The ability of patients and health care providers to use various forms of technology for general health has significantly increased in the past several years with the expansion of telehealth, digital applications, personal digital devices, smartphones, and other Internet-connected platforms and devices. For individuals with diabetes, this also includes connected blood glucose meters, continuous glucose monitoring devices, and insulin delivery systems. In this article, the authors outline several steps to facilitate the acquisition, management, and meaningful use of digital diabetes data that can enable successful implementation of both diabetes technology and telehealth services in primary care clinics.

Background Continuous glucose monitoring (CGM) can improve glycemic outcomes in pediatric type 1 diabetes management. However, its impact on the psychosocial functioning of caregivers is less well described. The objectives of this pilot study were to explore caregiver reasons for adding CGM to their child’s type 1 diabetes management, parental psychosocial function before initiating CGM, and the relationship between the two. Methods Thirty-two families with a child with type 1 diabetes from Rainbow Babies and Children’s Hospital diabetes clinics who were initiating CGM were recruited over 3 months. Before CGM initiation, the caregivers completed the Fear of Hypoglycemia Scale, State-Trait Anxiety Inventory, Problem Areas in Diabetes Scale, and a questionnaire assessing their primary reason for starting CGM. Participant characteristics and questionnaire results were summarized with descriptive statistics. Participants were grouped by reason for starting CGM, and results were compared among groups using ANOVA and reporting the global F test. Results Fifty percent of respondents indicated that they were starting CGM to optimize glycemic control. The majority of parents (71.8%) expressed worry about helplessness during a hypoglycemic episode. There were no statistically significant differences in patient characteristics or questionnaire results between groups. Forty-three percent of participating families started using CGM during the study’s 8-month follow-up period. The main reason (64%) for not starting CGM was not having the chance to start the process of obtaining a CGM system. There were no statistically significant differences between children who did and did not start CGM. Conclusion Caregivers have different reasons for starting CGM for their child with type 1 diabetes. Further studies are needed to understand whether these reasons are related to differences in psychosocial functioning. Despite interest in starting CGM, there remain barriers to implementation.

OBJECTIVE Diabetes technology has improved the lives of people with diabetes (PWD), but there is little research on how insulin pumps and continuous glucose monitoring (CGM) affect couples’ relationships. The purpose of this study was to examine how the use of diabetes technology affects couple interactions. METHODS In a secondary data analysis, we used a multiple-method qualitative analysis, including a constant-comparison approach, to examine similarities and differences in couple interactions related to diabetes technology. PWD and their spouses were interviewed separately, using a semi-structured interview guide; the interviews primarily focused on how couples coped with type 1 diabetes. RESULTS Participants (n = 134 couples) were using an insulin pump or CGM system. Average age was 44 ± 12.05 years for PWD and 44 ± 12.62 years for spouses. Couples’ average length of relationship was 18 ± 12.50 years. Among the PWD, 54 used a pump only, 12 used CGM only, and 68 used both. Four main themes emerged: 1) diabetes technology facilitates shared diabetes management for couples, 2) diabetes technology facilitates spousal involvement in diabetes care, 3) diabetes technology is a source of relationship tension, and 4) diabetes technology causes positive/negative responses to sleep and alarms. CONCLUSION Overall, couples perceived diabetes technology as having a positive effect on their relationship by increasing collaboration, promoting communication, and reducing diabetes burden and vigilance. Technology also was perceived to increase relationship tension, lifestyle inconveniences, and positive/negative responses regarding sleep and alarms. Involvement of spouses in diabetes technology education should be considered.

Time in glucose ranges is increasingly relevant for research and clinical practice. Whereas the clinical validity of these metrics has been demonstrated with regard to long-term complications, their associations with patient-reported outcomes such as well-being, diabetes distress, and fear of hypoglycemia remain an open research question. This article reviews existing evidence on links between times in glycemic ranges and patient-reported outcomes. It also describes a novel research approach of using ecological momentary assessment to analyze on a more granular level in real time possible associations of these parameters of glycemic control and patient-reported outcomes. Such an approach could further our understanding of how glucose and patient-reported outcomes may be interconnected.

Time in range (TIR) is gaining ground as an outcome measure in type 1 diabetes trials. However, inclusion of TIR raises several issues for trial design. In this article, the authors begin by defining TIR and describing the current international consensus around TIR targets. They then expand on evidence for the validity of TIR as a primary clinical trial outcome before concluding with some practical, ethical, and logistical implications.

