The main linked datasets available for disability research are:

• PLIDA (Person Level Integrated Data Asset), accessed through the ABS DataLab, and

• the National Health Data Hub (NHDH), accessed through AIHW (Australian Institute of Health and Welfare).

Eligible researchers include academics, universities, research institutes, government agencies and some NGOs.

Access pathways and approval processes differ between the two.

The next major population survey, SDAC, is planned for 2028 with results expected from late 2029 or early 2030.

Too apply for access to PLIDA, visit the ABS DataLab. 

For NHDH access, visit AIHW.

Disability flags are identifiers built into administrative datasets to help researchers identify people with disability across different data sources.

The NDDA program has developed disability flags for use in PLIDA and the NHDH. They are still being refined, and not everyone with disability is captured through administrative data. Understanding the limitations of flags is an important part of working with these datasets.

For more information on disability flags and the NDDA program, visit https://www.ndda.gov.au

 Key evidence gaps include people with disability who are outside the NDIS and not identified through hospital coding; people with mild, episodic or psychosocial disability; children and young people; people in regional and remote communities; people from CALD backgrounds; and intersectional experiences across these groups.

There is currently no systematic capture of reasonable adjustments or access needs in health datasets.

These gaps affect which populations a study can and cannot reach and should be considered in research design.

For more on children and young people's disability data gaps, read the CYDA response from our event. 
For more on health dataset gaps, read the AIHW response from our event. 

NDIS data provides detailed individual-level information on participants, including functional capacity, supports, and funding. However, it only covers people accepted into the scheme. Longitudinal analysis is also constrained by the NDIS reference period, which began in 2017.

Health datasets in the NHDH enable longitudinal analysis of care pathways, hospital use, and MBS and PBS data, but disability is not yet consistently identified across these datasets.

Linking NDIS and health data enables stronger outcome analysis, but reliance on diagnostic coding or proxies can lead to under-identification.

For more details on the strengths and limitations of NDIS, PLIDA and NHDH datasets, read the AIHW response from our event. 

Datasets define disability according to their purpose (eligibility, service use, population estimates or policy planning). It means that who is counted varies significantly depending on which dataset you use.

The ABS uses ICF-based measures across the SDAC, the Short Disability Module, and the Census.

Researchers need to be explicit about which definition underpins their dataset and what populations may be excluded as a result.

For a detailed comparison of ABS disability measures, including their conceptual underpinnings, strengths and weaknesses, visit ABS Sources of Disability Statistics 2018-2023. 

The NDDA program has established an inclusive co-governance model through the NDDA Council and a Disability-informed Ethical Oversight Panel.

Research projects using PLIDA or NHDH that have a disability focus are reviewed by the Panel, which provides advice on disability-informed ethical considerations before data custodians make final approval decisions.

The NDDA Charter outlines acceptable and unacceptable uses of de-identified data and was endorsed by disability ministers in June 2024.

For more information, visit the NDDA Council page and the Disability-informed Ethical Oversight Panel page. 

Data alone does not change systems.

Change happens when data is connected to lived experience, decision-making, funding, policy action and accountability.

Researchers can strengthen the translation of their findings by being explicit about what the data shows, who is missing from it, what lived experience adds, and what action or accountability should follow.

For more on how NDRP approaches evidence to action, visit our Research Agenda. 

Resources recommended by CYDA following the event:

Australian Bureau of Statistics (2025). Children and young people with disability, 2022. abs.gov.au/articles/children-and-young-people-disability-2022

Australian Bureau of Statistics (2024). Autism in Australia, 2022. abs.gov.au/articles/autism-australia-2022

Australian Curriculum, Assessment and Reporting Authority (2025). School students with disability. acara.edu.au/reporting/national-report-on-schooling-in-australia/school-students-with-disability

Australian Disability Clearinghouse on Education and Training (2026). Current higher education data analysis. adcet.edu.au/he-data-analysis

Australian Institute of Health and Welfare (2025). Young people in employment. aihw.gov.au/australias-disability-strategy/outcomes/employment-and-financial-security/young-people-in-employment

Children and Young People with Disability Australia (2025). Three in four disabled students are bullied or excluded at school. cyda.org.au/three-in-four-disabled-students-are-bullied-or-excluded-at-school-and-its-getting-worse-new-survey-reveals

O'Flaherty, M., et al. (2024). Australian children with disabilities' unmet support needs: Evidence from Better Support for Kids with Disabilities survey. doi.org/10.14264/db88eeb

Productivity Commission (2024). A path to universal early childhood education and care. pc.gov.au/inquiries-and-research/childhood/report

Quality Indicators for Teaching and Learning (2023). Student experience survey. qilt.edu.au/surveys/student-experience-survey-(ses)

Key resources for researchers working with Australian disability datasets:

ABS DataLab — access pathway for PLIDA and integrated ABS datasets. abs.gov.au/about/data-services/data-integration/data-integration-projects/apply-data-access

ABS Sources of Disability Statistics 2018–2023 — comparison of ABS disability measures including SDAC, Short Disability Module and Census, with strengths and limitations of each. abs.gov.au/statistics/health/disability/sources-disability-statistics/latest-release

ABS Disability Data Measures project — work to develop a shorter, consistent question set for use across population surveys and mainstream services, responding to Disability Royal Commission Recommendation 12.5. abs.gov.au/statistics/health/disability/disability-data-measures-project

AIHW National Health Data Hub — information on linked health datasets available for research. aihw.gov.au/about-our-data/our-data-collections aihw.gov.au/about-our-data/our-data-collections

NDDA Charter — outlines acceptable and unacceptable uses of de-identified disability data, endorsed by disability ministers June 2024. 

NDDA Council and Ethical Oversight Panel — information on co-governance structure and how to get involved.