Cost-effectiveness of a Novel Hypoglycaemia Programme: The 'HARPdoc vs BGAT' RCT.

AIMS: To assess the cost-effectiveness of HARPdoc (Hypoglycaemia Awareness Restoration Programme for adults with type 1 diabetes and problematic hypoglycaemia despite optimised care), focussed upon cognitions and motivation, versus BGAT (Blood Glucose Awareness Training), focussed on behaviours and education, as adjunctive treatments for treatment-resistant problematic hypoglycaemia in type 1 diabetes, in a randomised controlled trial. METHODS: Eligible adults were randomised to either intervention. Quality of life (QoL, measured using EQ-5D-5L); cost of utilisation of health services (using the adult services utilization schedule, AD-SUS) and of programme implementation and curriculum delivery were measured. A cost-utility analysis was undertaken using quality-adjusted life years (QALYs) as a measure of trial participant outcome and cost-effectiveness was evaluated with reference to the incremental net benefit (INB) of HARPdoc compared to BGAT. RESULTS: Over 24 months mean total cost per participant was £194 lower for HARPdoc compared to BGAT (95% CI: -£2498 to £1942). HARPdoc was associated with a mean incremental gain of 0.067 QALYs/participant over 24 months post-randomisation: an equivalent gain of 24 days in full health. The mean INB of HARPdoc compared to BGAT over 24 months was positive: £1521/participant, indicating comparative cost-effectiveness, with an 85% probability of correctly inferring an INB > 0. CONCLUSIONS: Addressing health cognitions in people with treatment-resistant hypoglycaemia achieved cost-effectiveness compared to an alternative approach through improved QoL and reduced need for medical services, including hospital admissions. Compared to BGAT, HARPdoc offers a cost-effective adjunct to educational and technological solutions for problematic hypoglycaemia.

Exploring Technology's Influence on Health Behaviours and Well-being in Type 1 Diabetes: a Review.

PURPOSE OF REVIEW: Maintaining positive health behaviours promotes better health outcomes for people with type 1 diabetes (T1D). However, implementing these behaviours may also lead to additional management burdens and challenges. Diabetes technologies, including continuous glucose monitoring systems, automated insulin delivery systems, and digital platforms, are being rapidly developed and widely used to reduce these burdens. Our aim was to review recent evidence to explore the influence of these technologies on health behaviours and well-being among adults with T1D and discuss future directions. RECENT FINDINGS: Current evidence, albeit limited, suggests that technologies applied in diabetes self-management education and support (DSME/S), nutrition, physical activity (PA), and psychosocial care areas improved glucose outcomes. They may also increase flexibility in insulin adjustment and eating behaviours, reduce carb counting burden, increase confidence in PA, and reduce mental burden. Technologies have the potential to promote health behaviours changes and well-being for people with T1D. More confirmative studies on their effectiveness and safety are needed to ensure optimal integration in standard care practices.

Towards an integrated type 1 diabetes management in low-resource settings: barriers faced by patients and their caregivers in healthcare facilities in Ghana.

BACKGROUND: In Low-Middle-Income Countries (LMICs), young people living with Type 1 Diabetes Mellitus (T1DM) face structural barriers which undermine adequate T1DM management and lead to poor health outcomes. However, research on the barriers faced by young people living with T1DM have mostly focused on patient factors, neglecting concerns regarding plausible barriers that may exist at the point of healthcare service delivery. OBJECTIVE: This study sought to explore barriers faced by young people living with T1DM and their caregivers at the point of healthcare service delivery. METHODS: Data were drawn from a qualitative research in southern Ghana. The research was underpinned by a phenomenological study design. Data were collected from 28 young people living with T1DM, 12 caregivers, and six healthcare providers using semi-structured interview guides. The data were collected at home, hospital, and support group centres via face-to-face interviews, telephone interviews, and videoconferencing. Thematic and framework analyses were done using CAQDAS (QSR NVivo 14). RESULTS: Eight key barriers were identified. These were: shortage of insulin and management logistics; healthcare provider knowledge gaps; lack of T1DM care continuity; poor healthcare provider-caregiver interactions; lack of specialists' care; sharing of physical space with adult patients; long waiting time; and outdated treatment plans. The multiple barriers identified suggest the need for an integrated model of T1DM to improve its care delivery in low-resource settings. We adapted the Chronic Care Model (CCM) to develop an Integrated Healthcare for T1DM management in low-resource settings. CONCLUSION: Young people living with T1DM, and their caregivers encountered multiple healthcare barriers in both in-patient and outpatient healthcare facilities. The results highlight important intervention areas which must be addressed/improved to optimise T1DM care, as well as call for the implementation of a proposed integrated approach to T1DM care in low-resource settings.