Continuous glucose monitoring (CGM) is being used with increasing frequency as an adjunct to self-monitoring of blood glucose in pregnancy, and novel targets based on CGM data are becoming standardized. This adoption of CGM is the result of its improving accuracy, patient preference, and evolving data demonstrating associations of novel targets such as time in range (TIR) with pregnancy and neonatal outcomes. A greater understanding of the relationship of various CGM metrics to outcomes in pregnancy complicated by diabetes is needed. It is clear that TIR parameters need to be uniquely lower for pregnant women than for nonpregnant individuals. CGM technology is also an integral part of hybrid closed-loop insulin delivery systems. These insulin delivery systems will be a significant advance in the management of diabetes during pregnancy if they can achieve the pre- and postprandial targets required for pregnancy and optimize TIR.

Time in range (TIR) and other continuous glucose monitoring (CGM)-derived metrics have been standardized in international consensus conferences. TIR correlates closely with A1C; a TIR of 70% correlates to an A1C of 6.7–7%. Evidence is emerging on the association of TIR with long-term diabetes complications, and each 10% increase in TIR shows a substantial decrease in risk for long-term complications. Application of TIR to clinical practice can be easily done with a stepped approach to the analysis and interpretation of CGM-derived metrics and the ambulatory glucose profile report. Clinician education and partnership with patients are crucial for successful implementation of TIR and all CGM-derived metrics in clinical practice.

Despite significant pharmacological and technological advances in the treatment of type 1 diabetes, the majority of youth in the United States do not meet the American Diabetes Association’s recommended A1C goal. Understanding and managing glycemic variability is important in children and adolescents. Because A1C provides an incomplete picture of day-to-day glycemic fluctuations, continuous glucose monitoring (CGM)-derived metrics are a promising addition to address glycemic management challenges in youth with diabetes. In this article, we discuss how to develop practical strategies to optimize the use of CGM in the pediatric population, interpret the valuable data it provides, and develop personalized and actionable treatment goals.

Continuous glucose monitoring (CGM) systems are becoming part of standard care for type 1 diabetes, and their use is increasing for type 2 diabetes. Consensus has been reached on standardized metrics for reporting CGM data, with time in range of 70–180 mg/dL and time below 54 mg/dL recognized as the key metrics of focus for diabetes management. The ambulatory glucose profile report has emerged as the standard for visualization of CGM data and will continue to evolve to incorporate other elements such as insulin, food, and exercise data to support glycemic management.

OBJECTIVE In response to the coronavirus disease 2019 (COVID-19) pandemic and social distancing guidelines, our pediatric diabetes team rapidly changed the format of conducting diabetes clinic from in person to telehealth. We compared the actual number and rate of completed, canceled, and no-show visits between an 8-week period in 2019, when we exclusively conducted visits in person and the same 8-week period in 2020, during the COVID-19 quarantine, when we exclusively conducted visits via telehealth. METHODS We used electronic health record data for all patients, as well as Dexcom continuous glucose monitoring data collected for a subset of youths during the COVID-19 quarantine and the immediate pre–COVID-19 period. RESULTS Although there was a difference in the absolute number of in-person versus telehealth visits canceled during these two time periods, there was no difference in the rates of completed, canceled, and no-show visits completed in person or via telehealth. This finding suggests that, despite a rapid shift to a completely new health care delivery model, our providers completed a similar rate of patient care via telehealth during the COVID-19 quarantine and that telehealth may be a feasible method for providing diabetes care. However, our results also suggested that youths’ glucose management was less optimal during the quarantine period. CONCLUSION COVID-19 presented an opportunity to adopt and test the feasibility of using a telehealth delivery model for routine diabetes care. Yet, to make telehealth a viable treatment delivery alternative will likely involve the uptake of new clinic procedures, investment in institutional infrastructure, and team-based flexibility.

BACKGROUND Glycemic control is suboptimal in many individuals with type 2 diabetes. Although use of flash continuous glucose monitoring (CGM) has demonstrated A1C reductions in patients with type 2 diabetes treated with a multiple daily injection or insulin pump therapy regimen, the glycemic benefit of this technology in patients with type 2 diabetes using nonintensive treatment regimens has not been well studied. METHODS This retrospective, observational study used the IBM Explorys database to assess changes in A1C after flash CGM prescription in a large population with suboptimally controlled type 2 diabetes treated with nonintensive therapy. Inclusion criteria were diagnosis of type 2 diabetes, age <65 years, treatment with basal insulin or noninsulin therapy, naive to any CGM, baseline A1C ≥8%, and a prescription for the FreeStyle Libre flash CGM system during the period between October 2017 and February 2020. Patients served as their own control subject. RESULTS A total of 1,034 adults with type 2 diabetes (mean age 51.6 ± 9.2 years, 50.9% male, baseline A1C 10.1 ± 1.7%) were assessed. More patients received noninsulin treatments (n = 728) than basal insulin therapy (n = 306). We observed a significant reduction in A1C within the full cohort: from 10.1 ± 1.7 to 8.6 ± 1.8%; Δ −1.5 ± 2.2% (P <0.001). The largest reductions were seen in patients with a baseline A1C ≥12.0% (n = 181, A1C reduction −3.7%, P <0.001). Significant reductions were seen in both treatment groups (basal insulin −1.1%, noninsulin −1.6%, both P <0.001). CONCLUSION Prescription of the flash CGM system was associated with significant reductions in A1C in patients with type 2 diabetes treated with basal insulin or noninsulin therapy. These findings provide evidence for expanding access to flash CGM within the broader population of people with type 2 diabetes.

