64 research outputs found

    Individual and national financial impacts of informal caring for people with mental illness in Australia, projected to 2030

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    Background Mental illness has a significant impact not only on patients, but also on their carers\u27 capacity to work. Aims To estimate the costs associated with lost labour force participation due to the provision of informal care for people with mental illness in Australia, such as income loss for carers and lost tax revenue and increased welfare payments for government, from 2015 to 2030. Method The output data of a microsimulation model Care&WorkMOD were analysed to project the financial costs of informal care for people with mental illness, from 2015 to 2030. Care&WorkMOD is a population-representative microsimulation model of the Australian population aged between 15 and 64 years, built using the Australian Bureau of Statistics Surveys of Disability, Ageing and Carers data and the data from other population-representative microsimulation models. Results The total annual national loss of income for all carers due to caring for someone with mental illness was projected to rise from AU451million(£219.6million)in2015toAU451 million (£219.6 million) in 2015 to AU645 million (£314 million) in 2030 in real terms. For the government, the total annual lost tax revenue was projected to rise from AU121million(£58.9million)in2015toAU121 million (£58.9 million) in 2015 to AU170 million (£82.8 million) in 2030 and welfare payments to increase from AU170million(£82.8million)toAU170 million (£82.8 million) to AU220 million (£107 million) in 2030. Conclusions The costs associated with lost labour force participation due to the provision of informal care for people with mental illness are projected to increase for both carers and government, with a widening income gap between informal carers and employed non-carers, putting carers at risk of increased inequality

    Economic costs of chronic disease through lost productive life years (PLYs) among Australians aged 45–64 years from 2015 to 2030:Results from a microsimulation model

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    Objectives: To project the number of older workers with lost productive life years (PLYs) due to chronic disease and resultant lost income; and lost taxes and increased welfare payments from 2015 to 2030. Design, setting and participants: Using a microsimulation model, Health&WealthMOD2030, the costs of chronic disease in Australians aged 45–64 were projected to 2030. The model integrates household survey data from the Australian Bureau of Statistics Surveys of Disability, Ageing and Carers (SDACs) 2003 and 2009, output from long-standing microsimulation models (STINMOD (Static Incomes Model) and APPSIM (Australian Population and Policy Simulation Model)) used by various government departments, population and labour force growth data from Treasury, and disease trends data from the Australian Burden of Disease and Injury Study (2003). Respondents aged 45–64 years in the SDACs 2003 and 2009 formed the base population. Main outcome measures: Lost PLYs due to chronic disease; resultant lost income, lost taxes and increased welfare payments in 2015, 2020, 2025 and 2030. Results: We projected 380 000 (6.4%) people aged 45–64 years with lost PLYs in 2015, increasing to 462 000 (6.5%) in 2030—a 22% increase in absolute numbers. Those with lost PLYs experience the largest reduction in income than any other group in each year compared to those employed full time without a chronic disease, and this income gap widens over time. The total economic loss due to lost PLYs consisted of lost income modelled at A12.6billionin2015,increasingtoA12.6 billion in 2015, increasing to A20.5 billion in 2030—a 62.7% increase. Additional costs to the government consisted of increased welfare payments at A6.2billionin2015,increasingtoA6.2 billion in 2015, increasing to A7.3 billion in 2030—a 17.7% increase; and a loss of A3.1billionintaxesin2015,increasingtoA3.1 billion in taxes in 2015, increasing to A4.7 billion in 2030—a growth of 51.6%. Conclusions: There is a need for greater investment in effective preventive health interventions which improve workers’ health and work capacity.Full Tex

