Search

Background People living with diabetes must manage a range of factors for optimal control of glycaemia and to minimise the risk of diabetes-related complications. Diabetes practitioners are expected to follow guidelines for the key process of care and clinical outcomes, to help people living with diabetes achieve clinical targets. In Australia, the performance of diabetes centres against guidelines is evaluated by the Australian National Diabetes Audit, an annual clinical audit and feedback activity. Previous work has identified areas for improvement in the feedback provided to participating diabetes centres and suggested additional educational and support resources to assist in using audit feedback for the development of quality improvement activities. This cluster randomised trial will test the acceptability, utility and impact on selected clinical outcomes of the developed study intervention (audit feedback and a tailored educational and peer support cointervention). Methods Two-armed cluster randomised trial with Australian Diabetes Centres that participated in the Australian National Diabetes Audit in 2021 as the clusters, stratified by location and type of centre. We aim to recruit 35 diabetes centres in each arm. Both the intervention and control arms will receive an augmented feedback report, accompanied by a partially pre-populated slide deck. In addition, the intervention arm will receive a tailored theory-based intervention designed to address identified, modifiable barriers to utilising and implementing the recommendations from diabetes audit feedback. The co-primary outcomes are (1) HbA1c at the patient level, measured at 6 months after delivery of the intervention, and (2) the acceptability and utility of the augmented feedback and cointerventions at the practitioner level, measured at 3 months after delivery of the intervention. Discussion This trial aims to test the effects of systematic development and implementation of theory and evidence-informed changes to the audit feedback delivered to diabetes centres participating in an established national clinical diabetes audit. Potential benefits of improved audit feedback include more optimal engagement with the feedback by end clinical users which, ultimately, may lead to improvements in care for people living with diabetes. Trial registration Australian and New Zealand Clinical Trials Registry ACTRN12621000765820. Prospectively registered on June 21, 2021

Background Management of glycaemia remains the mainstay of optimal diabetes care. As reported by the Australian National Diabetes Audit (ANDA) average glycaemia is suboptimal for many people living with diabetes. Whether centre-specific factors influence HbA1c variation among patients attending Australian primary, secondary or tertiary diabetes centres, is not known. Methods Data for 5,872 people with Type 1 or Type 2 diabetes (DM1/DM2) was collected for ANDA over a 4-6 week period. A linear mixed-effects model was built to examine the relative contribution of centre-specific (type of centre, location and volume of patients) and patient-specific factors in explaining variation in HbA1c, by diabetes type. Results Mean age of the cohort was 57.5±17.2 years, median disease duration 14 years (7,21) with 47% female. For people with DM1, number of patients was the only centre-specific factor that significantly contributed to HbA1c variation (p = 0.019). In contrast, for people with DM2, type of centre significantly contributed toHbA1c variation (p Conclusions Unlike patient factors, centre factors such as type, location and volume of patients appear to have less actionable impact on HbA1c variation. Key messages Centre-level interventions to target patient-specific factors (such as sick day management education to prevent acute hyperglycaemia, smoking cessation programs and culturally appropriate diabetes education) rather than centre-specific factors may be more important for improving glycaemia.

AIM To investigate temporal changes in glycaemic control and the use of antihyperglycaemic therapies in females and males with type 2 diabetes from 2013 to 2019. METHODS Data from adult patients with type 2 diabetes (n = 11 930; 44.9% females, mean [SD] age of 62.9 [12.9] years) were analysed from the 2013 to 2019 biennial cross-sectional Australian National Diabetes Audit. RESULTS Mean HbA1c remained similar throughout the years examined and between the sexes (7.8%-8.3%, 62-67 mmol/mol; P > .05). The number of antihyperglycaemic agents used by both sexes increased from 2013 to 2019 (P

