National diabetes registries: do they make a difference?

Incidence trend of type 2 diabetes from 2012 to 2021 in Germany: an analysis of health claims data of 11 million statutorily insured people

AIMS/HYPOTHESIS

The aim of the study is to describe the time trend of type 2 diabetes incidence in the largest state of Germany, Bavaria, from 2012 to 2021, and to compare the incidence rates during the pandemic period (2020-2021) to the pre-pandemic period (2012-2019).

METHODS

This secondary data analysis uses health claims data provided by the Bavarian Association of Statutory Health Insurance Physicians (KVB), covering approximately 11 million insurees, accounting for 85% of the total population of Bavaria, Germany. Newly diagnosed type 2 diabetes cases in adults (≥20 years) coded as E11 (Diabetes mellitus, Type 2) or E14 (Unspecified diabetes mellitus) under ICD-10, German modification (ICD-10-GM) for the study period 2012 to 2021 were included. Annual and quarterly age-standardised incidence rates (ASIR) stratified by sex, age and region were calculated using the European standard population. Sex-specific crude incidence rates (CIR) were calculated using 10-year age groups. Regression analyses adjusted for time trends, seasonal effects, and pandemic effects were used to analyse the incidence trend and to assess the effect of the pandemic.

RESULTS

Overall, 745,861 new cases of type 2 diabetes were diagnosed between 2012 and 2021: 50.4% (376,193 cases) in women. The male/female ratio remained stable over the observation period, while the median age at diagnosis decreased from 61 to 58 years in men and from 66 years to 61 years in women. ASIR were consistently higher for men compared with women, with the yearly difference remaining stable over time (2012: 18%; 2021: 20%). An overall decreasing trend in ASIR was observed during the study period, with a strong decrease from 2012 to 2017, followed by a less pronounced decline from 2018 to 2021 for both sexes. For men, ASIR decreased from 1514 per 100,000 person-years in 2012 to 995 per 100,000 person-years in 2021 (4.6% average annual reduction), and for women from 1238 per 100,000 person-years in 2012 to 796 per 100,000 person-years in 2021 (4.8% average annual reduction). This downward trend was also observed for age groups above 50 years. Regression analyses showed no significant change in incidence rates during the pandemic period (2020 and 2021) compared with the pre-pandemic period.

CONCLUSIONS/INTERPRETATION

For the first time, a 10-year incidence trend of type 2 diabetes is reported for Germany, showing a strong decline from 2012 to 2017, followed by a less pronounced decline from 2018 to 2021. The incidence trend of type 2 diabetes appears not to have been affected by the first 2 years of the COVID-19 pandemic. Despite an overall increasing prevalence, the incidence is decreasing, potentially resulting from robust screening by family physicians, reducing the median age at diagnosis by 3 to 5 years. However, further investigation is needed to fully identify the reasons for the declining incidence trend. Continued incidence monitoring is necessary to identify the long-term trend and the potential effect of the pandemic on diagnoses of type 2 diabetes.

The Development of the Municipal Registry of People with Diabetes in Porto Alegre, Brazil

Background/Objective: Diabetes registries that enhance surveillance and improve medical care are uncommon in low- and middle-income countries, where most of the diabetes burden lies. We aimed to describe the methodological and technical aspects adopted in the development of a municipal registry of people with diabetes using local and national Brazilian National Health System databases. Methods: We obtained data between July 2018 and June 2021 based on eight databases covering primary care, specialty and emergency consultations, medication dispensing, outpatient exam management, hospitalizations, and deaths. We identified diabetes using the International Classification of Disease (ICD), International Classification of Primary Care (ICPC), medications for diabetes, hospital codes for the treatment of diabetes complications, and exams for diabetes management. Results: After data processing and database merging using deterministic and probabilistic linkage, we identified 73,185 people with diabetes. Considering that 1.33 million people live in Porto Alegre, the registry captured 5.5% of the population. Conclusions: With additional data processing, the registry can reveal information on the treatment and outcomes of people with diabetes who are receiving publicly financed care in Porto Alegre. It will provide metrics for epidemiologic surveillance, such as the incidence, prevalence, rates, and trends of complications and causes of mortality; identify inadequacies; and provide information. It will enable healthcare providers to monitor the quality of care, identify inadequacies, and provide feedback as needed.

