Hospitalisations data
Admitted patients are people who undergo a public or private hospital’s formal admission process to receive treatment and/or care. The types of care included in these data are acute care, newborn care or mental health care. Also included are hospitalisations where the care type was unknown or not reported.
These data include weekly hospitalisations, grouped according to admission date, for selected conditions or condition groupings. The geographic grouping of the data is based on a patient’s usual residential address rather than the location of the hospital attended.
For detail on the data's construction and other important considerations for using the data (including changes to scope and data definitions over time), see Technical notes.
For data tables, see Data.
Figure 2: Hospitalisations data dashboard
The data dashboard allows users to explore the weekly hospitalisations data. The user can select a condition group of interest, statistical area level 4 (SA4) of interest, and a date to reflect the week of interest.
The data dashboard allows the user to explore the weekly hospitalisations data. The user can select:
- a condition group of interest
- statistical area level 4 (SA4) of interest
- a date to reflect the week of interest.
There are three panels, which all display data for the selected condition group.
The first panel, Hospitalisations per week, shows a time series of hospitalisations for the SA4 of interest over the complete period from 1 July 2002 to 30 June 2022. The user can opt to zoom in around the week of interest, selecting the number of years to display. The user can also choose to display either the number or rate (per 100,000 population) of hospitalisations per week. When rate is selected, the crude rate for the SA4 of interest is displayed, alongside the crude rates for the jurisdiction within which that SA4 is located, and Australia as a whole.
The second panel, Geographical variation in the crude rate, shows the geographical variation in the crude rate of hospitalisations between different SA4s around the week of interest. One graph shows the time series for each SA4 over a 12-month period around the week of interest. A second graph displays the box and whisker spread for the date of interest specifically. In both graphs, the SA4 of interest is shown in blue, other SA4s in the same jurisdiction are shown in orange, and all other SA4s shown in grey.
Box and whisker plots show the distribution of data values across different groups. The plot consists of a rectangular box showing the interquartile range (IQR) of the data, (that is, the difference between the 25th and 75th percentiles). The line inside the box is the median value. The whiskers extend from the box out to the minimum and maximum values that are within 1.5 times the IQR from the edges of the box. Outliers beyond the whiskers are shown as individual dots. In the second panel, the box and whisker plot shows the spread of the crude rate of hospitalisations for different SA4s on a specific date. The user can see how the selected SA4 compares to other SA4s and whether or not there are outliers.
The third panel, Year-on-year comparison, shows the year-on-year change in the weekly number of hospitalisations around the week of interest. One graph shows the time series for the SA4 of interest for the 12-month period around the week of interest alongside that of the previous year. A second graph displays the year-on-year percentage change (for the week of interest relative to the closest week in the previous year) for the SA4 of interest, compared to other SA4s. The SA4 of interest is shown in blue, other SA4s within the same jurisdiction are shown in orange, and all other SA4s in Australia are shown in grey. The box and whisker plot shows the spread of the percentage change in the number of hospitalisations (relative to the closest date one year prior) for different SA4s on the date of interest. The user can see how the selected SA4 compares to other SA4s and whether or not there are outliers.
Suppressed data are excluded from the visualisations.