Current Research on Telemonitoring In Patients with Diabetes Mellitus: A Short Pragmatic Narrative Review

Emmanuel Andrès
2019 Trends in Telemedicine & E-health  
This is a narrative review of remote monitoring (telemedicine) projects within the field of type 1 and type 2 diabetes, with special attention placed on telemedicine 2.0 projects and studies. Material and method: A literature search were performed using the PubMed database of US National Library of Medicine, along with Scholar Google. Textbooks on telemedicine and e-Health, from the American Diabetes Association (ADA) and the European Association for Study the Diabetes (EASD), as well as
more » ... tion from international meetings and commercial sites on the Web were used. Result: Since the beginning of the 1990's, several telemedicine projects and studies focused on type 1 and type 2 diabetes have been developed. Mainly, these projects and studies show that telemonitoring diabetic result in: improved blood glucose control; a significant reduction in HbA1c; improved patient ownership of the disease; greater patient adherence to therapeutic and hygiene-dietary measures; positive impact on co-morbidities (hypertension, weight, dyslipidemia); improved quality of life for patients; and at least good patient receptivity and accountability. To date, the magnitude of its effects remains debatable, especially with the variation in patients' characteristics (e.g. background, ability for self-management, medical condition), samples selection and approach for treatment of control groups. Over the last 5years, numerous telemedicine projects based on connected objects and new information and communication technologies (ICT) (elements defining telemedicine 2.0) have emerged or are still under development. Two examples are the DIABETe and Telesage telemonitoring project which perfectly fits within the telemedicine 2.0 framework, being the firsts to include artificial intelligence with MyPrediTM and DiabeoTM (AI). This concept makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions) and self-correction. Particular applications of AI include expert systems, speech recognition, and machine vision Trends Telemed E-Health
doi:10.31031/tteh.2019.01.000513 fatcat:wcnbjqc7qbdqvdogqr7j6bg2de