BackgroundAs the increasing prevalence of type 2 diabetes mellitus has put pressure on health systems to appropriately manage these patients, there have been a growing number of mobile apps designed to improve the self-management of diabetes. One such app, BlueStar, has been shown to significantly reduce hemoglobin A1c (HbA1c) levels in small studies and is the first app in the United States to receive Food and Drug Administration approval as a mobile prescription therapy. However, the impact of the app across real-world population among different clinical sites and health systems remains unclear.ObjectiveThe primary objective of this study was to conduct a pragmatic randomized controlled trial of the BlueStar mobile app to determine if app usage leads to improved HbA1c levels among diverse participants in real-life clinical contexts. We hypothesized that this mobile app would improve self-management and HbA1c levels compared with controls.MethodsThe study consisted of a multicenter pragmatic randomized controlled trial. Overall, 110 participants randomized to the immediate treatment group (ITG) received the intervention for 6 months, and 113 participants randomized to the wait-list control (WLC) group received usual care for the first 3 months and then received the intervention for 3 months. The primary outcome was glucose control measured by HbA1c levels at 3 months. Secondary outcomes assessed intervention impact on patient self-management, experience of care, and self-reported health utilization using validated scales, including the Problem Areas in Diabetes, the Summary of Diabetes Self-Care Activities, and the EuroQol-5D. Intervention usage data were collected directly from the app.ResultsThe results of an analysis of covariance controlling for baseline HbA1c levels did not show evidence of intervention impact on HbA1c levels at 3 months (mean difference [ITG−WLC] −0.42, 95% CI −1.05 to 0.21; P=.19). Similarly, there was no intervention effect on secondary outcomes measuring diabetes self-efficacy, quality of life, and health care utilization behaviors. An exploratory analysis of 57 ITG participants investigating the impact of app usage on HbA1c levels showed that each additional day of app use corresponded with a 0.016-point decrease in participants’ 3-month HbA1c levels (95% CI −0.03 to −0.003). App usage varied significantly by site, as participants from 1 site logged in to the app a median of 36 days over 14 weeks (interquartile range [IQR] 10.5-124); those at another site used the app significantly less (median 9; IQR 6-51).ConclusionsThe results showed no difference between intervention and control arms for the primary clinical outcome of glycemic control measured by HbA1c levels. Although there was low usage of the app among participants, results indicate contextual factors, particularly site, had a significant impact on overall usage. Future research into the patient and site-specific factors that increase app utilization are needed.Trial RegistrationClinicaltrials.gov NCT02813343; https://clinicaltr...

Recognize: Consider diabetes risk factors for all of your patients and screen appropriately for diabetes. Register: Develop a registry for all of your patients with diabetes to track care. Resource: Support self-management through the use of interprofessional teams, which could include the primary care provider, diabetes educator, registered dietitian, nurse, pharmacist, specialists and self-management supports, including linkage to community services. Relay: Facilitate information sharing between the person with diabetes and the health-care team for coordinated care and timely management changes. Recall: Develop a system to remind your patients and caregivers of timely review and reassessment.Conflict of interest statements can be found on page S33. Can J Diabetes 42 (2018) S27-S35

Aims/hypothesis Ethnicity and gestational diabetes mellitus (GDM) are both risk factors for the development of type 2 diabetes. However, it is uncertain whether ethnicity modifies the effect of GDM on diabetes risk. We aimed to determine the risk of diabetes following pregnancy with and without GDM for Chinese and South Asian women compared with white women. Methods Using healthcare databases, all 1,050,108 women aged 20-49 with live births between January 1995 and June 2008 in Ontario were identified. They were followed for up to 15 years for the diagnosis of diabetes. Results The age-standardised prevalences of GDM were 4.1%, 7.1% and 2.9% for Chinese, South Asian and white women, respectively. The cumulative incidence of diagnosed diabetes at the median follow-up time of 7.6 years was 16.5% and 1.8% for Chinese women with and without GDM, 31.8% and 3.6% for South Asian women with and without GDM, and 25.7% and 1.8% for white women with and without GDM. The presence of GDM conferred an increase in the risk for diabetes after pregnancy of more than 13-fold in white women, but only a nine-to tenfold increase among Chinese and South Asian women.Conclusions/interpretation Although one-third of South Asian women with GDM were diagnosed with diabetes within 8 years postpartum, the incremental impact of GDM on diabetes risk was not as strong among Chinese and South Asian women as it was among white women.

Background Transition from pediatric to adult care is a period of high risk for loss to follow‐up, morbidity, and mortality in adolescents and young adults (AYA) with hemoglobinopathies. The purpose of this study was to determine whether a transition program with transition navigator (TN) reduced loss to follow‐up and hospitalizations and improved medication adherence and appointment attendance compared with an unstructured transfer. Procedure A retrospective observational study compared all AYA with hemoglobinopathies who turned 18 one year prior to (n = 51) and one year after (n = 61) the initiation of the transition program. Data from one year prior to last pediatric appointment and one year following first adult appointment were collected from each patient. Results The transition program with TN reduced loss to follow‐up from 29% to 7% (P = 0.034). A greater proportion of patients in the transition cohort maintained or improved adherence to hydroxyurea or iron chelation to ≥4 days/week; exposure to the program was independently associated with such improvement (P = 0.047). A trend toward improvement or maintenance of ≥90% attendance to appointments was observed (P = 0.096). Frequency of hospitalization was not significantly different between the two cohorts (P = 0.985). Conclusions A transition program with TN significantly reduced loss to follow‐up, and significantly improved and maintained fair to good medication adherence. Further analysis of economic benefit and patient satisfaction will be conducted.

