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Given the proven benefits of screening to reduce diabetic ketoacidosis (DKA) likelihood at the time of stage 3 type 1 diabetes diagnosis, and emerging availability of therapy to delay disease progression, type 1 diabetes screening programs are being increasingly emphasized. Once broadly implemented, screening initiatives will identify significant numbers of islet autoantibody-positive (IAb+) children and adults who are at risk for (confirmed single IAb+) or living with (multiple IAb+) early-stage (stage 1 and stage 2) type 1 diabetes. These individuals will need monitoring for disease progression; much of this care will happen in nonspecialized settings. To inform this monitoring, JDRF, in conjunction with international experts and societies, developed consensus guidance. Broad advice from this guidance includes the following: 1) partnerships should be fostered between endocrinologists and primary care providers to care for people who are IAb+; 2) when people who are IAb+ are initially identified, there is a need for confirmation using a second sample; 3) single IAb+ individuals are at lower risk of progression than multiple IAb+ individuals; 4) individuals with early-stage type 1 diabetes should have periodic medical monitoring, including regular assessments of glucose levels, regular education about symptoms of diabetes and DKA, and psychosocial support; 5) interested people with stage 2 type 1 diabetes should be offered trial participation or approved therapies; and 6) all health professionals involved in monitoring and care of individuals with type 1 diabetes have a responsibility to provide education. The guidance also emphasizes significant unmet needs for further research on early-stage type 1 diabetes to increase the rigor of future recommendations and inform clinical care., (© 2024 by the American Diabetes Association and the European Association for the Study of Diabetes.)

Despite the benefits of continuous glucose monitoring (CGM), there is lower use of this technology among non-Hispanic Black and Hispanic people with type 1 diabetes compared with their non-Hispanic White counterparts. The T1D Exchange Quality Improvement Collaborative recruited five endocrinology centers to pilot an equity-focused quality improvement (QI) study to reduce racial inequities in CGM use. The centers used rapid QI cycles to test and expand interventions such as provider bias training, translation of CGM materials, provision of CGM education in multiple languages, screening for social determinants of health, and shared decision-making. After implementation of these interventions, median CGM use increased by 7% in non-Hispanic White, 12% in non-Hispanic Black, and 15% in Hispanic people with type 1 diabetes. The gap between non-Hispanic White and non-Hispanic Black patients decreased by 5%, and the gap between non-Hispanic White and Hispanic patients decreased by 8%., Competing Interests: O.E. is a compensated Health Equity Advisory Board member for Medtronic Diabetes and serves as principal investigator for investigator-led projects sponsored by Abbott, Eli Lilly, Insulet, and Medtronic. He is compensated through his organization, the T1D Exchange. No other potential conflicts of interest relevant to this article were reported., (© 2024 by the American Diabetes Association.)

This large type 1 diabetes cohort study showed that insulin pump utilization has increased over time and that use differs by sex, insurance type, and race/ethnicity. Insulin pump use was associated with more optimal A1C, increased use of continuous glucose monitoring (CGM), and lower rates of diabetic ketoacidosis and severe hypoglycemia. People who used an insulin pump with CGM had lower rates of acute events than their counterparts who used an insulin pump without CGM. These findings highlight the need to improve access of diabetes technology through provider engagement, multidisciplinary approaches, and efforts to address health inequities., Competing Interests: O.E. is on the Medtronic Health Equity Advisor Board. H.K.A. has received research grants through the University of Colorado from Dexcom, Eli Lilly, IM Therapeutics, MannKind, REMD, and Senseonics. No other potential conflicts of interest relevant to this article were reported., (© 2024 by the American Diabetes Association.)

The American Diabetes Association's Standards of Care in Diabetes recommends the use of diabetes technology such as continuous glucose monitoring systems and insulin pumps for people living with type 1 diabetes. Unfortunately, there are multiple barriers to uptake of these devices, including local diabetes center practices. This study aimed to examine overall change and center-to-center variation in uptake of diabetes technology across 21 pediatric centers in the T1D Exchange Quality Improvement Collaborative. It found an overall increase in diabetes technology use for most centers from 2021 to 2022 with significant variation., Competing Interests: M.A.C. is the chief medical officer of Glooko and receives research support from Abbott Diabetes Care and Dexcom. O.E. is a Diabetes Health Equity Advisory Board member for Medtronic; his organization, T1D Exchange, has received research support on his behalf from Abbott, Dexcom, Eli Lilly, Medtronic Diabetes, and Vertex; and he has received honoraria from Medtronic Diabetes and Vertex. No other potential conflicts of interest relevant to this article were reported., (© 2024 by the American Diabetes Association.)

Screening for autoantibodies associated with type 1 diabetes can identify people most at risk for progressing to clinical type 1 diabetes and provide an opportunity for early intervention. Drawbacks and barriers to screening exist, and concerns arise, as methods for disease prevention are limited and no cure exists today. The availability of novel treatment options such as teplizumab to delay progression to clinical type 1 diabetes in high-risk individuals has led to the reassessment of screening programs. This study explored awareness, readiness, and attitudes of endocrinology providers toward type 1 diabetes autoantibody screening., Competing Interests: R.S.W. participates in clinical trials that are sponsored, through her institution, by Boehringer Ingelheim, Eli Lilly, Insulet, Medtronic, Novo Nordisk, and Tandem, and uses Dexcom continuing glucose monitoring systems in clinical research studies. O.E. is a Health Equity Advisory Board member for Medtronic Diabetes. No other potential conflicts of interest relevant to this article were reported., (© 2024 by the American Diabetes Association.)

