Healthy Communities: Potentially preventable hospitalisations in 2013–14 - Technical Supplement - Geography

Healthy Communities: Potentially preventable hospitalisations in 2013–14

Geography

Primary Health Network areas

From 1 July 2015, Primary Health Networks (PHNs) replaced Medicare Locals. Their objectives are to increase the efficiency and effectiveness of medical services for patients, particularly those at risk of poor health outcomes. PHNs are also responsible for ensuring patients receive the most appropriate and timely care and in the most suitable setting.1

The data in the report relate to the period from July 2013 to June 2014, before PHNs were established and therefore do not reflect the performance of PHNs, but may be used as baseline information for future reporting.

Statistical Areas Level 3 (SA3s)

Statistical Areas Level 3 (SA3s) are geographic areas defined in the Australian Bureau of Statistics (ABS) Australian Statistical Geography Standard (ASGS).2

There are 333 spatial SA3s covering the whole of Australia without gaps or overlaps. They are designed to provide a regional breakdown of Australia. SA3s generally have a population of between 30,000 and 130,000 people. There are approximately 50 with fewer than 30,000 people and 35 with more than 130,000, as of 30 June 2011.

In major cities, they represent the area serviced by a major transport and commercial hub. They often closely align to large urban local government areas (for example, Parramatta, Geelong). In regional areas, they represent the area serviced by regional cities with populations of more than 20,000 people. In outer regional and remote areas, they represent areas which are widely recognised as having a distinct identity and have similar social and economic characteristics (for example, Macedon Ranges in Victoria, Southern Highlands in NSW).2

Assigning patients to geographic areas

Potentially preventable hospitalisations data are presented in this release at PHN area and SA3 level, based on the patient’s residential postcode at the time of the hospitalisation, not the hospital’s location. Statistics in this report have been compiled by applying geographic concordances (PHN area or SA3) to APC NMDS data determined by a patient’s postcode. This has led to several methodological decisions:

  • Where a postcode overlapped geographic area boundaries, hospital admissions have been apportioned to the area using concordance files from the Australian Bureau of Statistics (ABS) based on the percentage of the population of the postcode in each geographic area
  • Where a postcode overlapped geographic area boundaries over multiple states and territories, the patient’s state or territory of residence was used to apportion the hospitalisations across only the geographic areas in that particular patient’s state or territory of residence
  • Where a postcode did not map to a geographic area, these postcodes have been excluded in the compilation of statistics for maps and tables in the report. Only a small number of postcodes are excluded.

Fair comparisons

Previous reports by the Authority peer grouped Medicare Local catchments based on socioeconomic status, remoteness and distance to hospitals to allow for fairer comparisons of results. The 31 PHNs that replaced 61 Medicare Local catchments are much larger in size and have greater diversity in their populations’ characteristics and therefore have not been peer grouped.

Local area (SA3) results have, however, been categorised by remoteness, into:

  • Major cities
  • Inner regional
  • Outer regional
  • Remote (includes Very remote).

Local areas (SA3s) in major cities have been further categorised by socioeconomic status (SES), reported by:

  • Higher SES
  • Medium SES
  • Low SES.

Local areas (SA3s) have been grouped into five remoteness categories based on the ABS 2011 Australian Statistical Geography Standard.2 For each SA3, the percentage of the population that was in each remoteness category was calculated. The remoteness category with the highest percentage of the population was allocated to the SA3. Due to the small numbers of SA3s in the Remote and Very remote categories, these categories were combined to create four remoteness categories, Table 1.

Table 1: Number of SA3s by ASGS remoteness categories

ASGS remoteness Number of SA3s
Major cities 188
Inner regional 80
Outer regional 48
Remote (9) & Very remote (8) 17

The majority of SA3s (188 of 333) across Australia were in the Major cities remoteness category. To enable fairer comparisons within city areas, the Major cities category was further categorised into three socioeconomic groups: high, middle and low using the 2011 ABS Index of Relative Socioeconomic Disadvantage (IRSD). IRSD is one of the Socio-economic Indexes for Areas (SEIFA) produced by the ABS using the results of the Census.3

To allocate SA3s in Major cities into a socioeconomic group, socioeconomic quintiles for each Statistical Area Level 1 (SA1) within the SA3 (calculated by the ABS) were used. For each SA3, the number of SA1s in each quintile was calculated and the quintile with the largest number of SA1s was allocated to the SA3 (Table 2a).

Table 2a: Number of SA3s in the Major cities remoteness category, by SEIFA IRSD quintiles

ASGS remoteness Quintiles of SEIFA IRSD
1 2 3 4 5
(low) (high)
Major cities 30 27 33 37 61

The highest SES group (quintile 5) has nearly double the number of areas (61) than the average number in the other quintiles (32). This is because the socioeconomic index covers all of Australia, and city areas are generally more advantaged than rural areas. To create more equal sized groups, the Authority combined the lower quintiles (Table 2b).

Table 2b: Number of SA3s in the Major cities remoteness category, by combined SEIFA IRSD quintiles

ASGS remoteness Quintiles of SEIFA IRSD
1 2 3 4 5
(low) (high)
Major cities 57 70 61

The final step to create equal sized groups involved reallocating SA3s in Group 1 (high SES) and Group 2 (medium SES), which have a high overall average SES (as assessed by IRSD score), as follows and Table 3:

  • Group 1 (high SES) = SES quintile 5 or average SES > IRSD score 1,050
  • Group 2 (medium SES) = SES quintile 3 or 4 (and average SES < IRSD score 1,050)
  • Group 3 (low SES) = SES quintile 1 or 2.

Therefore, these are the final categories as seen in the report.

Table 3: Number of SA3s by ASGS remoteness categories and SEIFA IRSD

ASGS remoteness SEIFA IRSD
Low Medium High
Major cities 57 63 68
Inner regional 78
Outer regional 48
Remote 17
  1. Australian Government Department of Health. Primary Health Networks [Internet]. Canberra: Commonwealth of Australia; 2014 [cited 2015 Oct 13]. Available from: http://www.health.gov.au/internet/main/publishing.nsf/Content/primary_Health_NetworksExternal link, opens in a new window.
  2. Australian Bureau of Statistics. Australian Statistical Geography Standard (ASGS): Volume 1 – Main Structure and Greater Capital City Statistical Areas, July 2011 [Internet]. 2011 July [cited 2015 Oct 23]. Cat. no. 1270.0.55.001. Available from: http://www.abs.gov.au/ausstats/abs@.nsf/mf/1270.0.55.001External link, opens in a new window.
  3. Australian Bureau of Statistics. 2033.0.55.001 - Census of Population and Housing: Socio- Economic Indexes for Areas (SEIFA), Australia, 2011 [Internet]. 2013 Mar 28 [cited 2015 Oct 23]. Available from: http://www.abs.gov.au/ausstats/abs@.nsf/mf/2033.0.55.001External link, opens in a new window.