Automated Insulin Delivery Beyond Glycemic Outcomes: Endpoints and Evidence.

The Official Journal of ATTD Advanced Technologies & Treatments for Diabetes Conference 22‐25 February 2023 I Berlin & Online

Background: Understanding qualities that make up trust in AID systems is imperative for successful development of systems built for long-term use. Previous research has demonstrated that trust is associated with: (a) better glycemic outcomes, (b) decreased self-management burdens, and (c) continued use of therapy. Method: In December 2018, 5,037 individuals with diabetes responded to an online survey administered by dQ&A. We analyzed a subgroup of 386 survey participants who reported on their use of an AID system (The t:slim X2™ insulin pump with Basal-IQ® technology from Tandem Diabetes Care® = 116 ; The MiniMed 670G insulin pump system from Medtronic = 270). Results: Hierarchical multiple regression analysis was used to ascertain the significance of ease of use (device level) and psychosocial (individual level) predictors of trust in AID systems. There were no issues with multicollinearity (all VIFs < 3). In Model 1, ease of use accounted for 45% of variance in trust, F (3,382) = 106.74, p < .001. After psychosocial predictors were added in Model 2, variance accounted for was 64%, explaining an additional 19% of unique variance in trust, F (3,379) = 65.46, p < .001. Conclusion: These findings suggest that both ease of use and psychosocial outcomes are distinctly informative and instrumental in the development of trust in AID systems. Disclosure M.L. Manning: Employee; Self; Tandem Diabetes Care. M. McElwee-Malloy: Employee; Self; Tandem Diabetes Care. K.C. Stoner: Other Relationship; Self; Multiple companies and organizations in the diabetes field (greater than 10). S. Habif: Employee; Self; Tandem Diabetes Care.