    The Healthcare and Societal Costs of Familial Intellectual Disability

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    Most of the studies on the cost of intellectual disability are limited to a healthcare perspective or cohorts composed of individuals where the etiology of the condition is a mixture of genetic and non-genetic factors. When used in policy development, these can impact the decisions made on the optimal allocation of resources. In our study, we have developed a static microsimulation model to estimate the healthcare, societal, and lifetime cost of individuals with familial intellectual disability, an inheritable form of the condition, to families and government. The results from our modeling show that the societal costs outweighed the health costs (approximately 89.2% and 10.8%, respectively). The lifetime cost of familial intellectual disability is approximately AUD 7 million per person and AUD 10.8 million per household. The lifetime costs to families are second to those of the Australian Commonwealth government (AUD 4.2 million and AUD 9.3 million per household, respectively). These findings suggest that familial intellectual disability is a very expensive condition, representing a significant cost to families and government. Understanding the drivers of familial intellectual disability, especially societal, can assist us in the development of policies aimed at improving health outcomes and greater access to social care for affected individuals and their families

    The impact of diabetes prevention on labour force participation and income of older Australians: an economic study

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    Background: Globally, diabetes is estimated to affect 246 million people and is increasing. In Australia diabetes has been made a national health priority. While the direct costs of treating diabetes are substantial, and rising, the indirect costs are considered greater. There is evidence that interventions to prevent diabetes are effective, and cost-effective, but the impact on labour force participation and income has not been assessed. In this study we quantify the potential impact of implementing a diabetes prevention program, using screening and either metformin or a lifestyle intervention on individual economic outcomes of pre-diabetic Australians aged 45-64. Methods. The output of an epidemiological microsimulation model of the reduction in prevalence of diabetes from a lifestyle or metformin intervention, and another microsimulation model, Health&WealthMOD, of health and the associated impacts on labour force participation, personal income, savings, government revenue and expenditure were used to quantify the estimated outcomes of the two interventions. Results: An additional 753 person years in the labour force would have been achieved from 1993 to 2003 for the male cohort aged 60-64 years in 2003, if a lifestyle intervention had been introduced in 1983; with 890 person years for the equivalent female group. The impact on labour force participation was lower for the metformin intervention, and increased with age for both interventions. The male cohort aged 60-64 years in 2003 would have earned an additional 30millioninincomewiththemetforminintervention,andtheequivalentfemalecohortwouldhaveearnedanadditional30 million in income with the metformin intervention, and the equivalent female cohort would have earned an additional 25 million. If the lifestyle intervention was introduced, the same male and female cohorts would have earned an additional 34millionand34 million and 28 million respectively from 1993 to 2003. For the individuals involved, on average, males would have earned an additional 44,600peryearandfemalesanadditional44,600 per year and females an additional 31,800 per year, if they had continued to work as a result of preventing diabetes. Conclusions: In addition to improved health and wellbeing, considerable benefits to individuals, in terms of both additional working years and increased personal income, could be made by introducing either a lifestyle or metformin intervention to prevent diabetes

    Access to general practitioner services amongst underserved Australians: a microsimulation study

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    <p>Abstract</p> <p>Background</p> <p>One group often identified as having low socioeconomic status, those living in remote or rural areas, are often recognised as bearing an unequal burden of illness in society. This paper aims to examine equity of utilisation of general practitioner services in Australia.</p> <p>Methods</p> <p>Using the 2005 National Health Survey undertaken by the Australian Bureau of Statistics, a microsimulation model was developed to determine the distribution of GP services that would occur if all Australians had equal utilisation of health services relative to need.</p> <p>Results</p> <p>It was estimated that those who are unemployed would experience a 19% increase in GP services. Persons residing in regional areas would receive about 5.7 million additional GP visits per year if they had the same access to care as Australians residing in major cities. This would be a 18% increase. There would be a 20% increase for inner regional residents and a 14% increase for residents of more remote regional areas. Overall there would be a 5% increase in GP visits nationally if those in regional areas had the same access to care as those in major cities.</p> <p>Conclusion</p> <p>Parity is an insufficient goal and disadvantaged persons and underserved areas require greater access to health services than the well served metropolitan areas due to their greater poverty and poorer health status. Currently underserved Australians suffer a double disadvantage: poorer health and poorer access to health services.</p

    The personal and national costs of mental health conditions: impacts on income, taxes, government support payments due to lost labour force participation

