What can be done to improve the evidence?
Introduction
A useful framework for improving data is presented in Figure DATA.1. It involves making improvements in 3 key areas:
- maximising the use of existing data sources
- improving the quality and comparability of data across data sources
- adding to data sources, including by developing new data sources in priority areas and through data linkage.
Figure DATA.1: Priority themes to improve the evidence base for people with disability
Source: Adapted from Diagram 8 in ABS 2013.
Importantly, data gaps or issues should not prohibit reporting on what is available. Instead, data limitations should be acknowledged, and data agencies should work together to continually improve data availability and quality.
Maximise the use of existing data sources
Bringing together information from multiple data sources helps support a person-centred, whole-of-system view of the experiences of people with disability in Australia within a coherent reporting framework. This provides a more comprehensive picture than is possible by relying on any one data source.
Examples of national reporting and associated frameworks that draw on multiple sources to understand the experiences of people with disability are:
- this report
- reporting against the Australia's Disability Strategy 2021–2031 Outcomes Framework
- the Report on Government Services (SCRGSP 2024)
- the disability and wellbeing monitoring framework and indicators developed by the Centre of Research Excellence in Disability and Health (Fortune et al. 2020).
Such national reports complement the large body of research on the experiences of people with disability in Australia and reporting at state and territory levels. However, it is through the sharing of existing data sources, particularly for data linkage, that much greater gains in understanding will become possible.
Improve the quality and comparability of data sources
Many different agencies and sectors collect information about people with disability, including:
- AIHW
- Australian Bureau of Statistics (ABS)
- Department of Social Services (DSS)
- National Disability Insurance Agency (NDIA)
- NDIS Quality and Safeguards Commission.
Despite this, gaps exist, as do some inconsistencies in defining disability within different sources of data, often reflecting the differing roles for the respective data collections and agencies.
Some options that could improve the quality and comparability of existing data sources include:
- gaining agreement to adopt more consistent definitions across data collections, where possible
- adding a disability flag in mainstream data collections – an agreed set of questions to identify people with disability and the level of their disability.
These options come with issues to consider, including privacy, the role of service providers and cost. Given these issues, there is a growing view that data sharing and linkage, combined with accommodating different definitions of disability and adopting more consistent definitions and disability flags where feasible, is a practical way forward.
Adopting more consistent definitions across sources where possible
Disability is generally defined in a data set based on the purpose and type of data collected. This means that definitions differ between population surveys and across administrative data collections.
Variations in definition and scope can be managed, at least in part, by careful analysis and reporting. However, strategies to improve the consistency of definition and coverage between sources of data should also be considered. The World Health Organization's International Classification of Functioning, Disability and Health (ICF) is an international standard framework and classification system, and provides a valuable basis for disability data development.
Adding a disability flag in mainstream data sources
The inclusion of a flag (a set of questions to identify records of people with characteristics of interest within the data collection) in data sources enables key population groups, such as people with disability, to be identified. This can reduce the need to develop new data collections.
An example of a flag related to the identification of people with disability within mainstream data collections is the AIHW's standardised disability flag. This flag is derived from a standard set of questions about whether a person has difficulty or needs support with various everyday activities. These questions are based on the ICF, and are broadly consistent with the Short Disability Module questions the ABS uses in a number of its surveys. Versions of the flag have been implemented in the AIHW's Specialist Homelessness Services Collection, the National Social Housing Survey, and National Prisoner Health Data Collection, and are being implemented within other AIHW collections.
The AIHW is also developing a flag for use in data collections to indicate whether a person is receiving National Disability Insurance Scheme (NDIS) support. This flag could be used to look at the use of mainstream and other services by NDIS participants. If used together with the standardised disability flag, it could potentially also be used to look at whether there are differences in the use of mainstream services between NDIS participants and other people with disability.
A wider implementation of such flags, coupled with regular supply of these data for national collation and reporting, would improve the ability to report more comprehensively on people with disability. For example, the addition to, or improvement of, disability flags in existing national child protection, out-of-home care and youth justice data collections would improve visibility of children with disability in these systems.
Another way to create an indicator for people with disability in the mainstream data collections is through data linkage. For more information, please see ‘Safely share and link data to better understand pathways and outcomes’ section below, in particular the work under the National Disability Data Asset.
Add to data sources to address priority gap areas
Data gaps can be addressed by:
- enhancing or adding data items to existing data collections
- enabling data sharing and linkage of data
- creating new data collections or data assets to fill priority gaps.
Enhance existing data sources to capture data about disability population subgroups
Existing data sources could be improved to better capture the diversity and intersectionality in the disability population. For example, key data gaps exist for people with disability who:
- are Aboriginal and/or Torres Strait Islander
- live in rural and remote Australia
- live in care settings
- are LGBTIQ+ people
- are culturally and linguistically diverse
- have suffered abuse
- have suffered discrimination
- are homeless.
Challenges exist in collecting data on population subgroups, including data quality and coverage. It can be difficult, for example, to obtain a large representative sample of some populations in national surveys and data become less reliable and robust as sample size decreases.
