The impact of socio-economic deprivation on access to diabetes technology in adults with type 1 diabetes

Does size matter? Hospital volume and resource use in paediatric diabetes care

AIMS

Paediatric diabetes care has become increasingly specialised due to the multidisciplinary approach and technological developments. Guidelines recommend sufficient experience of treatment teams. This study evaluates associations between hospital volume and resource use and hospital expenditure in Dutch children with diabetes.

METHODS

Retrospective cohort study using hospital claims data of 5082 children treated across 44 Dutch hospitals (2019-2020). Hospitals were categorised into three categories; small (≥20-100 patients), medium (≥100-200 patients) and large (≥200 patients). All-cause hospitalisations, consultations, technology and hospital expenditure were analysed and adjusted for age, sex, socio-economic status (SES) and hospital of treatment.

RESULTS

Fewer hospitalisations were observed in large hospitals compared to small hospitals (OR 0.48; [95% CI 0.32-0.72]; p < 0.001). Median number of yearly paediatrician visits was 7 in large and 6 in small hospitals, the significance of which was attenuated in multilevel analysis (OR ≥7 consultations: 1.89; [95%CI 0.74-4.83]; p = 0.18). Technology use varies between individual hospitals, whereas pump usage and real-time continuous glucose monitoring showed no significant differences between hospital volumes. Mean overall expenditure was highest in medium-sized centres with €6434 per patient (IQR €2555-7955); the difference in diabetes care costs was not significant between hospital patient volumes.

CONCLUSIONS

Care provision patterns vary by hospital patient volume. Large hospitals had the lowest hospitalisation rates. The use of diabetes technology was not different between hospital patient volumes. Medium-sized hospitals showed the highest overall expenditure, but diabetes care costs were similar across hospital volumes.

Ward monitoring 4.0: real-time metabolic insights from continuous glucose monitoring into perioperative organ dysfunction

The now-routine clinical deployment of continuous glucose monitoring has demonstrated benefit in real-world settings. We make the case that continuous glucose monitoring can help re-examine, at scale, the role that (stress) hyperglycaemia plays in fuelling organ dysfunction after tissue trauma. Provided robust perioperative data do emerge, well-established continuous glucose monitoring technology could soon help transform the perioperative landscape.

Social deprivation and diabetic kidney disease: A European view

There is a large body of literature demonstrating a social gradient in health and increasing evidence of an association between social deprivation and diabetes complications. Diabetic kidney disease (DKD) increases mortality in people with diabetes. Socioeconomic deprivation is increasingly recognized as a modifier of risk factors for kidney disease but also an independent risk factor itself for kidney disease. This may not be truly appreciated by clinicians and warrants further attention and exploration. In this review we explore the literature to date from Europe on the relationship between social deprivation and DKD. The majority of the studies showed at least an association with microalbuminuria, an early marker of DKD, while many showed an association with overt nephropathy. This was seen across many countries in Europe using a variety of different measures of deprivation. We reviewed and considered the mechanisms by which deprivation may lead to DKD. Health related behaviors such as smoking and suboptimal control of risk factors such as hypertension, hyperglycemia and elevated body mass index (BMI) accounts for some but not all of the association. Poorer access to healthcare, health literacy, and stress are also discussed as potential mediators of the association. Addressing deprivation is difficult but starting points include targeted interventions for people living in deprived circumstances, equitable roll out of diabetes technology, and flexible outpatient clinic arrangements including virtual and community-based care.

Effect of Christmas Holidays on Type 1 Diabetes Mellitus in Users of Glucose Flash Systems

OBJECTIVE

Christmas holidays can impact weight and glycemic control in type 2 diabetes, but their effect on type 1 diabetes (T1D) remains understudied. This study assessed how Christmas holidays affect individuals with T1D who use flash continuous glucose monitoring systems.

METHODS

This retrospective study involved 812 adults diagnosed with T1D recruited from 3 hospitals. Clinical, anthropometric, and socioeconomic data were collected. Glucose metrics from 14 days before January 1st, and before December 1st and February 1st as control periods, were recorded. Analyses adjusted for multiple variables were conducted to assess the holiday season's impact on glycemic control.

RESULTS

The average time in range during the holidays (60.0 ± 17.2%) was lower compared to December (61.9 ± 17.2%, P < .001) and February (61.7 ± 17.7%, P < .001). Time above range (TAR > 180 mg/dL) was higher during Christmas (35.8 ± 18.2%) compared to December (34.1 ± 18.3%, P < .001) and February (34.2 ± 18.4%, P < .001). Differences were also observed in TAR >250 mg/dL, coefficient of variation, and average glucose (P < .05). No differences were found in time below range or other metrics. Linear regression models showed that the holidays reduced time in range by 1.9% (β = -1.92, P = .005) and increased TAR >180 mg/dL by 1.8% (β = 1.75, P = .016).

