National analysis of the Modified Monash Model, population distribution and a socio‐economic index to inform rural health workforce planning

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Standard

National analysis of the Modified Monash Model, population distribution and a socio‐economic index to inform rural health workforce planning. / Versace, Vincent L.; Skinner, Timothy C.; Bourke, Lisa; Harvey, Pam; Barnett, Tony.

I: Australian Journal of Rural Health, Bind 29, Nr. 5, 2021, s. 801-810.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Versace, VL, Skinner, TC, Bourke, L, Harvey, P & Barnett, T 2021, 'National analysis of the Modified Monash Model, population distribution and a socio‐economic index to inform rural health workforce planning', Australian Journal of Rural Health, bind 29, nr. 5, s. 801-810. https://doi.org/10.1111/ajr.12805

APA

Versace, V. L., Skinner, T. C., Bourke, L., Harvey, P., & Barnett, T. (2021). National analysis of the Modified Monash Model, population distribution and a socio‐economic index to inform rural health workforce planning. Australian Journal of Rural Health, 29(5), 801-810. https://doi.org/10.1111/ajr.12805

Vancouver

Versace VL, Skinner TC, Bourke L, Harvey P, Barnett T. National analysis of the Modified Monash Model, population distribution and a socio‐economic index to inform rural health workforce planning. Australian Journal of Rural Health. 2021;29(5):801-810. https://doi.org/10.1111/ajr.12805

Author

Versace, Vincent L. ; Skinner, Timothy C. ; Bourke, Lisa ; Harvey, Pam ; Barnett, Tony. / National analysis of the Modified Monash Model, population distribution and a socio‐economic index to inform rural health workforce planning. I: Australian Journal of Rural Health. 2021 ; Bind 29, Nr. 5. s. 801-810.

Bibtex

@article{e66a6889b11b447f816011ab7303ad25,
title = "National analysis of the Modified Monash Model, population distribution and a socio‐economic index to inform rural health workforce planning",
abstract = "AimsTo describe the population distribution and socio-economic position of residents across all states and territories of Australia, stratified using the 7 Modified Monash Model classifications. The numerical summary, and the methods described, can be applied by a variety of end users including workforce planners, researchers, policy-makers and funding bodies for guiding future investment under different scenarios, and aid in evaluating geographically focused programs.ContextThe Commonwealth Department of Health is transitioning to the Modified Monash Model to objectively describe geographical access. This change applies to the Rural Health Multidisciplinary Training Program, one of the Australian Government's key policies to address the maldistribution of the rural health workforce. Unlike the previously applied Australian Statistical Geography Standard-Remoteness Areas, a summary of the population in each Modified Monash Model classification is not available, nor is a socio-economic overview of the communities within these areas.ApproachSpatial analysis of Australian Bureau of Statistics data (Modified Monash Model, population data and the Index of Relative Socio-economic Advantage and Disadvantage collected or derived from the 2016 census) at the Statistical Area 1—the smallest unit for the release of census data.ConclusionLinking the Modified Monash Model, a socio-economic index and granular population data at the national level highlights the disadvantage of many residents in small rural towns (Modified Monash 5). The Modified Monash Model does not exhibit a continuum of the largest population residing in the most accessible classification and the smallest population residing in the least accessible classification that is seen in the Australian Statistical Geography Standard-Remoteness Areas. Coupled with policy relevance, the advantage of using the Modified Monash Model as the basis for analysis is that it highlights areas that have both a critical mass of residents and differing levels of socio-economic advantage and disadvantage. This will help end users to target funding to those regions where there is potential to improve access to services for the greatest number of rural residents.",
keywords = "Faculty of Social Sciences, Geographical information systems, GIS, Modified Monash Model, Regional health, Remote health, Remoteness Areas, Rural health, Social determinants, Spatial analysis",
author = "Versace, {Vincent L.} and Skinner, {Timothy C.} and Lisa Bourke and Pam Harvey and Tony Barnett",
year = "2021",
doi = "10.1111/ajr.12805",
language = "English",
volume = "29",
pages = "801--810",
journal = "Australian Journal of Rural Health",
issn = "1038-5282",
publisher = "Wiley-Blackwell",
number = "5",

}

RIS

TY - JOUR

T1 - National analysis of the Modified Monash Model, population distribution and a socio‐economic index to inform rural health workforce planning

AU - Versace, Vincent L.