Hypoglycemia remains a major concern for persons with T1D using injections or “open loop” insulin pump delivery. Risk avoidance strategies are required, but often at the expense of increased hyperglycemia and elevated A1C levels. AID systems may reduce the need for human intervention by minimizing out-of-range glucose levels. We evaluated glycemic outcomes of people with T1D using the Omnipod 5 AID System, stratified by each user's time below range (TBR, % <70 mg/dL) with their prior standard therapy (ST) . Participants of 3 age groups: 2-5.9, 6-13.9, and 14-70 years, with A1C<10% used AID for 3 months at home after a 14-day ST phase. TBR and time in range (TIR, % 70-180 mg/dL) were evaluated across 3 ST TBR groups: ≤1%, >1% to <4%, and ≥4%. Trends were similar across all age groups. Overall, those with high ST TBR (≥4%) had a higher ST TIR (64.9%) ; AID substantially decreased TBR (-3.4%, -49 min/d) and increased TIR (73.9%) (Table) . Those with low ST TBR (≤1%) had lower ST TIR (50.8%) ; AID increased TIR substantially (to 67.9%) , while TBR was low (0.7%) . AID was associated with significant reductions in time below range in cohorts with high hypoglycemia risk (≥4% TBR) at baseline. In the lowest hypoglycemia risk at baseline cohort (≤1% TBR) , the median TBR remained ≤1%, although TBR was modestly higher, but this group had the largest increase in TIR. Disclosure G.P.Forlenza: Advisory Panel; Lilly, Medtronic, Consultant; Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care, Inc., Research Support; Dexcom, Inc., Insulet Corporation, Medtronic, Tandem Diabetes Care, Inc. L.M.Laffel: Advisory Panel; Medtronic, Roche Diabetes Care, Consultant; Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompé, Insulet Corporation, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk, Provention Bio, Inc. J.Sherr: Advisory Panel; Bigfoot Biomedical, Inc., Cecelia Health, Insulet Corporation, Medtronic, Vertex Pharmaceuticals Incorporated, Consultant; Insulet Corporation, Lexicon Pharmaceuticals, Inc., Research Support; Dexcom, Inc., Insulet Corporation, Jaeb Center for Health Research, JDRF, Medtronic, National Institute of Diabetes and Digestive and Kidney Diseases, Speaker's Bureau; Lilly Diabetes. C.J.Levy: Advisory Panel; Dexcom, Inc., Eli Lilly and Company, Research Support; Abbott Diabetes, Dexcom, Inc., Insulet Corporation, T1D Exchange, Tandem Diabetes Care, Inc. I.B.Hirsch: Consultant; Abbott Diabetes, Bigfoot Biomedical, Inc., GWave, Roche Diabetes Care, Research Support; Beta Bionics, Inc., Insulet Corporation, Medtronic. S.A.Macleish: Advisory Panel; Insulet Corporation. D.Desalvo: Consultant; Dexcom, Inc., Insulet Corporation, Research Support; Insulet Corporation. V.Shah: Advisory Panel; Medscape, Sanofi, Consultant; Dexcom, Inc., Research Support; Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Novo Nordisk. A.Bhargava: Research Support; Abbott Diabetes, AbbVie Inc., Boehringer Ingelheim International GmbH, Boston Therapeutics, Inc., Covance, Dexcom, Inc., Eli Lilly and Company, Gan & Lee Pharmaceuticals, Insulet Corporation, Kowa Pharmaceuticals America, Inc., Lexicon Pharmaceuticals, Inc., Madrigal Pharmaceuticals, Inc., Medtronic, Novo Nordisk, Poxel SA, Quintiles, Sanofi, Senseonics, Tolerion, Inc., Viking Therapeutics, vTv Therapeutics. T.C.Jones: None. G.Aleppo: Consultant; Insulet Corporation, Research Support; AstraZeneca, Dexcom, Inc., Eli Lilly and Company, Fractyl Health, Inc., Insulet Corporation, Novo Nordisk, Speaker's Bureau; Dexcom, Inc. B.W.Bode: Advisory Panel; CeQur SA, MannKind Corporation, Medtronic, Novo Nordisk, Zealand Pharma A/S, Consultant; Bigfoot Biomedical, Inc., Research Support; Abbott, Beta Bionics, Inc., Dexcom, Inc., Diasome, Dompé, Eli Lilly and Company, Insulet Corporation, IQVIA Inc., Jaeb Center for Health Research, Medtronic, Novo Nordisk, Provention Bio, Inc., REMD Biotherapeutics, Sanvita Medical, Senseonics, ViaCyte, Inc., Speaker's Bureau; Abbott, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Insulet Corporation, MannKind Corporation, Novo Nordisk, Sanofi, Xeris Pharmaceuticals, Inc., Stock/Shareholder; AgaMatrix, Glytec, LLC. L.M.Huyett: Employee; Insulet Corporation, Stock/Shareholder; Insulet Corporation. T.T.Ly: Employee; Insulet Corporation, Stock/Shareholder; Insulet Corporation. Omnipod 5 research group: n/a. A.L.Carlson: Advisory Panel; MannKind Corporation; Employee; Bright Health Group; Other Relationship; Medtronic; Research Support; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Novo Nordisk, Sanofi, UnitedHealth Group. Funding This study was funded by Insulet Corporation.

Older adults with type 1 diabetes (≥65 years) are often under-represented in clinical trials of automated insulin delivery (AID) systems. We sought to test the efficacy of a recently FDA-approved AID system in this population. Participants with type 1 diabetes used sensor-augmented pump (SAP) therapy for four weeks and then used an AID system (Control-IQ) for four weeks. In addition to glucose control variables, patient-reported outcomes (PRO) were assessed with questionnaires and sleep parameters were assessed by actigraphy. Fifteen older adults (mean age 68.7 ± 3.3, HbA1c of 7.0 ± 0.8) completed the pilot trial. Glycemic outcomes improved during AID compared to SAP. During AID use, mean glucose was 146.0 mg/dL; mean percent time in range (TIR, 70-180 mg/dL) was 79.6%; median time below 70 mg/dL was 1.1%. The AID system was in use 92.6% ± 7.0% of the time. Compared to SAP, while participants were on AID the TIR increased significantly (+10%, P = .002) accompanied by a reduction in both time above 180 mg/dL (-6.9%, P = .005) and below 70 mg/dl (-0.4%, P = .053). Diabetes-related distress decreased significantly while using AID (P = .028), but sleep parameters remained unchanged. Use of this AID system in older adults improved glycemic control with high scores in ease of use, trust, and usability. Participants reported an improvement in diabetes distress with AID use. There were no significant changes in sleep.