Examples of disability population subgroups for whom information is limited
Aboriginal and Torres Strait Islander (First Nations) peoples
Improving estimates of Aboriginal and Torres Strait Islander people living with disability is crucial as First Nations Australians often have higher rates of disability and generally poorer outcomes than non-Indigenous Australians.
While data on Indigenous status are collected in national ABS surveys, data quality and reliability are compromised by sample size and/or geographical constraints (ABS 2019b). The Survey of Disability, Ageing and Carers (SDAC), for example, is the key source of disability prevalence data but it does not collect data from people living in very remote areas or from discrete Indigenous communities (ABS 2019a). As a result, information about Indigenous Australians living with disability who are aged or who are carers are instead usually sourced from the:
- Australian Census
- National Aboriginal and Torres Strait Islander Social Survey
- National Aboriginal and Torres Strait Islander Health Survey.
However, these surveys do not as comprehensively identify disability compared with the more expansive set of questions used in the SDAC.
LGBTIQ+ people
The LGBTIQ+ community includes individuals who identify as lesbian, gay, bisexual, transgender, intersex, queer or otherwise diverse in gender, sex or sexuality.
LGBTIQ+ people can face harassment and discrimination based on their identity. There is very limited data about the intersection of LGBTIQ+ and disability in existing data collections, including in national surveys.
People who have suffered abuse
The evidence base related to the abuse of, or by, people with disability (including domestic and sexual violence) needs to be improved, including by:
- acknowledging that some people with disability face additional challenges in reporting abuse (for example, those who struggle to communicate because of the nature of their disability)
- improving data on the prevalence and causes of violence, particularly in care settings
- improving data on the safety and quality of services provided to people with disability.
While some data are available for this subgroup, these data have limitations. For example:
- the ABS SDAC does not provide detail about the experience of violence against, or by, people with disability
- data on violence and safety is collected in national surveys, such as the ABS Personal Safety Survey, but these do not identify disability as well as the SDAC, do not collect data on disability at the time of the abuse, are limited to people who live in private dwellings, and are conducted by personal interview only and therefore exclude some people with communication difficulties (ABS 2018b)
- limited mandatory reporting of some forms of abuse is available for some, but not all, settings (for example, reporting on suspected, alleged or witnessed assaults is required in residential aged care settings but not in other care settings, such as services provided in a person's home).
People who have experienced discrimination
While the ABS SDAC collects data on discrimination against people with disability, it does not collect data on the experience of other forms of discrimination for people without disability. This means comparisons can be made only within the disability population and not between people with and without disability. Some information on this comparison is available from the ABS General Social Survey, which uses the ABS Short Disability Module to identify disability and includes questions on other forms of discrimination (such as age and sex discrimination). However, this module does not identify disability as well as the SDAC, and the resulting overestimate of disability means that the differences between those with and without disability are understated (ABS 2018a).
Limited data also exist on the direct effects of discrimination on people with disability. ABS SDAC data point to lower employment, lower income, lower social participation and poorer health outcomes for people with disability overall, and especially for those who have experienced discrimination because of their disability. However, these outcomes cannot be directly linked to an experience of discrimination.
People who are homeless
Population surveys with comprehensive measures of disability, such as the SDAC, do not include a measure of homelessness. Also, the ABS Census of Population and Housing, which includes a measure of homelessness, does not capture disability as well as the SDAC and does not capture disability at all for people enumerated using the Special Short Form. This shortened version of the Census form is used in most circumstances to gather information from rough sleepers (ABS 2023).
Improvements could also be made to the AIHW's Specialist Homeless Services Collection, which provides data about people who have sought assistance from a homelessness agency. This collection has included a version of the AIHW's standardised disability flag since 2013–14, but response rates, particularly in the early years, are an issue.
Another key area in which existing data could be improved relates to the disability workforce. While some information is collected from National Disability Services member organisations and through the ABS' Labour Force Survey, there are opportunities to improve national information in this area.
Safely share and link data to better understand pathways and outcomes
Safely sharing data for statistical purposes, including for data linkage, could lead to major improvements in understanding the experience of people with disability in Australia.
What is data sharing?
Data sharing in this context refers to the sharing of data between one or more parties to better realise the economic and social benefits of increased data use, while maintaining public trust and confidence.
Many government agencies and organisations have arrangements in place to share and release non-sensitive data under existing frameworks and authorities. However, in some circumstances, pathways are not available to agencies wanting to share or release the data they hold (PC 2017a). In response to recommendations of the Productivity Commission Inquiry Report into Data Availability and Use (PC 2017a), the Data Availability and Transparency Act 2022 (the Act) was introduced from 1 April 2022. The Act established the DATA Scheme, under which Commonwealth bodies are authorised to share their public sector data with Accredited Users.
The DATA Scheme can be accessed via Dataplace, a whole of government platform to request Australian Government data. The platform brings together those wanting to get access to Australian Government data (such as researchers and those working on public policy and delivering public services) with Commonwealth agencies who are the data custodians. The platform can be used to apply for accreditation to be a data user or a data service provider under the DATA Scheme, request Australian Government data (including under the DATA Scheme), or develop a data sharing agreement.