Potency of quality indicators in Dutch and international diabetes registries

BACKGROUND

Diabetes mellitus forms a slow pandemic. Cardiovascular risk and quality of diabetes care are strongly associated. Quality indicators improve diabetes management and reduce mortality and costs. Various national diabetes registries render national quality indicators. We describe diabetes care indicators for Dutch children and adults with diabetes, and compare them with indicators established by registries worldwide.

METHODS

Indicator scores were derived from the Dutch Pediatric and Adult Registry of Diabetes Indicator sets of other national diabetes registries were collected and juxtaposed with global and continental initiatives for indicator sets.

RESULTS

This observational cohort study included 3738 patients representative of the Dutch diabetic outpatient population. The Dutch Pediatric and Adult Registry of Diabetes harbors ten quality indicators comprising treatment volumes, HbA1c control, foot examination, insulin pump therapy, and real-time continuous glucose monitoring. Worldwide, nine national registries record quality indicators, with great variety between registries. HbA1c control is recorded most frequently, and no indicator is reported among all registries.

CONCLUSIONS

Wide variety among quality indicators recorded by national diabetes registries hinders international comparison and interpretation of quality of diabetes care. The potential of quality evaluation will be greatly enhanced when diabetes care indicators are aligned in an international standard set with variation across countries taken into consideration.

Exploring the association between primary care efficiency and health system characteristics across European countries: a two-stage data envelopment analysis

BACKGROUND

Primary care is widely seen as a core component of resilient and sustainable health systems, yet its efficiency is not well understood and there is a lack of evidence about how primary care efficiency is associated with health system characteristics. We examine this issue through the lens of diabetes care, which has a well-established evidence base for effective treatment and has previously been used as a tracer condition to measure health system performance.

METHODS

We developed a conceptual framework to guide the analysis of primary care efficiency. Using data on 18 European countries during 2010-2016 from several international databases, we applied a two-stage data envelopment analysis to estimate (i) technical efficiency of primary care and (ii) the association between efficiency and health system characteristics.

RESULTS

Countries varied widely in terms of primary care efficiency, with efficiency scores depending on the range of population characteristics adjusted for. Higher efficiency was associated with bonus payments for the prevention and management of chronic conditions, nurse-led follow-up, and a financial incentive or requirement for patients to obtain a referral to specialist care. Conversely, lower efficiency was associated with higher rates of curative care beds and financial incentives for patients to register with a primary care provider.

CONCLUSIONS

Our results underline the importance of considering differences in population characteristics when comparing country performance on primary care efficiency. We highlight several policies that could enhance the efficiency of primary care. Improvements in data collection would enable more comprehensive assessments of primary care efficiency across countries, which in turn could more effectively inform policymaking.

Which diabetes specific patient reported outcomes should be measured in routine care? A systematic review to inform a core outcome set for adults with Type 1 and 2 diabetes mellitus: The European Health Outcomes Observatory (H2O) programme

OBJECTIVES

The objective was to identify candidate patient reported outcomes with potential to inform individual patient care and service development for inclusion in a digital outcome set to be collected in routine care, as part of an international project to enhance care outcomes for people with diabetes.

METHODS

PubMed, COSMIN and COMET databases were searched. Published studies were included if they recommended patient reported outcomes that were clinically useful and/or important to people with diabetes. To aid selection decisions, recommended outcomes were considered in terms of the evidence endorsing them and their importance to people with diabetes.

RESULTS

Twenty-seven studies recommending 53 diabetes specific outcomes, and patient reported outcome measures, were included. The outcomes reflected the experience of living with diabetes (e.g. psychological well-being, symptom experience, health beliefs and stigma) and behaviours (e.g. self-management). Diabetes distress and self-management behaviours were most endorsed by the evidence.

CONCLUSIONS

The review provides a comprehensive list of candidate outcomes endorsed by international evidence and informed by existing outcome sets, and suggestions for measures.

PRACTICE IMPLICATIONS

The review offers evidence to guide clinical application. Integrated measurement of these outcomes in care settings holds enormous potential to improve provision of care and outcomes in diabetes.