The aim of this study was to describe rates of telemedicine use 18 months after the start of the coronavirus disease 2019 pandemic and to assess the institutional barriers to its implementation for type 1 diabetes care across centers of the T1D Exchange Quality Improvement Collaborative. Observational electronic health record data capturing telemedicine rates from 15 U.S. centers between September 2020 and September 2021 and a survey of 33 centers capturing telemedicine rates and key components of telemedicine were analyzed. A capacity score was developed and summed to a total capacity score and compared with overall telemedicine rates across centers. Telemedicine visits decreased by 17.4% from September 2020 to September 2021. Generally, it was observed that the lower the average telemedicine capacity score, the lower the rate of telemedicine visits. Despite a decline in the utilization of telemedicine 18 months after the start of the pandemic, visit rates were still 20% higher than in the pre-pandemic period. However, there is a need to improve structural components to ensure telemedicine capacity and robust telemedicine utilization., Competing Interests: J.M.L. is on the GoodRx medical advisory board and is a consultant for Tandem. O.E. is a Health Equity Advisory Board member for Medtronic Diabetes. F.V. is a consultant for Eli Lilly. No other potential conflicts of interest relevant to this article were reported., (© 2024 by the American Diabetes Association.)

Social determinants of health (SDOH) are strongly associated with outcomes for people with type 1 diabetes. Six centers in the T1D Exchange Quality Improvement Collaborative applied quality improvement principles to design iterative Plan-Do-Study-Act cycles to develop and expand interventions to improve SDOH screening rates. The interventions tested include staff training, a social risk index, an electronic health record patient-facing portal, partnerships with community organizations, and referrals to community resources. All centers were successful in improving SDOH screening rates, with individual site improvements ranging from 41 to 70% and overall screening across the six centers increasing from a baseline of 1% to 70% in 27 months., Competing Interests: O.E. is a compensated Health Equity Advisory Board member for Medtronic Diabetes and serves as principal investigator for investigator-led projects sponsored by Abbott, Eli Lilly, Insulet, and Medtronic. He is compensated through his organization, the T1D Exchange. No other potential conflicts of interest relevant to this article were reported., (© 2024 by the American Diabetes Association.)

Competing Interests: S.A. works as a health care disparities advisor for Beta Bionics and Medtronic, Inc. O.E. is an advisory board member for the Medtronic Diabetes Health Equity Council. No other potential conflicts of interest relevant to this article were reported.

Given the proven benefits of screening to reduce diabetic ketoacidosis (DKA) likelihood at the time of stage 3 type 1 diabetes diagnosis, and emerging availability of therapy to delay disease progression, type 1 diabetes screening programmes are being increasingly emphasised. Once broadly implemented, screening initiatives will identify significant numbers of islet autoantibody-positive (IAb + ) children and adults who are at risk of (confirmed single IAb + ) or living with (multiple IAb + ) early-stage (stage 1 and stage 2) type 1 diabetes. These individuals will need monitoring for disease progression; much of this care will happen in non-specialised settings. To inform this monitoring, JDRF in conjunction with international experts and societies developed consensus guidance. Broad advice from this guidance includes the following: (1) partnerships should be fostered between endocrinologists and primary-care providers to care for people who are IAb + ; (2) when people who are IAb + are initially identified there is a need for confirmation using a second sample; (3) single IAb + individuals are at lower risk of progression than multiple IAb + individuals; (4) individuals with early-stage type 1 diabetes should have periodic medical monitoring, including regular assessments of glucose levels, regular education about symptoms of diabetes and DKA, and psychosocial support; (5) interested people with stage 2 type 1 diabetes should be offered trial participation or approved therapies; and (6) all health professionals involved in monitoring and care of individuals with type 1 diabetes have a responsibility to provide education. The guidance also emphasises significant unmet needs for further research on early-stage type 1 diabetes to increase the rigour of future recommendations and inform clinical care., (© 2024. American Diabetes Association and European Association for the Study of Diabetes.)

Objective: To compare demographic, clinical, and therapeutic characteristics of children with type 1 diabetes age <6 years across three international registries: Diabetes Prospective Follow-Up Registry (DPV; Europe), T1D Exchange Quality Improvement Network (T1DX-QI; U.S.), and Australasian Diabetes Data Network (ADDN; Australasia)., Research Design and Methods: An analysis was conducted comparing 2019-2021 prospective registry data from 8,004 children., Results: Mean ± SD ages at diabetes diagnosis were 3.2 ± 1.4 (DPV and ADDN) and 3.7 ± 1.8 years (T1DX-QI). Mean ± SD diabetes durations were 1.4 ± 1.3 (DPV), 1.4 ± 1.6 (T1DX-QI), and 1.5 ± 1.3 years (ADDN). BMI z scores were in the overweight range in 36.2% (DPV), 41.8% (T1DX-QI), and 50.0% (ADDN) of participants. Mean ± SD HbA1c varied among registries: DPV 7.3 ± 0.9% (56 ± 10 mmol/mol), T1DX-QI 8.0 ± 1.4% (64 ± 16 mmol/mol), and ADDN 7.7 ± 1.2% (61 ± 13 mmol/mol). Overall, 37.5% of children achieved the target HbA1c of <7.0% (53 mmol/mol): 43.6% in DPV, 25.5% in T1DX-QI, and 27.5% in ADDN. Use of diabetes technologies such as insulin pump (DPV 86.6%, T1DX 46.6%, and ADDN 39.2%) and continuous glucose monitoring (CGM; DPV 85.1%, T1DX-QI 57.6%, and ADDN 70.5%) varied among registries. Use of hybrid closed-loop (HCL) systems was uncommon (from 0.5% [ADDN] to 6.9% [DPV])., Conclusions: Across three major registries, more than half of children age <6 years did not achieve the target HbA1c of <7.0% (53 mmol/mol). CGM was used by most participants, whereas insulin pump use varied across registries, and HCL system use was rare. The differences seen in glycemia and use of diabetes technologies among registries require further investigation to determine potential contributing factors and areas to target to improve the care of this vulnerable group., (© 2024 by the American Diabetes Association.)