Introduction & Objective: Glycemic outcomes in youth with T1D have not been compared between the two most commonly used AID systems in the United States, Insulet Omnipod 5 (OP5) and Tandem Control IQ (CIQ). Our aim is to perform the first head-to-head analysis of changes in TIR in youth initiating AID systems to further support clinical counseling and decision making. Methods: This single center, retrospective chart review included youth < 21 years who were prescribed OP5 or CIQ between 2022-2023. AID start dates, pump data, 14-day baseline and 90-day continuous glucose monitor data were obtained from proprietary cloud-based software. A multiple linear regression model assessed for differences in 90-day time in range (TIR) according to AID system initiated. Results: Among 470 youth, 228 (48.5%) started OP5 and 242 (51.4%) initiated CIQ. OP5 users were more likely to identify as female (57.5% vs 47.1%, p=0.03) and non-Hispanic Black (15.4% vs 4.5%, p=<0.01). OP5 users had a shorter TID duration (1.7 [IQR 0.7, 4.4] vs. 5.9 [IQR 2.9, 5.9], p=<0.01) and were more likely to have transitioned to AID from multiple daily injections (76.8% vs 19%, p<0.01). Baseline TIR was similar between groups (OP5 51.0% [IQR 36.3, 67.4] vs CIQ 52.9% [IQR 39.3, 66.3], p=0.74). There was no difference in AID active time (OP5 89.6% vs CIQ 87.4%, p=0.10) or user-initiated boluses per day (OP5 5.0 vs CIQ 5.3, p=0.21). 90-day TIR increased in both groups (p<0.001), rising by 11.9%-points (95% CI [10.3,13.4]) in OP5 users and 9.9%-points (95% CI[8.4,11.5]) in CIQ users. After adjusting for sex, race/ethnicity, T1D duration and prior regimen, improvements in 90-day TIR did not differ between AID systems (p=0.11). Conclusion: Improvements in 90-day TIR following AID initiation among youth with T1D are significant and do not differ between commonly prescribed systems. Further studies are required to understand patient-related factors that may lead to differential success with a particular AID system. Disclosure S. Gera: None. A. Rearson: None. G. Baker: None. J.L. Douvas: None. N. Alicea-Trelles: None. R.J. Gallop: None. S. Meighan: Speaker's Bureau; Dexcom, Inc. B.E. Marks: Research Support; Tandem Diabetes Care, Inc., Dexcom, Inc., Medtronic, Digostics. Advisory Panel; International Society for Pediatric and Adolescent Diabetes, American Diabetes Association, T1D Exchange. Board Member; Juvenile Diabetes Research Foundation (JDRF).

This study investigates glucose conditions preceding and following various hypoglycemia levels in individuals with type 1 diabetes using open-source automated insulin delivery (AID) systems. It also seeks to evaluate relationships between hypoglycemia and subsequent glycemic variability. Methods: Analysis of continuous glucose monitor (CGM) data from 122 adults with type 1 diabetes using open-source AID from the OpenAPS Data Commons was conducted. This study comprehensively analyzed the effects of hypoglycemia on glycemic variability, covering time periods before and after hypoglycemia. Results: Glucose variability normalization post-hypoglycemia can take up to 48 h, with severe hypoglycemia (41–50 mg/dL) linked to prolonged normalization. A cyclical pattern was observed where hypoglycemia predisposes individuals to further hypoglycemia, even with AID system use. A rise in glucose levels often precedes hypoglycemia, followed by an elevated mean time above range (TAR) post-hypoglycemia, indicating a ‘rebound’ effect. The experimental results are further validated on T1DEXI data (n = 222), originating from commercial AID systems. Different hypoglycemia categorization approaches did not show significant differences in glycemic variability outcomes. The level of hypoglycemia does influence the pattern of subsequent glucose fluctuations. Conclusion: Hypoglycemia, especially at lower levels, significantly impacts subsequent glycemic variability, even with the use of open-source AID systems. This should be studied further with a broader set of commercial AID systems to understand if these patterns are true of all types of AID systems. If these patterns occur in all types of AID systems, it underscores potential opportunities for enhancements in AID algorithms and highlights the importance of educating healthcare providers and people with diabetes about post-hypoglycemia glucose variability.

