Establishment of the T1D Exchange Quality Improvement Collaborative (T1DX-QI)

A systematic review and proposed framework for sustainable learning healthcare systems

BACKGROUND

The healthcare sector is a complex domain that faces challenges in effectively learning from practices and outcome data. The Learning Health System (LHS) has emerged as a potential framework to improve healthcare by promoting continuous learning. However, its adoption remains limited, often involving only a single clinical department or a part of the LHS cycle. There is a need to gain a better understanding of implementing LHS on a larger scale.

AIM

To identify complete implementations of the LHS for providing recommendations into their implementation strategies, success factors, barriers, and outcomes.

METHODS

A systematic review was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines using PubMed and Scopus databases. Data from the included papers were thematically categorized into four primary areas: (1) Scale of LHS Implementation; (2) Implementation strategies and the factors that facilitated the implementation of LHS; (3) LHS outcomes; and (4) Barriers /challenges related to the LHS implementation.

RESULTS

We identified 1,279 papers, of which 37 were included in the final analysis. Barriers to implementing LHS included interoperability, data integration, electronic health records (EHRs) challenges, organizational culture, leadership, and regulatory hurdles. Most LHS initiatives lacked discussion on long-term economic sustainability models, and only 16 papers provided objective measurements of performance changes. Drawing from the findings of the included studies, this paper offers recommendations for the effective implementation of the LHS.

CONCLUSION

The establishment of sustainable LHS necessitates several key components. First, there is a need to develop long-term economic sustainability models. Secondly, governance at the national level should promote common Application Programming Interfaces (APIs) across LHS implementations, communication channels to share tacit knowledge, efficient Institutional Review Board, ethical approval processes, and connect various initiatives currently operating independently. Lastly, the success of LHS relies not only on technological infrastructure but also on the active participation of multidisciplinary teams in decision-making and sharing of tacit knowledge.

Strategies to Increase the Use of Connected Insulin Pens Through Shared Decision-Making: A Quality Improvement Success Story

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 is part of a special article collection from the T1D Exchange Quality Improvement Collaborative. It describes an initiative to reduce inequities in diabetes technology access and use and increase the use of connected insulin pens at an academic endocrinology practice in Chicago, IL.

Depression Rates in Youth With Type 1 Diabetes During the COVID-19 Pandemic: Data From the T1D Exchange Quality Improvement Collaborative

This study used data from the T1D Exchange Quality Improvement Collaborative to compare depression rates in youth with type 1 diabetes before and during the coronavirus disease 2019 (COVID-19) pandemic and identify characteristics of individuals with moderate-to-severe depressive symptoms. Rates of moderate-to-severe depressive symptoms remained stable before and during the pandemic, at 9.6-10.7%. During the pandemic, youth who screened positive for depression were more likely to be female and on public insurance, to have a higher A1C, and to have a history of diabetic ketoacidosis or severe hypoglycemia. They were less likely to identify as non-Hispanic White and more likely to identify as Hispanic.

Improving Outcomes for People with Type 1 Diabetes Through Collaboration: Summary of Type 1 Diabetes Exchange Quality Improvement Collaborative Studies

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.

Creation of a quality improvement collaborative to address adolescent and young adult cancer clinical trial enrollment: ATAQI (AYA trial access quality initiative)

Adolescent and young adult (AYA) participation in cancer clinical trials (CCTs) is suboptimal, hindering further improvements in survival, quality of life, and basic understanding of cancer pathophysiology in this population. Prior studies have identified barriers and facilitators to AYA CCT enrollment; however, few interventional studies have attempted to address these barriers and measure tangible changes. In September 2020, a task force was established to address CCT enrollment barriers at a multi-institutional level utilizing a quality improvement collaborative model for improvement. The AYA Trial Access Quality Initiative was developed with the goal of bring multidisciplinary teams together across multiple sites to learn, apply and share their methods of improvement. It uses a structured process of learning sessions lead by quality improvement and clinical experts who help facilitate learning and problem solving which are followed by action phases. During the pilot phase of the collaboration, one key driver of CCT enrollment in AYA's will be addressed: communication between adult and pediatric oncology by implementation of various interventions at sites. The number of AYAs screened for and enrolled on CCTs will be tracked over the course of the collaborative along with the process measures. It is expected that the interventions will promote engagement of stakeholders in the process of screening AYA oncology patients for eligibility on CCTs. This will hopefully create a favorable environment conducive for increasing enrollment on CCTs and lead to the development of a system-wide quality improvement framework to improve AYA CCT enrollment.

