Reducing Inequity in the Use of Automated Insulin Delivery Systems by Adults With Type 1 Diabetes: Key Learnings From a Safety Net Diabetes Clinic Program.

BACKGROUND: Recent advancements in diabetes technology have significantly improved Type 1 diabetes (T1D) management, but disparities persist, particularly in the adoption of automated insulin delivery (AID) systems within minoritized communities. We aimed to improve patient access to AID system training and overcome clinical inertia to referral. METHODS: We report on a transformative program implemented at Boston Medical Center, the largest safety-net hospital in New England, aimed at reducing disparities in AID system utilization. We employed a multidisciplinary team and quality improvement principles to identify barriers and develop solutions. Strategies included increasing access to diabetes educators, creating a referral system, and developing telemedicine education classes. We also made efforts to raise clinician awareness and confidence in recommending AID therapy. RESULTS: At baseline, 13.5% of our clinic T1D population was using an insulin pump. The population referred included 97 people with T1D (49% female, mean A1c 8.7%, 68% public insurance beneficiaries, 25% Hispanic and 25% non-Hispanic Black). Results from the first year showed a 166% increase in AID system use rates, with 64% of referred patients starting on AID. Notably, 78% of patients with A1c >8.5% adopted AID systems, addressing a gap in representation observed in clinical efficacy trials. The initiative successfully narrowed disparities in AID use among minoritized populations. CONCLUSIONS: The program's success among minoritized patients underscores the significance of tailored, collaborative, team-based care and targeted educational initiatives. Our experience provides a foundation for future efforts to ensure equitable access to diabetes technologies, emphasizing the potential of local quality improvement interventions.

A daily study of stressors, continuously measured glucose, and diabetes symptoms in latinos with type 2 diabetes.

This study examined whether daily stressors and continuously monitored glucose levels and glucose variability predict daily diabetes symptoms. Fifty Latinos with type 2 diabetes were randomized to either diabetes education (DE-only; N = 23) or DE plus stress management and relaxation training (DE + SMR; N = 32). After treatment, for 7 days they wore 'blinded' continuous glucose monitors and reported common stressors and diabetes symptoms twice daily. Between individuals, participants with more numerous overall stressors and more time in hyperglycemia reported higher symptoms. Within individuals, symptoms were higher during intervals of greater than usual stressors. Yet, diabetes symptoms did not covary with changes in glucose levels or glucose variability. The within-person stressor-symptom association was stronger among older individuals and non-significant for participants in DE + SMR condition. Diabetes symptoms were associated with recent stressor exposure, but not recent glucose level or changes in glucose. CLINICAL TRIAL NUMBER: ClinicalTrials.gov Identifier (No. NCT01578096).

Mean Levels and Variability in Affect, Diabetes Self-Care Behaviors, and Continuously Monitored Glucose: A Daily Study of Latinos With Type 2 Diabetes.

OBJECTIVE: This study investigated between- and within-person associations among mean levels and variability in affect, diabetes self-care behaviors, and continuously monitored glucose in Latinos with type 2 diabetes. METHODS: Fifty participants (M [SD] age = 57.8 [11.7] years, 74% women, mean [SD] glycosylated hemoglobin A1c = 8.3% [1.5%]) wore a "blinded" continuous glucose monitor for 7 days, and they responded to twice daily automated phone surveys regarding positive affect, negative affect, and self-care behaviors. RESULTS: Higher mean levels of NA were associated with higher mean glucose (r = .30), greater percent hyperglycemia (r = .34) and greater percentage of out-of-range glucose (r = .34). Higher NA variability was also related to higher mean glucose (r = .34), greater percent of hyperglycemia (r = .44) and greater percentage of out-of-range glucose (r = .43). Higher positive affect variability was related to lower percentage of hypoglycemia (r = -.33). Higher mean levels of self-care behaviors were related to lower glucose variability (r = -.35). Finally, higher self-care behavior variability was related to greater percentage of hyperglycemia (r = .31) and greater percentage of out-of-range glucose (r = -.28). In multilevel regression models, within-person increases from mean levels of self-care were associated with lower mean levels of glucose (b = -7.4, 95% confidence interval [CI] = -12.8 to -1.9), lower percentage of hyperglycemia (b = -0.04, 95% CI = -0.07 to -0.01), and higher percentage of hypoglycemia (b = 0.02, 95% CI = 0.01 to 0.03) in the subsequent 10-hour period. CONCLUSIONS: Near-to-real time sampling documented associations of glucose with affect and diabetes self-care that are not detectable with traditional measures.