CONCLUSION

Christmas holidays are associated with a mild and reversible deterioration in glucose metrics among individuals with T1D using flash continuous glucose monitoring, irrespective of additional influencing factors. These discoveries can be useful to advise individuals with diabetes during the festive season and to recognize potential biases within studies conducted during this timeframe.

Socio-economic disparities in hospital care among Dutch patients with diabetes mellitus

AIM

Socio-economic status (SES) influences diabetes onset, progression and treatment. In this study, the associations between SES and use of hospital care were assessed, focusing on hospitalizations, technology and cardiovascular complications.

MATERIALS AND METHODS

This was an observational cohort study comprising 196 695 patients with diabetes (all types and ages) treated in 65 hospitals across the Netherlands from 2019 to 2020 using reimbursement data. Patients were stratified in low, middle, or high SES based on residential areas derived from four-digit zip codes.

RESULTS

Children and adults with low SES were hospitalized more often than patients with middle or high SES (children: 22%, 19% and 15%, respectively; p < .001, adults: 28%, 25% and 23%; p < .001). Patients with low SES used the least technology: no technology in 48% of children with low SES versus 40% with middle SES and 38% with high SES. In children, continuous subcutaneous insulin infusion (CSII) and real-time continuous glucose monitoring (rtCGM) use was higher in high SES {CSII: odds ratio (OR) 1.54 [95% confidence interval (CI) 1.35-1.76]; p < .001; rtCGM OR 1.39 [95% CI 1.20-1.61]; p < .001} and middle SES [CSII: OR 1.41 (95% CI 1.24-1.62); p < .001; rtCGM: OR 1.27 (95% CI 1.09-1.47); p = .002] compared with low SES. Macrovascular (OR 0.78 (95% CI 0.75-0.80); p < .001) and microvascular complications [OR 0.95 (95% CI 0.93-0.98); p < .001] occurred less in high than in low SES.

CONCLUSIONS

Socio-economic disparities were observed in patients with diabetes treated in Dutch hospitals, where basic health care is covered. Patients with low SES were hospitalized more often, used less technology, and adults with high SES showed fewer cardiovascular complications. These inequities warrant attention to guarantee equal outcomes for all.

The impact of socioeconomic factors, social determinants, and ethnicity on the utilization of glucose sensor technology among persons with diabetes mellitus: a narrative review

Continuous glucose monitoring (CGM) usage has been shown to improve disease outcomes in people living with diabetes by facilitating better glycemic management. However, previous research has suggested that access to these devices can be influenced by nonmedical factors such as socioeconomic status and ethnicity. It is critical that equitable access to CGM devices is ensured as people from those groups experience poorer diabetes-related health outcomes. In this narrative review, we provide an overview of the various healthcare systems worldwide and how socioeconomic status, social context, and ethnicity shape device usage and the associated health outcomes. In general, we found that having a lower socioeconomic status and belonging to an ethnic minority group negatively impact CGM usage. While financial means proved to be an important mediator in this process, it was not the sole driver as disparities persisted even after adjustment for factors such as income and insurance status. Recommendations to increase CGM usage for people of a lower socioeconomic status and ethnic minorities include increasing the availability of financial, administrative, and educational support, for both patients and healthcare providers. However, recommendations will vary due to local country-specific circumstances, such as reimbursement criteria and healthcare ecosystems.

The role of real-time continuous glucose monitoring in diabetes management and how it should link to integrated personalized diabetes management

Diabetes is a complex metabolic condition that demands tailored, individualized approaches for effective management. Real-time continuous glucose monitoring (rtCGM) systems have improved in terms of design, usability and accuracy over the years and play a pivotal role in the delivery of integrated personalized diabetes management (iPDM). iPDM is a comprehensive multidisciplinary approach that combines individualized care strategies utilizing technologies and interventions and encourages the active involvement of the person with diabetes in the care provided. The use of stand-alone rtCGM and its integration with other diabetes technologies, such as hybrid automated insulin delivery, have enabled improved glycaemic and quality of life outcomes for people with diabetes. As the uptake of rtCGM and associated technologies is increasing and becoming the standard of care for people with diabetes, it is important that efforts are focused on associated goals such as reducing health inequalities in terms of access, aligning structured education with rtCGM usage, choosing the right technology based on needs and preferences, and minimizing burden while aiming for optimal glucose outcomes. Utilizing rtCGM in other settings than outpatients and in diabetes cohorts beyond type 1 and type 2 diabetes needs further exploration. This review aims to provide an overview of the role of rtCGM and how best to link rtCGM to iPDM, highlighting its role in enhancing personalized treatment strategies.

Impact of socioeconomic status on chronic control and complications of type 1 diabetes mellitus in users of glucose flash systems: a follow-up study

BACKGROUND

This study investigates the association between socioeconomic status (SES) and glycemic control in individuals with type 1 diabetes (T1D) using flash glucose monitoring (FGM) devices within a public health system where these technologies are freely available and utilized according to recommended guidelines.