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.

Current Practices in Operationalizing and Addressing Racial Equity in the Provision of Type 1 Diabetes Care: Insights from the Type 1 Diabetes Exchange Quality Improvement Collaborative Health Equity Advancement Lab.

OBJECTIVE: Medical racism contributes to adverse health outcomes. Type 1 Diabetes Exchange Quality Improvement Collaborative (T1DX-QI) is a large population-based cohort engaged in data sharing and quality improvement to drive system changes in T1D care. The annual T1DX-QI survey included questions to evaluate racial equity in diabetes care and practices to promote equity. METHODS: The annual T1DX-QI survey was administered to participating clinics in fall 2022 and had a 93% response rate. There were 50 responses (pediatric: 66% and adult: 34%). Questions, in part, evaluated clinical resources and racial equity. Response data were aggregated, summarized, and stratified by pediatric/adult institutions. RESULTS: Only 21% pediatric and 35% adult institutions felt that all their team members can articulate how medical racism contributes to adverse diabetes outcomes. Pediatric institutions reported more strategies to address medical racism than adult (3.6 vs 3.1). Organizational strategies to decrease racial discrimination included employee trainings, equity offices/committees, patient resources, and hiring practices. Patient resources included interpreter services, transportation, insurance navigation, and housing and food assistance. Hiring practices included changing prior protocols, hiring from the community, and diversifying workforces. Most institutions have offered antiracism training in the last year (pediatric: 85% and adult: 72%) and annually (pediatric: 64% and adult: 56%). Pediatric teams felt that their antiracism training was effective more often (pediatric: 60% and adult: 45%) and more commonly, they were provided resources (pediatric: 67% and adult: 47%) to help address inequities. CONCLUSION: Despite increased antiracism training, insufficient institutional support and perceived subeffective training still represent obstacles, especially in adult institutions. Sharing effective strategies to address medical racism will help institutions take steps to mitigate inequities.

Estimating the cost-effectiveness of intermittently scanned continuous glucose monitoring in adults with type 1 diabetes in England.

OBJECTIVE: We previously showed that intermittently scanned continuous glucose monitoring (isCGM) reduces HbA1c at 24 weeks compared with self-monitoring of blood glucose with finger pricking (SMBG) in adults with type 1 diabetes and high HbA1c levels (58-97 mmol/mol [7.5%-11%]). We aim to assess the economic impact of isCGM compared with SMBG. METHODS: Participant-level baseline and follow-up health status (EQ-5D-5L) and within-trial healthcare resource-use data were collected. Quality-adjusted life-years (QALYs) were derived at 24 weeks, adjusting for baseline EQ-5D-5L. Participant-level costs were generated. Using the IQVIA CORE Diabetes Model, economic analysis was performed from the National Health Service perspective over a lifetime horizon, discounted at 3.5%. RESULTS: Within-trial EQ-5D-5L showed non-significant adjusted incremental QALY gain of 0.006 (95% CI: -0.007 to 0.019) for isCGM compared with SMBG and an adjusted cost increase of £548 (95% CI: 381-714) per participant. The lifetime projected incremental cost (95% CI) of isCGM was £1954 (-5108 to 8904) with an incremental QALY (95% CI) gain of 0.436 (0.195-0.652) resulting in an incremental cost-per-QALY of £4477. In all subgroups, isCGM had an incremental cost-per-QALY better than £20,000 compared with SMBG; for people with baseline HbA1c >75 mmol/mol (9.0%), it was cost-saving. Sensitivity analysis suggested that isCGM remains cost-effective if its effectiveness lasts for at least 7 years. CONCLUSION: While isCGM is associated with increased short-term costs, compared with SMBG, its benefits in lowering HbA1c will lead to sufficient long-term health-gains and cost-savings to justify costs, so long as the effect lasts into the medium term.

The Design of the Electronic Health Record in Type 1 Diabetes Centers: Implications for Metrics and Data Availability for a Quality Collaborative.

