Designing mobile support for glycemic control in patients with diabetes

Harris, Lynne T.; Tufano, James T.; Le, Tung Thanh; Rees, Courtney; Lewis, Ginny; Evert, Alison B.; Flowers, Jan; Collins, Carol; Hoath, James; Hirsch, Irl B.; Goldberg, Harold I.; Ralston, James D.

doi:10.1016/j.jbi.2010.05.004

Cited by 50 publications

(36 citation statements)

References 8 publications

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“…7 Numerous tools using mobile technology to support patients with diabetes exist, either alone or in combination with online services. 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.…”

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 Among those who withdrew or did not use the application extensively, the most common reasons given were outdated or difficult-touse phone.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

View full text Add to dashboard Cite

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“…Meanwhile, the smartphone can provide a lot of self-detecting methods: GPS positioning and gravity sensing technology to track elderly patients and provide timely feedback to medical staff [35]. the electrocardiogram, the blood glucose meter and the blood pressure meter connected through bluetooth can automatically upload the healthrelated data [36][37][38]. With the progress of technology, motion capture devices may also be applied in tele-rehabilitation.…”

Section: Discussionmentioning

confidence: 99%

The Effectiveness and Safety of Utilizing Mobile Phone–Based Programs for Rehabilitation After Lumbar Spinal Surgery: Multicenter, Prospective Randomized Controlled Trial (Preprint)

Hou¹,

Yang²,

Yang³

et al. 2018

Preprint

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Background:Rehabilitation is very important for postoperative patients with low back pain. However, the promotion of traditional clinic-based program is limited in developing countries like China, due to the maldistribution of medical resources. Smartphones may be a potential substitute for those who have no access to traditional rehabilitation. Objective:The aim of this study was to examine the efficacy of a smartphone based rehabilitation system in patients accepted lumbar spinal operation. Methods:Postoperative patients with low back pain were recruited and randomized to rehabilitation treatment provide by smartphone based e-health program (EH) or usual care treatment (UC) as control group. Primary outcomes were function and pain status assessed by Oswestry Disability Index (ODI) and visual analogue scale (VAS). Secondary outcomes were general mental health and life status (Likert scales, EQ-5D and SF-36). All the patients were assessed pre-operatively and then at 3, 6, 12 and 24 months post-operatively. ResultsA total of 168 of the 863 eligible patients were included and randomized in this study. The analysis showed that the improvement in EH group was superior to UC group at 24 months postoperatively (mean difference: ODI 7.02, SD 3.1, P<0.05; VAS 7.59, SD 3.42, P<0.05). No significant difference of primary outcomes was found at the other time points. Subgroup analysis showed that the improvements of the primary outcomes were more significant in those considered as high compliance in the EH group throughout the trial, compared with the UC group at 6, 12 and 24 months. Conclusion:This research demonstrated that E-health, a smart phone based tele-rehabilitation system can be an effective rehabilitation tool in self-management for postoperative patient with low back pain.The effectiveness of E-health was more evident in high adherent participants. Still, more researches are needed to understand factors associated with patients' adherence.Trial Registration: Chinese clinical trial registry, ChiCTR-TRC-13003314,

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“…En el estudio de Harris et al (26), uno de los hallazgos importantes en el diseño del sistema móvil para apoyar a los pacientes con diabetes incluye el hecho de permitir que los pacientes se conecten con sus proveedores de salud y que se obtenga el registro de datos del usuario de forma temprana y frecuente.…”

Section: Discussionunclassified

Aspectos importantes a incorporar en una aplicación móvil para la adherencia al tratamiento de la diabetes mellitus tipo 2 en Costa Rica según pacientes y profesionales de salud

Leiva

Solera

Calvo

et al. 2017

Perspect Nutr Humana

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Cómo citar este artículo: Porras Y, Richmond D, García MF, Jensen ML. Aspectos importantes a incorporar en una aplicación móvil para la adherencia al tratamiento de la diabetes mellitus tipo 2 en Costa Rica según pacientes y profesionales de salud. Perspect Nutr Humana. 2016;18:155-70. DOI:10.17533/udea.penh.v18n2a03 DOI:10.17533/udea.penh.v18n2a03 ResumenAntecedentes: la diabetes mellitus (DM) afecta al 12,8 % de los costarricenses. Recientemente, se ha presentado en Costa Rica un auge en el uso de tecnología móvil que permite innovar en el campo de aplicaciones móviles para la diabétes mellitus tipo 2 (DM2). Objetivo: explorar las perspectivas de pacientes y profesionales de la salud sobre los aspectos que podría contener una aplicación móvil para apoyar la adherencia del tratamiento en pacientes con DM2 en Costa Rica. Materiales y métodos: se utilizó un enfoque cualitativo para explorar la perspectiva de los participantes respecto al diseño de una aplicación móvil para DM2. Se aplicaron entrevistas semiestructuradas y grupos focales a 16 pacientes con DM2; y entrevistas semiestructuradas a 12 profesionales en salud (nutricionistas, enfermeras y médicos endocrinólogos). Resultados: solo dos pacientes habían utilizado una aplicación móvil para la DM2, y dos profesionales han recomendado su uso. Ambos grupos tienen intención de utilizar esta herramienta. La función de común interés es el registro de glucemia, aunque también se mencionaron otras. Los profesionales recomiendan supervisión continua en el uso de estas aplicaciones móviles. Conclusiones: los posibles usuarios brindan información valiosa con respecto a sus necesidades y expectativas de una aplicación móvil para DM2 para Costa Rica. La sencillez y el hecho de ser una aplicación móvil adaptada a Costa Rica son las características deseables más mencionadas. This study aimed to explore participants' perspectives related to the design of a mobile application to support T2DM care in Costa Rica. Materials and Methods: A qualitative design was used to explore participants' perspectives. Focus groups and semi-structured interviews were conducted with 16 T2DM patients, and semi-structured interviews were held with 12 healthcare professionals (nutritionists, nurses and medical doctors). Results: Only two patients had ever used an app for T2DM care, and only two professionals had previously recommended the use of these mobile applications. Both groups were willing to use these mobile applications. The most common function for which both groups showed interest was the record of blood glucose, but other functions were also mentioned. Healthcare professionals recommended continuous professional supervision in the use of these mobile applications. Conclusions: Potential mobile application users provide valuable insight regarding their needs and expectations for a T2DM care mobile application. Simplicity and being culturally adapted to Costa Rica are the most desirable mobile application features mentioned by the sample.

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Designing mobile support for glycemic control in patients with diabetes

Cited by 50 publications

References 8 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

The Effectiveness and Safety of Utilizing Mobile Phone–Based Programs for Rehabilitation After Lumbar Spinal Surgery: Multicenter, Prospective Randomized Controlled Trial (Preprint)

Aspectos importantes a incorporar en una aplicación móvil para la adherencia al tratamiento de la diabetes mellitus tipo 2 en Costa Rica según pacientes y profesionales de salud

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