Digital Diabetes Management Application Improves Glycemic Outcomes in People With Type 1 and Type 2 Diabetes (original) (raw)
Related papers
2019
Background Technology has long been used to carry out self-management as well as to improve adherence to treatment in people with diabetes. However, most technology-based apps do not meet the basic requirements for engaging patients. Objective This study aimed to evaluate the effect of use frequency of a diabetes management app on glycemic control. Methods Overall, 2 analyses were performed. The first consisted of an examination of the reduction of blood glucose (BG) mean, using a randomly selected group of 211 users of the SocialDiabetes app (SDA). BG levels at baseline, month 3, and month 6 were calculated using the intercept of a regression model based on data from months 1, 4, and 7, respectively. In the second analysis, the impact of low and high BG risk was examined. A total of 2692 users logging SDA ≥5 days/month for ≥6 months were analyzed. The highest quartile regarding low blood glucose index (LBGI) and high blood glucose index (HBGI) at baseline (t1) was selected (n=74 fo...
2018
Background: Technology has long been used to carry out self-management as well as to improve adherence to treatment in people with diabetes. However, most technology-based apps do not meet the basic requirements for engaging patients. Objective: This study aimed to evaluate the effect of use frequency of a diabetes management app on glycemic control. Methods: Overall, 2 analyses were performed. The first consisted of an examination of the reduction of blood glucose (BG) mean, using a randomly selected group of 211 users of the SocialDiabetes app (SDA). BG levels at baseline, month 3, and month 6 were calculated using the intercept of a regression model based on data from months 1, 4, and 7, respectively. In the second analysis, the impact of low and high BG risk was examined. A total of 2692 users logging SDA ≥5 days/month for ≥6 months were analyzed. The highest quartile regarding low blood glucose index (LBGI) and high blood glucose index (HBGI) at baseline (t1) was selected (n=74 for group A; n=440 for group B). Changes in HBGI and LBGI at month 6 (t2) were analyzed. Results: For analysis 1, baseline BG results for type 1 diabetes mellitus (T1DM) groups A and B were 213.61 (SD 31.57) mg/dL and 206.43 (SD 18.65) mg/dL, respectively, which decreased at month 6 to 175.15 (SD 37.88) mg/dL and 180.6 (SD 40.47) mg/dL, respectively. For type 2 diabetes mellitus (T2DM), baseline BG was 218.77 (SD 40.18) mg/dL and 232.55 (SD 46.78) mg/dL, respectively, which decreased at month 6 to 160.51 (SD 39.32) mg/dL and 173.14 (SD 52.81) mg/dL for groups A and B, respectively. This represents a reduction of estimated A 1c (eA 1c) of approximately 1.3% (P<.001) and 0.9% (P=.001) for T1DM groups A and B, respectively, and 2% (P<.001) for both A and B T2DM groups, respectively. For analysis 2, T1DM baseline LBGI values for groups A and B were 5.2 (SD 3.9) and 4.4 (SD 2.3), respectively, which decreased at t2 to 3.4 (SD 3.3) and 3.4 (SD 1.9), respectively; this was a reduction of 34.6% (P=.005) and 22.7% (P=.02), respectively. Baseline HBGI values for groups A and B were 12.6 (SD 4.3) and 10.6 (SD 4.03), respectively, which decreased at t2 to 9.0 (SD 6.5) and 8.6 (SD 4.7), respectively; this was a reduction of 30% (P=.001) and 22% (P=.003), respectively. Conclusions: A significant reduction in BG was found in all groups, independent of the use frequency of the app. Better outcomes were found for T2DM patients. A significant reduction in LBGI and HBGI was found in all groups, regardless of the use frequency of the app. LBGI and HBGI indices of both groups tend to have similar values after 6 months of app use.
Designing mobile support for glycemic control in patients with diabetes
Journal of Biomedical Informatics, 2010
We assessed the feasibility and acceptability of using mobile phones as part of an existing Web-based system for collaboration between patients with diabetes and a primary care team. In design sessions, we tested mobile wireless glucose meter uploads and two approaches to mobile phone-based feedback on glycemic control. Mobile glucose meter uploads combined with graphical and tabular data feedback were the most desirable system features tested. Participants had a mixture of positive and negative reactions to an automated and tailored messaging feedback system for self-management support. Participants saw value in the mobile system as an adjunct to the Web-based program and traditional office-based care. Mobile diabetes management systems may represent one strategy to improve the quality of diabetes care.
BMC Medical Informatics and Decision Making, 2016
Background: Management of diabetes through improved glycemic control and risk factor modification can help prevent long-term complications. Much diabetes management is self-management, in which healthcare providers play a supporting role. Well-designed e-Health solutions targeting behavior change can improve a range of measures, including glycemic control, perceived health, and a reduction in hospitalizations. Methods: The primary objective of this study is to evaluate if a mobile application designed to improve self-management among patients with type 2 diabetes (T2DM) improves glycemic control compared to usual care. The secondary objectives are to determine the effects on patient experience and health system costs; evaluate how and why the intervention worked as observed; and gain insight into considerations for system-wide scale-up. This pragmatic, randomized, wait-list-control trial will recruit adult participants from three Diabetes Education Programs in Ontario, Canada. The primary outcome is glycemic control (measured by HbA1c). Secondary outcomes include patient-reported outcomes and patient-reported experience measures, health system utilization, and intervention usability. The primary outcome will be analyzed using an ANCOVA, with continuous secondary outcomes analyzed using Poisson regression. Direct observations will be conducted of the implementation and application-specific training sessions provided to each site. Semi-structured interviews will be conducted with participants, healthcare providers, organizational leaders, and system stakeholders as part of the embedded process evaluation. Thematic analysis will be applied to the qualitative data in order to describe the relationships between (a) key contextual factors, (b) the mechanisms by which they effect the implementation of the intervention, and (c) the impact on the outcomes of the intervention, according to the principles of Realist Evaluation. Discussion: The use of mobile health and virtual tools is on the rise in health care, but the evidence of their effectiveness is mixed and their evaluation is often lacking key contextual data. Results from this study will provide much needed information about the clinical and cost-effectiveness of a mobile application to improve diabetes self-management. The process evaluation will provide valuable insight into the contextual factors that influence the application effectiveness, which will inform the potential for adoption and scale.