Effect of Continuous Glucose Monitoring on Glycemic Control in Adults With Type 1 Diabetes Using Insulin Injections: The DIAMOND Randomized Clinical Trial.

Importance: Previous clinical trials showing the benefit of continuous glucose monitoring (CGM) in the management of type 1 diabetes predominantly have included adults using insulin pumps, even though the majority of adults with type 1 diabetes administer insulin by injection. Objective: To determine the effectiveness of CGM in adults with type 1 diabetes treated with insulin injections. Design, Setting, and Participants: Randomized clinical trial conducted between October 2014 and May 2016 at 24 endocrinology practices in the United States that included 158 adults with type 1 diabetes who were using multiple daily insulin injections and had hemoglobin A1c (HbA1c) levels of 7.5% to 9.9%. Interventions: Random assignment 2:1 to CGM (n = 105) or usual care (control group; n = 53). Main Outcomes and Measures: Primary outcome measure was the difference in change in central-laboratory-measured HbA1c level from baseline to 24 weeks. There were 18 secondary or exploratory end points, of which 15 are reported in this article, including duration of hypoglycemia at less than 70 mg/dL, measured with CGM for 7 days at 12 and 24 weeks. Results: Among the 158 randomized participants (mean age, 48 years [SD, 13]; 44% women; mean baseline HbA1c level, 8.6% [SD, 0.6%]; and median diabetes duration, 19 years [interquartile range, 10-31 years]), 155 (98%) completed the study. In the CGM group, 93% used CGM 6 d/wk or more in month 6. Mean HbA1c reduction from baseline was 1.1% at 12 weeks and 1.0% at 24 weeks in the CGM group and 0.5% and 0.4%, respectively, in the control group (repeated-measures model P < .001). At 24 weeks, the adjusted treatment-group difference in mean change in HbA1c level from baseline was -0.6% (95% CI, -0.8% to -0.3%; P < .001). Median duration of hypoglycemia at less than <70 mg/dL was 43 min/d (IQR, 27-69) in the CGM group vs 80 min/d (IQR, 36-111) in the control group (P = .002). Severe hypoglycemia events occurred in 2 participants in each group. Conclusions and Relevance: Among adults with type 1 diabetes who used multiple daily insulin injections, the use of CGM compared with usual care resulted in a greater decrease in HbA1c level during 24 weeks. Further research is needed to assess longer-term effectiveness, as well as clinical outcomes and adverse effects. Trial Registration: clinicaltrials.gov Identifier: NCT02282397.

Optimizing Glycemic Outcomes for Minoritized and Medically Underserved Adults Living with Type 1 Diabetes.

Individuals living with type 1 diabetes (T1D) from medically underserved communities have poorer health outcomes. Efforts to improve outcomes include a focus on team-based care, activation of behavior change, and enhancing self-management skills and practices. Advanced diabetes technologies are part of the standard of care for adults with T1D. However, health care providers often carry implicit biases and may be uncomfortable with recommending technologies to patients who have traditionally been excluded from efficacy trials or have limited real-world exposure to devices. We review the literature on this topic and provide an approach to address these issues in clinical practice.

Proof-of-concept Application of Continuous Glucose Monitoring Data Analytics to Identify Diabetes Glucotypes.

Background: In this proof-of-concept study, we evaluated if monogenic diabetes resulting from mutations of the HNF-1α gene (HNF1A-MODY) has a distinctive continuous glucose monitoring (CGM) glucotype, in comparison to type 1 diabetes (T1D). Methods: Using CGM data from 5 subjects with HNF1A-MODY and 115 subjects with T1D, we calculated multiple glucose metrics, including measures of within- and between-day variability (such as coefficient variation for each hour [CVb_1h]). Results: The MODY and T1D cohorts had minimum CVb_1h of 11.3 ± 4.4 and 18.0 ± 4.9, respectively (P = .02) and maximum CVb_1h of 33.9 ± 5.0 and 50.3 ± 10, respectively (P < .001). All subjects with HNF1A-MODY had a minimum %CVb_1h ≤ 17.3% and maximum %CVb_1h ≤ 37.1%. In contrast, only 12 of 115 subjects with T1D had both a minimum and maximum %CVb_1h below these thresholds (P < .001). Conclusion: HNF1A- MODY is characterized by a low hourly, between-day glucose variability. CGM-derived glucose metrics may have potential applicability for screening for atypical diabetes phenotypes in the T1D population.