Effect of automated insulin delivery systems on person-reported outcomes in people with diabetes: a systematic review and meta-analysis

As there is a pressing need for better treatment options for type 2 diabetes (T2D) , it is crucial to explore new technologies such as automated insulin delivery (AID) in this population. Little is known about how successful these systems will be in T2D, especially over a longer duration of use. The safety and practicability of the Omnipod 5 AID System in adults with T2D was previously demonstrated during an 8-week outpatient feasibility trial. Those completing this initial study were invited to continue system use for an additional 26 weeks to assess longer-term efficacy. We present results from the first 13-week follow-up assessment of the extension study. In the initial study, adults with T2D (A1C >8%) previously on either basal-only (n=12) or basal-bolus insulin injections (n=12) , with or without CGM, used AID for 8 weeks following 14 days of their standard therapy. Those participating in the extension study continued AID use, and A1C was measured again after 13 weeks (21 weeks of total AID use) . Efficacy was assessed by change in A1C from baseline. Most participants (N=22, 92%) continued into the extension phase. Two of these participants had completed the initial study before the extension study was available but were allowed to re-join, resulting in a 2-4-month return to their standard therapy before resuming AID. Participants were aged (mean±SD) 61±8y with BMI 33.9±4.4kg/m2, diabetes duration 19±9y, and baseline A1C 9.4±0.9% (range: 8.1-11.7%) . Mean A1C decreased to 8.0±0.7% after 8 weeks of AID (p<0.05) . After an additional 13 weeks of use, mean A1C was 7.7±0.7%, corresponding to an overall decrease of 1.6±1.0% from baseline to 21 weeks of total use (p<0.05) . There were no episodes of severe hypoglycemia during the study. The continued improvement in A1C with longer duration of AID use with the Omnipod 5 System demonstrates a durable and clinically meaningful benefit for participants with previously sub-optimal glycemic control outcomes on injection insulin therapy. Disclosure G.M.Davis: Consultant; Medscape, Research Support; Insulet Corporation. A.L.Peters: Advisory Panel; Abbott Diabetes, AstraZeneca, Eli Lilly and Company, Novo Nordisk, Shouti, Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S, Other Relationship; Omada Health, Inc., Research Support; Abbott Diabetes, Dexcom, Inc., Insulet Corporation, Leona M. and Harry B. Helmsley Charitable Trust, Stock/Shareholder; Teladoc Health. B.W.Bode: Advisory Panel; CeQur SA, MannKind Corporation, Medtronic, Novo Nordisk, Zealand Pharma A/S, Consultant; Bigfoot Biomedical, Inc., Research Support; Abbott, Beta Bionics, Inc., Dexcom, Inc., Diasome, Dompé, Eli Lilly and Company, Insulet Corporation, IQVIA Inc., Jaeb Center for Health Research, Medtronic, Novo Nordisk, Provention Bio, Inc., REMD Biotherapeutics, Sanvita Medical, Senseonics, ViaCyte, Inc., Speaker's Bureau; Abbott, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Insulet Corporation, MannKind Corporation, Novo Nordisk, Sanofi, Xeris Pharmaceuticals, Inc., Stock/Shareholder; AgaMatrix, Glytec, LLC. A.L.Carlson: Advisory Panel; MannKind Corporation, Employee; Bright Health Group, Other Relationship; Medtronic, Research Support; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Novo Nordisk, Sanofi, UnitedHealth Group. B.Dumais: Employee; Insulet Corporation. T.Vienneau: Employee; Insulet Corporation, Stock/Shareholder; Dexcom, Inc., GlaxoSmithKline plc., Insulet Corporation. L.M.Huyett: Employee; Insulet Corporation, Stock/Shareholder; Insulet Corporation. T.T.Ly: Employee; Insulet Corporation, Stock/Shareholder; Insulet Corporation. Funding This study was funded by Insulet Corporation.