Type 1 diabetes (T1D) is associated with an increased risk of cardiovascular disease (CVD). CVD occurs much earlier in people with T1D than in the general population, and several risk factors have been identified some of which are modifiable. Risk prediction models and imaging tests to detect early signs of CVD have not been extensively validated. Strategies to promote cardiovascular health (CVH) in T1D include identifying risk factors, early treatment to achieve CVH targets, and improving the education of health care providers and people with T1D., Competing Interests: Disclosure No competing financial interests exist., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Type 1 diabetes management is intricately influenced by social determinants of health. Economic status impacts access to vital resources like insulin and diabetes technology. Racism, social injustice, and implicit biases affect equitable delivery of care. Education levels affect understanding of self-care, leading to disparities in glycemic outcomes. Geographic location can limit access to health care facilities. Stressors from discrimination or financial strain can disrupt disease management. Addressing these social factors is crucial for equitable diabetes care, emphasizing the need for comprehensive strategies that go beyond medical interventions to ensure optimal health outcomes for all individuals with type 1 diabetes., Competing Interests: Conflict of interest None., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Type 1 diabetes (T1D) management has evolved over the last decade. Innovations and groundbreaking research have paved the way for improved outcomes for people with T1D. One of the major T1D focused research network that has supported real-world research studies in the United States is the T1D Exchange Quality Improvement Collaborative (T1DX-QI) Network.T1DX-QI is a large multicenter network of 55 T1D clinics that uses quality improvement, health equity framework, and population health principles to improve outcomes for people with T1D. This article summarizes insights from T1DX-QI clinical and population health improvement studies., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Digital health technologies are being utilized increasingly in the modern management of diabetes. These include tools such as continuous glucose monitoring systems, connected blood glucose monitoring devices, hybrid closed-loop systems, smart insulin pens, telehealth, and smartphone applications (apps). Although many of these technologies have a solid evidence base, from the perspective of a person living with diabetes, there remain multiple barriers preventing their optimal use, creating a digital divide. In this article, we describe many of the origins of these barriers and offer recommendations on widening access to digital health technologies for underserved populations living with diabetes to improve their health outcomes., (© 2024 The Authors. Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.)

Background: Systematic and comprehensive data acquisition from the electronic health record (EHR) is critical to the quality of data used to improve patient care. We described EHR tools, workflows, and data elements that contribute to core quality metrics in the Type 1 Diabetes Exchange Quality Improvement Collaborative (T1DX-QI)., Method: We conducted interviews with quality improvement (QI) representatives at 13 T1DX-QI centers about their EHR tools, clinic workflows, and data elements., Results: All centers had access to structured data tools, nine had access to patient questionnaires and two had integration with a device platform. There was significant variability in EHR tools, workflows, and data elements, thus the number of available metrics per center ranged from four to 17 at each site. Thirteen centers had information about glycemic outcomes and diabetes technology use. Seven centers had measurements of additional self-management behaviors. Centers captured patient-reported outcomes including social determinants of health (n = 9), depression (n = 11), transition to adult care (n = 7), and diabetes distress (n = 3). Various stakeholders captured data including health care professionals, educators, medical assistants, and QI coordinators. Centers that had a paired staffing model in clinic encounters distributed the burden of data capture across the health care team and was associated with a higher number of available data elements., Conclusions: The lack of standardization in EHR tools, workflows, and data elements captured resulted in variability in available metrics across centers. Further work is needed to support measurement and subsequent improvement in quality of care for individuals with type 1 diabetes., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: JL is on the GoodRx medical advisory board, is a consultant for Tandem Diabetes Care and has participated on a Sanofi Digital Advisory Board. OE is an advisor for Medtronic Diabetes and Sanofi Diabetes. He has received research support through his institution (T1D Exchange) from Abbott, Vertex, Eli Lilly, Dexcom and Medtronic. RW receives research support through her institution (Johns Hopkins) from Novo Nordisk as the center PI of a trial.

Objective: Medical racism contributes to adverse health outcomes. Type 1 Diabetes Exchange Quality Improvement Collaborative (T1DX-QI) is a large population-based cohort engaged in data sharing and quality improvement to drive system changes in T1D care. The annual T1DX-QI survey included questions to evaluate racial equity in diabetes care and practices to promote equity., Methods: The annual T1DX-QI survey was administered to participating clinics in fall 2022 and had a 93% response rate. There were 50 responses (pediatric: 66% and adult: 34%). Questions, in part, evaluated clinical resources and racial equity. Response data were aggregated, summarized, and stratified by pediatric/adult institutions., Results: Only 21% pediatric and 35% adult institutions felt that all their team members can articulate how medical racism contributes to adverse diabetes outcomes. Pediatric institutions reported more strategies to address medical racism than adult (3.6 vs 3.1). Organizational strategies to decrease racial discrimination included employee trainings, equity offices/committees, patient resources, and hiring practices. Patient resources included interpreter services, transportation, insurance navigation, and housing and food assistance. Hiring practices included changing prior protocols, hiring from the community, and diversifying workforces. Most institutions have offered antiracism training in the last year (pediatric: 85% and adult: 72%) and annually (pediatric: 64% and adult: 56%). Pediatric teams felt that their antiracism training was effective more often (pediatric: 60% and adult: 45%) and more commonly, they were provided resources (pediatric: 67% and adult: 47%) to help address inequities., Conclusion: Despite increased antiracism training, insufficient institutional support and perceived subeffective training still represent obstacles, especially in adult institutions. Sharing effective strategies to address medical racism will help institutions take steps to mitigate inequities., Competing Interests: Disclosure A.A. is supported by NIDDK K23 (K23DK13134201). Helmsley Charitable Foundation funds the T1DX-QI Collaborative. The other authors have no multiplicity of interest to disclose., (Copyright © 2023 AACE. Published by Elsevier Inc. All rights reserved.)