Background Diabetes has high burden on the health system and the individual, and many people living with diabetes struggle to optimally manage their condition. In Australia, people living with diabetes attend a mixture of primary, secondary and tertiary care centres. Many of these Diabetes Centres participate in the Australian National Diabetes Audit (ANDA), a quality improvement (QI) activity that collects clinical information (audit) and feeds back collated information to participating sites (feedback). Despite receiving this feedback, many process and care outcomes for Diabetes Centres continue to show room for improvement. The purpose of this qualitative study was to inform improvement of the ANDA feedback, identify the needs of those receiving feedback and elicit the barriers to and enablers of optimal feedback use. Methods Semi-structured interviews were conducted with representatives of Australian Diabetes Centres, underpinned by the Consolidated Framework for Implementation Research (CFIR). De-identified transcripts were analysed thematically, underpinned by the domains and constructs of the CFIR. Results Representatives from 14 Diabetes centres participated in this study, including a diverse range of staff typical of the Diabetes Centres who take part in ANDA. In general, participants wanted a shorter report with a more engaging, simplified data visualisation style. Identified barriers to use of feedback were time or resource constraints, as well as access to knowledge about how to use the data provided to inform the development of QI activities. Enablers included leadership engagement, peer mentoring and support, and external policy and incentives. Potential cointerventions to support use include exemplars from clinical change champions and peer leaders, and educational resources to help facilitate change. Conclusions This qualitative study supported our contention that the format of ANDA feedback presentation can be improved. Healthcare professionals suggested actionable changes to current feedback to optimise engagement and potential implementation of QI activities. These results will inform redesign of the ANDA feedback to consider the needs and preferences of end users and to provide feedback and other supportive cointerventions to improve care, and so health outcomes for people with diabetes. A subsequent cluster randomised trial will enable us to evaluate the impact of these changes.

Type 2 diabetes in young adults (nominally, 18-30 years of age) is a more aggressive condition than that seen in older age, with a greater risk of major morbidity and early mortality. This first Australian consensus statement on the management of type 2 diabetes in young adults considers areas where existing type 2 diabetes guidance, directed mainly towards older adults, may not be appropriate or relevant for the young adult population. Where applicable, recommendations are harmonised with current national guidance for type 2 diabetes in children and adolescents (aged 18 years). The full statement is available at https://www.diabetessociety.com.au, https://www.adea.com.au and https://www.apeg.org.au.Advice is provided on important aspects of care including screening, diabetes type, psychological care, lifestyle, glycaemic targets, pharmacological agents, cardiovascular disease risk management, comorbidity assessment, contraception and pregnancy planning, and patient-centred education. Special considerations for Aboriginal and Torres Strait Islander Australians are highlighted separately.Management recommendations for young adults, which differ from those for adults, include: ▪screening for diabetes in young adults with overweight or obesity and additional risk factors, including in utero exposure to type 2 diabetes or gestational diabetes mellitus; ▪more stringent glucose targets (glycated haemoglobin ≤ 6.5% [≤ 48 mmol/mol]); ▪in the context of obesity or higher cardio-renal risk, glucagon-like peptide 1 receptor agonists and sodium-glucose cotransporter 2 inhibitors are preferred second line agents; ▪β-cell decline is more rapid, so frequent review, early treatment intensification and avoidance of therapeutic inertia are indicated; ▪a blood pressure target of 130/80 mmHg, as the adult target of ≤ 140/90 mmHg is too high; ▪absolute cardiovascular disease risk calculators are not likely to be accurate in this age group; early statin use should therefore be considered; and ▪a multidisciplinary model of care including an endocrinologist and a certified diabetes educator.

To evaluate the utilisation of technologies and associated glycaemia among adults with type 1 diabetes.De-identified data from adults with type 1 diabetes (≥18 years old) in the Australian National Diabetes Audit (ANDA)-2019 were analysed. Proportions using insulin pumps or injections with continuous glucose monitoring (CGM) or capillary-glucose testing were compared. Technology use among adults was compared to young people (21 years old) with subsidised CGM. Glycaemia and complication-burden were assessed across management strategies.1,693 adults were analysed. Mean(±SD) age, diabetes duration, and HbA1c were 43.3 ± 17.0 years, 20.3 ± 14.3 years and 8.4% ± 1.7 [68 ± 19 mmol/mol], respectively. Among adults, 40% used at least one device, 27% used insulin pumps, and 23% used CGM. CGM was used by 62% of young people with subsidised access. Mean HbA1c was consistently lower among adults using CGM, insulin pumps, or combined insulin pump and CGM compared to standard care (8.3% ± 1.6 [67 ± 18 mmol/mol], 8.2% ± 1.4 [66 ± 15 mmol/mol], and 7.8% ± 1.4 [62 ± 15 mmol/mol] respectively compared to 8.6% ± 1.8 [70 ± 20 mmol/mol], p 0.001). Technology use was not associated with diabetic ketoacidosis but CGM was associated with more hypoglycaemia.Government subsidy is an important consideration for utilisation of technologies among adults with type 1 diabetes. Technology use across the adult lifespan was associated with lower HbA1c than insulin injections and capillary-glucose testing.