AU - Skinner, Timothy C.

AU - Bourke, Lisa

AU - Harvey, Pam

AU - Barnett, Tony

PY - 2021

Y1 - 2021

N2 - AimsTo describe the population distribution and socio-economic position of residents across all states and territories of Australia, stratified using the 7 Modified Monash Model classifications. The numerical summary, and the methods described, can be applied by a variety of end users including workforce planners, researchers, policy-makers and funding bodies for guiding future investment under different scenarios, and aid in evaluating geographically focused programs.ContextThe Commonwealth Department of Health is transitioning to the Modified Monash Model to objectively describe geographical access. This change applies to the Rural Health Multidisciplinary Training Program, one of the Australian Government's key policies to address the maldistribution of the rural health workforce. Unlike the previously applied Australian Statistical Geography Standard-Remoteness Areas, a summary of the population in each Modified Monash Model classification is not available, nor is a socio-economic overview of the communities within these areas.ApproachSpatial analysis of Australian Bureau of Statistics data (Modified Monash Model, population data and the Index of Relative Socio-economic Advantage and Disadvantage collected or derived from the 2016 census) at the Statistical Area 1—the smallest unit for the release of census data.ConclusionLinking the Modified Monash Model, a socio-economic index and granular population data at the national level highlights the disadvantage of many residents in small rural towns (Modified Monash 5). The Modified Monash Model does not exhibit a continuum of the largest population residing in the most accessible classification and the smallest population residing in the least accessible classification that is seen in the Australian Statistical Geography Standard-Remoteness Areas. Coupled with policy relevance, the advantage of using the Modified Monash Model as the basis for analysis is that it highlights areas that have both a critical mass of residents and differing levels of socio-economic advantage and disadvantage. This will help end users to target funding to those regions where there is potential to improve access to services for the greatest number of rural residents.

AB - AimsTo describe the population distribution and socio-economic position of residents across all states and territories of Australia, stratified using the 7 Modified Monash Model classifications. The numerical summary, and the methods described, can be applied by a variety of end users including workforce planners, researchers, policy-makers and funding bodies for guiding future investment under different scenarios, and aid in evaluating geographically focused programs.ContextThe Commonwealth Department of Health is transitioning to the Modified Monash Model to objectively describe geographical access. This change applies to the Rural Health Multidisciplinary Training Program, one of the Australian Government's key policies to address the maldistribution of the rural health workforce. Unlike the previously applied Australian Statistical Geography Standard-Remoteness Areas, a summary of the population in each Modified Monash Model classification is not available, nor is a socio-economic overview of the communities within these areas.ApproachSpatial analysis of Australian Bureau of Statistics data (Modified Monash Model, population data and the Index of Relative Socio-economic Advantage and Disadvantage collected or derived from the 2016 census) at the Statistical Area 1—the smallest unit for the release of census data.ConclusionLinking the Modified Monash Model, a socio-economic index and granular population data at the national level highlights the disadvantage of many residents in small rural towns (Modified Monash 5). The Modified Monash Model does not exhibit a continuum of the largest population residing in the most accessible classification and the smallest population residing in the least accessible classification that is seen in the Australian Statistical Geography Standard-Remoteness Areas. Coupled with policy relevance, the advantage of using the Modified Monash Model as the basis for analysis is that it highlights areas that have both a critical mass of residents and differing levels of socio-economic advantage and disadvantage. This will help end users to target funding to those regions where there is potential to improve access to services for the greatest number of rural residents.

KW - Faculty of Social Sciences

KW - Geographical information systems

KW - GIS

KW - Modified Monash Model

KW - Regional health

KW - Remote health

KW - Remoteness Areas

KW - Rural health

KW - Social determinants

KW - Spatial analysis

U2 - 10.1111/ajr.12805

DO - 10.1111/ajr.12805

M3 - Journal article

C2 - 34672057

VL - 29

SP - 801

EP - 810

JO - Australian Journal of Rural Health

JF - Australian Journal of Rural Health

SN - 1038-5282

IS - 5

ER -

ID: 282691416