Private Healthcare Australia (PHA)

DASHBOARD

The dashboard has a home page and four main components plus a link to the on-line map provided through our association with ESRI.

THE SUMMARY SECTION

This is an executive summary that pulls together the threads identified in the PROFILES and DEMOGRAPHICS sections. This is a good, but high level, summary of the analysis undertaken by Health Geographics (HGS).

USING HE ELECTORATES SECTION

The ELECTORATES section provides a seat by seat summary of PHA summary data on the take up of Private Health Insurance and Hospital Cover. A calculation of the potential market for Private Health insurance in any federal seat is the difference between the two datasets. This information relies on the data supplied by PHA.

There is a basic 2PP analysis of the 2019 election for each seat and a summary of four of our ADS ‘voter’ stereotypes – Working Families; Swinging Voters; Goats Cheese Circle and the Coming of Age.

See this link for an explanation of the stereotypes.

https://www.educationgeographics.net.au/stereotypes-and-voting/

Comments have been provided in the LEARN MORE drop down comments in the PROFILES and DEMOGRAPHICS (Cultural) sections to relate the analysis to these voter stereotypes. Once you have the context of those comments, the ELECTORATES section can provide you with an appropriate target group for each electorate plus a broad indication of potential demand from such group(s) for health and hospital insurance.

USING THE PROFILES SECTION

The PROFILES section is a single page summary of the 800+ demographic variables analysed in the 40+ charts in the DEMOGRAPHICS section. The PROFILES section uses the same six categories as used in the DEMOGRAPHICS section.  These are:

  1. Education
  2. Income
  3. Workplace
  4. Age and Family
  5. Culture and Religion
  6. The Home

For each of the six categories, the twelve strongest correlations to taking up Private Health Insurance are listed. Also included is the means of the ‘Best Seats’. The best seats represent the top 10 electorates in Australia for Private Health Insurance membership.

In the DEMOGRAPHICS section we also include the ‘Worst Seats’ – the 10 electorates in Australia with the worst take-up of Private Health insurance.

These electorates are:

BEST SEATS WORST SEATS
Moore WA  84.2% Lingiari NT 24.0%
Berowra NSW  83.3% Calwell Vic 27.6%
Langney WA  82.9% Bruce Vic 29.8%
Bradfield NSW  82.8% Gorton Vic 30.7%
Curtin WA  78.7% Holt Vic 32.4%
Warringah NSW  77.6% Chifley NSW 33.4%
Mitchell NSW  77.6% Gippsland Vic 33.5%
Goldstein Vic  77.6% Fraser Vic 33.8%
Mackellar NSW 76.9% Fowler NSW 34.8%
Kooyong Vic 75.8% Scullin Vic 35.0%

The LEARN MORE drop down comments in the PROFILES section provide an overview of what drives health insurance take-up throughout the various regions and areas of Australia. You can use this informative overview to enhance your understanding of the DEMOGRAPHICS section analysis and appreciate what the data for each seat in the electorates section is indicating.

THE DEMOGRAPHICS SECTION

The DEMOGRAPHICS section is based on the ADS Elaborate database and contains a wealth of information. Read the LEARN MORE drop down comments for each chart and examine the CORRELATIONS drop down chart to understand the context of any demographic variable and private health insurance.

USING THE ONLINE MAP

The ONLINE MAP opens with an interactive ESRI base map of Australia, showing a ticker tape below with eight key indicators for Australia. As you zoom in and out, these numbers all change to show an average of the seats you are looking at. Click on the two dots below the data to move from one set of four figures to the next.

You can turn the ticker tape on and off via the square widget at the top right of your map. The explanations for the various widget functions are found by clicking first on the information widget, show by a white circle containing the letter i in bold italics.

You can zoom into your chosen areas via your mouse controls in the usual fashion or find a seat via the box at top left or the state via the filter button at bottom right.

The ONLINE MAP contains the key seven layers which dominated the regression modelling and made the most impact on the predicted PHI and Hospital Cover percentages. They can be accessed via the layer widget at top right of the map.

These include Per Capita Private Health Insurance, Swinging Voter Index (blue for Layering), Highest Earning Quartile, Part Time Working Women, Population 80 plus years, Swinging Voter Index (Blue to Red), Per Capita Private Health Insurance Residuals.

If you click on any particular seat, you see a pop-up summary with some relevant modelling data for that seat.