The Diabeo Software Enabling Individualized Insulin Dose Adjustments Combined With Telemedicine Support Improves HbA1c in Poorly Controlled Type 1 Diabetic Patients

Charpentier, G.; Benhamou, Pierre‐Yves; Dardari, D.; Clergeot, Annie; Franc, Sylvia; Schaepelynck-Bélicar, P.; Catargi, Bogdan; Melki, V.; Chaillous, Lucy; Farret, Anne; Bosson, Jean‐Luc; Penfornis, A.

doi:10.2337/dc10-1259

Cited by 280 publications

(312 citation statements)

References 15 publications

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“…8,9 Using mobile phones as a communications tool for people with diabetes has been shown effective, 10 and using mobile phone technology in conjunction with telemedical support improves HbA1c levels. 11 Given the large amount of data assembled by T1D patients and the ubiquitous nature of these devices, utilizing phones' computational power for data analysis and visualization is a natural step forward. At the Norwegian Centre for Integrated Care and Telemedicine (Tromsø, Norway), a diabetes diary known as the Few Touch Application (FTA) has been developed as a research tool for self-management intended for both T1D and type 2 diabetes (T2D) patients.…”

Section: Introductionmentioning

confidence: 99%

Mobile Phone-Based Pattern Recognition and Data Analysis for Patients with Type 1 Diabetes

Skrøvseth

Årsand

Godtliebsen

et al. 2012

Diabetes Technology & Therapeutics

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Background: Persons with type 1 diabetes who use electronic self-help tools, most commonly blood glucose meters, record a large amount of data about their personal condition. Mobile phones are powerful and ubiquitous computers that have a potential for data analysis, and the purpose of this study is to explore how self-gathered data can help users improve their blood glucose management. Subjects and Methods: Thirty patients with insulin-regulated type 1 diabetes were equipped with a mobile phone application for 3-6 months, recording blood glucose, insulin, dietary information, physical activity, and disease symptoms. The data were analyzed in terms of usage of the different modules and which data processing and visualization tools could be constructed to support the use of these data. Results: Eighteen patients (denoted ''adopters'') recorded complete data for over 80 consecutive days, up to 247 days. Among those who withdrew or did not use the application extensively, the most common reasons given were outdated or difficult-touse phone. Data analysis using period finding and scale-space trends was found to yield significant patterns for most adopters. Pattern recognition methods to predict low or high blood glucose were found to be performing poorly. Conclusions: Minimally intrusive mobile applications enable users with type 1 diabetes to record data that can provide datadriven feedback to the user, potentially providing relevant insight into their disease.

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Section: Introductionmentioning

confidence: 99%

Mobile Phone-Based Pattern Recognition and Data Analysis for Patients with Type 1 Diabetes

Skrøvseth

Årsand

Godtliebsen

et al. 2012

Diabetes Technology & Therapeutics

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“…Despite a significant improvement in HbA1c, the quality of life and self-care activities were not improved [35]. However, it may be noted that the self-care activities and quality of life do not always correlate with HbA1c in type 1 diabetic patients [36].…”

Section: Smartphone Apps For Patient Educationmentioning

confidence: 95%

Novel Health Mobile Technology as an Emerging Strategy in Diabetes Management

David¹,

Rafiullah²

2017

Case Study of Innovative Projects - Successful Real Cases

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Advances in mobile phone technology and its applications coupled with equally robust growth of telecommunication technology can serve to give patients a better access to the healthcare. More and more healthcare providers and patients started using these applications. Mobile applications are useful in handling various aspects of healthcare namely, health promotion and disease prevention, diagnosis, treatment, monitoring and supporting health services. Clinical studies evaluating mobile applications often come up with mixed results. In this chapter, application of mobile health technology or mHealth in diabetes management is presented as a case study. We have reviewed 25 articles from pubmed database that fulfilled our selection criteria which included original clinical studies that evaluated mobile health technology in the management of diabetes mellitus. Most studies (88%) reported positive outcomes after use of the mobile health applications in various aspects of diabetes treatment such as disease management, behavioural monitoring and patient education. Educational SMS were effective but inferior to Smartphone Apps or teleconsultations. User-friendliness of the systems influenced patient compliance and outcomes. Smartphone/web applications offer significant benefits for patient care, education and behavioural modifications. As providing continuous patient support would require adequate infrastructure and personnel, cost effectiveness of such interventions need to be studied.

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“…Outcome: The software proves to be noticeably effective in improving metabolic control, at low cost and no need for physician referral [22].…”

Section: Self-care In Chronic Diseasesmentioning

confidence: 99%

Mobile Health: An Efficient Service to Promote Self-care among People Introducing e-selfcare

Moghaddasi¹,

Sajjadi²,

Sm³

2016

J Health Med Inform

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Mobile health is one of the most important electronic health services which use portable, smart devices, such as the mobile phone. With a very high rate of accessibility and a relatively low cost, this type of electronic health service can be used to offer health services to people anywhere, at any time. The main objective of the current study is to introduce the mobile health as a new service for promotion of self-care in the society. The study will continue to focus on numerous medical applications of mobile phone, particularly as an efficient and cost-effective modern device for self-care.

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The Diabeo Software Enabling Individualized Insulin Dose Adjustments Combined With Telemedicine Support Improves HbA1c in Poorly Controlled Type 1 Diabetic Patients

Cited by 280 publications

References 15 publications

Mobile Phone-Based Pattern Recognition and Data Analysis for Patients with Type 1 Diabetes

Mobile Phone-Based Pattern Recognition and Data Analysis for Patients with Type 1 Diabetes

Novel Health Mobile Technology as an Emerging Strategy in Diabetes Management

Mobile Health: An Efficient Service to Promote Self-care among People Introducing e-selfcare

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