BACKGROUND: Systematic and comprehensive data acquisition from the electronic health record (EHR) is critical to the quality of data used to improve patient care. We described EHR tools, workflows, and data elements that contribute to core quality metrics in the Type 1 Diabetes Exchange Quality Improvement Collaborative (T1DX-QI). METHOD: We conducted interviews with quality improvement (QI) representatives at 13 T1DX-QI centers about their EHR tools, clinic workflows, and data elements. RESULTS: All centers had access to structured data tools, nine had access to patient questionnaires and two had integration with a device platform. There was significant variability in EHR tools, workflows, and data elements, thus the number of available metrics per center ranged from four to 17 at each site. Thirteen centers had information about glycemic outcomes and diabetes technology use. Seven centers had measurements of additional self-management behaviors. Centers captured patient-reported outcomes including social determinants of health (n = 9), depression (n = 11), transition to adult care (n = 7), and diabetes distress (n = 3). Various stakeholders captured data including health care professionals, educators, medical assistants, and QI coordinators. Centers that had a paired staffing model in clinic encounters distributed the burden of data capture across the health care team and was associated with a higher number of available data elements. CONCLUSIONS: The lack of standardization in EHR tools, workflows, and data elements captured resulted in variability in available metrics across centers. Further work is needed to support measurement and subsequent improvement in quality of care for individuals with type 1 diabetes.

Diabetes and artificial intelligence beyond the closed loop: a review of the landscape, promise and challenges.

The discourse amongst diabetes specialists and academics regarding technology and artificial intelligence (AI) typically centres around the 10% of people with diabetes who have type 1 diabetes, focusing on glucose sensors, insulin pumps and, increasingly, closed-loop systems. This focus is reflected in conference topics, strategy documents, technology appraisals and funding streams. What is often overlooked is the wider application of data and AI, as demonstrated through published literature and emerging marketplace products, that offers promising avenues for enhanced clinical care, health-service efficiency and cost-effectiveness. This review provides an overview of AI techniques and explores the use and potential of AI and data-driven systems in a broad context, covering all diabetes types, encompassing: (1) patient education and self-management; (2) clinical decision support systems and predictive analytics, including diagnostic support, treatment and screening advice, complications prediction; and (3) the use of multimodal data, such as imaging or genetic data. The review provides a perspective on how data- and AI-driven systems could transform diabetes care in the coming years and how they could be integrated into daily clinical practice. We discuss evidence for benefits and potential harms, and consider existing barriers to scalable adoption, including challenges related to data availability and exchange, health inequality, clinician hesitancy and regulation. Stakeholders, including clinicians, academics, commissioners, policymakers and those with lived experience, must proactively collaborate to realise the potential benefits that AI-supported diabetes care could bring, whilst mitigating risk and navigating the challenges along the way.

[The value of assessing the socioeconomic context during the transition of adolescents with type 1 diabetes]. / Intérêt de l'évaluation du contexte socio-économique lors de la transition des adolescents diabétiques de type 1.

The follow-up of diabetic patients is marked by a period of transition from pediatric care to adult services. The major challenge of this transition is to ensure continuity of care under the best possible conditions. Socio-economic factors must be taken into account to ensure that care is adapted to patients' needs.

Cost and utilization of healthcare services for persons with diabetes.

AIMS: Describe and compare healthcare costs and utilization for insured persons with type 1 diabetes (T1D), type 2 diabetes (T2D), and without diabetes in the United States. METHODS: Using a nationally representative healthcare claims database, we identified matched persons with T1D, T2D, and without diabetes using a propensity score quasi-randomization technique. In each year between 2009 and 2018, we report costs (total and out-of-pocket) and utilization for all healthcare services and those specific to medications, diabetes-related supplies, visits to providers, hospitalizations, and emergency department visits. RESULTS: In 2018, we found out-of-pocket costs and total costs were highest for persons with T1D (out-of-pocket: $2,037.2, total: $25,652.0), followed by T2D (out-of-pocket: $1,543.3, total: $22,408.1), and without diabetes (out-of-pocket: $1,122.7, total: $14,220.6). From 2009 to 2018, out-of-pocket costs were increasing for persons with T1D(+6.5 %) but decreasing for T2D (-7.5 %) and without diabetes (-2.3 %). Medication costs made up the largest proportion of out-of-pocket costs regardless of diabetes status (T1D: 51.4 %, T2D: 55.4 %,without diabetes: 51.1 %). CONCLUSIONS: Given the substantial out-of-pocket costs for people with diabetes, especially for those with T1D, providers should screen all persons with diabetes for financial toxicity (i.e., wide-ranging problems stemming from healthcare costs). In addition, policies that aim to lower out-of-pocket costs of cost-effective diabetes related healthcare are needed with a particular focus on medications.

