2005
DOI: 10.1071/ah050167
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Distributional impact of recent changes in private health insurance policies

Abstract: The impacts of changes to private health insurance (PHI) policies introduced since 1999 -in particular the 30% PHI rebate and the Lifetime Health Cover -have been much debated. We present historical analyses of the impacts in terms of the proportion of Australians having hospital insurance cover under different PHI policies, by age, gender and socioeconomic status, and project these to 2010 using a new Private Health Insurance coverage model.The combined effect of the 30% rebate and Lifetime Health Cover was t… Show more

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Cited by 18 publications
(23 citation statements)
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“…17 Frech et al [8] gave yet another estimate of the decline using trend analysis. See also Walker et al [21] for further estimates based on trend analysis. These different estimates suggest that methodological differences do produce rather different values, and it is difficult to suggest whether one is superior to another.…”
Section: Determinants Of Private Health Insurance Purchasementioning
confidence: 99%
See 1 more Smart Citation
“…17 Frech et al [8] gave yet another estimate of the decline using trend analysis. See also Walker et al [21] for further estimates based on trend analysis. These different estimates suggest that methodological differences do produce rather different values, and it is difficult to suggest whether one is superior to another.…”
Section: Determinants Of Private Health Insurance Purchasementioning
confidence: 99%
“…The results are summarised in Table 7. 21 Table 7 suggests that around $887 million per year may have been spent on subsidising households who would have purchased PHI in any case. We make two remarks.…”
Section: Quantifying the Amount Of Unnecessary Subsidymentioning
confidence: 99%
“…The model and the simulated scenarios are described in an earlier publication. 4 Briefly, the model uses logistic regression to estimate the probability of a person having private health insurance. Predictive variables are: age, sex, year (as number of years from 1983), premium costs (as a proportion of average household disposable income) and, to account for SES, gross income quintiles (at income unit level).…”
Section: The Phi Model and Scenariosmentioning
confidence: 99%
“…4 In Box 5 we reproduced the earlier income-based table, 4 but rearranged the income brackets into quintiles based on ABS data, 17 with the $0-$15 000 annual household income group representing SES quintile 1; $15 001-$35 000 quintile 2; $35 001-$50 000 quintile 3; $50 000-$70 000 quintile 4; and the over $70 000 group quintile 5. We then used the Box 5 tabulation to link the PHI and NSW hospitals models.…”
Section: Linking the Modelsmentioning
confidence: 99%
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