Sociodemographic factors affecting glycaemic control in Finnish paediatric patients with type 1 diabetes

AIMS

Socioeconomic problems may present significant challenges when trying to reach optimal glycaemic control in paediatric patients with type 1 diabetes. We examined sociodemographic factors affecting metabolic control in patients in one of the biggest paediatric diabetes clinics in Finland.

METHODS

One hundred ninety-one children (age 2-15 years; median 11 years; 47% female) with type 1 diabetes and their families were recruited during outpatient visits in the paediatric diabetes clinic of Tampere University Hospital, Finland. The participants completed a questionnaire on the family's sociodemographic background. The child's glycaemic control was assessed by both glycosylated haemoglobin (HbA1c) and time in range (TIR). Risk factors for poor (HbA1c ≥75 mmol/mol; TIR <40%) and optimal (HbA1c <53 mmol/mol; TIR ≥70%) metabolic control were searched using logistic regression analyses.

RESULTS

Living in a nuclear family, male gender, younger age and a school assistant for diabetes management were associated with the simultaneous presence of both indicators of optimal metabolic control. Poor glycaemic control, as estimated by HbA1c, was associated with lower parental education and the child's older age. Parental smoking and the child's older age were associated with poor TIR.

CONCLUSION

This study confirms the importance of sociodemographic factors in care of Finnish paediatric patients with type 1 diabetes. Sociodemographic status markers of the family could be used as triggers to alert paediatric diabetes teams to offer more tailored care to families with new-onset type 1 diabetes mellitus.

Benchmarking Diabetes Technology Use Among 21 U.S. Pediatric Diabetes Centers

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.

Increasing Social Determinants of Health Screening Rates Among Six Endocrinology Centers Across the United States: Results From the T1D Exchange Quality Improvement Collaborative

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.

Increasing Continuous Glucose Monitoring Use for Non-Hispanic Black and Hispanic People With Type 1 Diabetes: Results From the T1D Exchange Quality Improvement Collaborative Equity Study

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%.

Insulin Pump Utilization in 2017-2021 for More Than 22,000 Children and Adults With Type 1 Diabetes: A Multicenter Observational Study

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.

Understanding Providers' Readiness and Attitudes Toward Autoantibody Screening: A Mixed-Methods Study

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.

Association Between Health Insurance Type and Adverse Outcomes for Children and Young Adults With Type 1 Diabetes and Coronavirus Disease 2019

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.

Improving Planning for Transition to Adult Care in a Pediatric Diabetes Clinic

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 efforts at a large midwestern pediatric health system to improve planning for patients' transition from pediatric to adult diabetes care settings.

Patient Demographics and Clinical Outcomes Among Type 1 Diabetes Patients Using Continuous Glucose Monitors: Data From T1D Exchange Real-World Observational Study

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.

Implementation of Psychosocial Screening into Diabetes Clinics: Experience from the Type 1 Diabetes Exchange Quality Improvement Network

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.

Comorbidities increase COVID-19 hospitalization in young people with type 1 diabetes

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.

Making Diabetes Electronic Medical Record Data Actionable: Promoting Benchmarking and Population Health Improvement Using the T1D Exchange Quality Improvement Portal

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.

