Data gaps and opportunities
Comprehensive, accurate and timely data are necessary for effective population health monitoring of diabetes with Goal 7 of the Australian National Diabetes Strategy 2021–2030 outlining the need to ‘Strengthen prevention and care through research, evidence and data’.
Although national health information collections continue to develop and improve, there are still gaps and the information that is collected is not always used to its full potential (AIHW 2020). There are also instances where data may be available but are not brought together efficiently for analysis.
Increasing digitisation of health information means more detailed data are being collected, expanding the possibilities for analysing and reporting. There is greater demand for information that is:
- available in real time and at small geographic levels for service planning and delivery
- easily accessible, flexible and interactive
- comparable at national and sub-national levels
- that maintains privacy and confidentiality.
Current gaps on the health of people living with diabetes include:
- regular national data on biomedical risk factors including blood glucose management, pre-diabetes and undiagnosed people living with diabetes in the Australian community
- national, comparable and reportable data on primary health care activity and outcomes
- person-centred data, including social and economic factors that affect health and wellbeing, and a person’s pathways through the health system, across jurisdictional boundaries and between sectors
- information on some population groups, including Aboriginal and Torres Strait Islander people, people with disability, culturally and linguistically diverse populations, refugees and LGBTQI+ populations
- longitudinal data relating to diabetes and mental health which can explore the causal pathway between these conditions and the impact of medications on the development of diabetes
- routine data for smaller geographical areas to identify variations in health status and care by location. An example of this can be see in Geographical variation in disease: diabetes, cardiovascular and chronic kidney disease.
- measures of health system efficiency and cost-effectiveness
- indicators of health system safety and quality, including outcomes of interventions and person-rated outcome and experience measures.
Goal 7 of the Australian National Diabetes Strategy 2021–2030 identifies the need to ‘Strengthen prevention and care through research, evidence and data’.
The National Health and Medical Research Council (NHMRC) expended around $43.0 million on diabetes disease expenditure in 2021 with over $1.0 billion expended since 2000.
From its inception in 2015 to 31 March 2023, the Medical Research Future Fund (MRFF) has invested $101.29 million in 17 grants with a focus on diabetes research.
- $25.0 million to the Juvenile Diabetes Research Foundation Australia to positively impact the lives of people with type 1 diabetes through the support and translation of research.
- $2.92 million to the Menzies School of Health Research for the project 'A life course approach to reduce intergenerational diabetes risk in remote Northern Australia through improved systems of care and consumer engagement'.
Digital health is the use of technology by individuals and by clinicians and administrators to collect and share health information (ADHA 2021). Digital health technology has the potential to remove barriers to service access, for example through the use of telemedicine to provide specialist care to remote or isolated communities.
Digital health records can improve continuity in patient care through the use of electronic health records, such as My Health Record. They can also enhance clinical decision-making and system-wide responses with real-time access to health information by services, sectors and jurisdictions.
Data linkage, also known as data integration, brings together information from more than one source. Matching disparate pieces of information together can fill gaps in our knowledge on specific diseases, effectiveness and quality of health services and population groups, as well as knowledge gaps across the health and welfare sectors (Jensen 2022).
Two examples of recently linked data sets include the National Integrated Health Services Information Analysis Asset (NIHSI) developed by the Australian Institute of Health and Welfare (AIHW), and the Multi-Agency Data Integration Project (MADIP) developed by the Australian Bureau of Statistics (ABS).
The AIHW is currently working towards the development of the Kidney and Diabetes Data Integration (KADDI) project, a national linked dataset providing information on individuals with diabetes and kidney disease, their treatment, health service usage, diabetes related complications and comorbidity over time. The AIHW and researchers will use this dataset to develop new methodology to refine national monitoring of diabetes.
The AIHW is also working with the Communicable Diseases Network Australia (CDNA) and states and territories to develop a national person-based research linked data set of all people who have tested positive for COVID-19 (along with a control group) in Australia since the start of the pandemic. The COVID-19 linked data set will enable linkage at the national level to administrative data, including MBS, PBS, deaths, immunisation, hospitals and aged care data.
The aim of the project is to support current data needs arising from the COVID-19 pandemic, by providing an evidence base for research into the medium and long-term effects of COVID-19.
Data on the Australian health system are largely organised around occasions of service. Goal 7 of the Australian National Diabetes Strategy 2021–2030 calls for integrated national health care data linkage to improve population health monitoring and to provide an evidence base for strategic planning for health policy and services. Linking national health-care data together with other data, including data from surveys, allows for a richer understanding of how people and population groups interact with services and their health outcomes.
Following individuals from a diagnosis of diabetes, through interactions with the health system, to recovery, further illness or death improves our ability to analyse the development and trajectory of disease; the interaction of determinants and interventions; and the role and performance of the health system in managing, treating and preventing disease.
Current opportunities for improving person-centred diabetes data include:
- improving national, comparable and reportable data on primary health care activity and outcomes, particularly for allied health professionals not included on the National Registration and Accreditation Scheme
- collecting comprehensive general practitioner (GP) data from the primary health care setting, which could provide a fuller picture of chronic disease management, associated comorbidities, and long-term outcomes. A National Primary Health Care Data Collection is currently under development (AIHW 2021)
- linkage between clinical quality registries and other administrative health databases allows for detailed investigation of the relationships between clinical measures and long-term health outcomes. An investment in scoping work will determine the benefits of establishing national enduring linkage to clinical quality registers to identify and assess data improvement opportunities
- conducting health surveys measuring clinical biomarkers of diabetes, other markers of chronic disease and nutrition status will allow for the determination of population health trends and better understanding of the number of people living with pre-existing and previously undiagnosed diabetes. The ABS is undertaking a comprehensive multi-year Intergenerational Health and Mental Health Study in 2020–2024, which will include a biomedical component (ABS 2021).
ABS (Australian Bureau of Statistics) (2021) Intergenerational Health and Mental Health Study (IHMHS), ABS website, accessed 15 December 2021.
ADHA (Australian Digital Health Agency) (2021) National Digital Health Strategy, Sydney: ADHA, accessed 15 December 2021.
AIHW (Australian Institute of Health and Welfare) (2020) Australia’s health 2022 data insights, AIHW, Australian Government, accessed 15 December 2021.
AIHW (2021) Primary health care, AIHW, Australian Government, accessed 7 December 2021.
Jensen, L. R. (2022) Using Data Integration to Improve Health and Welfare Insights, International Journal of Environmental Research and Public Health, 19(2), 836. MDPI AG.