The mainstay of type 1 diabetes (T1D) management in pregnancy is optimization of glucose levels in a tight range. Achieving euglycemia has been revolutionized by advances in diabetes technology, including the development of automated insulin delivery (AID) systems. A small but growing population of gravidas with T1D elects to pursue off-label use of AID systems in pregnancy, and their outcomes have been described in numerous observational cohorts. This review aims to aggregate data from all available observational studies examining glycemic, maternal, and neonatal outcomes associated with antenatal AID use. A total of 243 pregnancies managed antenatally with AID were described in 24 publications, with largely reassuring outcomes data. Time in range (TIR) with commercial AID systems was generally acceptable, with many patients reaching pregnancy target TIR > 70% by the third trimester. Time in range with open-source AID systems appeared even higher, although with the potential tradeoff of worse time below range (TBR). Clinically, there do not appear to be major differences in pregnancy outcomes between AID systems and other methods of insulin delivery, although this assumption is based largely on indirect comparisons with other population-level reports rather than direct comparisons within analytic observational cohorts. Clinical outcomes appear superior with open-source AID compared with commercial AID, although this should be interpreted with caution based on the small sample size of this subpopulation (n = 16) and potential confounding. The real-world evidence generated by these observational studies provides invaluable information for patients and providers seeking to improve outcomes for gravidas with T1D.

Background and Objectives: Automated insulin delivery (AID) systems represent a major advancement in type 1 diabetes (T1D) management, particularly in pediatric populations. However, real-world evidence comparing their effectiveness to conventional multiple daily injection (MDI) therapy in youth remains limited. This study aimed to evaluate the impact of transitioning from MDI therapy to AID systems on glycemic control in children and adolescents with T1D, and to explore potential differences based on baseline HbA1c levels and device type. Materials and Methods: In this single-center, retrospective observational study, 76 children and adolescents with T1D were evaluated before and after switching from MDI to either the Medtronic MiniMed™ 780G or Tandem t:slim X2™ Control-IQ system. Glycemic control was assessed using continuous glucose monitoring (CGM)-derived metrics at three time points: the last 15 days of MDI therapy (T0), 15 days after (T1), and 6 months after (T2) AID initiation. Statistical comparisons were conducted across time points and between subgroups stratified by baseline HbA1c and AID system. Results: Significant improvements in glycemic control were observed as early as 15 days after AID initiation, with sustained benefits at 6 months. Time in range (TIR) increased from 62.0% at baseline to 76.7% at 15 days and 75.8% at 6 months, and time in tight range (TITR) from 39.8% to 53.9% at T1 and 52.1% at T2 (both p < 0.001). Improvements were more pronounced in participants with higher baseline HbA1c (+16.9% for TITR and +22.3% for TIR). No significant differences in glycemic outcomes were observed between device groups, although algorithm-driven differences in insulin delivery patterns were noted. Total daily insulin dose and BMI increased significantly over time (p < 0.001 and p = 0.008, respectively). Conclusions: AID therapy leads to rapid and sustained improvements in glycemic control among youth with T1D, particularly in those with suboptimal baseline control. These benefits highlight the clinical value of AID systems, while also emphasizing the need for monitoring potential metabolic impacts.