An integrated personalized assistive devices approach to reduce the risk of foot ulcer recurrence in diabetes (DIASSIST): study protocol for a multicenter randomized controlled trial.

BACKGROUND: Preventing foot ulcers in people with diabetes can increase quality of life and reduce costs. Despite the availability of various interventions to prevent foot ulcers, recurrence rates remain high. We hypothesize that a multimodal treatment approach incorporating various footwear, self-management, and education interventions that matches an individual person's needs can reduce the risk of ulcer recurrence with beneficial cost-utility. The aim of this study is to assess the effect on foot ulcer recurrence, footwear adherence, and cost-utility of an integrated personalized assistive devices approach in high-risk people with diabetes. METHODS: In a parallel-group multicenter randomized controlled trial, 126 adult participants with diabetes mellitus type 1 or 2, loss of protective sensation based on the presence of peripheral neuropathy, a healed plantar foot ulcer in the preceding 4 years, and possession of any type of custom-made footwear will be included. Participants will be randomly assigned to either enhanced therapy or usual care. Enhanced therapy consists of usual care and additionally a personalized treatment approach including pressure-optimized custom-made footwear, pressure-optimized custom-made footwear for indoor use, at-home daily foot temperature monitoring, and structured education, which includes motivational interviewing and personalized feedback on adherence and self-care. Participants will be followed for 12 months. Assessments include barefoot and in-shoe plantar pressure measurements; questionnaires concerning quality of life, costs, disease, and self-care knowledge; physical activity and footwear use monitoring; and clinical monitoring for foot ulcer outcomes. The study is powered for 3 primary outcomes: foot ulcer recurrence, footwear adherence, and cost-utility, the primary clinical, patient-related, and health-economic outcome respectively. DISCUSSION: This is the first study to integrate multiple interventions for ulcer prevention into a personalized state-of-the-art treatment approach and assess their combined efficacy in a randomized controlled trial in people with diabetes at high ulcer risk. Proven effectiveness, usability, and cost-utility will facilitate implementation in healthcare, improve the quality of life of high-risk people with diabetes, and reduce treatment costs. TRIAL REGISTRATION: ClinicalTrials.gov NCT05236660. Registered on 11 February 2022.

Socioeconomic Disparities in Glycemic Management in Children and Youth With Type 1 Diabetes: A Retrospective Cohort Study.

OBJECTIVE: In Canada, few studies have addressed health inequalities in type 1 diabetes (T1D) outcomes. In this study, we examined the relationship between socioeconomic status (SES) and glycemic management in children with T1D and determine whether technology use (insulin pumps or continuous glucose monitoring [CGM]), diabetes-related physician visits, and depressive symptoms modified the association. METHODS: This work was a retrospective cohort study using the Montréal Children's Hospital Pediatric Diabetes Database of children 0 to 18 years old, diagnosed with T1D for ≥1 year, and with a hospital visit between November 2019 and October 2020. Main exposure was SES measured by the Material and Social Deprivation Index (least, moderately, or most deprived). We determined the association between SES and mean glycated hemoglobin (A1C; main outcome) in the year after the index visit using multivariable linear regression, adjusting for age, sex, diabetes duration, technology use, diabetes-related physician visits, and depressive symptoms (subgroup). We examined interaction terms for technology use, diabetes-related physician visits, and depressive symptoms. RESULTS: The study cohort included 306 children (mean age 13.6 years, mean A1C 8.5%). Children in the most-deprived compared with least-deprived quintiles had higher mean A1C; effect modification was significant with CGM only. Children not using CGM in the most-deprived compared with least-deprived quintiles had higher mean A1C (0.52%; 95% confidence interval, 0.14% to 0.86%), whereas the association was not significant for children using CGM. CONCLUSIONS: Lower SES was associated with higher A1C; these disparities were not observed among CGM users. Further research is required to determine strategies to promote CGM access among children of lower SES in the Canadian health-care context.