Diabetes Technology Meeting 2022.

Diabetes Technology Society hosted its annual Diabetes Technology Meeting from November 3 to November 5, 2022. Meeting topics included (1) the measurement of glucose, insulin, and ketones; (2) virtual diabetes care; (3) metrics for managing diabetes and predicting outcomes; (4) integration of continuous glucose monitor data into the electronic health record; (5) regulation of diabetes technology; (6) digital health to nudge behavior; (7) estimating carbohydrates; (8) fully automated insulin delivery systems; (9) hypoglycemia; (10) novel insulins; (11) insulin delivery; (12) on-body sensors; (13) continuous glucose monitoring; (14) diabetic foot ulcers; (15) the environmental impact of diabetes technology; and (16) spinal cord stimulation for painful diabetic neuropathy. A live demonstration of a device that can allow for the recycling of used insulin pens was also presented.

Continuous glucose monitoring: a review for behavioral researchers.

OBJECTIVE: Continuous glucose monitoring (CGM) systems collect and store glucose data in an ongoing fashion for several days at a time. The main advantage of CGM is that it can help identify fluctuations and trends that would otherwise go unnoticed with other glucose measures. Here, we provide a review of CGM for behavioral researchers. METHODS: We begin with a brief review of diabetes and glucose measurement and then describe what CGM is and reference the commercial CGM systems currently available. We discuss the challenges involved in using CGM in behavioral research. We then present a broad overview of CGM in behavioral research, including data from ours and others' research programs. Finally, we cover some practical issues to be considered when using CGM, suggest reporting guidelines for the behavioral researcher, and offer suggestions for future research. RESULTS: Only a handful of behavioral researchers are using CGM, although its use is increasing. The main ways that CGM is being used in behavioral research is to investigate basic biobehavioral processes, to assess the effects of behavioral interventions on diabetes control, and to use CGM itself as a behavior modification and teaching tool in diabetes self-management interventions. CONCLUSIONS: Continuous glucose monitoring holds promise to help behavioral researchers unravel the complex relationships among glucose and intrapersonal, interpersonal, and contextual factors. However, the uptake of CGM for this purpose is limited, and the possibilities for its use are largely unmet. We encourage behavioral researchers to implement CGM in their protocols and to do so in a way that maximizes its explanatory power.

Making sense of glucose sensors in end-stage kidney disease: A review.

Diabetes mellitus remains the leading cause of end-stage kidney disease worldwide. Inadequate glucose monitoring has been identified as one of the gaps in care for hemodialysis patients with diabetes, and lack of reliable methods to assess glycemia has contributed to uncertainty regarding the benefit of glycemic control in these individuals. Hemoglobin A1c, the standard metric to evaluate glycemic control, is inaccurate in patients with kidney failure, and does not capture the full range of glucose values for patients with diabetes. Recent advances in continuous glucose monitoring have established this technology as the new gold standard for glucose management in diabetes. Glucose fluctuations are uniquely challenging in patients dependent on intermittent hemodialysis, and lead to clinically significant glycemic variability. This review evaluates continuous glucose monitoring technology, its validity in the setting of kidney failure, and interpretation of glucose monitoring results for the nephrologist. Continuous glucose monitoring targets for patients on dialysis have yet to be established. While continuous glucose monitoring provides a more complete picture of the glycemic profile than hemoglobin A1c and can mitigate high-risk hypoglycemia and hyperglycemia in the context of the hemodialysis procedure itself, whether the technology can improve clinical outcomes merits further investigation.

The Development of an Exercise Advisor App for Type 1 Diabetes: Digitization Facilitates More Individualized Guidance.

Maintaining blood glucose levels in the target range during exercise can be onerous for people with type 1 diabetes (T1D). Using evidence-based research and consensus guidelines, we developed an exercise advisor app to reduce some of the burden associated with diabetes management during exercise. The app will guide the user on carbohydrate feeding strategies and insulin management strategies before, during, and after exercise and provide targeted and individualized recommendations. As a basis for the recommendations, the decision trees for the app use various factors including the type of insulin regimen, time of activity, previous insulin boluses, and current glucose level. The app is designed to meet the various needs of people with T1D for different activities to promote safe exercise practices.