Glycemic outcomes in youth with type 1 diabetes (T1D) in the United States using the 2 most common automated insulin delivery (AID) systems, Insulet Omnipod 5 (OP5) and Tandem Control IQ (CIQ), have not been compared. We performed the first head-to-head analysis of changes in glycemic metrics among youth initiating AID. This single-center, retrospective study included youth < 21 years with T1D, who started OP5 or CIQ between January 2020 and December 2023, and had ≥ 70% continuous glucose monitoring (CGM) active time. We obtained 14-day baseline and 90-day CGM and AID data. A multiple linear regression model assessed for changes in 90-day time in range (TIR) according to AID system, adjusting for covariates. Subanalyses were conducted according to baseline TIR categories. Among the 428 included youth, there were 214 (50%) in each AID group. OP5 users had a shorter T1D duration (1.6 vs 5.5 years, P < .001) and were more likely to have transitioned from multiple daily injections (76.1% vs 20.1%, P < .001). Baseline TIR was similar between groups (OP5 51.6% vs CIQ 53.1%, P = .70). 90-day TIR increased in both groups (P < .001), rising by 11.8 percentage points (95% CI [10.4, 13.3]) in OP5 users and 9.8 percentage points (95% CI [8.3, 11.2]) in CIQ users, without any significant between-group differences (P = .08). There were no between-group differences in 90-day TIR according to categorical baseline TIR. There are no clinically significant differences in 90-day TIR among youth with T1D initiating the 2 most commonly used AID systems. Patient preference and shared decision making should continue to guide the selection of AID systems.

MiniMed 780G was the first automated insulin delivery (AID) system approved in Poland. Although it has been studied extensively, there are relatively less data regarding its use in children with type 1 diabetes from the onset of the disease. We aimed to evaluate and compare glycemic parameters in children treated from type 1 diabetes onset with either an AID system or a pump with predictive-low glucose suspend (SAP-PLGS). We retrospectively gathered anthropometric data and systems records of 50 children with a newly diagnosed type 1 diabetes, 22 using an AID system (aged 9.66 ± 3.76 years), and 28 using a SAP-PLGS device (aged 8.13 ± 4.2 years). Glycemic parameters and other collected data were compared at four different time points: the first 2 weeks using the insulin pump and 2 weeks after 3, 6, and 12 months of insulin therapy. After the first year of treatment, we found in the AID group higher time in range (TIR) 70-180 mg/dL (P = 0.001) as well as time in tight range (TITR) 70-140 mg/dL (P = 0.0003). There were no significant differences in the C-peptide level after 1 year of treatment between the two studied groups (P = 0.41). Using the AID system from the onset of type 1 diabetes resulted in improved glycemic control parameters in the studied children compared with using SAP-PLGS. The C-peptide preservation was comparable in both analyzed groups.

A Review of Automated Insulin Delivery Use in Type 1 Diabetes During Pregnancy.

