11 datasets found
  1. Modified Monash Model (MMM) 2015

    • researchdata.edu.au
    Updated Sep 30, 2019
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    Department of Health and Aged Care (2019). Modified Monash Model (MMM) 2015 [Dataset]. https://researchdata.edu.au/modified-monash-model-mmm-2015/1433648
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    Dataset updated
    Sep 30, 2019
    Dataset provided by
    Data.govhttps://data.gov/
    Authors
    Department of Health and Aged Care
    License

    Attribution 2.5 (CC BY 2.5)https://creativecommons.org/licenses/by/2.5/
    License information was derived automatically

    Description

    In 2015, the Department of Health introduced the Modified Monash Model (MMM) classification system as it better targets health workforce programs by categorising metropolitan, regional, rural and remote areas according to both geographical remoteness, as defined by the Australian Bureau of Statistics, and town size. The MMM 2015 is based on Australian Bureau of Statistics (2011) Census data and geography information.

  2. m

    Modified Monash Model (MMM) 2023

    • demo.dev.magda.io
    zip
    Updated Mar 18, 2025
    + more versions
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    Department of Health and Aged Care (2025). Modified Monash Model (MMM) 2023 [Dataset]. https://demo.dev.magda.io/dataset/ds-dga-f20ea7f5-e9bf-490f-a52f-03e8e56c5f21
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    zipAvailable download formats
    Dataset updated
    Mar 18, 2025
    Dataset provided by
    Department of Health and Aged Care
    License

    Attribution 2.5 (CC BY 2.5)https://creativecommons.org/licenses/by/2.5/
    License information was derived automatically

    Description

    In 2015, the Department of Health introduced the Modified Monash Model (MMM) classification system as it better targets health workforce programs by categorising metropolitan, regional, rural and …Show full descriptionIn 2015, the Department of Health introduced the Modified Monash Model (MMM) classification system as it better targets health workforce programs by categorising metropolitan, regional, rural and remote areas according to both geographical remoteness, as defined by the Australian Bureau of Statistics, and town size. The MMM 2019 was updated on 1 July 2019. The MMM2023 was updated on 10 March 2025 to use the latest available Australian Bureau of Statistics (2021) Census data and geography information. The 2023 MMM uses the following data sets: • Australian Statistical Geography Standard 2021 Statistical Area 1; and Urban Centres and Localities as the geographic bases; • Australian Statistical Geography Standard – Remoteness Area 2021 as the ABS remoteness classification (based on Accessibility and Remoteness Index of Australia (ARIA+); • Estimated Resident Population 2023; and • Esri ArcGIS StreetMap Premium Asia Pacific 2021

  3. Indicative search strategy for medline complete via EBSCO.

    • plos.figshare.com
    xls
    Updated Jun 3, 2023
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    Bianca E. Kavanagh; Hannah Beks; Vincent L. Versace; Shae E. Quirk; Lana J. Williams (2023). Indicative search strategy for medline complete via EBSCO. [Dataset]. http://doi.org/10.1371/journal.pone.0278606.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Bianca E. Kavanagh; Hannah Beks; Vincent L. Versace; Shae E. Quirk; Lana J. Williams
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Indicative search strategy for medline complete via EBSCO.

  4. Association of measures of remoteness with mortality following abdominal...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Jun 5, 2023
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    Jonathan Golledge; Aaron Drovandi; Ramesh Velu; Frank Quigley; Joseph Moxon (2023). Association of measures of remoteness with mortality following abdominal aortic aneurysm repair. [Dataset]. http://doi.org/10.1371/journal.pone.0241802.t002
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    xlsAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Jonathan Golledge; Aaron Drovandi; Ramesh Velu; Frank Quigley; Joseph Moxon
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Association of measures of remoteness with mortality following abdominal aortic aneurysm repair.

  5. Comparison of risk factors for participants that did or did not die.

    • plos.figshare.com
    xls
    Updated Jun 13, 2023
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    Jonathan Golledge; Aaron Drovandi; Ramesh Velu; Frank Quigley; Joseph Moxon (2023). Comparison of risk factors for participants that did or did not die. [Dataset]. http://doi.org/10.1371/journal.pone.0241802.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Jonathan Golledge; Aaron Drovandi; Ramesh Velu; Frank Quigley; Joseph Moxon
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Comparison of risk factors for participants that did or did not die.

  6. g

    Rural Distribution Section - Distribution Priority Area (for General...

    • gimi9.com
    Updated Dec 13, 2024
    + more versions
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    (2024). Rural Distribution Section - Distribution Priority Area (for General Practitioners) | gimi9.com [Dataset]. https://gimi9.com/dataset/au_distribution-priority-area-for-general-practitioners
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    Dataset updated
    Dec 13, 2024
    License

    Attribution 2.5 (CC BY 2.5)https://creativecommons.org/licenses/by/2.5/
    License information was derived automatically

    Description

    The Distribution Priority Area (DPA) classification system for GPs is an impartial mechanism used by the Government to encourage a more equitable distribution of GPs who are restricted under s19AB of the Health Insurance Act 1973, including International Medical Graduates (IMGs) and Foreign Graduates of Accredited Medical Schools (FGAMS). • The DPA classification system is also used to distribute Australian-trained Bonded doctors who have a return of service obligation. • The Distribution Priority Area (DPA) replaced the Districts of Workforce Shortage (DWS) system for GPs in 2019. DWS remains in use for non-GP specialists. • DPA considers the demographics of a region, including age, gender and socio-economic groupings, along with MBS activity data, to determine a benchmark figure that reflects community need for GP service. • DPA is calculated for 827 distinct, non-overlapping GP catchments throughout Australia. Catchments assessed below the benchmark are classified DPA. • Areas classified MM 2-7 under the Modified Monash Model (MMM) geographical remoteness classification system are automatically DPA. Inner metropolitan locations are automatically non-DPA. The attached file for the DPA as at November 2023 (most recent annual update). As the files may be updated at short notice for program purposes, please ensure you use the Health Workforce Locator for the most up-to-date and official DPA location status.