Objective: Previous studies revealed that hemoglobin A1c (HbA1c) increased overall in the United States in the past decade. In addition, health inequities in type 1 diabetes (T1D) outcomes by race/ethnicity and insurance type persist. This study examines the trends in HbA1c from 2016 to 2022 stratified by race/ethnicity and insurance in a large multicenter national database. Research Design and Methods: We analyzed glycemic outcomes and diabetes device use trends for >48,000 people living with type 1 diabetes (PwT1D) from 3 adult and 12 pediatric centers in the T1D Exchange Quality Improvement Collaborative (T1DX-QI), comparing data from 2016 to 2017 with data from 2021 to 2022. Results: The mean HbA1c in 2021-2022 was lower at 8.4% compared with the mean HbA1c in 2016-2017 of 8.7% (0.3% improvement; P  < 0.01). Over the same period, the percentage of PwT1D using a continuous glucose monitor (CGM), insulin pump, or hybrid closed-loop system increased (45%, 12%, and 33%, respectively). However, these improvements were not equitably demonstrated across racial/ethnic groups or insurance types. Racial/ethnic and insurance-based inequities persisted over all 7 years across all outcomes; comparing non-Hispanic White and non-Hispanic Black PwT1D, disparate gaps in HbA1c (1.2%-1.6%), CGM (30%), pump (25%-35%), and hybrid-closed loop system (up to 20%) are illuminated. Conclusion: Population-level data on outcomes, including HbA1c, can provide trends and insights into strategies to improve health for PwT1D. The T1DX-QI cohort showed a significant improvement in HbA1c from 2016 to 2022. Improvements in diabetes device use are also demonstrated. However, these increases were inconsistent across all racial/ethnic groups or insurance types, an important focus for future T1D population health improvement work.

Background: Health insurance coverage type differs significantly by socioeconomic status and racial group in the United States. The aim of this study was to determine whether publicly insured children and young adults with type 1 diabetes were more likely to experience adverse outcomes compared with privately insured patients with acute coronavirus disease 2019 (COVID-19) infections., Methods: Data from 619 patients with previously established type 1 diabetes who were <24 years of age with acute COVID-19 infections were analyzed from the T1D Exchange COVID-19 surveillance registry. Data for the registry was collected from 52 endocrinology clinics across the United States using an online survey tool. Each site completed the survey using electronic health record data between April 2020 and December 2021., Results: Of the 619 patients included in this study, 257 had public insurance and 362 had private insurance. Of the 257 publicly insured patients with COVID-19, 57 reported severe adverse outcomes (22%), defined as diabetic ketoacidosis (DKA) or severe hypoglycemia. In comparison, there were 25 reported adverse outcomes (7%) among the 362 privately insured patients., Conclusion: Our data reveal high rates of hospitalization and DKA among publicly insured racial/ethnic minority children and young adults with type 1 diabetes and COVID-19., Competing Interests: O.E. is the principal investigator for research projects funded through his institution by Dexcom, Eli Lilly, and Medtronic; he is also a member of the Medtronic Diabetes Health Inequity Advisory Board. No other potential conflicts of interest relevant to this article were reported., (© 2023 by the American Diabetes Association.)

This article describes successful interventions from the T1D Exchange Quality Improvement Collaborative (T1DX-QI) to reduce inequities in access to and use of continuous glucose monitoring (CGM). The author proposes a roadmap with recommendations for different stakeholders to achieve CGM equity using insights from the T1DX-QI experience., Competing Interests: O.E. is a member of the Medtronic Diabetes Health Equity Advisory Board and Sanofi Diabetes T1D Screening Advisory Board. His organization, the T1D Exchange, has received research support on his behalf from Abbott, Dexcom, Eli Lilly, Medtronic Diabetes, and Vertex. He has received honoraria from Medtronic Diabetes and Vertex. No other potential conflicts of interest relevant to this article were reported., (© 2023 by the American Diabetes Association.)