BackgroundManagement 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.MethodsThe 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.DiscussionThe 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.Trial registrationClinicaltrials.gov NCT02813343. Registered on 24 June 2016 (retrospectively registered).Trial Sponsor: Ontario Telemedicine Network

Background: Virtual care for patients with coronavirus disease 2019 (COVID-19) allows providers to monitor COVID-19-positive patients with variable trajectories while reducing the risk of transmission to others and ensuring health care capacity in acute care facilities. The objective of this descriptive analysis was to assess the initial adoption, feasibility and safety of a family medicine–led remote monitoring program, COVIDCare@Home, to manage the care of patients with COVID-19 in the community. Methods: COVIDCare@Home is a multifaceted, interprofessional team–based remote monitoring program developed at an ambulatory academic centre, the Women’s College Hospital in Toronto. A descriptive analysis of the first cohort of patients admitted from Apr. 8 to May 11, 2020, was conducted. Lessons from the implementation of the program are described, focusing on measure of adoption (number of visits per patient total, with a physician or with a nurse; length of follow-up), feasibility (received an oximeter or thermometer; consultation with general internal medicine, social work or mental health, pharmacy or acute ambulatory care unit) and safety (hospitalizations, mortality and emergency department visits). Results: The COVIDCare@Home program cared for a first cohort of 97 patients (median age 41 yr, 67% female) with 415 recorded virtual visits. Patients had a median time from positive testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to first appointment of 3 (interquartile range [IQR] 2–4) days, with a median virtual follow-up time of 8 (IQR 5–10) days. A total of 4 (4%) had an emergency department visit, with no patients requiring hospitalization and no deaths; 16 (16%) of patients required support with mental and social health needs. Interpretation: A family medicine–led, team-based remote monitoring program can safely manage the care of outpatients diagnosed with COVID-19. Virtual care approaches, particularly those that support patients with more complex health and social needs, may be an important part of ongoing health system efforts to manage subsequent waves of COVID-19 and other diseases.

Key Points Question How do individuals narrate their experiences of living with type 1 diabetes during early emerging adulthood (the developmental life stage roughly spanning between the ages of 18 and 24 years)? Findings This qualitative study involved in-depth interviews with 33 emerging adults with type 1 diabetes. Narrative analysis identified 3 distinct story types encompassing differing perceptions of living with type 1 diabetes (3i), termed ingrained (characterized by actively integrating diabetes within one’s life), intrusive (characterized by struggles to accept diabetes and a sense of striving for control), and inconspicuous (characterized by attempts to minimize attention toward diabetes to protect one’s sense of normalcy). Meaning The 3i conceptual framework provides a means by which differing emerging adult perceptions of type 1 diabetes can be recognized and articulated, which may help health care professionals better individualize their approaches to self-management support during the transitioning years.

BackgroundMental illness is a substantial and rising contributor to the global burden of disease. Access to and utilization of mental health care, however, is limited by structural barriers such as specialist availability, time, out-of-pocket costs, and attitudinal barriers including stigma. Innovative solutions like virtual care are rapidly entering the health care domain. The advancement and adoption of virtual care for mental health, however, often occurs in the absence of rigorous evaluation and adequate planning for sustainability and spread.MethodsA pragmatic randomized controlled trial with a nested comparative effectiveness arm, and concurrent realist process evaluation to examine acceptability, effectiveness, and cost-effectiveness of the Big White Wall (BWW) online platform for mental health self-management and peer support among individuals aged 16 and older who are accessing mental health services in Ontario, Canada. Participants will be randomized to 3 months of BWW or treatment as usual. At the end of the 3 months, participants in the intervention group will have the opportunity to opt-in to an intervention extension arm. Those who opt-in will be randomized to receive an additional 3 months of BWW or no additional intervention. The primary outcome is recovery at 3 months as measured by the Recovery Assessment Scale-revised (RAS-r). Secondary outcomes include symptoms of depression and anxiety measured with the Personal Health Questionnaire-9 item (PHQ-9) and the Generalized Anxiety Disorder Questionnaire-7 item (GAD-7) respectively, quality of life measured with the EQ-5D-5L, and community integration assessed with the Community Integration Questionnaire. Cost-effectiveness evaluations will account for the cost of the intervention and direct health care costs. Qualitative interviews with participants and stakeholders will be conducted throughout.DiscussionUnderstanding the impact of virtual strategies, such as BWW, on patient outcomes and experience, and health system costs is essential for informing whether and how health system decision-makers can support these strategies system-wide. This requires clear evidence of effectiveness and an understanding of how the intervention works, for whom, and under what circumstances. This study will produce such effectiveness data for BWW, while simultaneously exploring the characteristics and experiences of users for whom this and similar online interventions could be helpful.Trial registrationClinicaltrials.gov NCT02896894. Registered on 31 August 2016 (retrospectively registered).