Background

People with disability experience profound inequalities in health and are increasingly being recognised as a priority population in public health research. However, since disability information is not routinely collected in Australian administrative data collections, disability epidemiological research has been predominantly limited to population surveys. There is an urgent need to improve Australian disability data to advance understanding of disability-related inequalities and progress towards equity.

Methods

We used data from the Person Level Integrated Data Asset, which brings together whole population linked data from various administrative sources, to identify disability items within available linked data collections that aligned with a functional conceptualisation of disability. We created two algorithms (broad & narrow) to derive disability flags and conducted a comprehensive validation, evaluating the sensitivity and specificity of each flag against the Survey of Disability, Ageing and Carers (SDAC), the gold standard for measuring disability in Australia.

Results

We used data items from social services, National Disability Insurance Scheme, Medicare Benefit Schedule and Pharmaceutical Benefit Scheme datasets that met defined inclusion criteria. The disability flags had high specificity and moderate sensitivity. Compared to SDAC, we found that working aged people and people with moderate-to-high family income were underrepresented in the disability flags and that specificity decreased substantially for ages 65+ years. The flags also underrepresent people with less severe functioning limitations who are less likely to access, or be eligible for, disability services.

Conclusion

Disability flags in linked administrative data increase the visibility of people with disability in data and have the potential to advance disability-related health inequalities research, evidence that is critical for improving outcomes, advancing equity, realising human rights, and designing effective policy. However, it is important to understand the disability cohort identified, including what subgroups are systematically underrepresented, and interpret findings in light of these limitations.