Temporal Changes in Hemoglobin A1c and Diabetes Technology Use in DPV, NPDA, and T1DX Pediatric Cohorts from 2010 to 2018

Objective: The German/Austrian Diabetes Patient Follow-up Registry (Diabetes-Patienten-Verlaufsdokumentation or DPV), England/Wales National Pediatric Diabetes Audit (NPDA), and Type 1 Diabetes Exchange (T1DX) in the United States investigated changes in hemoglobin A1c (HbA1c) and diabetes technology use from 2010 to 2018. Methods: Registry/audit data from 2010 to 2018 were analyzed in annual cohorts using linear regression for those <18 years of age with type 1 diabetes diagnosed at age >6 months. Time trends in HbA1c, pump, and continuous glucose monitoring (CGM) use were studied using repeated measurements linear and logistic regression models with an autoregressive covariance structure and with year and data source as independent variables. Results: A total of 1,172,980 visits among 114,264 (54,119 DPV, 43,550 NPDA, 16,595 T1DX) patients were identified. HbA1c remained clinically stable in DPV (7.7% [61 mmol/mol] to 7.6% [60 mmol/mol]), decreased in the NPDA (8.7% [72 mmol/mol] to 7.9% [63 mmol/mol]), and increased in T1DX (8.0% [64 mmol/mol] to 8.5% [69 mmol/mol] from 2010 to 2018). In all registries/audits, insulin pump and CGM use increased over time with greatest pump use in T1DX and lowest uptake reported in NPDA. Conclusions: These data reveal three different longitudinal patterns of change in registry/audit HbA1c from 2010 to 2018. Diabetes technology use increased throughout, at different rates. Quality improvement (QI) programs in DPV have been ongoing for 25 years, began in NPDA in 2009 and T1DX in 2016. We speculate that in England/Wales, development of networks, peer review, and implementation of QI measures contributed to reductions in population HbA1c. Many of these interventions had been implemented in DPV before 2010. Further efforts to understand this improvement, including the role of QI, and continued success within standardized documentation and benchmarking could inform T1DX programs to reduce HbA1c.

Implicit Racial-Ethnic and Insurance-Mediated Bias to Recommending Diabetes Technology: Insights from T1D Exchange Multicenter Pediatric and Adult Diabetes Provider Cohort

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.

A collaborative comparison of international pediatric diabetes registries

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.

Testing an Automated Approach to Identify Variation in Outcomes among Children with Type 1 Diabetes across Multiple Sites

Introduction

Efficient methods to obtain and benchmark national data are needed to improve comparative quality assessment for children with type 1 diabetes (T1D). PCORnet is a network of clinical data research networks whose infrastructure includes standardization to a Common Data Model (CDM) incorporating electronic health record (EHR)-derived data across multiple clinical institutions. The study aimed to determine the feasibility of the automated use of EHR data to assess comparative quality for T1D.

Methods

In two PCORnet networks, PEDSnet and OneFlorida, the study assessed measures of glycemic control, diabetic ketoacidosis admissions, and clinic visits in 2016-2018 among youth 0-20 years of age. The study team developed measure EHR-based specifications, identified institution-specific rates using data stored in the CDM, and assessed agreement with manual chart review.

Results

Among 9,740 youth with T1D across 12 institutions, one quarter (26%) had two or more measures of A1c greater than 9% annually (min 5%, max 47%). The median A1c was 8.5% (min site 7.9, max site 10.2). Overall, 4% were hospitalized for diabetic ketoacidosis (min 2%, max 8%). The predictive value of the PCORnet CDM was >75% for all measures and >90% for three measures.

Conclusions

Using EHR-derived data to assess comparative quality for T1D is a valid, efficient, and reliable data collection tool for measuring T1D care and outcomes. Wide variations across institutions were observed, and even the best-performing institutions often failed to achieve the American Diabetes Association HbA1C goals (<7.5%).

Effect of COVID-19 pandemic on presentation and referral patterns of newly diagnosed children with type 1 diabetes in a developing country

OBJECTIVES

The global spread of coronavirus disease 2019 (COVID-19), had a great impact on patients worldwide, including those with chronic diseases. We aim to study the effect of COVID-19 pandemic on presentation patterns of patients with type 1 diabetes (T1D) in Jordan, as an example a developing country with limited resources.

METHODS

Medical charts were reviewed for patients presented with new-onset T1D to Jordan University hospital during the first year of pandemic and the preceding year. Categorical data were compared using Pearson Chi-Square and Fisher's exact test. Continuous data were compared using the Independent Sample t-Test.