Longitudinal Trends in Glycemic Outcomes and Technology Use for Over 48,000 People with Type 1 Diabetes (2016-2022) from the T1D Exchange Quality Improvement Collaborative

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.

Evidence of increasing incidence of type 1 diabetes and ketoacidosis among children in the Republic of Srpska in period 2017-2022 with special focus on COVID-19 global pandemic years

Background and objectives

Primary focus of the research was to determine the incidence of type 1 diabetes mellitus in the period from 2017 to 2022, and whether COVID-19 had an impact on the increase in the number of newly diagnosed children with diabetes type 1 under the age of 15 in the Republic of Srpska (Bosnia and Herzegovina). In the period 2001-2016 the incidence of type 1 diabetes mellitus was 11/100,000, with an annual increasing rate of 14.2%.

Methods

Available data from pediatric endocrinology clinics, in the Republic of Srpska, on the number of newly diagnosed patients with diabetes mellitus in the period from January 1, 2017 until December 31, 2022 were used. A retrospective analysis was performed, and the capture-recapture method was used for the final assessment, and the obtained result corresponds to about 99% of the population.

Results

The total number of children in the group of 0-14 years of age diagnosed with type 1 diabetes mellitus in this period was 183, of which 96 (52.46%) were boys, and 87 (47.54%) were girls. The average age at which diabetes mellitus was diagnosed was 8.3 ± 3.9 years. Average incidence of diabetes in the period 2017-2022 was 19/100,000 (95% CI 13.1-25.0). The highest incidence was 28.7/100,000 in 2020, the first year of the global COVID-19 pandemic. Out of a total of 183 newly diagnosed cases in the period 2017-2022, 73 (39.9%) were diagnosed with ketoacidosis upon admission. The largest number of newly diagnosed children was recorded in the group of children aged 10-14 years.

Conclusion

In the last 6 years, there has been a significant increase in the incidence of type 1 diabetes mellitus in children under the age of 15. With an incidence of 19.4/100,000 in the Republic of Srpska, we entered the group of countries with high-risk for diabetes. Further steps must focus on the education of the entire society in order to recognize the symptoms of the disease in time and prevent the occurrence of ketoacidosis, which could significantly reduce the burden on health systems, especially in times of global pandemics, such as the COVID-19 pandemic.

Response Consistency of Crowdsourced Web-Based Surveys on Type 1 Diabetes

Although Amazon Mechanical Turk facilitates the quick surveying of a large sample from various demographic and socioeconomic backgrounds, it may not be an optimal platform for obtaining reliable diabetes-related information from the online type 1 diabetes population.

Validation of Register-Based Diabetes Classifiers in Danish Data

Purpose

To validate two register-based algorithms classifying type 1 (T1D) and type 2 diabetes (T2D) in a general population using Danish register data.

Patients and Methods

After linking data on prescription drug usage, hospital diagnoses, laboratory results and diabetes-specific healthcare services from nationwide healthcare registers, diabetes type was defined for all individuals in Central Denmark Region age 18-74 years on 31 December 2018 according to two distinct register-based classifiers: 1) a novel register-based diabetes classifier incorporating diagnostic hemoglobin-A1C measurements, the Open-Source Diabetes Classifier (OSDC), and 2) an existing Danish diabetes classifier, the Register for Selected Chronic Diseases (RSCD). These classifications were validated against self-reported data from the Health in Central Denmark survey - overall and stratified by age at onset of diabetes. The source-code of both classifiers was made available in the open-source R package osdc.

Results

A total of 2633 (9.0%) of 29,391 respondents reported having any type of diabetes, divided across 410 (1.4%) self-reported cases of T1D and 2223 (7.6%) cases of T2D. Among all self-reported diabetes cases, 2421 (91.9%) were classified as diabetes cases by both classifiers. In T1D, sensitivity of OSDC-classification was 0.773 [95% CI 0.730-0.813] (RSCD: 0.700 [0.653-0.744]) and positive predictive value (PPV) 0.943 [0.913-0.966] (RSCD: 0.944 [0.912-0.967]). In T2D, sensitivity of OSDC-classification was 0.944 [0.933-0.953] (RSCD: 0.905 [0.892-0.917]) and PPV 0.875 [0.861-0.888] (RSCD: 0.898 [0.884-0.910]). In age at onset-stratified analyses of both classifiers, sensitivity and PPV were low in individuals with T1D onset after age 40 and T2D onset before age 40.

