A.A. Zulfiqar1,2, A. Hajjam3, B. Gény2, S. Talha2,4, M. Hajjam5, J. Hajjam6, S. Ervé6, D. Letourneau7, E. Andrès2,8
1. Department of Geriatrics, University Hospital of Rouen, France; 2. Research Unit EA 3072 «Mitochondrie, Stress oxydant et Protection musculaire», Faculté de Médecine de Strasbourg, Université de Strasbourg (UdS), 4 rue Kirschleger, 67091 Strasbourg, France; 3. Research Unit EA 4662 «Nanomédecine, Imagerie, Thérapeutiques», Université de Technologie de Belfort-Montbéliard (UTBM), Belfort-Montbéliard, France; 4. Service de Physiologie et d’Explorations fonctionnelles, Hôpitaux Universitaires de Strasbourg (HUS), 1, porte de l’Hôpital, 67091 Strasbourg cedex, France; 5. PREDIMED Technology, Mulhouse, France; 6. Centre d’expertise des Technologies de l’Information et de la Communication pour l’autonomie (CenTich) et Mutualité Française Anjou-Mayenne (MFAM), Angers, France; 7. Fondation de l’Avenir pour la Recherche Médicale Appliquée, 75015 Paris, France; 8. Department of Internal Medicine, Diabetes, University Hospital of Strasbourg, 1, porte de l’Hôpital, 67091 Strasbourg cedex, France. Corresponding author: A.A. Zulfiqar, Department of Geriatrics, University Hospital of Rouen, France; email@example.com
Jour Nursing Home Res 2019;5:20
Published online Februay 19, 2019, http://dx.doi.org/10.14283/jnhrs.2019.3
To the Editor,
Year on year, the number of patients in the emergency departments from nursing homes continues to grow. It is necessary to provide tools to health care teams for these nursing homes, such as assistance in the prevention of decompensation of some geriatric syndromes.
The aim of the GER-e-TEC™ project is to study the contribution of telemonitoring residents in nursing homes of Rouen University Hospital, with a structuring and recording of medical care in order to avoid situations of acute decompensation and complication of geriatric risks.
The objective of the project is to experiment with recorded personalized medical monitoring of the residents of the Rouen University Hospital nursing homes using the E-care intelligent telemedicine platform, winner of the Investissements d’Avenir in 2012 and then of the Fondation d’Avenir (Future Foundation) in 2015 and 2017. The latter assists caregivers by automating the processing of information from sensors and from questionnaires in order to detect and make an early diagnosis of medical risk situations. E-care will provide personalized care for the main geriatric risks, to avoid the occurrence of an acute decompensation factor in the elderly patient. The information collected will be supplemented by codified therapeutic management, following international recommendations, directly usable in nursing homes. The E-care platform uses an intelligent algorithm to process the data and generate alerts based on medical knowledge of the pathologies treated and modeled by ontologies. The general principle adopted by this platform is the anticipation of decompensation through the detection of warning signs that ultimately lead to hospitalization. The E-care platform was tested at the Strasbourg University Hospital from 2013 to 2014 and then in homes in 2015. It is currently deployed in the PRADO-INCADO project in Strasbourg, a collaborative project between the Strasbourg University Hospital, the Bas-Rhin Medical Insurance and the Grand-Est Regional Health Agency to monitor heart failure patients where they live. This platform is in the process of being certified as an EU Medical Device. In addition, the DIABETe platform has just been accredited by the Alsace BioValley competitiveness and innovation centre (1-2-3-4)
The collection of information by the platform will increase knowledge of the patients and provide a particularly effective tool for transmission between nursing staff in nursing homes, thus allowing a continuity of care. This information collection will also allow the extraction of markers to improve the early detection of any decompensation and thus improve patient monitoring and reduce the number of hospitalizations. The platform will also provide any paramedical and medical health professional with the resident’s geriatric data, which will be updated regularly, including the anthropometric, nutritional, cognitive and iatrogenic data, constituting a real illustration integrated into the electronic platform of the standardized gerontological evaluation, thanks to simple and non-time-consuming measures. Geriatric risks will include the risk of falling, constipation, dehydration, confusion, iatrogenicity, undernutrition, heart failure, diabetes, infections and bedsores.
This study will start in January 2019.
Conflict of Interest: None
1. Andres E, Talha S, Hajjam M, Hajjam J , Erve S, Hajjam A. Telemedicine to Monitor Elderly Patients with Chronic Diseases, with a Special Focus on Patients with Chronic Heart Failure. J Gerontol Geriatr Res 5: 311. doi:10.4172/2167-7182.1000311, 2016
2. Benmimoune L, Hajjam A, Ghodous P, Andres E, Talha S, Hajjam M. Ontology-Based Information Gathering System for Patients with Chronic Diseases: Lifestyle Questionnaire Design. In Progress in Artificial Intelligence, Vol. 9273 of Lecture Notes in Artificial Intelligence, pp 110-115, ISBN: 978-3-319-23485-4. ISSN: 0302- 9743. DOI: 10.1007/978-3-319-23485-4, 2015
3. Andres E, Talha S, Hajjam A, Hajjam M, Keller O, Erve S, Hajjam J. Déploiement d’un système de détection automatisé des situations à risque de décompensation de comorbidités, Congrés annuel de la SFU, CNIT – Paris La Défense, 2015.
4. Andrès E, Talha S, Hajjam M, Hajjam J, Ervé S, Hajjam A. Experimentation of 2.0 telemedicine in elderly patients with chronic heart failure: A study prospective in 175 patients. Eur J Intern Med. 2018 Mar 7. pii: S0953-6205(18)30082-7. doi: 10.1016/j.ejim.2018.02.022.