AIM This cross-sectional study compares the self-care practices of younger and older people with Type 2 diabetes. METHODS Data were analysed from the Australian National Diabetes Audit (ANDA) including 2552 adults with Type 2 diabetes from Australian Diabetes Centres. Pre-specified demographic and clinical variables were obtained. Self-care variables (physical activity, following dietary recommendations, medication adherence and monitoring blood glucose levels) were compared in people ≤ 64 and > 64 years of age. RESULTS Mean age (± sd) of participants was 63 ± 13 years overall, 53 ± 9 years for the younger group and 73 ± 6 years for the older group. A greater proportion of younger people had HbA1c levels > 53 mmol/mol (> 7.0%) (76% vs. 68%), reported difficulty following dietary recommendations (50% vs. 32%) and forgetting medications (37% vs. 22%) compared with older people (all P-values 64 years required insulin therapy (59% vs. 57%, P = 0.200). Younger age was associated with a twofold increase in the odds of not following the recommended self-care practices after adjustment for gender, smoking, insulin therapy, depression and allied health attendance (all P

Type 2 diabetes (T2DM) is increasingly diagnosed in younger patients. The trajectory of complications in patients diagnosed at a younger or older age is not well understood. We examine the associations between age, age at diagnosis and diabetes duration and vascular complications in patients with T2DM.A cross-sectional study of pre-specified demographic and clinical data, from 3419 adults with T2DM participating in the Australian National Diabetes Audit (2015). Factors associated with diabetes complications were analysed using logistic regression.Mean (±SD) current age was 62.9±12.5years, age at diagnosis was 49.4±12.3years and mean diabetes duration was 13.5±9.4years. Macrovascular complications were more prevalent in patients who were older at diabetes diagnosis whereas microvascular complications were more prevalent in patients who were younger at diabetes diagnosis. Age, age at diagnosis and diabetes duration were all independently associated with increased risk of macrovascular complications after adjustment for sex, smoking, BMI and microvascular complications (all p0.001). In contrast, only diabetes duration was independently associated with microvascular complications after adjustment for sex, smoking, BMI and macrovascular complications (p0.001).Age, age at diagnosis, and diabetes duration were all independently associated with macrovascular complications whereas only diabetes duration was independently associated with microvascular complications.

Coronavirus disease 2019 (COVID-19) has mandated substantive changes in health care provision to minimize the risk of transmission within health care facilities. Introduction of physical distancing, a heightened focus on hand hygiene and workplace cleanliness, and widespread moves to telehealth provision have been observed (1,2). However, little is known about the impact of the pandemic on provision of diabetes care in countries like Australia with universal health care coverage. Because of mandated changes in clinical environments, we were unable to administer the scheduled Australian National Diabetes Audit (ANDA), a national annual benchmarking audit of diabetes center performance. In lieu of ANDA, we developed and administered the ANDA–COVID-19 service survey in consultation with the National Association of Diabetes Centres. The survey examined seven areas of service delivery: preparedness and ability to adapt to a crisis such as COVID-19; changes made to the health service space; challenges in delivery; changes in access to services from other health professionals and shortages of medications; and the impact on staffing as a result of COVID-19, workload in key clinical areas, and different modes of health care delivery. A health professional from each participating site was invited to complete the survey. Monash Health Human and Research Ethics Committee approved the study as an amendment to ANDA (LNR/17/MonH/123, amendment number AM/35106/MonH-2020-212691). …

The purpose of this article is to illustrate that setting standards of care is the cornerstone for excellence in diabetes management. This is underpinned by 3 activities: a standards and accreditation process, an audit and benchmarking program and a linked quality improvement plan. While there are many examples of local auditing and quality improvement programs, there are very few that are at a national level. The National Association of Diabetes Centres (NADC) was formed by the Australian Diabetes Society and the Australian Diabetes Educators Association to set standards of diabetes care in Australia. A rigorous accreditation process was put in place to recognize primary, secondary, and tertiary level diabetes centers that meet these standards. The NADC accreditation process is underpinned by a quality improvement plan, which must be submitted for accreditation to be granted and is informed by the Australian National Diabetes Audit (ANDA). ANDA is conducted annually to gather information about treatments, complications, self-care practices and quality of life outcomes and provides a national as well as an individual report to the participating center that is used to benchmark against other like centers. The ANDA reports are important to inform national policy and advocacy for diabetes care and to also provide information for quality improvement purposes for the individual participating center. We believe that the NADC Standards and Accreditation can be an exemplar for other countries to adapt and adopt to standardize diabetes care at the highest level.