Use of Connected Pen as a Diagnostic Tool to Evaluate Missed Bolus Dosing Behavior in People with Type 1 and Type 2 Diabetes.

Objective: This study used connected pen to determine missed bolus dose (MBD) frequency during masked and unmasked continuous glucose monitoring (CGM) periods and examined its link with time-in-range (TIR), time-above-range (TAR), time-below-range (TBR), and key participant characteristics in people with diabetes. Methods: This was a 12-week, single-arm, exploratory, two-period study for people with type 1 diabetes (T1D) or type 2 diabetes (T2D). The primary objective was to estimate the average number of MBD during masked and real-time CGM use. The secondary objective was to estimate the average percent TIR and its relationship to MBD. An exploratory objective was to investigate the participant characteristics that were associated with MBD. Data were analyzed for differences in MBD by diabetes type and other participant characteristics, by CGM period, and by hypoglycemic fear scores. Results: Participants (n = 64; T1D, n = 38; T2D, n = 26) were 48 ± 11.9 years old and 44% were female. From the masked to the unmasked period, MBD, %TAR, %TBR, and glycated hemoglobin decreased significantly (0.74 MBD/day to 0.62 MBD/day, P = 0.008; 53.6%-48.1%, P = 0.004; 4.49%-2.93%, P < 0.001; mean 8.8%-8.4%, P < 0.001, respectively), while %TIR increased significantly (41.9%-49.0%, P < 0.001). MBD/day was negatively associated with TIR (P = 0.016) and positively associated with TAR (P = 0.015) for T1D and positively associated with TBR (P = 0.024) for T2D in the masked period only. MBD was significantly associated with fear of hypoglycemia for T2D, but not T1D. Conclusions: MBD is associated with reduced TIR when CGM is masked and tailored therapeutic approaches are needed for T1D and T2D populations.

Continuous glucose monitoring and intensive treatment of type 1 diabetes.

BACKGROUND: The value of continuous glucose monitoring in the management of type 1 diabetes mellitus has not been determined. METHODS: In a multicenter clinical trial, we randomly assigned 322 adults and children who were already receiving intensive therapy for type 1 diabetes to a group with continuous glucose monitoring or to a control group performing home monitoring with a blood glucose meter. All the patients were stratified into three groups according to age and had a glycated hemoglobin level of 7.0 to 10.0%. The primary outcome was the change in the glycated hemoglobin level at 26 weeks. RESULTS: The changes in glycated hemoglobin levels in the two study groups varied markedly according to age group (P=0.003), with a significant difference among patients 25 years of age or older that favored the continuous-monitoring group (mean difference in change, -0.53%; 95% confidence interval [CI], -0.71 to -0.35; P<0.001). The between-group difference was not significant among those who were 15 to 24 years of age (mean difference, 0.08; 95% CI, -0.17 to 0.33; P=0.52) or among those who were 8 to 14 years of age (mean difference, -0.13; 95% CI, -0.38 to 0.11; P=0.29). Secondary glycated hemoglobin outcomes were better in the continuous-monitoring group than in the control group among the oldest and youngest patients but not among those who were 15 to 24 years of age. The use of continuous glucose monitoring averaged 6.0 or more days per week for 83% of patients 25 years of age or older, 30% of those 15 to 24 years of age, and 50% of those 8 to 14 years of age. The rate of severe hypoglycemia was low and did not differ between the two study groups; however, the trial was not powered to detect such a difference. CONCLUSIONS: Continuous glucose monitoring can be associated with improved glycemic control in adults with type 1 diabetes. Further work is needed to identify barriers to effectiveness of continuous monitoring in children and adolescents. (ClinicalTrials.gov number, NCT00406133.)

Insulin Metrics: Need for Development of Consensus Standards for Reporting of Insulin Dosing Data.

The advent of connected insulin pens will generate an avalanche of digital insulin data, especially in the context of prandial- and multiple daily injection-insulin regimens. There is a need for the diabetes community to develop standards for such data, analogous to what has been achieved using the ambulatory glucose profile and associated metrics for glucose, permitting harmonization of data reporting for multiple devices and facilitating integration of glucose, insulin, food intake, and physical activity data. Several studies have estimated the timing of meals by analyses of glucose excursions but using diverse criteria. There is need for uniform criteria for multiple types of insulin boluses, including premeal, perimeal, delayed, missed, and correction boluses to facilitate research studies and patient care. This article contains a first preliminary proposal for standards regarding reporting of insulin dosing data. Clinical usage of these reports will require sensitive communication between health care providers and patients.

