Initiating hybrid closed loop: A program evaluation of an educator-led Control-IQ follow-up at a large pediatric clinic

Increasing Use of Diabetes Devices: What Do Health Care Professionals Need?

Despite evidence of improved diabetes outcomes with diabetes technology such as continuous glucose monitoring (CGM) systems, insulin pumps, and hybrid closed-loop (HCL) insulin delivery systems, these devices are underutilized in clinical practice for the management of insulin-requiring diabetes. This low uptake may be the result of health care providers' (HCPs') lack of confidence or time to prescribe and manage devices for people with diabetes. We administered a survey to HCPs in primary care, pediatric endocrinology, and adult endocrinology practices in the United States. Responding HCPs expressed a need for device-related insurance coverage tools and online data platforms with integration to electronic health record systems to improve diabetes technology uptake in these practice settings across the United States.

Consensus Recommendations for the Use of Automated Insulin Delivery Technologies in Clinical Practice

The significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers, and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past 6 years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials and real-world studies have shown that the use of AID systems is safe and effective in helping PwD achieve their long-term glycemic goals while reducing hypoglycemia risk. Thus, AID systems have recently become an integral part of diabetes management. However, recommendations for using AID systems in clinical settings have been lacking. Such guided recommendations are critical for AID success and acceptance. All clinicians working with PwD need to become familiar with the available systems in order to eliminate disparities in diabetes quality of care. This report provides much-needed guidance for clinicians who are interested in utilizing AIDs and presents a comprehensive listing of the evidence payers should consider when determining eligibility criteria for AID insurance coverage.

Efficacy and Safety of Tandem Control IQ Without User-Initiated Boluses in Adults with Uncontrolled Type 1 Diabetes

Background: Adults with poorly controlled type 1 diabetes (T1D) who are missing meal boluses are typically excluded from clinical trials of diabetes technologies. We investigated the long-term real-life outcomes of the Tandem Control IQ automated insulin delivery (AID) system in adults with T1D who are missing meal boluses. Methods: In this single-center study with 30 adults with T1D, we evaluated efficacy (A1c and time in target range [TIR]) and safety (time below range [TBR]) in adults with T1D who initiated Tandem Control IQ with minimal or no user-initiated boluses (auto >90%) compared with age, gender, and diabetes duration matched adults with T1D with intermediate (auto 50%-90%) and high bolusing behaviors (auto 10%-49%). Results: Regardless of engagement with Control IQ system, there were significant improvements in A1c and TIR in all three groups over 3, 6, and 12 months. Compared with baseline, there was significant decrease in A1c by 1.6% ± 0.8% and increase in TIR by 19.3% ± 6.4% (P < 0.001 for both) over 12 months of Tandem Control IQ use in auto >90% use group without increasing TBR. Conclusions: Tandem Control IQ is effective in lowering A1c and improving TIR without increasing TBR regardless of users' engagement with the system. Therefore, adults with T1D with high A1c who are mostly missing meal boluses should not be considered as inappropriate candidates for Control IQ AID system.

Barriers and Facilitators to Diabetes Device Adoption for People with Type 1 Diabetes

PURPOSE OF REVIEW

Diabetes technology (insulin pumps, continuous glucose monitoring, automated insulin delivery systems) has advanced significantly and provides benefits to the user. This article reviews the current barriers to diabetes device adoption and sustained use, and outlines the known and potential facilitators for increasing and sustaining device adoption.

RECENT FINDINGS

Barriers to diabetes device adoption continue to exist at the system-, provider-, and individual-level. Known facilitators to promote sustained adoption include consistent insurance coverage, support for providers and clinics, structured education and support for technology users, and device user access to support as needed (e.g., through online resources). Systemic barriers to diabetes device adoption persist while growing evidence demonstrates the increasing benefits of newest devices and systems. There are ongoing efforts to develop evidence-based structured education programs to support device adoption and sustained use.

Trends in Glycemic Control Among Youth and Young Adults With Diabetes: The SEARCH for Diabetes in Youth Study

OBJECTIVE

To describe temporal trends and correlates of glycemic control in youth and young adults (YYA) with youth-onset diabetes.

RESEARCH DESIGN AND METHODS

The study included 6,369 participants with type 1 or type 2 diabetes from the SEARCH for Diabetes in Youth study. Participant visit data were categorized into time periods of 2002-2007, 2008-2013, and 2014-2019, diabetes durations of 1-4, 5-9, and ≥10 years, and age groups of 1-9, 10-14, 15-19, 20-24, and ≥25 years. Participants contributed one randomly selected data point to each duration and age group per time period. Multivariable regression models were used to test differences in hemoglobin A1c (HbA1c) over time by diabetes type. Models were adjusted for site, age, sex, race/ethnicity, household income, health insurance status, insulin regimen, and diabetes duration, overall and stratified for each diabetes duration and age group.

RESULTS

Adjusted mean HbA1c for the 2014-2019 cohort of YYA with type 1 diabetes was 8.8 ± 0.04%. YYA with type 1 diabetes in the 10-14-, 15-19-, and 20-24-year-old age groups from the 2014-2019 cohort had worse glycemic control than the 2002-2007 cohort. Race/ethnicity, household income, and treatment regimen predicted differences in glycemic control in participants with type 1 diabetes from the 2014-2019 cohort. Adjusted mean HbA1c was 8.6 ± 0.12% for 2014-2019 YYA with type 2 diabetes. Participants aged ≥25 years with type 2 diabetes had worse glycemic control relative to the 2008-2013 cohort. Only treatment regimen was associated with differences in glycemic control in participants with type 2 diabetes.