The Omnipod 5 AID System is a tubeless hybrid closed-loop system with on-body operation and customizable glucose targets. Safe and effective system use was demonstrated in children aged 2-5.9y with type 1 diabetes (T1D) during a 3-mo pivotal study. To evaluate durability of glycemic benefit, we analyzed results from 9mo of an ongoing extension study, totaling 12mo of system use. In the pivotal study, participants used the system for 3mo at home, after 14d of their standard therapy (ST, pump or multiple daily injections) . They were then invited to participate in the extension study. Safety endpoints were occurrence of severe hypoglycemia (SH) and diabetic ketoacidosis (DKA) . Glycemic outcomes were A1C and percent time in ranges (TIR 70-180 mg/dL, TBR &amp;lt;70 mg/dL, TAR &amp;gt;180 mg/dL) during 3-mo AID intervals compared with ST. All pivotal trial participants (N=80) , aged (mean±SD) 4.7±1.0y with T1D duration 2.3±1.1y and total daily insulin of 14±4U (range: 5.3-27U) at baseline, enrolled in the extension. Improved outcomes were observed for up to 12mo, including lower A1C and greater TIR during each AID interval compared with ST (all p&amp;lt;0.05, Table) . There were no episodes of DKA or SH in the 12-mo study. The safety and improved glycemic outcomes from the initial 3mo pivotal study persisted for an additional 9mo, indicating the potential long-term benefit of the Omnipod 5 System in very young children with T1D. Disclosure D.Desalvo: Consultant; Dexcom, Inc., Insulet Corporation, Research Support; Insulet Corporation. D.W.Hansen: None. T.T.Ly: Employee; Insulet Corporation, Stock/Shareholder; Insulet Corporation. Omnipod 5 in preschoolers study group: n/a. B.W.Bode: Advisory Panel; CeQur SA, MannKind Corporation, Medtronic, Novo Nordisk, Zealand Pharma A/S, Consultant; Bigfoot Biomedical, Inc., Research Support; Abbott, Beta Bionics, Inc., Dexcom, Inc., Diasome, Dompé, Eli Lilly and Company, Insulet Corporation, IQVIA Inc., Jaeb Center for Health Research, Medtronic, Novo Nordisk, Provention Bio, Inc., REMD Biotherapeutics, Sanvita Medical, Senseonics, ViaCyte, Inc., Speaker's Bureau; Abbott, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Insulet Corporation, MannKind Corporation, Novo Nordisk, Sanofi, Xeris Pharmaceuticals, Inc., Stock/Shareholder; AgaMatrix, Glytec, LLC. G.P.Forlenza: Advisory Panel; Lilly, Medtronic, Consultant; Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care, Inc., Research Support; Dexcom, Inc., Insulet Corporation, Medtronic, Tandem Diabetes Care, Inc. L.M.Laffel: Advisory Panel; Medtronic, Roche Diabetes Care, Consultant; Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompé, Insulet Corporation, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk, Provention Bio, Inc. B.A.Buckingham: Advisory Panel; Arecor, Lilly Diabetes, Medtronic, Other Relationship; Insulet Corporation, Research Support; Insulet Corporation, Lilly Diabetes, Medtronic. A.B.Criego: Advisory Panel; Insulet Corporation, Other Relationship; Medscape, Sanofi, Research Support; Abbott Diabetes, Dexcom, Inc., Insulet Corporation, Medtronic. M.Schoelwer: Other Relationship; Dexcom, Inc., Research Support; Insulet Corporation, Medtronic, Tandem Diabetes Care, Inc. S.A.Macleish: Advisory Panel; Insulet Corporation. J.Sherr: Advisory Panel; Bigfoot Biomedical, Inc., Cecelia Health, Insulet Corporation, Medtronic, Vertex Pharmaceuticals Incorporated, Consultant; Insulet Corporation, Lexicon Pharmaceuticals, Inc., Research Support; Dexcom, Inc., Insulet Corporation, Jaeb Center for Health Research, JDRF, Medtronic, National Institute of Diabetes and Digestive and Kidney Diseases, Speaker's Bureau; Lilly Diabetes. Funding Insulet Corporation

As increasing numbers of people with insulin-managed diabetes use automated insulin delivery (AID) systems or seek such technologies, healthcare providers are faced with a steep learning curve. Healthcare providers need to understand how to support these technologies to help inform shared decision making, discussing available options, implementing them in the clinical setting, and guiding users in special situations. At the same time, there is a growing diversity of commercial and open source automated insulin delivery systems that are evolving at a rapid pace. This practical guide seeks to provide a conversational framework for healthcare providers to first understand and then jointly assess AID system options with users and caregivers. Using this framework will help HCPs in learning how to evaluate potential new commercial or open source AID systems, while also providing a guide for conversations to help HCPs to assess the readiness and understanding of users for AID systems. The choice of an AID system is not as simple as whether the system is open source or commercially developed, and indeed there are multiple criteria to assess when choosing an AID system. Most importantly, the choices and preferences of the person living with diabetes should be at the center of any decision around the ideal automated insulin delivery system or any other diabetes technology. This framework highlights issues with AID use that may lead to burnout or perceived failures or may otherwise cause users to abandon the use of AID. It discusses the troubleshooting of basic AID system operation and discusses more advanced topics regarding how to maximize the time spent on AID systems, including how to optimize settings and behaviors for the best possible outcomes with AID technology for people with insulin-requiring diabetes. This practical approach article demonstrates how healthcare providers will benefit from assessing and better understanding all available AID system options to enable them to best support each individual.