Diabetes is a serious chronic disease with high associated burden and disproportionate costs to communities based on socioeconomic, gender, racial, and ethnic status. Addressing the complex challenges of global inequity in diabetes will require intentional efforts to focus on broader social contexts and systems that supersede individual-level interventions. We codify and highlight best practice approaches to achieve equity in diabetes care and outcomes on a global scale. We outline action plans to target diabetes equity on the basis of the recommendations established by The Lancet Commission on Diabetes, organising interventions by their effect on changing the ecosystem, building capacity, or improving the clinical practice environment. We present international examples of how to address diabetes inequity in the real world to show that approaches addressing the individual within a larger social context, in addition to addressing structural inequity, hold the greatest promise for creating sustainable and equitable change that curbs the global diabetes crisis., Competing Interests: Declaration of interests AFW is supported by The Leona M and Harry B Helmsley Charitable Trust (2005-03934) and the National Institutes of Health-National Institute of Diabetes and Digestive Kidney Disease (5P30DK111024-07). LM-B is supported by an Australian National Health and Medical Research Council (NHMRC) investigator grant (1194698), and leads projects that are funded by NHMRC, the Australian Department of Health, and the Australian Medical Research Future Fund. LEE and JAC are supported by the National Institutes of Health-National Institute of Diabetes and Digestive Kidney Disease (R01DK118038 and R01DK120861, awarded to LEE; K01DK131319, awarded to JAC). LEE and RJW are supported by the National Institute on Minority Health and Health Disparities (R01MD013826, awarded to LEE and RJW; R01MD017574, awarded to LEE). RJW is supported by the American Diabetes Association (1-19-JDF-075). ANW is supported by the National Institutes of Health-Fogarty International Centre (K43TW010698). ANW declares an honorarium received from Sanofi for serving as a panel member at an educational event on thyroid cancer. JCM receives honorarium from Servier Laboratories for serving on the advisory committee at educational events. OE is a health-care disparities adviser (on a temporary advisory board role) for Medtronic. OE has received research support through his organisation T1D Exchange from Medtronic, Vertex, Dexcom, and Eli Lilly. Medtronic supports components of T1DX-QI health equity work. The T1DX-QI is funded by The Leona M and Harry B Helmsley Charitable Trust. LAD has received research support to her institution from Dompé, Lilly, MannKind, Medtronic, Provention, and Zealand Pharma; and served as a consultant for Abata Therapeutics and Vertex. SA is supported by the National Institutes of Health-National Institute of Diabetes and Digestive Kidney Disease (R01DK132302, K23115896, and P30DK111022-07), JDRF, and The Leona M and Harry B Helmsley Charitable Trust. SA receives research devices, but not salary support from Dexcom and Abbott, and is a health-care disparities adviser (on a temporary advisory board role) for Medtronic and Beta Bionics. All other authors declare no competing interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Objectives: We sought to examine in individuals with SARS-CoV-2 infection whether risk for thrombotic and thromboembolic events (TTE) is modified by presence of a diabetes diagnosis. Furthermore, we analysed whether differential risk for TTEs exists in type 1 diabetes mellitus (T1DM) versus type 2 diabetes mellitus (T2DM)., Design: Retrospective case-control study., Setting: The December 2020 version of the Cerner Real-World Data COVID-19 database is a deidentified, nationwide database containing electronic medical record (EMR) data from 87 US-based health systems., Participants: We analysed EMR data for 322 482 patients >17 years old with suspected or confirmed SARS-CoV-2 infection who received care between December 2019 and mid-September 2020. Of these, 2750 had T1DM; 57 811 had T2DM; and 261 921 did not have diabetes., Outcome: TTE, defined as presence of a diagnosis code for myocardial infarction, thrombotic stroke, pulmonary embolism, deep vein thrombosis or other TTE., Results: Odds of TTE were substantially higher in patients with T1DM (adjusted OR (AOR) 2.23 (1.93-2.59)) and T2DM (AOR 1.52 (1.46-1.58)) versus no diabetes. Among patients with diabetes, odds of TTE were lower in T2DM versus T1DM (AOR 0.84 (0.72-0.98))., Conclusions: Risk of TTE during COVID-19 illness is substantially higher in patients with diabetes. Further, risk for TTEs is higher in those with T1DM versus T2DM. Confirmation of increased diabetes-associated clotting risk in future studies may warrant incorporation of diabetes status into SARS-CoV-2 infection treatment algorithms., Competing Interests: Competing interests: MAC is the Chief Medical Officer at Glooko. He receives research support from Dexcom and Abbott Diabetes Care. MNK receives, or has received, research grant support from AstraZeneca and Boehringer Ingelheim, as well as other research support form AstraZeneca. He receives, or has received, research honoraria from AstraZeneca, Boehringer Ingelheim and Novo Nordisk. He serves, or has served, as a consultant and/or advisor for Alnylam, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Cytokinetics, Eli Lilly, Esperion Therapeutics, Janssen, Lexicon, Merck (Diabetes and Cardiovascular), Novo Nordisk, Pharmacosmos, Sanofi and Vifor Pharma. He has received support for attending meetings and/or travel from AstraZeneca, Bayer, Boehringer Ingelheim and Novo Nordisk, and he participated on an advisory board for Applied Therapeutics., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: Fear of hypoglycemia (FoH) affects quality of life, emotional well-being, and diabetes management among people with type 1 diabetes (PwT1D). American Diabetes Association's (ADA) guidelines recommend assessing FoH in clinical practice. However, existing FoH measures are commonly used in research and not in clinical practice. In this study, prevalence of FoH was assessed in PwT1D using a newly developed FoH screener for clinical practice; its association with established measures and outcomes was also determined. In addition, healthcare providers' (HCPs) perspectives on implementing FoH screener into real-world practice were explored., Research Design and Methods: This multiphase observational study used mixed methods in two phases. First, we collected a cross-sectional survey (including the screener) from PwT1D (≥18 years) from T1D Exchange Quality Improvement Collaborative adult clinics. Pearson correlations and regression analyses were performed on diabetes outcome measures using screener scores. Second, we conducted focus groups among HCPs who treat PwT1D and descriptive analysis to summarize results., Results: We included 553 PwT1D. Participants had a mean±SD age of 38.9±14.2 years and 30% reported a high FoH total score. Regression analyses showed that higher A1c and higher number of comorbidities were significantly associated with high FoH (p<0.001). High FoH worry and behavior scores were significantly associated with 8-Item Patient Health Questionnaire and 7-Item Generalized Anxiety Disorder Scale scores. Participants with ≥1 severe hypoglycemia event(s) and impaired awareness of hypoglycemia had higher odds of high FoH. Eleven HCPs participated in focus group interviews; they expressed that the FoH screener is clinically necessary and relevant but poses implementation challenges that must be addressed., Conclusions: Our results demonstrate FoH is common in PwT1D and affects their psychosocial well-being and diabetes management. In alignment with ADA position statement, HCP focus group results emphasize importance of screening for FoH. Implementing this newly developed FoH screener may help HCPs identify FoH in PwT1D., Competing Interests: Competing interests: JLP, MP-N, and BM are employees and stockholders of Eli Lilly and Company. MEP, NR, KC, WAW, HN, and OE are employees of T1D Exchange. JL was an employee of T1D Exchange at the time of this research. MB and HKA received advisory fees from Eli Lilly and Company., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: We used real-world electronic health record (EHR) data to examine HbA1c levels among children and adults with type 1 diabetes (T1D) who are classified as continuous glucose monitor (CGM) users after T1D diagnosis and switch to self-monitoring of blood glucose (SMBG) during follow-up, versus people who opt for SMBG after T1D diagnosis and switch to CGM during follow-up visits., Methods: We conducted an observational, case-crossover study using electronic medical record (EMR) data from the T1D Exchange Quality Improvement Collaborative. The primary outcome in this study was HbA1c. Baseline HbA1c levels were taken at the index date, corresponding to initial device classification, and compared with HbA1c value recorded at the clinic visit following device switch., Results: Of all patients classified in the SMBG group, 7,706 switched to CGM use within the 5-year study time frame, and 5,123 of all initial CGM users switched to SMBG within the study time frame and were included in this analysis. At baseline, median (interquartile range [IQR]) HbA1c for SMBG use was 8.1 (2.4), whereas postcrossover to CGM use, there was a decline in median (IQR) levels to 7.7 (1.9) ( P < .001). For baseline CGM users, median (IQR) HbA1c levels were 7.9 (2.0), and postcrossover to SMBG, median (IQR) HbA1c levels increased to 8.0 (2.9) ( P < .001)., Conclusion: We found that people who switched to CGM use had significantly improved HbA1c levels compared to those who switched to glucose monitoring with SMBG., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: NN is PI on Dexcom and Vertex funded research projects through her organization T1D Exchange. GN is employed at Dexcom. OE is PI on Dexcom, MannKind, Medtronic, Vertex, Abbott funded research projects through his organization T1D Exchange. OE is an advisor for Medtronic Diabetes and Vertex Pharmaceuticals.