RESULTS

A total of 137 children were diagnosed with T1D during the study period, with 60.6% of those children were diagnosed in the pre-pandemic year compared to 39.4% during the first year of pandemic, p-value=0.013. Percentage of patients diagnosed with DKA as first presentation of T1D during the pre-pandemic year was 34.9% compared to 51.9% during the pandemic year, p-value=0.049. Significant differences in family monthly income (p-value=0.006) and paternal education level (p-value=0.036) were found between children with DKA and those without DKA in the pre-pandemic year, but they were not significant during the pandemic year.

CONCLUSIONS

The unprecedented COVID-19 pandemic had affected presentation pattern of newly diagnosed T1D patients, manifested by lower number of children diagnosed with T1D and higher percentage of DKA as first presentation compared to the preceding year. Health care services should be at utmost preparedness for possible future waves and other pandemics.

Trends in Type 1 Diabetic Ketoacidosis During COVID-19 Surges at 7 US Centers: Highest Burden on non-Hispanic Black Patients

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.

Increase in newly diagnosed type 1 diabetes in youth during the COVID-19 pandemic in the United States: A multi-center analysis

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.

Teamwork, Targets, Technology, and Tight Control in Newly Diagnosed Type 1 Diabetes: the Pilot 4T Study

CONTEXT

Youth with type 1 diabetes (T1D) do not meet glycated hemoglobin A1c (HbA1c) targets.

OBJECTIVE

This work aimed to assess HbA1c outcomes in children with new-onset T1D enrolled in the Teamwork, Targets, Technology and Tight Control (4T) Study.

METHODS

HbA1c levels were compared between the 4T and historical cohorts. HbA1c differences between cohorts were estimated using locally estimated scatter plot smoothing (LOESS). The change from nadir HbA1c (month 4) to 12 months post diagnosis was estimated by cohort using a piecewise mixed-effects regression model accounting for age at diagnosis, sex, ethnicity, and insurance type. We recruited 135 youth with newly diagnosed T1D at Stanford Children's Health. Starting July 2018, all youth within the first month of T1D diagnosis were offered continuous glucose monitoring (CGM) initiation and remote CGM data review was added in March 2019. The main outcomes measure was HbA1c.

RESULTS

HbA1c at 6, 9, and 12 months post diagnosis was lower in the 4T cohort than in the historic cohort (-0.54% to -0.52%, and -0.58%, respectively). Within the 4T cohort, HbA1c at 6, 9, and 12 months post diagnosis was lower in those patients with remote monitoring than those without (-0.14%, -0.18% to -0.14%, respectively). Multivariable regression analysis showed that the 4T cohort experienced a significantly lower increase in HbA1c between months 4 and 12 (P < .001).

CONCLUSION

A technology-enabled, team-based approach to intensified new-onset education involving target setting, CGM initiation, and remote data review statistically significantly decreased HbA1c in youth with T1D 12 months post diagnosis.

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

OBJECTIVE

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

RESEARCH DESIGN AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Age and Hospitalization Risk in People With Type 1 Diabetes and COVID-19: Data From the T1D Exchange Surveillance Study

CONTEXT

COVID-19 morbidity and mortality are increased in type 1 diabetes (T1D), but few data focus on age-based outcomes.

OBJECTIVE

This work aimed to quantify the risk for COVID-19-related hospitalization and adverse outcomes by age in people with T1D.

METHODS

For this observational, multisite, cross-sectional study of patients with T1D and laboratory-confirmed COVID-19 from 56 clinical sites in the United States, data were collected from April 2020 to March 2021. The distribution of patient factors and outcomes across age groups (0-18, 19-40, and > 40 years) was examined. Descriptive statistics were used to describe the study population, and multivariate logistic regression models were used to analyze the relationship between age, adverse outcomes, and hospitalization. The main outcome measure was hospitalization for COVID-19.

