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Rural Health Workforce Mapping Tool

Welcome! The National Rural Health Alliance is pleased you are here and hopes you find this interactive data tool useful.

The Rural Health Workforce Mapping Tool is first and foremost a data tool, with the objective of providing accessible data on the distribution of health workforce in Australia in a visual geographic format. This tool focusses on integrating data across professions for specific geographic regions and comparing it to the workforce in major cities, highlighting disparities around the country. The bigger the deficit, the worse the maldistribution of the health workforce.

This tool might be useful to media, government, non-government organisations, local healthcare service planners and health professionals, among others.

The tool utilises workforce data on the registered health professions, managed by the Department of Health and Aged Care as part of the National Health Workforce Dataset. Hence, self-regulating health professions are not currently included. Data has also been sourced from the Australian Bureau of Statistics, the Australian Institute of Health and Welfare and the Population Health Information Development Unit (Torrens University).

Data is displayed in the following ways:

  • To illustrate disparities in workforce at the local level around the country using Local Government Areas (LGA)
  • To give an aggregated picture of workforce in areas of similar geographic remoteness around the country at the national level using Modified Monash Model (MMM) areas.  The MMM map aggregates the data so that workforce distribution can be shown nationally for each of the seven MMM categories (MMM1, MMM2, MMM3, MMM4, MMM5, MMM6, MMM7). 
  • To ensure data integrity, this tool does not  able to list the MMM classification of individual LGAs in our maps, however, the Health Workforce Locator, made available by the Department of Health and Aged Care, enables you to readily search different geographic locations and cross-reference with other classification systems. 

An instructional video has been produced for both the LGA level maps and the MMM level maps as well as two (one, two) LGA examples. 

Local government area data is coupled with data on health outcomes to give local context.

Assumptions in the Rural Health Workforce Mapping Tool

The maps display workforce data as:

  • A comparison of workforce in each region to the workforce present in MM1 areas., described as a deficit. This assumes that workforce resourcing in major cities is optimal.
  • A summation of workforce across professions, depending on the map title (for example, all registered professions, allied health and other, nursing and midwifery or medical practitioners). This provides and indication of access to multidisciplinary healthcare but can be influenced by large or small numbers of single professions and may mask gaps for individual professions.
  • Clinical full time equivalent (Clin FTE) rather than a headcount, to adjust for differences in hours worked by different clinicians and time spent on travel and other non-clinical tasks that might increase with geographic remoteness.
  • Data adjusted for population differences between areas and therefore standardised as a figure per 100,000 people. This enables comparison between areas with very different population sizes (and therefore different absolute workforce needs, based solely on population). Note: in remote and very remote areas, more clinicians are required due to the need to service small populations spread over vast distances.
  • Workforce in the health and related sectors at large – ie. it is not specific to one part of the health system such as primary healthcare. 

Pop-up boxes for a given geographic region on each map are a rich source of data for that region:

  • They provide the name of the region, the population of that region and the relevant total workforce compared to MM1 (as a Clin FTE per 100,000 population)
  • For LGAs, they also provide median age at death for males and females and the rate of one or more chronic conditions, where available
  • You can access (and copy/paste to extract) the raw workforce data (Clin FTE) for each included profession in that area on that map, along with the population adjusted data (Clin FTE/100,000 population) and the difference in total workforce compared to MM1.

For a full discussion of the methodology and caveats/assumptions of this tool, please see the Technical Notes.

If you require assistance with use of the tool or have questions, please contact [email protected] or call the secretariat office on (02) 6285 4660. We also welcome your feedback!