Quality Improvement Success Stories are published by the American Diabetes Association in collaboration with the American College of Physicians and the National Diabetes Education Program. This series is intended to highlight best practices and strategies from programs and clinics that have successfully improved the quality of care for people with diabetes or related conditions. Each article in the series is reviewed and follows a standard format developed by the editors of Clinical Diabetes . The following article describes an effort to improve the remote collection of insulin pump data in an academic center in South Florida., Competing Interests: No potential conflicts of interest relevant to this article were reported., (© 2023 by the American Diabetes Association.)

Purpose: The purpose of this research is to develop a set of continuous glucose monitoring (CGM)-related measure concepts to be tested in a health care system. Existing measures assessing the quality of diabetes care do not include modern approaches to diabetes management, such as CGM. Continuous glucose monitors rival traditional methods of measuring diabetes management by providing real-time, longitudinal data and demonstrating glucose variability over time. The Improving Diabetes Quality Initiative seeks to address this gap in diabetes quality measurement., Methods: A Technical Expert Panel (TEP) was convened to curate a diabetes quality measures portfolio and conceptualize three new CGM-related quality measures within the portfolio. From the additional measure concepts identified in the portfolio, the TEP prioritized three for conceptualization. High-level measure concept specifications were made available during a public comment period., Results: The measure concepts prioritized by the TEP included a shared decision-making measure to assess the value of initiating CGM for disease management, a utilization measure to address disparities in access and use of CGM, and a patient-provider review of CGM data to promote routine consideration of these assessments in treatment and ongoing management. Clinical literature, public comments, and TEP feedback informed full measure specifications., Conclusions: The evolution of diabetes technology reflects the need to shift diabetes quality of care. The measure concepts will be tested in a flexible pilot setting to understand the future of diabetes care and communicate the value of CGM to people with diabetes, providers, and payers.

Background: The benefits of Continuous Glucose Monitoring (CGM) on glycemic management have been demonstrated in numerous studies; however, widespread uptake remians limited. The aim of this study was to provide real-world evidence of patient attributes and clinical outcomes associated with CGM use across clinics in the U.S. based T1D Exchange Quality Improvement (T1DX-QI) Collaborative., Method: We examined electronic Health Record data from eight endocrinology clinics participating in the T1DX-QI Collaborative during the years 2017-2019., Results: Among 11,469 type 1 diabetes patients, 48% were CGM users. CGM use varied by race/ethnicity with Non-Hispanic Whites having higher rates of CGM use (50%) compared to Non-Hispanic Blacks (18%) or Hispanics (38%). Patients with private insurance were more likely to use CGM (57.2%) than those with public insurance (33.3%) including Medicaid or Medicare. CGM users had lower median HbA1c (7.7%) compared to nonusers (8.4%). Rates of diabetic ketoacidosis (DKA) and severe hypoglycemia were significantly higher in nonusers compared to CGM users., Conclusion: In this real-world study of patients in the T1DX-QI Collaborative, CGM users had better glycemic control and lower rates of DKA and severe hypoglycemia (SH) events, compared to nonusers; however, there were significant sociodemographic disparities in CGM use. Quality improvement and advocacy measures to promote widespread and equitable CGM uptake have the potential to improve clinical outcomes.

Purpose of Review: Although advances in diabetes technology and pharmacology have significantly and positively impacted diabetes management and health outcomes for some, diabetes care remains burdensome and can be challenging to balance with other life priorities. The purpose of this article is to review the rationale for assessment of psychosocial domains in diabetes care settings and strategies for the implementation of psychosocial screening into routine practice. Survey data from the Type 1 Diabetes Exchange Quality Improvement Network is highlighted., Recent Findings: Implementation of psychosocial screening requires identifying the population; selecting validated tools to assess target domains; determining frequency of screening and mode of survey delivery; and scoring, interpreting, documenting, and facilitating referrals such that these processes are part of clinical workflows. Recognizing the influence of psychosocial factors for people with diabetes (PWD), professional society guidelines for comprehensive diabetes care recommend the integration of psychosocial screening into routine care., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The optimal care of type 1 diabetes involves consistent glycemic management to avoid short- and long-term complications. However, despite advancements in diabetes technology and standards, achieving adequate glycemic levels in children and adolescents remains a challenge. This study aimed to identify factors associated with achieving the recommended A1C target of <7% from the United States-based multicenter T1D Exchange Quality Improvement Collaborative cohort, including 25,383 children and adolescents living with type 1 diabetes., (© 2022 by the American Diabetes Association.)

This article describes how the T1D Exchange Quality Improvement Collaborative leverages an innovative web platform, the QI Portal, to gather and store electronic medical record (EMR) data to promote benchmarking and population health improvement in a type 1 diabetes learning health system. The authors explain the value of the QI Portal, the process for mapping center-level data from EMRs using standardized data specifications, and the QI Portal's unique features for advancing population health., (© 2022 by the American Diabetes Association.)

This study sought to identify barriers and facilitators to successful smart insulin pen (SIP) use and gauge prescribing practices and integration into clinical practice by assessing provider and care team perspectives at participating endocrinology clinics within the T1D Exchange Quality Improvement Collaborative. The identified provider-related, patient-related, and clinic- and operational-level barriers and facilitators varied based on clinic knowledge, capacity, and resources. High-impact barriers included insurance coverage and prescribing processes; high-impact facilitators included improved diabetes clinic visit quality and use of SIPs as an alternative to insulin pump therapy. Findings indicated the need for provider and care team education and training on proper SIP features, use, and prescribing., (© 2022 by the American Diabetes Association.)