Some data collected on people with disability are not widely available for use or sharing. These include, but are not limited to, data collected by non-government organisations but not collated for national analysis.
Improving the ability to access these data would assist in expanding the evidence base, particularly in understanding other services people with disability use.
Some benefits of data sharing, however, cannot be realised without data linkage. At present, for example, it is difficult to understand how different specialist disability support systems interact, such as how the NDIS interacts with other specialist disability services. It is also difficult to understand how these specialist disability services interact with mainstream supports.
What is data linkage?
Data linkage (also called data matching, data integration or record matching) combines information from multiple data sources while preserving privacy. This tells a much more powerful story than is possible from individual data sources in isolation. It can also improve understanding of a range of issues.
Examples of improving the evidence base through data linkage
Data linkage can be used in many ways to improve the evidence base about people with disability. Some examples using existing data include linking:
- disability support services or payments data to national hospital data, the Medicare Benefits Schedule and the Pharmaceutical Benefits Scheme – to provide insights into how some people with disability interact with mainstream health services, and how these services complement specialist disability supports
- disability support services data to aged care or mental health data – to help improve understanding of how these sectors interact
- employment services data (including specialist disability employment services data) with income support payments data over time – to provide valuable information about the relationship between seeking employment and income support
- disability support services data to data on the use of mainstream services (early childhood, education, justice, housing and homelessness supports) – to describe the use of mainstream services and outcomes achieved for people with disability; these data linkage projects were part of the National Disability Data Asset Pilot (AIHW 2023).
While data linkage is a powerful tool, challenges remain before its benefits can be fully realised. The lack of consistent linkage information across administrative systems in Australia, and complexities in data sharing and access arrangements, mean that linking data from various sources is often complex, time consuming and costly. There are also issues associated with working with linked data that add to the complexity, timeliness and cost, such as extensive data cleaning often being required before linkage (for example, as a result of different data ‘rules’ being applied to seemingly similar data items in different sources), and the careful work required to ensure protection of privacy.
The Australian, state and territory governments are working together with the disability community to design the National Disability Data Asset. The disability data asset went through 2 years of development and testing called the Pilot. The Pilot tested how to best link data to understand outcomes for people with disability, while protecting people's privacy. The Pilot was delivered jointly by the Australian Government and the governments of the Australian Capital Territory, New South Wales, Victoria, South Australia and Queensland. The Pilot provided new insights into how people with disability interact with government services and programs (AIHW 2023).
The NDDA will provide more information about the outcomes, experiences and needs of people with disability by linking de-identified information. This information will help improve programs and services. When complete, the National Disability Data Asset will be used to:
- provide a more complete picture of the programs and services used by people with disability
- help governments improve these programs and services
- share information about how opportunities and outcomes could be improved
- improve reporting on outcomes for people with disability under Australia's Disability Strategy 2021–2031.
One way that the disability data asset will achieve this is through the development of disability indicators. These indicators would be constructed within the linked data asset using disability-relevant information from various data sources that make up the asset, so that all data sources within the linked asset can potentially be analysed by disability status. These indicators will be developed in consultation with disability representatives. Once available, they will improve the types of data that can be reported on for people with disability, without the need to change existing data sources. The indicators are designed to align with the ICF and will continue to be developed throughout the lifetime of the disability data asset.
The AIHW and the ABS are developing the underlying technical and governance infrastructure that will deliver the NDDA. This infrastructure system is known as the Australian National Data Integration Infrastructure (ANDII). The ANDII refers to the national linkage and integration infrastructure. This includes a national spine and linkage model. It also includes data governance and streamlined data sharing arrangements. Subject to future agreements, the underlying infrastructure for the NDDA could be used to create other specific data assets on other important policy issues.
The ANDII builds on recent government reforms, including the Data Availability and Transparency Act 2022 and the Intergovernmental agreement on data sharing between the Australian and state and territory governments. The ANDII will streamline the approach and reduce the time required to build and access integrated datasets.
Fill gaps where limited or no data currently exist
New data collections may need to be developed. One example is the collation of transport data, specifically data about the accessibility of transport and services for people with disability. Another is information about mainstream services of critical importance to some people with disabilities (for example, speech therapy and other allied health services).
Another example relates to specialist disability services provided outside the NDIS. While a large scheme, the NDIS will not provide all specialist disability supports to all people with disability. The AIHW's Disability Services National Minimum Data Set (DS NMDS) filled part of this gap but, post 2018–19, the last year of collection under the DS NMDS, no national data have been available on services outside the NDIS, other than open employment services. Such data are vital for examining the interactions between the NDIS and other services (PC 2017b, 2019).
As part of Australia's Disability Strategy, the Australian and state and territory governments agreed to develop a comprehensive data plan to ensure data needed to measure outcomes for people with disability are collected, shared and progressively improved over the life of the Strategy, and to identify where data need to be linked between systems to improve understanding of the impact of the Strategy.