Health Internet Technology for Chronic Conditions: Review of Diabetes Management Apps (Preprint)
2019
BACKGROUND Mobile health (mHealth) smartphone apps have shown promise in the self-management of chronic disease. In today’s oversaturated health app market, selection criteria that consumers are employing to choose mHealth apps for disease self-management are of paramount importance. App quality is critical in monitoring disease controls but is often linked to consumer popularity rather than clinical recommendations of effectiveness in disease management. Management of key disease variances can be performed through these apps to increase patient engagement in disease self-management. This paper provides a comprehensive review of features found in mHealth apps frequently used in the self- management of diabetes. OBJECTIVE The purpose of this study was to review features of frequently used and high consumer-rated mHealth apps used in the self-management of diabetes. This study aimed to highlight key features of consumer-favored mHealth apps used in the self-management of diabetes. MET...
Rapid Evidence Review of Mobile Applications for Self-management of Diabetes
Journal of general internal medicine, 2018
Patients with diabetes lack information on which commercially available applications (apps) improve diabetes-related outcomes. We conducted a rapid evidence review to examine features, clinical efficacy, and usability of apps for self-management of type 1 and type 2 diabetes in adults. Ovid/Medline and the Cochrane Database of Systematic Reviews were searched for systematic reviews and technology assessments. Reference lists of relevant systematic reviews were examined for primary studies. Additional searches for primary studies were conducted online, through Ovid/Medline, Embase, CINAHL, and ClinicalTrials.gov . Studies were evaluated for eligibility based on predetermined criteria, data were extracted, study quality was assessed using a risk of bias tool, information on app features was collected, and app usability was assessed. Results are summarized qualitatively. Fifteen articles evaluating 11 apps were identified: six apps for type 1 and five apps for type 2 diabetes. Common f...
2019
BACKGROUND Self-management is integral for control of type 2 diabetes mellitus (T2DM). Patient self-management is improved when they receive real-time information on their health status and behaviors and ongoing facilitation from health professionals. Yet, timely information for these behaviors is notably absent in the healthcare system. Providing real-time data could help improve patient understanding of the dynamics of their illness and assist clinicians in developing targeted approaches to improve health outcomes and in delivering personalized care when and where it is most needed. Mobile technologies (e.g., wearables, apps, connected scales) have the potential to make these patient-provider interactions a reality. To date, there are no studies on the application of these devices for real-time care and tracking data related to T2DM. What strategies might best help patients overcome self-management challenges using self-generated diabetes-related data? How might clinicians effecti...
Mobile Applications for Control and Self Management of Diabetes: A Systematic Review
Journal of Medical Systems, 2016
Mobile applications (apps) can be very useful software on smartphones for all aspects of people's lives. Chronic diseases, such as diabetes, can be made manageable with the support of mobile apps. Applications on smartphones can also help people with diabetes to control their fitness and health. A systematic review of free apps in the English language for smartphones in three of the most popular mobile app stores: Google Play (Android), App Store (iOS) and Windows Phone Store, was performed from November to December 2015. The review of freely available mobile apps for self-management of diabetes was conducted based on the criteria for promoting diabetes self-management as defined by Goyal and Cafazzo (monitoring blood glucose level and medication, nutrition, physical exercise and body weight). The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) was followed. Three independent experts in the field of healthcare-related mobile apps were included in the assessment for eligibility and testing phase. We tested and evaluated 65 apps (21 from Google Play Store, 31 from App Store and 13 from Windows Phone Store). Fifty-six of these apps did not meet even minimal requirements or did not work properly. While a wide selection of mobile applications is available for self-management of diabetes, current results show that there are only nine (5 from Google Play Store, 3 from App Store and 1 from Windows Phone Store) out of 65 reviewed mobile apps that can be versatile and useful for successful self-management of diabetes based on selection criteria. The levels of inclusion of features based on selection criteria in selected mobile apps can be very different. The results of the study can be used as a basis to prvide app developers with certain recommendations. There is a need for mobile apps for self-management of diabetes with more features in order to increase the number of long-term users and thus influence better self-management of the disease.
Improving Type 1 Diabetes Management With Mobile Tools
Journal of Diabetes Science and Technology, 2014
Background: This study aims to provide a better understanding of the ability of mobile health tools to offer glycemic control for patients with type 1 diabetes mellitus. Methods: Data gained from research articles searched in PubMed, Ovid (Medline), and CINAHL from 2005 to 2013 focused on interventions introduced to a type 1 diabetic population. Articles were screened to identify interventions that examined mobile health tools effect on glycemic control using %A1C as a proxy. Fourteen articles were included in this study. Descriptive data, %A1C difference, and statistical significance, if available, were extracted for comparison. Results: Five major categories were identified across the spectrum of interventions, including “Internet,” “Mobile,” “Mobile and Internet,” “Phone,” and “Videoconference and phone.” Seven of the 14 articles reported statistically significant decreases in measured outcomes. Seven studies examine a single cohort, and 7 examined a double cohort. Eleven of the ...