Aims: We examined diabetes status (no diabetes; type 1 diabetes [T1D]; type 2 diabetes [T2D]) and other demographic and clinical factors as correlates of coronavirus disease 2019 (COVID-19)-related hospitalization. Further, we evaluated predictors of COVID-19-related hospitalization in T1D and T2D., Methods: We analyzed electronic health record data from the de-identified COVID-19 database (December 2019 through mid-September 2020; 87 US health systems). Logistic mixed models were used to examine predictors of hospitalization at index encounters associated with confirmed SARS-CoV-2 infection., Results: In 116,370 adults (>=18 years old) with COVID-19 (93,098 no diabetes; 802 T1D; 22,470 T2D), factors that independently increased risk for hospitalization included diabetes, male sex, public health insurance, decreased body mass index (BMI; <25.0-29.9 kg/m 2 ), increased BMI (>25.0-29.9 kg/m 2 ), vitamin D deficiency/insufficiency, and Elixhauser comorbidity score. After further adjustment for concurrent hyperglycemia and acidosis in those with diabetes, hospitalization risk was substantially higher in T1D than T2D and in those with low vitamin D and elevated hemoglobin A1c (HbA1c)., Conclusions: The higher hospitalization risk in T1D versus T2D warrants further investigation. Modifiable risk factors such as vitamin D deficiency/insufficiency, BMI, and elevated HbA1c may serve as prognostic indicators for COVID-19-related hospitalization in adults with diabetes., Competing Interests: Declaration of Competing Interest MAC is the Chief Medical Officer at Glooko. He receives research support from Dexcom and Abbott Diabetes Care. NP receives research grant support from Dexcom through an investigator-initiated study. SP has been a contributing editor for diaTribe and has served on a medical advisory board for Medtronic MiniMed, Inc. Through the University of Colorado, she has received research funding from Dexcom, Inc., Eli Lilly, JDRF, the Leona M. & Harry B. Helmsley Charitable Trust, the National Institutes of Health, and Sanofi US Services. JML serves on a medical advisory board for GoodRx and serves as a consultant for Tandem Diabetes Care. No other potential conflicts of interest relevant to this article were reported., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

This article describes the evolution of the Type 1 Diabetes Exchange Quality Improvement Collaborative (T1DX-QI) and provides insight into the development and growth of a successful type 1 diabetes quality improvement (QI) program. Since its inception 8 years ago, the collaborative has expanded to include centers across the United States with varying levels of QI experience, while simultaneously achieving many tangible improvements in type 1 diabetes care. These successes underscore the importance of learning health systems, data-sharing, benchmarking, and peer collaboration as drivers for continuous QI. Future efforts will include recruiting additional small- to medium-sized centers focused on adult care and underserved communities to further the goal of improving care and outcomes for all people living with type 1 diabetes., (© 2022 by the American Diabetes Association.)

Many adults with diabetes do not reach optimal glycemic targets, and, despite advances in diabetes management, diabetes technology use remains significantly lower in racial/ethnic minority groups. This study aimed to identify factors associated with achieving the recommended A1C target of <7% using data on 12,035 adults with type 1 diabetes from 15 centers participating in the T1D Exchange Quality Improvement Collaborative. Individuals attaining the target A1C were more likely to be older, White, have private health insurance, and use diabetes technology and less likely to report depressive symptoms or episodes of severe hypoglycemia or diabetic ketoacidosis than those with higher A1C levels. These findings highlight the importance of overcoming inequities in diabetes care., (© 2022 by the American Diabetes Association.)

Achieving glycemic targets in youth and young adults with type 1 diabetes (T1D) is challenging. Diabetes devices, including continuous glucose monitors (CGM) may impact glycemic control. We analyzed the proportion of CGM use in youth and young adults with T1D at nine U.S. T1D Exchange Quality Improvement (T1DX-QI) Collaborative centers and 402 European diabetes prospective follow-up registry (Diabetes-Patienten-Verlaufsdokumentation [DPV]) sites from 2017 to 2020 and examined the association of CGM use to glycemic control as measured by hemoglobin A1c (HbA1c). CGM use increased each year from 2017 to 2020 across all age ranges (<6, 6-<12, 12-<18, 18-<25 years) in both registries and lower mean HbA1c was observed in CGM users compared with nonusers regardless of insulin delivery method for all years analyzed. CGM use appeared to increase more so in the European DPV than the U.S. T1DX-QI, which may be due to transatlantic differences in health care systems, insurance coverage, and prescriber habits.

Objectives: We evaluated COVID-19 outcomes in children and young adults with type 1 diabetes (T1D) to determine if those with comorbidities are more likely to experience severe COVID-19 compared to those without., Research Design and Methods: This cross-sectional study included questionnaire data on patients <25 years of age with established T1D and laboratory-confirmed COVID-19 from 52 sites across the US between April 2020 and October 2021. We examined patient factors and COVID-19 outcomes between those with and without comorbidities. Multivariate logistic regression analysis examined the odds of hospitalization among groups, adjusting for age, HbA1c, race and ethnicity, insurance type and duration of diabetes., Results: Six hundred fifty-one individuals with T1D and COVID-19 were analyzed with mean age 15.8 (SD 4.1) years. At least one comorbidity was present in 31%, and more than one in 10%. Obesity and asthma were the most frequently reported comorbidities, present in 19% and 17%, respectively. Hospitalization occurred in 17% of patients and 52% of hospitalized patients required ICU level care. Patients with at least one comorbidity were almost twice as likely to be hospitalized with COVID-19 than patients with no comorbidities (Odds ratio 2.0, 95% CI: 1.3-3.1). This relationship persisted after adjusting for age, HbA1c, race and ethnicity (minority vs nonminority), insurance type (public vs. private), and duration of diabetes., Conclusions: Our findings show that comorbidities increase the risk for hospitalization with COVID-19 in children and young adults highlighting the need for tailored COVID-19 prevention and treatment strategies in T1D., (© 2022 The Authors. Pediatric Diabetes published by John Wiley & Sons Ltd.)

