Are we counting the wrong people? Data gaps reveal GP visit numbers skewed by 20%

New research from the University of South Australia shows that the way we count our population could distort how health services are planned and funded – with some regions potentially over- or under-invested by more than 20%.

Comparing General Practitioner (GP) visits using two of Australia’s most trusted population health measures – the Australian Bureau of Statistics’ Estimated Resident Population (ERP) and Medicare enrolment data – researchers found that while national doctor attendance rates appeared similar overall (about a 2% difference), discrepancies emerged at local and demographic levels.

Specifically, in the ACT, GP attendance rates for young people aged 15–24 were 16% lower when calculated with ABS data instead of Medicare data. Similarly, in the Northern Territory, rates for women aged 85 and over were 21% higher when based on the ABS figures.

Lead researcher UniSA’s Dr Imaina Widagdo says the findings show how small differences in the way we count people can have big consequences for healthcare planning.

“Most people assume health statistics are objective, but who we count and how we count them can significantly skew the story,” Dr Widagdo says.

“Health planners rely on data to decide where to place doctors, clinics, and services, and to prioritise health interventions. If the population figures are off – even slightly – we risk misallocating resources, which could mean too few doctors in some communities and too many in others.”

The study highlights how ERP data (26 million people based on Census, birth, death, and migration data) and Medicare enrolment data (26.2 million people eligible for publicly funded care) capture different populations.

The researchers stress that data inconsistencies are common, particularly among First Nations peoples who are often under-represented in administrative datasets, contributing to equity gaps.

Dr Widagdo says that failing to account for data differences can unintentionally bias results, especially in areas with high mobility, migration, or non-Medicare populations.

“In regions with small or shifting populations – like the NT or ACT – the impact of counting differences can be significant,” Dr Widagdo says.

“Ultimately, if we count people differently, we may end up putting doctors, pharmacists or health services in the wrong place – and that could have serious consequences for minority groups or vulnerable communities.

“While there’s no single ‘perfect’ population measure, at the very least, we should be reporting which dataset is used and understanding its limitations. This is essential for fair and accurate health planning.”

The research team says further studies should explore the use of whole-of-population linked datasets – such as the ABS Person Level Integrated Data Asset (PLIDA) – to build more accurate population measures and better target services and funding.

The University of South Australia and the University of Adelaide are joining forces to become Australia’s new major university – Adelaide University. Building on the strengths, legacies and resources of two leading universities, Adelaide University will deliver globally relevant research at scale, innovative, industry-informed teaching and an outstanding student experience. Adelaide University will open its doors in January 2026. Find out more on the Adelaide University website.

…………………………………………………………………………………………………………………………

Media Enquiries: Annabel Mansfield E: Annabel.Mansfield@unisa.edu.au M: +61 479 182 489
Researcher: Dr Imaina Widagdo E: Imaina.Widagdo@unisa.edu.au

New research from the University of South Australia shows that the way we count our population could distort how health services are planned and funded – with some regions potentially over- or under-invested by more than 20%.

Comparing General Practitioner (GP) visits using two of Australia’s most trusted population health measures – the Australian Bureau of Statistics’ Estimated Resident Population (ERP) and Medicare enrolment data – researchers found that while national doctor attendance rates appeared similar overall (about a 2% difference), discrepancies emerged at local and demographic levels.

Specifically, in the ACT, GP attendance rates for young people aged 15–24 were 16% lower when calculated with ABS data instead of Medicare data. Similarly, in the Northern Territory, rates for women aged 85 and over were 21% higher when based on the ABS figures.

Lead researcher UniSA’s Dr Imaina Widagdo says the findings show how small differences in the way we count people can have big consequences for healthcare planning.

“Most people assume health statistics are objective, but who we count and how we count them can significantly skew the story,” Dr Widagdo says.

“Health planners rely on data to decide where to place doctors, clinics, and services, and to prioritise health interventions. If the population figures are off – even slightly – we risk misallocating resources, which could mean too few doctors in some communities and too many in others.”

The study highlights how ERP data (26 million people based on Census, birth, death, and migration data) and Medicare enrolment data (26.2 million people eligible for publicly funded care) capture different populations.

The researchers stress that data inconsistencies are common, particularly among First Nations peoples who are often under-represented in administrative datasets, contributing to equity gaps.

Dr Widagdo says that failing to account for data differences can unintentionally bias results, especially in areas with high mobility, migration, or non-Medicare populations.

“In regions with small or shifting populations – like the NT or ACT – the impact of counting differences can be significant,” Dr Widagdo says.

“Ultimately, if we count people differently, we may end up putting doctors, pharmacists or health services in the wrong place – and that could have serious consequences for minority groups or vulnerable communities.

“While there’s no single ‘perfect’ population measure, at the very least, we should be reporting which dataset is used and understanding its limitations. This is essential for fair and accurate health planning.”

The research team says further studies should explore the use of whole-of-population linked datasets – such as the ABS Person Level Integrated Data Asset (PLIDA) – to build more accurate population measures and better target services and funding.

The University of South Australia and the University of Adelaide are joining forces to become Australia’s new major university – Adelaide University. Building on the strengths, legacies and resources of two leading universities, Adelaide University will deliver globally relevant research at scale, innovative, industry-informed teaching and an outstanding student experience. Adelaide University will open its doors in January 2026. Find out more on the Adelaide University website.

…………………………………………………………………………………………………………………………

Media Enquiries: Annabel Mansfield E: Annabel.Mansfield@unisa.edu.au M: +61 479 182 489
Researcher: Dr Imaina Widagdo E: Imaina.Widagdo@unisa.edu.au