Parameters Evaluated and Statistical Analyses
Administrative Requirements
Results
Number of Alerts for Geriatric Syndromes and Chronic Diseases
10. Clinical Relevance of Alerts
12. Conclusions
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