Background: Tobacco smoking and diabetes mellitus contribute significantly to the overall health burden and mortality of Australians. We aimed to assess the relationship of smoking with glycemic control, metabolic profile and complications in Australian patients living with diabetes. Methods: We analysed the 2011-2017 biennial Australian National Diabetes Audit cross-sectional data. Patients were classified as current, past or never smokers. Linear (or quantile) and logistic regression models were used to assess for associations. Results: Data from 15,352 patients were analysed, including 72.2% with type 2 diabetes. Current smokers comprised 13.5% of the study population. Current and past smokers had a median HbA1c that was 0.49% and 0.14% higher than never smokers, respectively, as well as higher triglyceride and lower HDL levels (p

ObjectiveTo compare the glycaemic control and cardiovascular risk factor profiles of younger and older patients with type 2 diabetes. Cross-sectional analysis of data from the 2015 Australian National Diabetes Audit was undertaken.MethodsData were obtained from adults with type 2 diabetes presenting to Australian secondary/tertiary diabetes centres. Logistic regression examined associations with glycated haemoglobin A1c (HbA1c) >7% (53 mmol/mol) and cardiovascular risk factors.ResultsData from 3492 patients were analysed. Mean (±SD) age was 62.9±12.5 years, mean diabetes duration 13.5±9.4 years and mean HbA1c 8.2%±1.8%. Mean HbA1c was 8.6%±2.1% and 8.0%±1.6% for the younger (7.0% was 1.5 times higher (95% CI 1.22 to 1.84) for younger patients compared with older patients after adjustment for gender, smoking, diabetes duration, renal function and body mass index. Younger patients were also more likely to have dyslipidaemia (aOR 2.02, 95% CI 1.53 to 2.68; pConclusionsYounger age was associated with poorer glycaemic control and adverse cardiovascular risk factor profiles. It is imperative to optimise and monitor treatment in order to improve long-term outcomes.

Introduction: Type 2 diabetes is increasingly diagnosed among younger people. Patient engagement with self-care practices is crucial for the optimal management of type 2 diabetes. This study examines the self-care practices of younger and older patients with type 2 diabetes. Methods: Data were analysed from the Australian National Diabetes Audit (ANDA) that included 2552 adult patients with type 2 diabetes from 56 participating Diabetes Centres. Pre-specified demographic and clinical variables were obtained. Self-care variables (physical activity, following dietary recommendations, medication adherence and monitoring blood glucose levels) were compared in patients ≤64 years and >64 years of age. Results: Mean age (±SD) of participants was 63±13 years overall, 53±9 years for the younger group and 73±6 years for the older group. Mean diabetes duration was 9±8 years and 15±10 years for younger and older patients, respectively (p Conclusion: Despite shorter diabetes duration, younger age was associated with worse glycaemic control and poorer diabetes self-care practices among patients with type 2 diabetes. Targeted strategies are urgently required to optimise diabetes self-care practices and thereby improve glycaemic control. Disclosure N. Nanayakkara: None. A.J. Pease: None. S. Ranasinha: None. N. Wischer: None. B. de Courten: None. S. Zoungas: Advisory Panel; Self; AstraZeneca.

