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What influences the distribution of GPs across areas? The geography of GP supply using small area data and spatial econometrics Michelle McIsaac, Anthony Scott, Guyonne Kalb Melbourne Institute of Applied Economic and Social Research The University of Melbourne
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www.mabel.org.au Map of GP supply in Australia (2008)
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www.mabel.org.au Aim of this presentation To examine the association between geographic characteristics and the supply of GPs. To examine how the factors influencing GP supply are spatially correlated, and how this influences associations To examine the importance of the geographic unit of measurement
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www.mabel.org.au Methodology Tobit regression model Unit of analysis is the postal area – smallest available Dependent variable –Number of GPs per capita Independent variables –Hospitals, private schools, income, mortality, labour force participation rate, rurality, indigenous, age/gender mix of population
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www.mabel.org.au Methodology Spatial Heterogeneity Model: –Spatially weighted Tobit Account for correlations between 5 and 10 nearest neighbours Includes additional independent variables of the mean value of the variable of neighbours
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www.mabel.org.au Results Higher GP supply in areas with high taxable income –Important at the regional level, rather than postal area Higher GP supply associated higher labour force participation rate –Neighbouring areas with high LFP lead to lower supply Mortality (need) not associated with GP supply Higher GP supply associated with the number of hospitals –Neighbouring areas with hospitals have no effect on GP supply
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www.mabel.org.au Results Higher GP supply where there are more private schools –Neighbouring areas with private schools lead to higher GP supply Also effects of different age-gender mixes –Age-gender mix of neighbouring areas have an effect on GP supply
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www.mabel.org.au Summary GP supply is higher in affluent areas, with high employment, with hospitals, private schools, and in metropolitan areas. Mortality rate (need) rate is unrelated to GP supply. Accounting for spatial correlation matters
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www.mabel.org.au Conclusions, speculations and further work Implies a 2-stage decision making process of GPs location choices; 1) First choose broad area (eg North of city – affluent and private schools) 2) Then choose practice within or close to this area Implies that policies aimed at changing practice characteristics may have less of an effect on GP choice of broad area in which to work This is to be more formally tested in future work
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