Are GP numbers going where they’re really needed?
24 Oct 2025
A study from the University of South Australia (UniSA) has found that the way populations are counted can significantly affect where doctors and health services are placed — with differences of up to 20% in GP visit data depending on which dataset is used.
Researchers compared GP attendance rates using two widely trusted population measures — the Australian Bureau of Statistics’ (ABS) Estimated Resident Population (ERP) and Medicare enrolment data — and found major inconsistencies between them.
While national attendance rates looked similar overall (just a 2% difference), some regions and age groups showed far greater variation.
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In the ACT, GP visits among young people aged 15–24 were 16% lower when calculated using ABS data.
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In the Northern Territory, GP attendance among women aged 85 and over was 21% higher under the ABS measure.
Lead researcher Dr Imaina Widagdo said these differences matter because they directly influence how health funding and workforce planning decisions are made.
“Most people assume health statistics are objective, but who we count and how we count them can significantly skew the story,” Dr Widagdo said.
“If population figures are even slightly off, we risk putting too few doctors in some communities and too many in others.”
The study highlights how the two datasets capture slightly different populations:
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ABS ERP data is based on Census, birth, death, and migration figures (about 26 million people).
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Medicare enrolment data includes around 26.2 million people eligible for publicly funded healthcare.
Dr Widagdo said the inconsistencies are especially problematic for First Nations communities, who are often underrepresented in national datasets, and for areas with high mobility or temporary populations such as international students or tourists.
At the Rural Medicine Australia conference in Perth, RACGP Rural Chair Associate Professor Michael Clements said the findings highlight well-known data gaps in rural and remote areas.
“The quality and usefulness of data decreases the further we move from urban centres,” he said.
“In many rural communities, services like the Royal Flying Doctor Service don’t bill Medicare at all, so those patients simply don’t appear in the data.”
Associate Professor Clements also pointed out that rural hospitals often need a minimum number of doctors to stay viable, regardless of population size — something that simple population-based models don’t account for.
Dr Widagdo said better transparency is essential.
“There’s no perfect dataset, but at the very least, health planners should state which data they’re using and recognise its limitations,” she said.
“Otherwise, we risk misallocating doctors, pharmacists, and services — and that can have real consequences for vulnerable communities.”
Her message to GPs: data differences don’t always reflect care quality or service demand.
“When looking at performance or planning workload, always check which population figures are being used — especially in areas with high migration or tourism,” Dr Widagdo said.
Source: University of South Australia / newsGP