Conclusion

Both register-based classifiers identified valid populations of T1D and T2D in a general population, but sensitivity was substantially higher in OSDC compared to RSCD. Register-classified diabetes type in cases with atypical age at onset of diabetes should be interpreted with caution. The validated, open-source classifiers provide robust and transparent tools for researchers.

Establishing the Australian National Endometriosis Clinical and Scientific Trials (NECST) Registry: A protocol paper

Endometriosis is a common yet under-recognised chronic inflammatory disease, affecting 176 million women, trans and gender diverse people globally. The National Endometriosis Clinical and Scientific Trials (NECST) Registry is a new clinical registry, collecting and tracking diagnostic and treatment data, and patient-reported outcomes on people with endometriosis. The registry is a research priority action item from the 2018 National Action Plan for Endometriosis and aims to provide, large-scale, national and longitudinal population-based data on endometriosis. Working groups (consisting of patients with endometriosis, clinicians and researchers) developing the NECST Registry data dictionary and data collection platform started in 2019. Our data dictionary was developed based on existing and validated questionnaires, tools, meta-data and data cubes - World Endometriosis Research Foundation (WERF) Endometriosis Phenome and Biobanking Harmonisation Project (EPHect), endometriosis CORE outcomes set, patient-reported outcome measures, the International Statistical Classification of Diseases-10th Revision Australian Modification diagnosis codes, and Australian Government datasets: Australian Institute for Health and Welfare (for sociodemographic data), Medicare Benefits Schedule (MBS; for medical procedures) and the Pharmaceutical Benefits Scheme (PBS; for medical therapies). The resulting NECST Registry is an online, secure cloud-based database; prospectively collecting minimum core clinical and health data across eight patient and clinician modules and longitudinal data tracking disease life course. The NECST Registry has ethics approval (HREC/62508/MonH-2020) and is registered on the Australian New Zealand Clinical Trials Registry (ACTRN12622000987763).

Availability and access to pediatric diabetes care: a global descriptive study

A decade since the discovery of insulin, the increasing prevalence of type 1 diabetes mellitus (T1DM) has underscored the prevailing inequalities in the provision of essential care for T1DM worldwide. However, the details on the availability of insulin types and associated medical devices remain unclear. A cross-sectional electronic survey was distributed across a global network of pediatric societies under the umbrella of the International Pediatric Association (IPA). Access to and availability of pediatric diabetes care were investigated using standardized questions. Responses from 25 of 132 pediatric societies across six regions were included. Pediatric endocrinologists typically manage T1DM together with pediatricians or adult endocrinologists. Nonetheless, 24% of the respondents reported pediatricians to be the sole healthcare professionals. According to the respondents, the patients were either partially or completely responsible for payments of insulin (40%), A1C (24%), C-peptide (28%), and antibody testing for diagnosis (28%). Government support is generally available for insulin, but this was merely 20% for insulin pumps and 12% for continuous glucose monitors. There are considerable disparities in the access, availability, and affordability of diabetes testing, medications, and support between countries with significant out-of-pocket payments for care. Country- and region-specific improvements to national programs are necessary to achieve optimal pediatric diabetes care globally.

Characteristics of diabetes mellitus patients in Turkey: An analysis of national electronic health records

BACKGROUND

It was estimated that there were 537 million people with diabetes mellitus in 2021, representing 10.5% of the global adult population. Diabetes prevalence in Turkey is 13.5%, according to a meta-analysis and 17.3% according to a recent study. Although the primary purpose of Electronic Health Records (EHRs) is clinical, researchers can use them to conduct epidemiologic investigations. This study aims to document the prevalence of diabetes and to evaluate the healthcare utilization of people with diabetes compared to the people without diabetes, based on national EHR.

METHODS

Only people over 14 years old were included in the analysis. Our criteria for being diabetic were 1) having an HbA1c over 6.5% (48 mmol/mol), 2) having a prescription with DM diagnosis, ICD-10 codes E10-E14, or 3) having at least two fasting blood glucose measurements over 126 mg/dl.

