Equity first: mapping who gets what is essential to re‐designing the NDIS

Recent media commentary on the operation of the National Disability Insurance Scheme (NDIS) has focused on costs, fraud, and preventing dubious provider practices. This discussion obscures the broader importance of the NDIS for overcoming the entrenched disadvantages that prevent people with disability fully participating in Australian society.1 However, disability support in Australia, provided by the NDIS or otherwise, is not equitable. Access to and the use of disability support varies widely for a variety of reasons, and people who need considerable support but are ineligible for the NDIS are left with a sparse array of uncoordinated support.2,3 We hear about inequity time and time again from service providers and people with disability, but quantifying inequity is often difficult.4

The article by Disney and colleagues5 in this issue of the MJA provides much needed insights into the operation of the NDIS for different groups. The authors quantified socio‐demographic differences in NDIS eligibility and resource allocation by analysing NDIS unit record data. These data are essential for understanding who is granted support by the NDIS, how much of the allocated support they use, and whether these outcomes differ by socio‐demographic characteristics. Disney and his colleagues found that, in certain disability categories, applicants aged 55 years or older, women and girls, and people living in socio‐economically disadvantaged areas were more likely to be found ineligible for the NDIS, as were people with psychosocial disability. The authors noted possible structural reasons, including the use of diagnosis‐based eligibility lists that include, for example, autism, for which the eligibility rate is high, but not psychosocial disability‐related diagnoses. People with conditions not included in these lists may have to provide more evidence to prove they are eligible for support.5

People with psychosocial disability or living in lower socio‐economic status areas can find it more difficult to gather the evidence required because they cannot afford the private care providers who could provide the required information in formats more acceptable to the National Disability Insurance Agency (NDIA).6 We need qualitative research into decision making by the NDIA and how it assesses evidence, and to learn from NDIS participants about barriers to gathering the required information. Rural and remote regions are often also lower socio‐economic status areas, and access in this areas to specialist assessments that would help people provide evidence of disability in an appropriate manner is more limited.7 Inequality of access is therefore linked to social inequities.8 NDIS eligibility criteria that disadvantage people who cannot afford the right type of evidence or obtain help with their application could further marginalise already marginalised groups.

The study by Disney and colleagues excluded NDIS applications that were cancelled before submission. Characterising this group of applicants is important because it some people may not proceed with applications because of financial limitations or information requirements, or because of language or cultural barriers.9 Future studies should include such applicants, which may include, for example, First Nations Australians and people with psychosocial disability, as well as people who are homeless, among whom the prevalence of disability is high but participation in the NDIS lower than expected.6

The NDIS is designed to provide reasonable and necessary support, tailored to individual needs and goals, rather than offering equal access and funding for all. While the focus on equality by Disney and colleagues is welcome, the differences between equality and equity should be considered by future studies, recognising the heterogeneous support needs that may lead to different support use rates.10 Some people require more resources or different types of support to achieve their goals. Further, statistical methods such as interrupted time series analysis could be used to examine temporal trends, exploring how changes in NDIS operation, assessment rules, eligibility criteria, and external factors (such as the COVID‐19 pandemic) affect access to the scheme and plan use. Researchers could also apply new approaches, such as equity impact analysis,11 to evaluate what has reduced gaps in outcomes between advantaged and disadvantaged groups. As all research depends on the data collected by the NDIA,10 it should employ a greater range of outcome measures that assess the impact of the NDIS on individual wellbeing, functional capabilities, and social and economic participation.