Assessment of a new home-based care pathway for children newly diagnosed with type 1 diabetes.

AIM: To compare the outcomes of home-based and conventional hospital-based care for children newly diagnosed with type 1 diabetes mellitus. METHODS: A descriptive study was conducted of all children newly diagnosed with diabetes mellitus at the Timone Hospital in Marseille, France, between November 2017 and July 2019. The patients received either home-based or in-patient hospital care. The primary outcome was the length of initial hospital stay. The secondary outcome measures were glycemic control in the first year of treatment, families' diabetes knowledge, the effect of diabetes on quality of life, and overall quality of care. RESULTS: A total of 85 patients were included, 37 in the home-based care group and 48 in the in-patient care group. The initial length of hospital stay was 6 days in the home-based care group versus 9 days in the in-patient care group. Levels of glycemic control, diabetes knowledge and quality of care were comparable in the two groups despite a higher rate of socioeconomic deprivation in the home-based care group. CONCLUSION: Home-based care for children with diabetes is safe and effective. This new healthcare pathway provides good overall social care, especially for socioeconomically deprived families.

Healthcare Resource Utilization in Controlled Versus Uncontrolled Adults Living With Type 1 Diabetes in the South African Public Healthcare Sector.

OBJECTIVES: This study aimed to understand the cost implications of managing people living with type 1 diabetes mellitus in the South African public healthcare system. METHODS: A multicenter, noninterventional retrospective chart review study was performed. Data on healthcare resource consumption, demographics, risk factors, clinical history, and acute events were collected. Direct medical costs were collected over a 1-year period, stratified by controlled versus uncontrolled patients. In addition, the costs in people with controlled (glycated hemoglobin < 7%) versus uncontrolled glycated hemoglobin (≥ 7%) at time horizons of 1, 5, 10, and 25 years were modeled using the IQVIA Core Diabetes Model. RESULTS: The costs based on the retrospective chart review were $630 versus $1012 (controlled versus uncontrolled population). The modeled costs at various time horizons were as follows: at 1 year, $900 versus $1331; at 5 years, $4163 versus $6423; at 10 years, $7759 versus $16 481; and at 25 years, $16 969 versus $66 268. The largest cost in the controlled population was severe hypoglycemia requiring nonmedical assistance, severe hypoglycemia requiring medical assistance, and treatment costs. In the uncontrolled population, the largest cost was the cost of diabetic ketoacidosis, severe hypoglycemia requiring nonmedical assistance, severe hypoglycemia requiring medical assistance, and foot complications. CONCLUSIONS: Strict glycemic control reduces healthcare resource use overall. Patients in the controlled group still experienced high resource use related to hypoglycemic events. The introduction of a structured patient education program and analog insulins may result in less episodes of hypoglycemia and potential cost savings.

Flash glucose monitoring in young people with type 1 diabetes-a qualitative study of young people, parents and health professionals: 'It makes life much easier'.

OBJECTIVES: Flash glucose monitoring for patients with T1 diabetes avoids frequent painful finger-prick testing, thus potentially improving frequency of glucose self-monitoring. Our study aimed to explore experiences of young people using Freestyle Libre sensors and their parents, and to identify benefits and challenges to National Health Service (NHS) staff of its adoption in their care provision. PARTICIPANTS: Young people with T1 diabetes, their parents and healthcare professionals were interviewed between February and December 2021. Participants were recruited via social media and through NHS diabetes clinic staff. DESIGN: Semistructured interviews were conducted online and analysed using thematic methods. Staff themes were mapped onto normalisation process theory (NPT) constructs. RESULTS: Thirty-four participants were interviewed: 10 young people, 14 parents and 10 healthcare professionals. Young people reported that life was much easier since changing to flash glucose monitoring, increasing confidence and independence to manage their condition. Parents' quality of life improved and they appreciated access to real-time data. Using the NPT concepts to understand how technology was integrated into routine care proved useful; health professionals were very enthusiastic about flash glucose monitoring and coped with the extra data load to facilitate more tailored patient support within and between clinic visits. CONCLUSION: This technology empowers young people and their parents to understand their diabetes adherence more completely; to feel more confident about adjusting their own care between clinic appointments; and provides an improved interactive experience in clinic. Healthcare teams appear committed to delivering improving technologies, acknowledging the challenge for them to assimilate new information required to provide expert advice.