Creating an interactive map visualising the geographic variations of the burden of diabetes to inform policymaking: An example from a cohort study in Tasmania, Australia.

OBJECTIVES: To visualise the geographic variations of diabetes burden and identify areas where targeted interventions are needed. METHODS: Using diagnostic criteria supported by hospital codes, 51,324 people with diabetes were identified from a population-based dataset during 2004-2017 in Tasmania, Australia. An interactive map visualising geographic distribution of diabetes prevalence, mortality rates, and healthcare costs in people with diabetes was generated. The cluster and outlier analysis was performed based on statistical area level 2 (SA2) to identify areas with high (hot spot) and low (cold spot) diabetes burden. RESULTS: There were geographic variations in diabetes burden across Tasmania, with highest age-adjusted prevalence (6.1%), excess cost ($2627), and annual costs per person ($5982) in the West and Northwest. Among 98 SA2 areas, 16 hot spots and 25 cold spots for annual costs, and 10 hot spots and 10 cold spots for diabetes prevalence were identified (p<0.05). 15/16 (94%) and 6/10 (60%) hot spots identified were in the West and Northwest. CONCLUSIONS: We have developed a method to graphically display important diabetes outcomes for different geographical areas. IMPLICATIONS FOR PUBLIC HEALTH: The method presented in our study could be applied to any other diseases, regions, and countries where appropriate data are available to identify areas where interventions are needed to improve diabetes outcomes.

Risk of hospital admission or emergency department presentation due to diabetes complications: a retrospective cohort study in Tasmania, Australia.

Objective To estimate the risk of an emergency department (ED)/inpatient visit due to complications in people with diabetes and compare them to their non-diabetes counterparts. Methods This matched retrospective cohort study used a linked dataset in Tasmania, Australia for the 2004-17 period. People with diabetes (n = 45 378) were matched on age, sex and geographical regions with people without diabetes (n = 90 756) based on propensity score matching. The risk of an ED/inpatient visit related to each complication was estimated using negative binomial regression. Results In people with diabetes, the combined ED and admission rates per 10 000 person-years were considerable, especially for macrovascular complications (ranging from 31.8 (lower extremity amputation) to 205.2 (heart failure)). The adjusted incidence rate ratios of ED/inpatient visits were: retinopathy 59.1 (confidence interval 25.8, 135.7), lower extremity amputation 11.1 (8.8, 14.1), foot ulcer/gangrene 9.5 (8.1, 11.2), nephropathy 7.4 (5.4, 10.1), dialysis 6.5 (3.8, 10.9), transplant 6.3 (2.2, 17.8), vitreous haemorrhage 6.0 (3.7, 9.8), fatal myocardial infarction 3.4 (2.3, 5.1), kidney failure 3.3 (2.3, 4.5), heart failure 2.9 (2.7, 3.1), angina pectoris 2.1 (2.0, 2.3), ischaemic heart disease 2.1 (1.9, 2.3), neuropathy 1.9 (1.7, 2.0), non-fatal myocardial infarction 1.7 (1.6, 1.8), blindness/low vision 1.4 (0.8, 2.5), non-fatal stroke 1.4 (1.3, 1.6), fatal stroke 1.3 (0.9, 2.1) and transient ischaemic attack 1.1 (1.0, 1.2). Conclusions Our results demonstrated the high demand on hospital services due to diabetes complications (especially macrovascular complications) and highlighted the importance of preventing and properly managing microvascular complications. These findings will support future resource allocation to reduce the increasing burden of diabetes in Australia.

Costs of major complications in people with and without diabetes in Tasmania, Australia.