Predictive Low-Glucose Suspend Necessitates Less Carbohydrate Supplementation to Rescue Hypoglycemia: Need to Revisit Current Hypoglycemia Treatment Guidelines.

Current guidelines recommend 15-20 g of carbohydrate (CHO) for treatment of mild to moderate hypoglycemia. However, these guidelines do not account for reduced insulin during suspensions with predictive low-glucose suspend (PLGS). We assessed insulin suspensions, hypoglycemic events, and CHO treatment during a 20-h inpatient evaluation of an investigational system with a PLGS feature, including an overnight basal up-titration period to activate the PLGS. Among 10 adults with type 1 diabetes, there were 59 suspensions; 7 suspensions were associated with rescue CHO and 5 with hypoglycemia. Rescue treatment consisted of median 9 g CHO (range: 5-16 g), with no events requiring repeat CHO. No rescue CHO were given during or after insulin suspension for the overnight basal up-titration. To minimize rebound hyperglycemia and needless calorie intake from hypoglycemia overtreatment, updated guidance for PLGS systems should reflect possible need to reduce CHO amounts for hypoglycemia rescue associated with an insulin suspension. The clinical trial was registered with ClinicalTrials.gov (NCT03890003).

Performance of an Automated Insulin Delivery System: Results of Early Phase Feasibility Studies.

Background: Automated insulin delivery (AID) systems have demonstrated improvements in time-in-range (TIR, blood glucose 70-180 mg/dL) without increasing hypoglycemia. Testing a closed-loop system in an inpatient environment with supervised challenges allows for initial evaluation of performance and safety of the system. Methods: Adults with type 1 diabetes (T1D) were enrolled into two similar studies (n = 10 per study), with 3-day inpatient analysis periods. Participants tested a Lilly hybrid closed-loop (HCL) system comprising an investigational insulin pump, insulin lispro, a pump-embedded model predictive control algorithm, a continuous glucose monitor (CGM), and an external dedicated controller. Each protocol included meal-related and exercise challenges to simulate real-world diabetes self-management errors. Only study staff interacted with the HCL system. Performance was assessed using standard CGM metrics overall and within prespecified periods. Results: Participants (25% male) had mean ± standard deviation (SD) age 44.7 ± 14.2 years, T1D duration 30.2 ± 11.1 years, A1C 7.2% ± 0.8%, and insulin usage 0.53 ± 0.21 U/(kg·day). Percentage TIR 70-180 mg/dL (mean ± SD) was 81.2 ± 8.4 overall, 85.2 ± 8.1 outside of challenge periods, 97.3 ± 5.3 during the nocturnal periods, and 74.5 ± 16.2 for the postprandial periods. During challenge periods, percentage TIR for the overbolus challenge was 65.4 ± 29.2 and that for the delayed bolus challenge was 57.1 ± 25.1. No adverse events (AEs), serious AEs, or unanticipated adverse device events occurred while participants were using the HCL system. Conclusions: In participants with T1D, Lilly AID system demonstrated expected algorithm performance and safety with satisfactory glycemic outcomes overall and in response to simulated diabetes management challenges. Additional studies in less supervised conditions and with broader patient populations are warranted. ClinicalTrials.gov Registration number NCT03743285, NCT03849612.

Experiences of Adults With Type 1 Diabetes Using Glucose Sensor-Based Mobile Technology for Glycemic Variability: Qualitative Study.