  7. Distribution Priority Area (for General Practitioners)

    • demo.dev.magda.io
    • researchdata.edu.au
    csv, shp, zip
    Updated Mar 18, 2025
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    Department of Health and Aged Care (2025). Distribution Priority Area (for General Practitioners) [Dataset]. https://demo.dev.magda.io/dataset/ds-dga-7d889af7-9506-4eb5-930e-cefe6b5f39c1
    Explore at:
    csv, zip, shpAvailable download formats
    Dataset updated
    Mar 18, 2025
    Dataset provided by
    Australian Government Department of Healthhttp://health.gov.au/
    License

    Attribution 2.5 (CC BY 2.5)https://creativecommons.org/licenses/by/2.5/
    License information was derived automatically

    Description

    The Distribution Priority Area (DPA) classification system for GPs is a mechanism used by the Government to encourage a more equitable distribution of GPs who are restricted under s19AB of the …Show full descriptionThe Distribution Priority Area (DPA) classification system for GPs is a mechanism used by the Government to encourage a more equitable distribution of GPs who are restricted under s19AB of the Health Insurance Act 1973, including International Medical Graduates (IMGs) and Foreign Graduates of Accredited Medical Schools (FGAMS). • The DPA classification system is also used to distribute Australian-trained Bonded doctors who have a return of service obligation. • The Distribution Priority Area (DPA) replaced the Districts of Workforce Shortage (DWS) system for GPs in 2019. DWS remains in use for non-GP specialists. • DPA considers the demographics of a region, including age, gender and socio-economic groupings, along with MBS activity data, to determine a benchmark figure that reflects community need for GP service. • DPA is calculated for 824 distinct, non-overlapping GP catchments throughout Australia. Catchments assessed below the benchmark are classified DPA. • Areas classified MM 2-7 under the Modified Monash Model (MMM) geographical remoteness classification system are automatically DPA. MM1 Inner metropolitan locations are automatically non-DPA. Areas that held DPA status prior to this update will continue to hold DPA status under a No Losers policy. The attached file for the DPA is as at March 2025 (most recent annual update). As the files may be updated at short notice for program purposes, please ensure you use the Department of Health and Aged Care Health Workforce Locator (https://www.health.gov.au/resources/apps-and-tools/health-workforce-locator) for the most up-to-date and official DPA location status.

  8. m

    Data from: Figure 2

    • bridges.monash.edu
    • researchdata.edu.au
    tiff
    Updated Nov 16, 2023
    + more versions
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    Robert Bryson-Richardson; Lee Miles (2023). Figure 2 [Dataset]. http://doi.org/10.26180/24571300.v1
    Explore at:
    tiffAvailable download formats
    Dataset updated
    Nov 16, 2023
    Dataset provided by
    Monash University
    Authors
    Robert Bryson-Richardson; Lee Miles
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Raw data and analysis files for Figure 2

  9. m

    Data from: Figure 3

    • bridges.monash.edu
    • researchdata.edu.au
    tiff
    Updated Nov 16, 2023
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    Robert Bryson-Richardson; Lee Miles (2023). Figure 3 [Dataset]. http://doi.org/10.26180/24571297.v1
    Explore at:
    tiffAvailable download formats
    Dataset updated
    Nov 16, 2023
    Dataset provided by
    Monash University
    Authors
    Robert Bryson-Richardson; Lee Miles
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Raw data and analysis files for Figure 3

  10. m

    Figure S2

    • bridges.monash.edu
    • researchdata.edu.au
    tiff
    Updated Jul 12, 2023
    + more versions
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    Robert Bryson-Richardson; Lee Miles (2023). Figure S2 [Dataset]. http://doi.org/10.26180/23626488.v1
    Explore at:
    tiffAvailable download formats
    Dataset updated
    Jul 12, 2023
    Dataset provided by
    Monash University
    Authors
    Robert Bryson-Richardson; Lee Miles
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Description

    Raw data for Figure S2

Share
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Email
Click to copy link
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Department of Health and Aged Care (2019). Modified Monash Model (MMM) 2015 [Dataset]. https://researchdata.edu.au/modified-monash-model-mmm-2015/1433648
Organization logo

Modified Monash Model (MMM) 2015

Explore at:
Dataset updated
Sep 30, 2019
Dataset provided by
Data.govhttps://data.gov/
Authors
Department of Health and Aged Care
License

Attribution 2.5 (CC BY 2.5)https://creativecommons.org/licenses/by/2.5/
License information was derived automatically

Description

In 2015, the Department of Health introduced the Modified Monash Model (MMM) classification system as it better targets health workforce programs by categorising metropolitan, regional, rural and remote areas according to both geographical remoteness, as defined by the Australian Bureau of Statistics, and town size. The MMM 2015 is based on Australian Bureau of Statistics (2011) Census data and geography information.

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