RESULTS

At the end of 2020, there were 7,178,674 individuals with diabetes, with 11.12% prevalence, 13.10% in women while 9.12% in men. Age-adjusted healthcare facility admission per capita was 15.5 for people with diabetes, 9.5 for people without diabetes, while the number of prescriptions was 7.9 for people with diabetes while 4.5 for people without diabetes in 2019. The mean number of prescriptions containing antidiabetics was 2.88 per person with diabetes in 2019.

DISCUSSION

Approximately 11% of Turkish people have diagnosed with diabetes. We estimate that about one-third of people with diabetes are undiagnosed and the majority of these people are men. The results show that such large databases have the capability of supplying a vast amount of information to the scientific community.

Six Digital Health Technologies That Will Transform Diabetes

The digital health revolution is transforming the landscape of medicine through innovations in sensor data, software, and wireless communication tools. As one of the most prevalent chronic diseases in the United States, diabetes is particularly impactful as a model disease for which to apply innovation. As with any other newly developed technologies, there are three key questions to consider: 1) How can the technology benefit people with diabetes?, 2) What barriers must be overcome to further advance the technology?, and 3) How will the technology be applied in the future?. In this article, we highlight six areas of innovation that have the potential to reduce the burden of diabetes for individuals living with the condition and their families as well as provide measurable benefits for all stakeholders involved in diabetes care. The six technologies which have the potential to transform diabetes care are (i) telehealth, (ii) incorporation of diabetes digital data into the electronic health record, (iii) qualitative hypoglycemia alarms, (iv) artificial intelligence, (v) cybersecurity of diabetes devices, and (vi) diabetes registries. To be successful, a new digital health technology must be accessible and affordable. Furthermore, the people and communities that would most likely benefit from the technology must be willing to use the innovation in their management of diabetes.

Trends in diabetes-related foot disease hospitalizations and amputations in Australia, 2010 to 2019

AIM

To determine trends in the incidence of hospitalizations and amputations for diabetes-related foot disease (DFD) in Australia.

METHODS

We included 70,766 people with type 1, and 1,087,706 with type 2 diabetes from the Australian diabetes registry from 2010 to 2019, linked to hospital admissions databases. Trends in age-adjusted incidence were summarized as annual percent changes (APC).

RESULTS

In people with type 1 diabetes, total DFD hospitalizations increased from 20.8 to 30.5 per 1,000 person-years between 2010 and 2019 (APC: 5.1% (95% CI: 3.5, 6.8)), including increases for ulceration (13.3% (2.9, 24.7)), osteomyelitis (5.6% (2.7, 8.7)), peripheral arterial disease (7.7% (3.7, 11.9)), and neuropathy (8.7% (5.5, 12.0)). In people with type 2 diabetes, DFD hospitalizations changed from 18.6 to 24.8 per 1,000 person-years between 2010 and 2019 (APC: 4.5% (3.6, 5.4); 2012-2019), including increases for ulceration (8.7% (4.0, 13.7)), cellulitis (5.4% (3.7, 7.0)), osteomyelitis (6.7% (5.7, 7.7)), and neuropathy (6.9% (5.2, 8.5)). Amputations were stable in type 1, whereas in type 2, above knee amputations decreased (-6.0% (-9.1, -2.7). Adjustment for diabetes duration attenuated the magnitude of most increases, but many remained significant.

CONCLUSIONS

DFD hospitalizations increased markedly in Australia, mainly driven by ulceration and neuropathy, highlighting the importance of managing DFD to prevent hospitalizations.

Development and operationalization of a data framework to assess quality of integrated diabetes care in the fragmented data landscape of Belgium

Background

To assess the quality of integrated diabetes care, we should be able to follow the patient throughout the care path, monitor his/her care process and link them to his/her health outcomes, while simultaneously link this information to the primary care system and its performance on the structure and organization related quality indicators. However the development process of such a data framework is challenging, even in period of increasing and improving health data storage and management. This study aims to develop an integrated multi-level data framework for quality of diabetes care and to operationalize this framework in the fragmented Belgium health care and data landscape.