Aims: To evaluate burden of cardiovascular risk factors and associations with cardiovascular disease (CVD) among adults with type 1 diabetes attending Australian diabetes centers. Methods: De-identified, prospectively collected data from patients with type 1 diabetes aged ≥18 years included in ANDA-2015 were analysed. Cardiovascular risk factors (age, sex, diabetes duration, HbA1c, BP, high density lipoprotein-cholesterol (HDL-C), BMI, smoking status and albuminuria) and associations with CVD inclusive of stroke, myocardial infarction, coronary artery bypass graft/angioplasty and peripheral vascular disease were assessed. Likelihood ratio test and restricted cubic splines assessed for interactions and non-linear associations. Discriminatory ability of multivariate models was assessed with area under the receiver operating characteristic curves (AUC). Results: Data from 1,169 patients were analysed. Median (IQR) age and diabetes duration were 37.0 (24.9-52.0) and 16.0 (8.0-27.0) years respectively. Cardiovascular risk factors were prevalent including hypertension (22%), dyslipidemia (89%), overweight or obesity (56%), ever smoking (39%), albuminuria (31%), and an HbA1c >7.0% (53mmol/mol) (81%). Older age, longer diabetes duration, smoking and antihypertensive use were positively associated, while higher HDL-C was negatively associated with CVD (all p Conclusions: Cardiovascular risk factors were prevalent and strongly associated with CVD among adults with type 1 diabetes. Given the approximate J-shaped association between diabetes duration and CVD, the impact of cardiovascular risk stratification and management before and after 20 years duration will need to be further assessed. Disclosure A.J. Pease: None. A. Earnest: None. N. Nanayakkara: None. S. Ranasinha: None. J.R. Flack: None. W.A. Davis: Speaker's Bureau; Self; Eli Lilly and Company. Speaker's Bureau; Spouse/Partner; Novo Nordisk A/S. Advisory Panel; Spouse/Partner; Novo Nordisk A/S. Research Support; Spouse/Partner; Novo Nordisk A/S. Other Relationship; Spouse/Partner; Novo Nordisk A/S. Speaker's Bureau; Spouse/Partner; Merck Sharp & Dohme Corp.. Advisory Panel; Spouse/Partner; Merck Sharp & Dohme Corp.. Speaker's Bureau; Spouse/Partner; AstraZeneca. Advisory Panel; Spouse/Partner; AstraZeneca. Speaker's Bureau; Spouse/Partner; Boehringer Ingelheim GmbH, Pfizer Inc.. G.M. Kilmartin: None. N. Wischer: None. S. Zoungas: Advisory Panel; Self; AstraZeneca.

Background Cardiovascular risk stratification is complex in type 1 diabetes. We hypothesised that traditional and diabetes-specific cardiovascular risk factors were prevalent and strongly associated with cardiovascular disease (CVD) among adults with type 1 diabetes attending Australian diabetes centres. Methods De-identified, prospectively collected data from patients with type 1 diabetes aged ≥ 18 years in the 2015 Australian National Diabetes Audit were analysed. The burden of cardiovascular risk factors [age, sex, diabetes duration, glycated haemoglobin (HbA1c), blood pressure, lipid profile, body mass index, smoking status, retinopathy, renal function and albuminuria] and associations with CVD inclusive of stroke, myocardial infarction, coronary artery bypass graft surgery/angioplasty and peripheral vascular disease were assessed. Restricted cubic splines assessed for non-linearity of diabetes duration and likelihood ratio test assessed for interactions between age, diabetes duration, centre type and cardiovascular outcomes of interest. Discriminatory ability of multivariable models were assessed with area under the receiver operating characteristic (ROC) curves. Results Data from 1169 patients were analysed. Mean (± SD) age and median diabetes duration was 40.0 (± 16.7) and 16.0 (8.0–27.0) years respectively. Cardiovascular risk factors were prevalent including hypertension (21.9%), dyslipidaemia (89.4%), overweight/obesity (56.4%), ever smoking (38.5%), albuminuria (31.1%), estimated glomerular filtration rate 7.0% (53 mmol/mol) (81.0%). Older age, longer diabetes duration, smoking and antihypertensive therapy use were positively associated with CVD, while high density lipoprotein-cholesterol and diastolic blood pressure were negatively associated (p

Diabetes is well suited to digital interventions. Older people are capable of using technology. Technologies should be simple to use and fit into the lifestyle and resources of the person. Technologies should offer solutions and remove barriers to existing problems. Technologies should be integrated with and complement the existing lifestyle and drug treatments of individuals with diabetes Validation matters! Work with and support the older person with diabetes to use technology.

This study explores the prevalence of, and factors associated with, likely depression and diabetes distress in adults with type 2 diabetes in a large, national sample. Australian National Diabetes Audit data were analysed from adults with type 2 diabetes attending 50 diabetes centres. The Brief Case find for Depression and Diabetes Distress Score 17 were administered to screen for likely depression and diabetes-related distress, respectively. A total of 2,552 adults with type 2 diabetes participated: (mean ± SD) age was 63 ± 13 years, diabetes duration was 12 ± 10 years, and HbA1c was 8 ± 2%. Twenty-nine percent of patients had likely depression, 7% had high diabetes distress, and 5% had both. Difficulty following dietary recommendations, smoking, forgetting medications, and diabetes distress were all associated with greater odds of depression whereas higher own health rating was associated with lower odds (all p