With the support of CVMM Collaborative Funding, Dr Juliana de Oliveira Costa and Dr Jialing Lin from the Medicines and Intelligence Research Program, the School of Population Health, led and conducted an investigation into the use of new medicines for Type 2 diabetes.
The aim of the study was to investigate and understand the geographic and socio-economic variation in the utilisation of sodium-glucose cotransporter 2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP-1RAs) among individuals with type 2 diabetes (T2D).
The study was also the inaugural publication arising from research projects using the MedIntel Data Platform - a large, linked dataset developed using RIS grant funding. The Medicines Intelligence (MedIntel) Data Platform is an enduring, anonymised data platform, established to undertake population-based studies examining the use, safety and cost-effectiveness of prescribed medicines.
The study looked at the use of new medicines for Type 2 diabetes: SGLT2 inhibitors (SGLT2is) and GLP-1 receptor agonists (GLP-1RAs) in New South Wales. These medicines, taken with traditional diabetes medicines significantly improve blood sugar levels, and reduce the risk of heart and kidney disease. It was found that only half of patients who were using traditional diabetes medicines also used SGLT2is, and approximately 15% used GLP-1RAs.
Importantly, patterns of use varied depending on where people lived. SGLT2is were less commonly used in regions where people have lower incomes and poorer health. One area in north-east NSW showed higher GLP-1RA use than other regions.
To increase the use of these highly effective medicines, they recommend lowering costs to patients, changing restrictions on who is eligible to access them, and educating care providers about their benefits for patients. Monitoring medicine use by where people live will allow focus interventions in specific locations to maximise use in people who will benefit the most.
For researchers, these findings highlight the importance of considering local prescribing patterns when exploring medicine use across geographies (e.g. urban and regional area) - as these can overshadow any broader trends observed.