Methods

Based on document reviews, iterative working group discussions and expert consultations, theoretical approaches and quality indicators were identified and assessed. After mapping and assessing the validity of existing health information systems and available data sources through expert consultations, the theoretical framework was translated in a data framework with measurable quality indicators. The construction of the data base included sampling procedures, data-collection, and several technical and privacy-related aspects of linking and accessing Belgian datasets.

Results

To address three dimensions of quality of care, we integrated the chronic care model and cascade of care approach, addressing respectively the structure related quality indicators and the process and outcome related indicators. The corresponding data framework is based on self-collected data at the primary care practice level (using the Assessment of quality of integrated care tool), and linked health insurance data with lab data at the patient level.

Conclusion

In this study, we have described the transition of a theoretical quality of care framework to a unique multilevel database, which allows assessing the quality of diabetes care, by considering the complete care continuum (process and outcomes) as well as organizational characteristics of primary care practices.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-08625-8.

Global incidence, prevalence, and mortality of type 1 diabetes in 2021 with projection to 2040: a modelling study

BACKGROUND

Accurate data on type 1 diabetes prevalence, incidence, associated mortality and life expectancy are crucial to inform public health policy, but these data are scarce. We therefore developed a model based on available data to estimate these values for 201 countries for the year 2021 and estimate the projected prevalent cases in 2040.

METHODS

We fitted a discrete-time illness-death model (Markov model) to data on type 1 diabetes incidence and type 1 diabetes-associated mortality to produce type 1 diabetes prevalence, incidence, associated mortality and life expectancy in all countries. Type 1 diabetes incidence and mortality data were available from 97 and 37 countries respectively. Diagnosis rates were estimated using data from an expert survey. Mortality was modelled using random-forest regression of published type 1 diabetes mortality data, and life expectancy was calculated accordingly using life tables. Estimates were validated against observed prevalence data for 15 countries. We also estimated missing prevalence (the number of additional people who would be alive with type 1 diabetes if their mortality matched general population rates).

FINDINGS

In 2021, there were about 8·4 (95% uncertainty interval 8·1-8·8) million individuals worldwide with type 1 diabetes: of these 1·5 million (18%) were younger than 20 years, 5·4 million (64%) were aged 20-59 years, and 1·6 million (19%) were aged 60 years or older. In that year there were 0·5 million new cases diagnosed (median age of onset 39 years), about 35 000 non-diagnosed individuals died within 12 months of symptomatic onset. One fifth (1·8 million) of individuals with type 1 diabetes were in low-income and lower-middle-income countries. Remaining life expectancy of a 10-year-old diagnosed with type 1 diabetes in 2021 ranged from a mean of 13 years in low-income countries to 65 years in high-income countries. Missing prevalent cases in 2021 were estimated at 3·7 million. In 2040, we predict an increase in prevalent cases to 13·5-17·4 million (60-107% higher than in 2021) with the largest relative increase versus 2021 in low-income and lower-middle-income countries.

INTERPRETATION

The burden of type 1 diabetes in 2021 is vast and is expected to increase rapidly, especially in resource-limited countries. Most incident and prevalent cases are adults. The substantial missing prevalence highlights the premature mortality of type 1 diabetes and an opportunity to save and extend lives of people with type 1 diabetes. Our new model, which will be made publicly available as the Type 1 Diabetes Index model, will be an important tool to support health delivery, advocacy, and funding decisions for type 1 diabetes.

FUNDING

JDRF International.

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.

Implementing the Digital Diabetes Questionnaire as a Clinical Tool in Routine Diabetes Care: Focus Group Discussions With Patients and Health Care Professionals

BACKGROUND

The Diabetes Questionnaire is a digital patient-reported outcome and experience measure for adults living with diabetes. The Diabetes Questionnaire is intended for use in routine clinical visits in diabetes care and to enable patient perspectives to be integrated into the Swedish National Diabetes Register. The Diabetes Questionnaire was developed on the basis of patients' perspectives, and evidence for its measurement qualities has been demonstrated. Patients receive an invitation to complete the questionnaire before clinical visits, and the patient and health care professional (HCP) can discuss the findings, which are instantly displayed during the visit. Implementation processes for new tools in routine care need to be studied to understand the influence of contextual factors, the support needed, and how patients and HCPs experience clinical use.