RESULTS

A total of 767 patients were analyzed. Fifty-four percent (n = 415) were aged 0 to 18 years, 32% (n = 247) were aged 19 to 40 years, and 14% (n = 105) were older than 40 years. A total of 170 patients were hospitalized, and 5 patients died. Compared to the 0- to 18-years age group, those older than 40 years had an adjusted odds ratio of 4.2 (95% CI, 2.28-7.83) for hospitalization after adjustment for sex, glycated hemoglobin A1c, race, insurance type, and comorbidities.

CONCLUSION

Age older than 40 years is a risk factor for patients with T1D and COVID-19, with children and younger adults experiencing milder disease and better prognosis. This indicates a need for age-tailored treatments, immunization, and clinical management of individuals affected by T1D.

Factors Associated With Achieving Target A1C in Children and Adolescents With Type 1 Diabetes: Findings From the T1D Exchange Quality Improvement Collaborative

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.

Baseline Quality Improvement Capacity of 33 Endocrinology Centers Participating in the T1D Exchange Quality Improvement Collaborative

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.

Follow-Up Mental Health Care in Youth and Young Adults With Type 1 Diabetes After Positive Depression Screen and/or Suicidal Ideation

Individuals with type 1 diabetes have higher rates of depression and suicidal ideation than the general population, and symptoms of depression are often associated with higher A1C levels and complications. This study evaluated mental health follow-up rates in youth and young adults with type 1 diabetes who screened positive for depressive symptoms or suicidal ideation and identified differences between those who obtained follow-up mental health care and those who did not. Specifically, males were less likely to obtain follow-up, and those who had mental health follow-up had decreasing A1C over the following year. These findings suggest increased assistance and monitoring are needed to ensure follow-up mental health care is obtained.

Factors Associated With Improved A1C Among Adults With Type 1 Diabetes in the United States

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.

Changes in HbA1c Between 2011 and 2017 in Germany/Austria, Sweden, and the United States: A Lifespan Perspective

Aims: This study assessed hemoglobin A1c (HbA1c) across the lifespan in people with type 1 diabetes (T1D) in Germany/Austria, Sweden, and the United States between 2011 and 2017 to ascertain temporal and age-related trends. Methods: Data from the Diabetes-Patienten-Verlaufsdokumentation (DPV) (n = 25,651 in 2011, n = 29,442 in 2017); Swedish Pediatric Diabetes Quality Registry (SWEDIABKIDS)/National Diabetes Register (NDR), (n = 44,474 in 2011, n = 53,690 in 2017); and T1D Exchange (n = 16,198 in 2011, n = 17,087 in 2017) registries were analyzed by linear regression to compare mean HbA1c overall and by age group. Results: Controlling for age, sex, and T1D duration, HbA1c increased in the United States between 2011 and 2017, decreased in Sweden, and did not change in Germany/Austria. Controlling for sex and T1D duration, mean HbA1c decreased between 2011 and 2017 in all age cohorts in Sweden (P < 0.001). In the United States, HbA1c stayed the same for participants <6 years and 45 to <65 years and increased in all other age groups (P < 0.05). In Germany/Austria, HbA1c stayed the same for participants <6 to <13 years and 18 to <25 years; decreased for participants ages 13 to <18 years (P < 0.01); and increased for participants ≥25 years (P < 0.05). Conclusions: The comparison of international trends in HbA1c makes it possible to identify differences, explore underlying causes, and share quality improvement processes. National quality improvement initiatives are well accepted in Europe but have yet to be implemented systematically in the United States. However, disparities created by the lack of universal access to health care coverage, unequal access to diabetes technologies (e.g., continuous glucose monitoring) regardless of insurance status, and high out-of-pocket cost for the underinsured ultimately limit the potential of quality improvement initiatives.

Facilitators and Barriers to Smart Insulin Pen Use: A Mixed-Method Study of Multidisciplinary Stakeholders From Diabetes Teams in the United States

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.

Alert burden in pediatric hospitals: a cross-sectional analysis of six academic pediatric health systems using novel metrics

BACKGROUND

Excessive electronic health record (EHR) alerts reduce the salience of actionable alerts. Little is known about the frequency of interruptive alerts across health systems and how the choice of metric affects which users appear to have the highest alert burden.