The purpose of this study was to determine clinician attitudes about the distinct barriers to uptake of continuous glucose monitoring (CGM) among people with diabetes. Survey data were collected measuring individual barriers, prerequisites to CGM, confidence in addressing barriers, and clinic staff resources. Results show that clinicians commonly report barriers to using CGM among people with diabetes in their clinic. Furthermore, clinicians who report a high number of barriers do not feel confident in overcoming the barriers to CGM. Interventions that attempt to empower clinicians to address concerns about CGM among people with diabetes may be warranted because low uptake does not appear to be directly related to available resources or prerequisites to starting CGM.

OBJECTIVE Daily self-monitoring of blood glucose (SMBG) is essential for type 1 diabetes management yet is challenging during adolescence. Ecological momentary assessment (EMA) is the repeated sampling of behaviors and experiences in real time in the natural environment. The purpose of this study was to evaluate 1) the validity of self-reported SMBG values via text message–delivered EMA surveys compared with objective SMBG values via glucose meters and 2) in-the-moment motivators and barriers to performing SMBG in a pediatric type 1 diabetes population. Methods Youth (n = 62, aged 11–21 years) with type 1 diabetes received three text messages daily for 10 days containing surveys inquiring about SMBG engagement. Objective SMBG values were downloaded from glucose meters. Results On average, participants reported performing SMBG 4 times/day. Of the self-reported SMBG values, 39.6% were accurate. Inaccurate values included additions (i.e., self-reported value with no objective value), omissions (i.e., objective value with no self-reported value), and alterations (difference between self-report and objective SMBG values ≥10 mg/dL). Of the matched pairs of self-reported and objective SMBG values, 41.3% were altered. Bland–Altman plots determined that the mean difference between self-reported and objective glucose data were −5.43 mg/dL. Participants reported being motivated to check their blood glucose because it was important for their health, and reported barriers included wanting to ignore the task, forgetting, and not having devices. Conclusion Youth’s self-reported SMBG values may not align with objective readings. The results of this study can facilitate future research to determine individual factors related to SMBG and accuracy of self-reporting.

IN BRIEF In this article, the authors discuss several innovative concepts UnitedHealth Group Research & Development is exploring to help patients manage their type 2 diabetes. The article focuses on efforts to use remote support programs and wearable technology to empower patients to take more active roles in managing their health and to foster more interactive patient-provider conversations. Additionally, the authors reflect on how such efforts could particularly benefit medically underserved communities. They offer observations from claims data about current health outcomes and costs in underserved areas.

Full realization of the benefits of continuous glucose monitoring (CGM) depends on addressing barriers such as cost, accuracy, burdens of daily use, and uncertainty about applying the data. Lack of systematic education has also hampered widespread adoption among patients and health care professionals. This article describes the practical application of an affordable and intuitive category of CGM called “flash” that requires users to scan the sensor with a handheld reader for on-demand access to continuous data. The data may be used for in-the-moment therapy adjustment, retrospective review of glucose patterns, and observation of glucose trending in response to behavior. Higher rates of flash CGM scanning have been associated with increased time in the glycemic target range and reduced time in hyper- and hypoglycemia. Growing interest in this technology suggests new opportunities for helping more patients incorporate CGM into their daily self-care.

IN BRIEF Diabetes care lends itself to interactions centered around data—counting carbohydrate for meals, calculating correction doses, viewing logbooks or device data, and discussing A1C levels—and digital technology has enhanced diabetes care through the improved collection and analysis of data from multiple sources. With these technological advancements have come great improvements in quality of life for people with type 1 diabetes. These technologies allow for more informed and immediate decision-making through better access to blood glucose data and sometimes allow the devices themselves to make decisions, removing the need for patients or clinicians to be involved in decision-making altogether. At the same time, these new technologies bring new challenges for both patients and health care providers, who must now analyze and make sense of more diabetes data.

IN BRIEF Automated insulin delivery (AID; also known as artificial pancreas) has improved the regulation of blood glucose concentrations, reduced the frequency of hyperglycemic and hypoglycemic episodes, and improved the quality of life of people with diabetes and their families. Three different types of algorithms—proportional-integral-derivative control, model predictive control, and fuzzy-logic knowledge-based systems—have been used in AID control systems. This article will highlight the foundations of these algorithms and discuss their strengths and limitations. Multivariable artificial pancreas and dual-hormone (insulin and glucagon) systems will be introduced.