OBJECTIVE

The aim of this study was to describe patients' and HCPs' experiences of initiating the use of the digital Diabetes Questionnaire as a clinical tool in routine diabetes care, supported by a structured implementation strategy involving initial education, local facilitators, and regular follow-ups.

METHODS

In this qualitative study, semistructured focus group discussions were conducted 12 months after the use of the Diabetes Questionnaire was initiated. Participants were diabetes specialist nurses and physicians (20 participants in 4 groups) at hospital-based outpatient clinics or primary health care clinics and adults with type 1 or type 2 diabetes (15 participants in 4 groups). The audiotaped transcripts were analyzed using inductive qualitative content analysis.

RESULTS

The results revealed 2 main categories that integrated patients' and HCPs' experiences, which together formed an overarching theme: While implementation demands new approaches, the Diabetes Questionnaire provides a broader perspective. The first main category (The Diabetes Questionnaire supports person-centered clinical visits) comprised comments expressing that the digital Diabetes Questionnaire can initiate and encourage reflection in preparation for clinical visits, bring important topics to light during clinical visits, and broaden the scope of discussion by providing additional information. The second main category (The process of initiating the implementation of the Diabetes Questionnaire) comprised comments that described differences in engagement among HCPs and their managers, challenges of establishing new routines, experiences of support during implementation, thoughts about the Diabetes Questionnaire, need to change local administrative routines, and opportunities and concerns for continued use.

CONCLUSIONS

The Diabetes Questionnaire can broaden the scope of health data in routine diabetes care. While implementation demands new approaches, patients and HCPs saw potential positive impacts of using the questionnaire at both the individual and group levels. Our results can inform further development of implementation strategies to support the clinical use of the questionnaire.

The Incidence of Adult-Onset Type 1 Diabetes: A Systematic Review From 32 Countries and Regions

BACKGROUND

The epidemiology of adult-onset type 1 diabetes (T1D) incidence is not well-characterized due to the historic focus on T1D as a childhood-onset disease.

PURPOSE

We assess the incidence of adult-onset (≥20 years) T1D, by country, from available data.

DATA SOURCES

A systematic review of MEDLINE, Embase, and the gray literature, through 11 May 2021, was undertaken.

STUDY SELECTION

We included all population-based studies reporting on adult-onset T1D incidence and published from 1990 onward in English.

DATA EXTRACTION

With the search we identified 1,374 references of which 46 were included for data extraction. Estimates of annual T1D incidence were allocated into broad age categories (20-39, 40-59, ≥60, or ≥20 years) as appropriate.

DATA SYNTHESIS

Overall, we observed the following patterns: 1) there is a paucity of data, particularly in low- and middle-income countries; 2) the incidence of adult-onset T1D is lowest in Asian and highest in Nordic countries; 3) adult-onset T1D is higher in men versus women; 4) it is unclear whether adult-onset T1D incidence declines with increasing age; and 5) it is unclear whether incidence of adult-onset T1D has changed over time.

LIMITATIONS

Results are generalizable to high-income countries, and misclassification of diabetes type cannot be ruled out.

CONCLUSIONS

From available data, this systematic review suggests that the incidence of T1D in adulthood is substantial and highlights the pressing need to better distinguish T1D from T2D in adults so that we may better assess and respond to the true burden of T1D in adults.

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.

Making Use of Comparable Health Data to Improve Quality of Care and Outcomes in Diabetes: The EUBIROD Review of Diabetes Registries and Data Sources in Europe

Background

Registries and data sources contain information that can be used on an ongoing basis to improve quality of care and outcomes of people with diabetes. As a specific task of the EU Bridge Health project, we carried out a survey of diabetes-related data sources in Europe.

Objectives

We aimed to report on the organization of different sources of diabetes information, including their governance, information infrastructure and dissemination strategies for quality control, service planning, public health, policy and research.

Methods

Survey using a structured questionnaire to collect targeted data from a network of collaborating institutions managing registries and data sources in 17 countries in the year 2017.