BACKGROUND: Adults with type 1 diabetes (PWDs) face challenging self-management regimens including monitoring their glucose values multiple times a day to assist with achieving glycemic targets and reduce the risk of long-term diabetes complications. Recent advances in diabetes technology have reportedly improved glycemia, but little is known about how PWDs utilize mobile technology to make positive changes in their diabetes self-management. OBJECTIVE: The aim of this qualitative study was to explore PWDs' experiences using Sugar Sleuth, a glucose sensor-based mobile app and Web-based reporting system, integrated with the FreeStyle Libre glucose monitor that provides feedback about glycemic variability. METHODS: We used a qualitative descriptive research design and conducted semistructured interviews with 10 PWDs (baseline mean glycated hemoglobin, HbA1c) 8.0%, (SD 0.45); 6 males and 4 females, aged 52 years (SD 15), type 1 diabetes (T1D) duration 31 years (SD 13), 40% (4/10, insulin pump) following a 14-week intervention during which they received clinical support and used Sugar Sleuth to evaluate and understand their glucose data. Audio-recorded interviews were transcribed, coded, and analyzed using thematic analysis and NVivo 11 (QSR International Pty Ltd). RESULTS: A total of 4 main themes emerged from the data. Participants perceived Sugar Sleuth as an Empowering Tool that served to inform lifestyle choices and diabetes self-management tasks, promoted preemptive self-care actions, and improved discussions with clinicians. They also described Sugar Sleuth as providing a Source of Psychosocial Support and offering relief from worry, reducing glycemic uncertainty, and supporting positive feelings about everyday life with diabetes. Participants varied in their Approaches to Glycemic Data: 40% (4/10) described using Sugar Sleuth to review data, understand glycemic cause and effect, and plan for future self-care. On the contrary, 60% (6/10) were reluctant to review past data; they described receiving benefits from the immediate numbers and trend arrows, but the app still prompted them to enter in the suspected causes of glucose excursions within hours of their occurrence. Finally, only 2 participants voiced Concerns About Use of Sugar Sleuth; they perceived the app as sometimes too demanding of information or as not attuned to the socioeconomic backgrounds of PWDs from diverse populations. CONCLUSIONS: Results suggest that Sugar Sleuth can be an effective educational tool to enhance both patient-clinician collaboration and diabetes self-management. Findings also highlight the importance of exploring psychosocial and socioeconomic factors that may advance the understanding of PWDs' individual differences when using glycemic technology and may promote the development of customized mobile tools to improve diabetes self-management.

Sensor-augmented insulin pump therapy: results of the first randomized treat-to-target study.

BACKGROUND: The objective of the study was to evaluate the clinical effectiveness and safety of a device that combines an insulin pump with real-time continuous glucose monitoring (CGM), compared to using an insulin pump with standard blood glucose monitoring systems. METHODS: This 6-month, randomized, multicenter, treat-to-target study enrolled 146 subjects treated with continuous subcutaneous insulin infusion between the ages of 12 and 72 years with type 1 diabetes and initial A1C levels of >or=7.5%. Subjects were randomized to pump therapy with real-time CGM (sensor group [SG]) or to pump therapy and self-monitoring of blood glucose only (control group [CG]). Clinical effectiveness and safety were evaluated. RESULTS: A1C levels decreased (P<0.001) from baseline (8.44+/-0.70%) in both groups (SG, -0.71+/-0.71%; CG, -0.56+/-0.072%); however, between-group differences did not achieve significance. SG subjects showed no change in mean hypoglycemia area under the curve (AUC), whereas CG subjects showed an increase (P=0.001) in hypoglycemia AUC during the blinded periods of the study. The between-group difference in hypoglycemia AUC was significant (P<0.0002). Greater than 60% sensor utilization was associated with A1C reduction (P=0.0456). Fourteen severe hypoglycemic events occurred (11 in the SG group and three in the CG group, P=0.04). CONCLUSIONS: A1C reduction was no different between the two groups. Subjects in the CG group had increased hypoglycemia AUC and number of events during blinded CGM use; however, there was no increase in hypoglycemia AUC or number of events in the SG group. Subjects with greater sensor utilization showed a greater improvement in A1C levels.

Clinical application of emerging sensor technologies in diabetes management: consensus guidelines for continuous glucose monitoring (CGM).

Continuous glucose monitoring (CGM) is an evolving technology poised to redefine current concepts of glycemic control and optimal diabetes management. To date, there are few randomized studies examining how to most effectively use this new tool. Therefore, a group of eight diabetes specialists heard presentations on continuous glucose sensor technology and then discussed their experience with CGM in order to identify fundamental considerations, objectives, and methods for applying this technology in clinical practice. The group concluded that routine use of CGM, with real-time data showing the rate and direction of glucose change, could revolutionize current approaches to evaluating and managing glycemia. The need for such progress is indicated by the growing prevalence of inadequately treated hyperglycemia. Coordinating financial and educational resources and developing clear protocols for using glucose sensor technology are urgent priorities in promoting wide adoption of CGM by patients and health care providers. Finally, researchers, manufacturers, payers, and advocacy groups must join forces on the policy level to create an environment conducive to managing continuous data, measuring outcomes, and formalizing best practices.