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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.
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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.
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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%.
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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.
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Diabetes Mellitus Tipo 1 , Humanos , Diabetes Mellitus Tipo 1/diagnóstico , Diabetes Mellitus Tipo 1/terapia , Fatores Sociais , Determinantes Sociais da SaúdeRESUMO
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.
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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/m2), increased BMI (>25.0-29.9 kg/m2), 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.
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COVID-19 , Diabetes Mellitus Tipo 1 , Diabetes Mellitus Tipo 2 , Deficiência de Vitamina D , Adulto , Masculino , Humanos , Adolescente , COVID-19/epidemiologia , Diabetes Mellitus Tipo 2/complicações , Diabetes Mellitus Tipo 2/epidemiologia , Estudos Retrospectivos , SARS-CoV-2 , Diabetes Mellitus Tipo 1/complicações , Diabetes Mellitus Tipo 1/epidemiologia , HospitalizaçãoRESUMO
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.
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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.
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Diabetes Mellitus Tipo 1 , Seguro , Adulto , Atitude do Pessoal de Saúde , Criança , Etnicidade , Disparidades em Assistência à Saúde , HumanosRESUMO
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.
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Insulin pump therapy in pediatric type 1 diabetes has been associated with better glycemic control than multiple daily injections. However, insulin pump use remains limited. This article describes an initiative from the T1D Exchange Quality Improvement Collaborative aimed at increasing insulin pump use in patients aged 12-26 years with type 1 diabetes from a baseline of 45% in May 2018 to >50% by February 2020. Interventions developed by participating centers included increasing in-person and telehealth education about insulin pump technology, creating and distributing tools to assist in informed decision-making, facilitating insulin pump insurance approval and onboarding processes, and improving clinic staff knowledge about insulin pumps. These efforts yielded a 13% improvement in pump use among the five participating centers, from 45 to 58% over 22 months.
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Continuous glucose monitoring (CGM) use is associated with improved A1C outcomes and quality of life in adolescents and young adults with diabetes; however, CGM uptake is low. This article reports on a quality improvement (QI) initiative of the T1D Exchange Quality Improvement Collaborative to increase CGM use among patients in this age-group. Ten centers participated in developing a key driver diagram and center-specific interventions that resulted in an increase in CGM use from 34 to 55% in adolescents and young adults over 19-22 months. Sites that performed QI tests of change and documented their interventions had the highest increases in CGM uptake, demonstrating that QI methodology and sharing of learnings can increase CGM uptake.