OBJECTIVE

(1) Analyze alert burden by alert type, care setting, provider type, and individual provider across 6 pediatric health systems. (2) Compare alert burden using different metrics.

MATERIALS AND METHODS

We analyzed interruptive alert firings logged in EHR databases at 6 pediatric health systems from 2016-2019 using 4 metrics: (1) alerts per patient encounter, (2) alerts per inpatient-day, (3) alerts per 100 orders, and (4) alerts per unique clinician days (calendar days with at least 1 EHR log in the system). We assessed intra- and interinstitutional variation and how alert burden rankings differed based on the chosen metric.

RESULTS

Alert burden varied widely across institutions, ranging from 0.06 to 0.76 firings per encounter, 0.22 to 1.06 firings per inpatient-day, 0.98 to 17.42 per 100 orders, and 0.08 to 3.34 firings per clinician day logged in the EHR. Custom alerts accounted for the greatest burden at all 6 sites. The rank order of institutions by alert burden was similar regardless of which alert burden metric was chosen. Within institutions, the alert burden metric choice substantially affected which provider types and care settings appeared to experience the highest alert burden.

CONCLUSION

Estimates of the clinical areas with highest alert burden varied substantially by institution and based on the metric used.

Feasibility of Electronic Health Record Assessment of 6 Pediatric Type 1 Diabetes Self-management Habits and Their Association With Glycemic Outcomes

IMPORTANCE

A low-burden electronic health record (EHR) workflow has been devised to systematize the collection and validation of 6 key diabetes self-management habits: (1) checks glucose at least 4 times/day or uses continuous glucose monitor (CGM); (2) gives at least 3 rapid-acting insulin boluses per day; (3) uses insulin pump; (4) delivers boluses before meals; (5) reviewed glucose data since last clinic visit, and (6) has changed insulin doses since the last clinic visit.

OBJECTIVE

To describe the performance of these habits and examine their association with hemoglobin A1c (HbA1c) levels and time in range (TIR).

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study included individuals with known type 1 diabetes who were seen in a US pediatric diabetes clinic in 2019.

MAIN OUTCOMES AND MEASURES

Habit performance, total habit score (sum of 6 habits per person), HbA1c levels, and TIR.

RESULTS

Of 1344 patients, 1212 (609 [50.2%] males; 66 [5.4%] non-Hispanic Black; 1030 [85.0%] non-Hispanic White; mean [SD] age, 15.5 [4.5] years) were included, of whom 654 (54.0%) were using CGM and had a TIR. Only 105 patients (8.7%) performed all 6 habits. Habit performance was lower among older vs younger patients (age ≥18 years vs ≤12 years: 17 of 411 [4.1%] vs 57 of 330 [17.3%]; P < .001), Black vs White patients (3 [4.5%] vs 95 [9.2%]; P < .001), those with public vs private insurance (14 of 271 [5.2%] vs 91 of 941 [9.7%]; P < .001), and those with lower vs higher parental education levels (<college degree vs ≥college degree: 35 of 443 [7.9%] vs 66 of 574 [11.5%]; P < .001). After adjustment for demographic characteristics and disease duration, for every 1-unit increase in total habit score, we found a mean (SE) 0.6% (0.05) decrease in HbA1c among all participants and a mean (SE) 2.86% (0.71) increase in TIR among those who used CGMs. Multiple regression models revealed that performing each habit was associated with a significantly lower HbA1c level (habit 1: -0.16% [95% CI, -1.91% to -1.37%]; habit 2: -1.01% [-1.34% to -0.69%]; habit 3: -0.71% [95% CI, -0.93% to -0.49%]; habit 4: -0.97% [95% CI, -1.21% to -0.73%]; habit 5: -0.44% [95% CI, -0.71% to -0.17%]; habit 6: -0.75% [95% CI, -0.96% to -0.53%]; all P < .001). There were differences in HbA1c according to race, insurance, and parental education, but these associations were attenuated with the inclusion of the 6 habits, which had more robust associations with HbA1c levels than the demographic characteristics.

