Australia has long called itself the lucky country. But the data on preventable hospitalisations tells a different story — one where luck is distributed unequally, and your postcode determines your share of it. Every year, a huge number of Australians end up in the hospital for things that should have been taken care of with good basic healthcare. The numbers show a clear trend: your address and how well-off your neighborhood is play a big role in whether a manageable condition sends you to hospital.
In Australia, a huge number of people ended up in the hospital for things that could have been prevented. We’re talking about over 800,000 cases in just one year, from 2022 to 2023. These were conditions like complications from diabetes, dental problems, and chronic breathing issues - things that should be manageable with a simple visit to the doctor. But during the COVID-19 pandemic, the number of these cases actually went down, probably because people weren’t going to the doctor as much and weren’t reporting their problems. Now that the pandemic has passed, however, these numbers have bounced back up to almost what they were before.
If we look at the numbers, it’s clear that people who are struggling the most are ending up in the hospital a lot more often than those who are better off. In fact, the most disadvantaged fifth of Australians (Quintile 1) are being hospitalized for preventable conditions at a rate that’s 71% higher than the least disadvantaged (Quintile 5) - we’re talking 3,247 cases per 100,000 people compared to 1,899 per 100,000 people in 2022-23. What’s really striking is that this pattern holds true across every PPH category. You can use the buttons to dig deeper into chronic, acute, or vaccine-preventable conditions and see the specifics.
It’s clear that where you live can have a big impact on your health. In fact, people living in the most disadvantaged areas are a staggering 71% more likely to end up in the hospital for a condition that could have been prevented. This is based on recent data from 2022-23, which highlights the significant gap in health outcomes between different communities.
If you look at all 338 areas in Australia, you can see a clear trend. The areas that have low SEIFA disadvantage score have higher rates of PPH. Each area is shown as a bubble on the map - the bigger the bubble, the more people live there, and the colors show states. You can click on a state in the legend to highlight it. Two areas that really stand out: Alice Springs in the Northern Territory and Kimberley in Western Australia. They have much higher rates than you would expect, with over 8,000 cases per 100,000 people.
Some health problems that can be prevented are worse than others. For people living in regional areas, dental issues are a big concern - they are 24% more likely to end up in the hospital because of dental problems compared to those living in cities. In the case of chronic obstructive pulmonary disease, or COPD, the difference is even more striking. People in regional areas are 63% more likely to be hospitalised for this condition. What’s really important in these cases is having access to doctors, dentists, and specialists - something that’s often harder to come by in regional areas.
For years, people have been working to improve health policies, but the difference in hospitalization rates between remote areas and cities hasn’t gotten any better. In fact, people living in remote and very remote areas are still being hospitalized at rates that are more than twice as high as those in major cities. This gap didn’t change much even during the COVID pandemic, and now it’s actually getting wider again. You can use the slider to take a closer look at what’s been happening over time.
Remote Australians are hospitalised for preventable conditions at 2.3 times the rate of people in major cities (5,325 vs 2,428 per 100,000 in 2023-24).
Generative AI (Claude, Anthropic) was used for help with fixing my R code for this project. However, all the important decisions about what to analyze, conclude, and how to make the visuals look were made by me.
Data accessed via AIHW and ABS open data portals. All visualisations built using R (version 4.5.x) with the following packages: tidyverse, data.table, plotly, readxl, stringi.
Australian Bureau of Statistics. (2023). Socio-Economic Indexes for Areas (SEIFA), Australia, 2021 [Data set]. ABS. https://www.abs.gov.au/statistics/people/people-and-communities/socio-economic-indexes-areas-seifa-australia/2021
Australian Institute of Health and Welfare. (2024). Potentially preventable hospitalisations in Australia by small geographic areas, 2017-18 to 2023-24 [Data set]. AIHW. https://www.aihw.gov.au/reports/primary-health-care/potentially-preventable-hospitalisations
Anthropic. (2025). Claude (Version claude-sonnet-4-6) [Large language model]. https://www.anthropic.com
Yi, J. S., Kang, Y. A., & Stasko, J. (2007). Toward a deeper understanding of the role of interaction in information visualization. IEEE Transactions on Visualization and Computer Graphics, 13(6), 1224-1231. https://doi.org/10.1109/TVCG.2007.70515