METHODS

A follow-up study of 1060 adults (mean age 47.4 ± 15.0 years, 49.0% women) with T1D, receiving care at three Spanish university hospitals that regularly employ the FGM system. SES was assessed using the Spanish Deprivation Index and the average annual net income per person. Glycemic data were collected over a 14-day follow-up period, including baseline glycated hemoglobin (HbA1c) levels prior to sensor placement, the last available HbA1c levels, and FGM-derived glucose metrics. Individuals with sensor usage time < 70% were excluded. Chronic micro and macrovascular complications related to diabetes were documented. Regression models, adjusted for clinical variables, were employed to determine the impact of SES on optimal sensor control (defined as time in range (TIR) ≥ 70% with time below range < 4%) and disease complications.

RESULTS

The average follow-up was of 2 years. The mean TIR and the percentage of individuals with optimal control were higher in individuals in the highest SES quartile (64.9% ± 17.8% and 27.9%, respectively) compared to those in the lowest SES quartile (57.8 ± 17.4% and 12.1%) (p < 0.001). Regression models showed a higher risk of suboptimal control (OR 2.27, p < 0.001) and ischemic heart disease and/or stroke (OR 3.59, p = 0.005) in the lowest SES quartile. No association was observed between SES and the risk of diabetic nephropathy and retinopathy. FGM system improved HbA1c levels across all SES quartiles. Although individuals in the highest SES quartile still achieved a significantly lower value at the end of the follow-up 55 mmol/mol (7.2%) compared to those in the lowest SES quartile 60 mmol/mol (7.6%) (p < 0.001), the significant disparities in this parameter between the various SES groups were significantly reduced after FGM technology use.

CONCLUSIONS

Socioeconomic status plays a significant role in glycemic control and complications in individuals with T1D, extending beyond access to technology and its proper utilization. The free utilization of FGM technology helps alleviate the impact of social inequalities on glycemic control.

Clinical Translation of Bio-Artificial Pancreas Therapies: Ethical, Legal and Psychosocial Interdisciplinary Considerations and Key Recommendations

The field of regenerative medicine offers potential therapies for Type 1 Diabetes, whereby metabolically active cellular components are combined with synthetic medical devices. These therapies are sometimes referred to as "bioartificial pancreases." For these emerging and rapidly developing therapies to be clinically translated to patients, researchers must overcome not just scientific hurdles, but also navigate complex legal, ethical and psychosocial issues. In this article, we first provide an introductory overview of the key legal, ethical and psychosocial considerations identified in the existing literature and identify areas where research is currently lacking. We then highlight two principal areas of concern in which these discrete disciplines significantly overlap: 1) individual autonomy and 2) access and equality. Using the example of beta-cell provenance, we demonstrate how, by harnessing an interdisciplinary approach we can address these key areas of concern. Moreover, we provide practical recommendations to researchers, clinicians, and policymakers which will help to facilitate the clinical translation of this cutting-edge technology for Type 1 Diabetes patients. Finally, we emphasize the importance of exploring patient perspectives to ensure their responsible and acceptable translation from bench to body.

Area deprivation and demographic factors associated with diabetes technology use in adults with type 1 diabetes in Germany

Introduction

Diabetes technology improves glycemic control and quality of life for many people with type 1 diabetes (T1D). However, inequalities in access to diabetes technology exist in many countries. In Germany, disparities in technology use have been described in pediatric T1D, but no data for adults are available so far. We therefore aimed to analyze whether demographic factors and area deprivation are associated with technology use in a representative population of adults with T1D.

Materials and methods

In adults with T1D from the German prospective diabetes follow-up registry (DPV), we analyzed the use of continuous subcutaneous insulin infusion (CSII), continuous glucose monitoring (CGM), and sensor augmented pump therapy (SAP, with and without automated insulin delivery) in 2019-2021 by age group, gender, migration background, and area deprivation using multiple adjusted regression models. Area deprivation, defined as a relative lack of area-based resources, was measured by quintiles of the German index of Multiple Deprivation (GIMD 2015, from Q1, least deprived, to Q5, most deprived districts).

Results

Among 13,351 adults with T1D, the use of technology decreased significantly with older age: CSII use fell from 56.1% in the 18-<25-year age group to 3.1% in the ≥80-year age group, CGM use from 75.3% to 28.2%, and SAP use from 45.1% to 1.5% (all p for trend <0.001). The use of technology was also significantly higher in women than in men (CSII: 39.2% vs. 27.6%; CGM: 61.9% vs. 58.0%; SAP: 28.7% vs. 19.6%, all p <0.001), and in individuals without migration background than in those with migration background (CSII: 38.8% vs. 27.6%; CGM: 71.1% vs. 61.4%; SAP: 30.5% vs. 21.3%, all p <0.001). Associations with area deprivation were not linear: the use of each technology decreased only from Q2 to Q4.

Discussion

Our real-world data provide evidence that higher age, male gender, and migration background are currently associated with lower use of diabetes technology in adults with T1D in Germany. Associations with area deprivation are more complex, probably due to correlations with other factors, like the higher proportion of migrants in less deprived areas or the federal structure of the German health care system.