CONCLUSIONS AND RELEVANCE

These findings suggest that a focus on increasing adherence to the 6 habits could be critical for improving disparities in glycemic outcomes; these metrics have been adopted by the Type 1 Diabetes Exchange Quality Improvement Collaborative for continuous quality improvement.

Diabetic ketoacidosis drives COVID-19 related hospitalizations in children with type 1 diabetes

BACKGROUND

Diabetes is a risk factor for poor COVID-19 outcomes, but pediatric patients with type 1 diabetes are poorly represented in current studies.

METHODS

T1D Exchange coordinated a US type 1 diabetes COVID-19 registry. Forty-six diabetes centers submitted pediatric cases for patients with laboratory confirmed COVID-19. Associations between clinical factors and hospitalization were tested with Fisher's Exact Test. Logistic regression was used to calculate odds ratios for hospitalization.

RESULTS

Data from 266 patients with previously established type 1 diabetes aged <19 years with COVID-19 were reported. Diabetic ketoacidosis (DKA) was the most common adverse outcome (n = 44, 72% of hospitalized patients). There were four hospitalizations for severe hypoglycemia, three hospitalizations requiring respiratory support (one of whom was intubated and mechanically ventilated), one case of multisystem inflammatory syndrome in children, and 10 patients who were hospitalized for reasons unrelated to COVID-19 or diabetes. Hospitalized patients (n = 61) were more likely than nonhospitalized patients (n = 205) to have minority race/ethnicity (67% vs 39%, P < 0.001), public insurance (64% vs 41%, P < 0.001), higher A1c (11% [97 mmol/mol] vs 8.2% [66 mmol/mol], P < 0.001), and lower insulin pump and lower continuous glucose monitoring use (26% vs 54%, P < 0.001; 39% vs 75%, P < 0.001). Age and gender were not associated with risk of hospitalization. Higher A1c was significantly associated with hospitalization, with an odds ratio of 1.56 (1.34-1.84) after adjusting for age, gender, insurance, and race/ethnicity.

CONCLUSIONS

Higher A1c remained the only predictor for hospitalization with COVID-19. Diabetic ketoacidosis is the primary concern among this group.

Multi-Clinic Quality Improvement Initiative Increases Continuous Glucose Monitoring Use Among Adolescents and Young Adults With Type 1 Diabetes

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.

Quality Improvement in Diabetes Care: A Review of Initiatives and Outcomes in the T1D Exchange Quality Improvement Collaborative

Despite immense strides in therapeutic advances, clinical outcomes continue to be less than ideal for people with type 1 diabetes. This discrepancy has prompted an outpouring of quality improvement (QI) initiatives to address the medical, psychosocial, and health equity challenges that complicate ideal type 1 diabetes care and outcomes. This article reviews a framework for QI in diabetes care that guided the development of the T1D Exchange Quality Improvement Collaborative to improve care delivery and health outcomes in type 1 diabetes. Evaluation of the methodology, outcomes, and knowledge gained from these initiatives will highlight the importance of continued QI initiatives in diabetes care.

Inequities in Health Outcomes in Children and Adults With Type 1 Diabetes: Data From the T1D Exchange Quality Improvement Collaborative

Health care inequities among racial and ethnic groups remain prevalent. For people with type 1 diabetes who require increased medical access and care, disparities are seen in access to care and health outcomes. This article reports on a study by the T1D Exchange Quality Improvement Collaborative evaluating differences in A1C, diabetic ketoacidosis (DKA), severe hypoglycemia, and technology use among racial and ethnic groups. In a diverse cohort of nearly 20,000 children and adults with type 1 diabetes, A1C was found to differ significantly among racial and ethnic groups. Non-Hispanic Blacks had higher rates of DKA and severe hypoglycemia and the lowest rate of technology use. These results underscore the crucial need to study and overcome the barriers that lead to inequities in the care and outcomes of people with type 1 diabetes.

Increasing Insulin Pump Use Among 12- to 26-Year-Olds With Type 1 Diabetes: Results From the T1D Exchange Quality Improvement Collaborative

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.