Objective We set out to estimate healthcare costs of diabetes complications in the year of first occurrence and the second year, and to quantify the incremental costs of diabetes versus non-diabetes related to each complication. Methods In this cohort study, people with diabetes (n = 45 378) and their age/sex propensity score matched controls (n = 90 756) were identified from a linked dataset in Tasmania, Australia between 2004 and 2017. Direct costs (including hospital, emergency room visits and pathology costs) were calculated from the healthcare system perspective and expressed in 2020 Australian dollars. The average-per-patient costs and the incremental costs in people with diabetes were calculated for each complication. Results First-year costs when the complications occurred were: dialysis $78 152 (95% CI 71 095, 85 858), lower extremity amputations $63 575 (58 290, 68 688), kidney transplant $48 487 (33 862, 68 283), non-fatal myocardial infarction $30 827 (29 558, 32 197), foot ulcer/gangrene $29 803 (27 183, 32 675), ischaemic heart disease $29 160 (26 962, 31 457), non-fatal stroke $27 782 (26 285, 29 354), heart failure $27 379 (25 968, 28 966), kidney failure $24 904 (19 799, 32 557), angina pectoris $18 430 (17 147, 19 791), neuropathy $15 637 (14 265, 17 108), nephropathy $15 133 (12 285, 18 595), retinopathy $14 775 (11 798, 19 199), transient ischaemic attack $13 905 (12 529, 15 536), vitreous hemorrhage $13 405 (10 241, 17 321), and blindness/low vision $12 941 (8164, 19 080). The second-year costs ranged from 16% (ischaemic heart disease) to 74% (dialysis) of first-year costs. Complication costs were 109-275% higher than in people without diabetes. Conclusions Diabetes complications are costly, and the costs are higher in people with diabetes than without diabetes. Our results can be used to populate diabetes simulation models and will support policy analyses to reduce the burden of diabetes.

A Comprehensive Systematic Review of Data Linkage Publications on Diabetes in Australia.

Aims: Our study aimed to identify the common themes, knowledge gaps and to evaluate the quality of data linkage research on diabetes in Australia. Methods: This systematic review was developed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (the PRISMA Statement). Six biomedical databases and the Australian Population Health Research Network (PHRN) website were searched. A narrative synthesis was conducted to comprehensively identify the common themes and knowledge gaps. The guidelines for studies involving data linkage were used to appraise methodological quality of included studies. Results: After screening and hand-searching, 118 studies were included in the final analysis. Data linkage publications confirmed negative health outcomes in people with diabetes, reported risk factors for diabetes and its complications, and found an inverse association between primary care use and hospitalization. Linked data were used to validate data sources and diabetes instruments. There were limited publications investigating healthcare expenditure and adverse drug reactions (ADRs) in people with diabetes. Regarding methodological assessment, important information about the linkage performed was under-reported in included studies. Conclusions: In the future, more up to date data linkage research addressing costs of diabetes and its complications in a contemporary Australian setting, as well as research assessing ADRs of recently approved antidiabetic medications, are required.

Incremental healthcare expenditure attributable to diabetes mellitus: A cost of illness study in Tasmania, Australia.

AIMS: To quantify the incremental direct medical costs in people with diabetes from the healthcare system perspective; and to identify trends in the incremental costs. METHODS: This was a matched retrospective cohort study based on a linked data set developed for investigating chronic kidney disease in Tasmania, Australia. Using propensity score matching, 51,324 people with diabetes were matched on age, sex and residential area with 102,648 people without diabetes. Direct medical costs (Australian dollars 2020-2021) due to hospitalisation, Emergency Department visits and pathology tests were included. The incremental costs and cost ratios between mean annual costs of people with diabetes and their controls were calculated. RESULTS: On average, people with diabetes had healthcare costs that were almost double their controls ($2427 [95% CI 2322-2543]; ratio 1.87 [95% CI 1.85-1.91]; pooled from 2007-2017). While in the first year of follow-up, the costs of a person with diabetes were $1643 (95% CI 1489-1806); ratio 1.83 (95% CI 1.76-1.92) more than their control, this increased to $2480 (95% CI 2265-2680); ratio 1.69 (95% CI 1.62-1.77) in the final year. Although the incremental costs were higher in older age groups (e.g., ≥70: $2498 [95% CI 2265-2754]; 40-49: $2117 [95% CI 1887-2384]), the cost ratios were higher in younger age groups (≥70: 1.52 [95% CI 1.48-1.56]; 40-49: 2.37 [95% CI 2.25-2.61]). CONCLUSIONS: Given the increasing burden that diabetes imposes, our findings will support policymakers in future planning for diabetes and enable targeting sub-groups with higher long-term costs for possible cost savings for the Tasmanian healthcare system.