Background: An estimated 1.1 million children and adolescents aged under 20 years have type 1 diabetes worldwide. Principal investigators from seven well-established longitudinal pediatric diabetes registries and the SWEET initiative have come together to provide an international collaborative perspective and comparison of the registries., Work Flow: Information and data including registry characteristics, pediatric participant clinical characteristics, data availability and data completeness from the Australasian Diabetes Data Network (ADDN), Danish Registry of Childhood and Adolescent Diabetes (DanDiabKids), Diabetes prospective follow-up registry (DPV), Norwegian Childhood Diabetes Registry (NCDR), National Paediatric Diabetes Audit (NPDA), Swedish Childhood Diabetes Registry (Swediabkids), T1D Exchange Quality Improvement Collaborative (T1DX-QI), and the SWEET initiative was extracted up until 31 December 2020., Registry Objectives and Outcomes: The seven diabetes registries and the SWEET initiative collectively show data of more than 900 centers and around 100,000 pediatric patients, the majority with type 1 diabetes. All share the common objectives of monitoring treatment and longitudinal outcomes, promoting quality improvement and equality in diabetes care and enabling clinical research. All generate regular benchmark reports. Main differences were observed in the definition of the pediatric population, the inclusion of adults, documentation of CGM metrics and collection of raw data files as well as linkage to other data sources. The open benchmarking and access to regularly updated data may prove to be the most important contribution from registries. This study describes aspects of the registries to enable future collaborations and to encourage the development of new registries where they do not exist., (© 2022 The Authors. Pediatric Diabetes published by John Wiley & Sons Ltd.)

Background: Despite documented benefits of diabetes technology in managing type 1 diabetes, inequities persist in the use of these devices. Provider bias may be a driver of inequities, but the evidence is limited. Therefore, we aimed to examine the role of race/ethnicity and insurance-mediated provider implicit bias in recommending diabetes technology. Method: We recruited 109 adult and pediatric diabetes providers across 7 U.S. endocrinology centers to complete an implicit bias assessment composed of a clinical vignette and ranking exercise. Providers were randomized to receive clinical vignettes with differing insurance and patient names as proxy for Racial-Ethnic identity. Bias was identified if providers: (1) recommended more technology for patients with an English name (Racial-Ethnic bias) or private insurance (insurance bias), or (2) Race/Ethnicity or insurance was ranked high (Racial-Ethnic and insurance bias, respectively) in recommending diabetes technology. Provider characteristics were analyzed using descriptive statistics and multivariate logistic regression. Result: Insurance-mediated implicit bias was common in our cohort ( n  = 66, 61%). Providers who were identified to have insurance-mediated bias had greater years in practice (5.3 ± 5.3 years vs. 9.3 ± 9 years, P  = 0.006). Racial-Ethnic-mediated implicit bias was also observed in our study ( n  = 37, 34%). Compared with those without Racial-Ethnic bias, providers with Racial-Ethnic bias were more likely to state that they could recognize their own implicit bias (89% vs. 61%, P  = 0.001). Conclusion: Provider implicit bias to recommend diabetes technology was observed based on insurance and Race/Ethnicity in our pediatric and adult diabetes provider cohort. These data raise the need to address provider implicit bias in diabetes care.

Context: The impact of the COVID-19 pandemic on individuals with type 1 diabetes remains poorly defined., Objective: We examined United States trends in diabetic ketoacidosis (DKA) among individuals with type 1 diabetes (T1D) during the COVID-19 pandemic at 7 large US medical centers and factors associated with these trends., Methods: We compared DKA events among children and adults with T1D during COVID-19 surge 1 (March-May 2020) and COVID-19 surge 2 (August-October 2020) to the same periods in 2019. Analysis was performed using descriptive statistics and chi-square tests., Results: We found no difference in the absolute number of T1D patients experiencing DKA in 2019 vs 2020. However, a higher proportion of non-Hispanic Black (NHB) individuals experienced DKA in 2019 than non-Hispanic White (NHW) individuals (44.6% vs 16.0%; P < .001), and this disparity persisted during the COVID-19 pandemic (48.6% vs 18.6%; P < .001). DKA was less common among patients on continuous glucose monitor (CGM) or insulin pump in 2020 compared to 2019 (CGM: 13.2% vs 15.0%, P < .001; insulin pump: 8.0% vs 10.6%, P < .001). In contrast to annual DKA totals, a higher proportion of patients had DKA during COVID-19 surges 1 and 2 compared to the same months in 2019 (surge 1: 7.1% vs 5.4%, P < .001; surge 2: 6.6% vs 5.7%, P = .001)., Conclusion: DKA frequency increased among T1D patients during COVID-19 surges with highest frequency among NHB patients. DKA was less common among patients using CGM or insulin pumps. These findings highlight the urgent need for improved strategies to prevent DKA among patients with T1D-not only under pandemic conditions, but under all conditions-especially among populations most affected by health inequities., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Endocrine Society.)

There are limited tools to address equity in diabetes research and clinical trials. The T1D Exchange has established a 10-step equity framework to advance equity in diabetes research. Herein, the authors outline this approach and expand on its practical application., (© 2022 by the American Diabetes Association.)

Background: An increase in newly diagnosed type 1 diabetes (T1D) has been posited during the COVID-19 pandemic, but data are conflicting. We aimed to determine trends in newly diagnosed T1D and severity of presentation at diagnosis for pediatric and adolescent patients during COVID-19 (2020) as compared to the previous year (2019) in a multi-center analysis across the United States., Methods: This retrospective study from seven centers in the T1D Exchange Quality Improvement Collaborative (T1DX-QI) included data on new onset T1D diagnosis and proportion in DKA at diagnosis from January 1 to December 31, 2020, compared to the prior year. Chi-square tests were used to compare differences in patient characteristics during the pandemic period compared to the prior year., Results: Across seven sites, there were 1399 newly diagnosed T1D patients in 2020, compared to 1277 in 2019 (p = 0.007). A greater proportion of newly diagnosed patients presented in DKA in 2020 compared to 2019 (599/1399(42.8%) vs. 493/1277(38.6%), p = 0.02), with a higher proportion presenting with severe DKA (p = 0.01) as characterized by a pH <7.1 and/or bicarbonate of <5 mmol/L. Monthly data trends demonstrated a higher number of new T1D diagnoses over the spring and summer months (March to September) of 2020 compared to 2019 (p < 0.001)., Conclusions: We found an increase in newly diagnosed T1D and a greater proportion presenting in DKA at diagnosis during the COVID-19 pandemic compared to the prior year. Future longitudinal studies are needed to confirm these findings with population level data and determine the long-term impact of COVID-19 on diabetes trends., (© 2022 The Authors. Pediatric Diabetes published by John Wiley & Sons Ltd.)