Data coverage and gaps for priority populations
Information on most priority populations is not well collected in existing data sources, and comprehensive reporting will initially be limited due to gaps in available data. Many priority populations are poorly identified in national data sets; others are under-represented due to service access, reporting practices or data collection settings. Some priority populations are not explicitly sampled in surveys, which limits how well the results represent them.
Table 2 outlines the level of coverage for priority populations across national data sources that capture some sexual and reproductive health information.
| Priority population | Coverage |
|---|---|
Aboriginal and Torres Strait Islander (First Nations) | Medium |
Culturally and linguistically diverse | Medium |
Experiencing family, domestic and sexual violence and/or coercion | Low |
Experiencing socioeconomic disadvantage, including those not in education, employment or training | Medium |
Have innate variations of sex characteristics | Low |
Ineligible for Medicare, including those on temporary work visas such as Pacific Australia Labour Mobility (PALM) scheme and international student visas | Low |
Lesbian, gay, bisexual, queer, and asexual | Medium |
Living in closed settings, including prisons, detention centres and residential rehabilitation centres and others restricted within the justice system | Low |
Living in insecurity, including unstable housing or experiencing homelessness | Low |
Living in regional, rural and remote areas | Medium to High |
Living in residential aged care or specialist disability accommodation | Low |
Living with chronic or complex health conditions and/or needs | Medium |
Living with disability | Medium |
New arrivals, including recent migrants and refugees | Low |
Neurodivergent | Low |
Older (aged 50 and over) | High |
Transgender and gender diverse | Low |
Sex workers | Low |
Young (under 25 years) | High |
Notes:
- High coverage: collected in most national data collections.
- Medium coverage: collected in some national data collections (for example, may not be routinely collected in administrative data, but captured in surveys or cohort studies).
- Low coverage: little to no coverage. Includes populations not routinely collected or identified in national administrative data collections and populations for which data collection is difficult to reach or sample reliably for surveys.
Where possible, and subject to inclusion in data sources and data quality, data will be disaggregated by characteristics such as age, state or territory, geographic region (including remoteness), Primary Health Network (PHN), finer geographic areas (such as postcode, local government area or statistical area), Indigenous status and gender.
Over time, the data strategy will support targeted data development activities that:
- enhance existing collections to better identify priority populations
- explore new data collections where gaps cannot be addressed through existing sources.
Improving identification, coverage and reporting in relation to priority populations will require a combination of approaches, including:
- strengthening and applying standard national classifications and data standards
- using data linkage to improve coverage (for example, linking survey and administrative data)
- partnering with priority populations to improve data collection
- incorporating qualitative data where appropriate
- being transparent about data limitations, including gaps in coverage and data quality.
This transparency supports appropriate interpretation of findings and helps guide future data development priorities.
Progress will depend on feasibility, data quality, governance arrangements and resourcing. Equity will be a consideration in decisions about where new investment in sexual and reproductive health data is likely to have the greatest impact.