Results

The 18 data sources participating in the study were most frequently academic centres (44.4%), national (72.2%), targeting all types of diabetes (61.1%) covering no more than 10% of the target population (44.4%). Although population-based in over a quarter of cases (27.8%), sources relied predominantly on provider-based datasets (38.5%), fewer using administrative data (16.6%). Data collection was continuous in the majority of cases (61.1%), but 50% could not perform data linkage. Public reports were more frequent (72.2%) as well as quality reports (77.8%), but one third did not provide feedback to policy and only half published ten or more peer reviewed papers during the last 5 years.

Conclusions

The heterogeneous implementation of diabetes registries and data sources hampers the comparability of quality and outcomes across Europe. Best practices exist but need to be shared more effectively to accelerate progress and deliver equitable results for people with diabetes.

DPARD: rationale, design and initial results from the Dutch national diabetes registry

BACKGROUND

Treatment of diabetes mellitus has majorly improved over the past century, however, the disease burden is high and its prevalence still expanding. Further insight in the diabetes population is imperative to improve the quality of diabetes care by enhancement of knowledge-based diabetes management strategies. To this end, in 2017 a Dutch nationwide consortium of diabetologists, paediatric endocrinologists, and diabetes patients has founded a national outpatient diabetes care registry named Dutch Pediatric and Adult Registry of Diabetes (DPARD). We aim to describe the implementation of DPARD and to provide an overview of the characteristics of patients included during the first 2 years.

METHODS

For the DPARD cohort with long-term follow-up of observational nature, hospital data are gathered directly from electronic health records and securely transferred and stored. DPARD provides weekly updated clinical information on the diabetes population care on a hospital-level benchmarked against the national average.

RESULTS

Between November 2017 and January 2020, 20,857 patients were included from 8 (11%) Dutch hospitals with a level of care distribution representative of all diabetic outpatients in the Netherlands. Among patients with known diabetes type, 41% had type 1 diabetes, 51% type 2 diabetes, and 8% had diabetes due to other causes. Characteristics of the total patient population were similar to patients with unknown diabetes classification. HbA1c levels decreased over the years, while BMI levels showed an increase over time.

CONCLUSIONS

The national DPARD registry aims to facilitate investigation of prevalence and long-term outcomes of Dutch outpatients with diabetes mellitus and their treatment, thus allowing for quality improvement of diabetes care as well as allowing for comparison of diabetes care on an international level.

Establishment of the SingHealth Diabetes Registry

Purpose

To describe the inception and structure of the SingHealth Diabetes Registry (SDR) as well as the methodology used to set up the registry. The SDR was established to facilitate systematic and standardized data collection for diabetes mellitus within Singapore Health Services (SingHealth), which is an Academic Medical Center (AMC) and Singapore's largest group of healthcare institutions. The diabetes casemix and outcome variables within the registry cohort are also provided.

Materials and Methods

The SDR is built from SingHealth's electronic medical records (EMR) and clinical databases. It covers all individuals aged 18 and above with diabetes mellitus, excluding those with pre-diabetes. Cases are annually ascertained using criteria that include diagnosis codes, prescription records and laboratory test records. Data collection of casemix and outcome variables for the period 2013 to 2019 is complete.

Results

The SDR stands at 208,102 ascertained individuals, distributed across 8 healthcare sites within the AMC. The cohort is broadly reflective of the local gender and ethnic compositions but has a high proportion of older individuals with a mean age of 65.8 ± 13.7 years. Majority (>99%) have type 2 diabetes mellitus, with multiple other comorbidities (hypertension 84.1%, hyperlipidemia 86.2%, established cardiovascular disease 34.1%). At present, majority of individuals are able to meet key process indicators and 52.7% have a mean HbA1c of <7% (53 mmol/mol). Areas of potential improvement include increasing eye and foot screening rates, as well as glycemic control for the 19.5% of individuals with mean HbA1c >8% (64 mmol/mol).

Conclusion

The SDR is a large-scale, comprehensive, and representative diabetes registry that incorporates EMR data across the primary and hospital-based care continuum, in a major AMC in Singapore. The SDR has identified areas of improvement in diabetes processes and outcomes. It will support future quality assessment and improvements in diabetes care.