CONCLUSIONS

Despite advances in diabetes technologies, medications, and dissemination of more aggressive glycemic targets, many current YYA are less likely to achieve desired glycemic control relative to earlier cohorts.

Real-World Use of a New Hybrid Closed Loop Improves Glycemic Control in Youth with Type 1 Diabetes

Objective: To describe real-world outcomes for youth using the Tandem t:slim X2 insulin pump with Control-IQ technology ("Control-IQ") for 6 months at a large pediatric clinic. Methods: Youth with type 1 diabetes, who started Control-IQ for routine care, were prospectively followed. Data on system use and glycemic control were collected before Control-IQ start, and at 1, 3, and 6 months after start. Mixed models assessed change across time; interactions with baseline hemoglobin A1c (HbA1c) and age were tested. Results: In 191 youth (median age 14, 47% female, and median HbA1c 7.6%), percent time with glucose levels 70-180 mg/dL (time-in-range [TIR]) improved from 57% at baseline to 66% at 6 months (P < 0.001). The proportion of participants reaching TIR target (>70%) doubled from 23.5% at baseline to 47.8% at 3 months, sustaining at 46.7% at 6 months (P < 0.001). Glucose management indicator (approximation of HbA1c) improved from 7.5% at baseline to 7.1% at 3 months and 7.2% at 6 months (P < 0.001). Those with higher baseline HbA1c experienced the most substantial improvements in glycemic control. Percent time using the Control-IQ feature was 86.4% at 6 months, and <4% of cohort discontinued use. Conclusion: The Control-IQ system clinically and significantly improved glycemic control in a large sample of youth. System use was high at 6 months, with only a small proportion discontinuing use, indicating potential for sustaining results long term.

Effectiveness of a closed-loop control system and a virtual educational camp for children and adolescents with type 1 diabetes: A prospective, multicentre, real-life study

AIM

To evaluate the impact of a virtual educational camp (vEC) on glucose control in children and adolescents with type 1 diabetes using a closed-loop control (CLC) system.

MATERIALS AND METHODS

This was a prospective multicentre study of children and adolescents with type 1 diabetes using the Tandem Basal-IQ system. Insulin pumps were upgraded to Control-IQ, and children and their parents participated in a 3-day multidisciplinary vEC. Clinical data, glucose metrics and HbA1c were evaluated over the 12 weeks prior to the Control-IQ update and over the 12 weeks after the vEC.

RESULTS

Forty-three children and adolescents (aged 7-16 years) with type 1 diabetes and their families participated in the vEC. The median percentage of time in target range (70-180 mg/dL; TIR) increased from 64% (interquartile range [IQR] 56%-73%) with Basal-IQ to 76% (IQR 71%-81%) with Control-IQ (P < .001). After the vEC, more than 75% of participants achieved a TIR of more than 70%. The percentage of time between 180 and 250 mg/dL and above 250 mg/dL decreased by 5% (P < .01) and 6% (P < .01), respectively, while the time between 70 and 54 mg/dL and below 54 mg/dL remained low and unaltered. HbA1c decreased by 0.5% (P < .01). There were no episodes of diabetic ketoacidosis or severe hypoglycaemia.

CONCLUSIONS

In this study of children managing their diabetes in a real-world setting, more than 75% of children who participated in a vEC after starting a CLC system could obtain and maintain a TIR of more than 70%. The vEC was feasible and resulted in a significant and persistent improvement in TIR in children and adolescents with type 1 diabetes.

Initiating hybrid closed loop: A program evaluation of an educator-led Control-IQ follow-up at a large pediatric clinic

BACKGROUND

Control-IQ (Tandem Diabetes) is a hybrid closed-loop (HCL) system that users self-initiate after completing online training. Best practices for clinical follow-up are not known. Our quality improvement objective was to evaluate the usefulness of an educator-led follow-up program for new HCL users in a type 1 diabetes pediatric clinic.

METHODS

We implemented an ''HCLCheck-in'' program, first determining when users started HCL, then having diabetes educators contact them for a follow-up call 2-weeks after start. Educators used a Clinical Tool to inform insulin dose and behavior recommendations, and used four benchmarks to determine need for further follow-up: ≥71% HCL use, ≥71% CGM use, ≥60% Time-in-Range (TIR, 70-180 mg/dL), <5% below 70 mg/dL. Family and educator satisfaction were surveyed.

RESULTS

One-hundred-twenty-three youth [mean age 13.6 ± 3.7 y, 53.7% female, mean HbA1c 7.6 ± 1.4% (60 mmol/mol)] completed an HCLCheck-in call a median (IQR) of 18(15, 21) days post-HCL start. 74 users (60%) surpassed benchmarks with 94% HCL use and 71% TIR. Of the 49 who did not, 16 completed a second call, and improved median TIR 12.5% (p = 0.03). HCL users reported high satisfaction with the program overall [median 10 (9, 10) out of 10]. Educators spent a median of 45 (32,70) minutes per user and rated satisfaction with the program as 8 (7,9.5) and the Tool as 9 (9, 10).

CONCLUSION

Our HCLCheck-in program received high satisfaction ratings and resulted in improved TIR for those initially not meeting benchmarks, suggesting users may benefit from early follow-up. Similar programs may be beneficial for other new technologies.