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    <p>Abstract</p> <p>Background</p> <p>Mental health conditions have the ability to interrupt an individual's ability to participate in the labour force, and this can have considerable follow on impacts to both the individual and the state.</p> <p>Method</p> <p>Cross-sectional analysis of the base population of Health&WealthMOD, a microsimulation model built on data from the Australian Bureau of Statistics' <it>Survey of Disability, Ageing and Carers </it>and STINMOD, an income and savings microsimulation model was used to quantify the personal cost of lost income and the cost to the state from lost income taxation, increased benefits payments and lost GDP as a result of early retirement due to mental health conditions in Australians aged 45-64 in 2009.</p> <p>Results</p> <p>Individuals aged 45 to 64 years who have retired early due to depression personally have 73% lower income then their full time employed counterparts and those retired early due to other mental health conditions have 78% lower incomes. The national aggregate cost to government due to early retirement from these conditions equated to 278million(£152.9million)inlostincometaxationrevenue,278 million (£152.9 million) in lost income taxation revenue, 407 million (£223.9 million) in additional transfer payments and around $1.7 billion in GDP in 2009 alone.</p> <p>Conclusions</p> <p>The costs of mental health conditions to the individuals and the state are considerable. While individuals has to bear the economic costs of lost income in addition to the burden of the conditions itself, the impact on the state is loss of productivity from reduced workforce participation, lost income taxation revenue, and increased government support payments - in addition to direct health care costs.</p

    Multi-dimensional poverty in Australia and the barriers ill health imposes on the employment of the disadvantaged

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    A little over one million individuals in Australia between the ages of 24 and 64 years are in Freedom poverty – they have low family income, and have either poor health or an insufficient level of education. These individuals are some of the most disadvantaged in society due to their multiple capability restrictions. Current political rhetoric focused on reducing the number of individuals out of the labour force to improve their living standards may offer a means of improving the lives of these most disadvantaged individuals. Indeed, of those in Freedom poverty, 80% are not in employment. But these individuals also have poor health and/or a poor education and these capability limitations may act as barriers to their labour force participation. Indeed, 49% of individuals in freedom poverty who were out of the labour force cited ill health as the reason for this (39% cited their own ill health, and 10% cited another's ill health). Not only will these individual's ill health act as a barrier to their engaging in the labour force, but ill health will also contribute to reduced quality of life. Political promises to improve the lives of citizens should not focus narrowly upon increasing labour force participation rates, but should take a holistic view of the lives of individuals taking note in particular of how health may be restraining their quality of life

    Multiple disadvantages among older citizens: what a multidimensional measure of poverty can show

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    Using the newly created Freedom Poverty Measure, a multidimensional measure of poverty, it can be seen that there were 534,700 individuals who were in freedom poverty, who had either poor health or poor education in addition to having low incomes. This multidimensional disadvantage would not normally be captured by single measures of poverty, such as income poverty measures. Men were significantly less likely to be in freedom poverty than women (OR = 0.63, 95% CI: 0.54–0.74, p < .0001), and the proportion of individuals in freedom poverty increased with age, with those older than 85 being 2.3 times more likely to be in freedom poverty than those aged 65 to 69 years (95% CI: 1.73–3.11, p < .0001). Policy responses to address the marginalization of disadvantaged older people should take a multidisciplinary approach, addressing health inequalities in particular, not just low income

    Freedom poverty: a new tool to identify the multiple disadvantages affecting those with CVD

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    Background: It is recognised that CVD affects an individual's financial situation, placing them in income poverty. However, recent developments in poverty measurement practice recognises other forms of disadvantage other than low income, such as poor health and insufficient education also affect living standards. Methods: Using the Freedom Poverty Measure, the multiple forms of disadvantage experienced by those with no health condition, heart disease, other diseases of the circulatory system, and all other health conditions was assessed using data on the adult Australian population contained in the 2003 Survey of Disability, Ageing and Carers. Results: 24% of those with heart disease and 23% of those with other diseases of the circulatory system were in freedom poverty, suffering from multiple forms of disadvantage. Those with heart disease and those with other diseases of the circulatory system were around three times more likely to be in freedom poverty (OR 3.02, 95% CI: 2.29–3.99, p < .0001; OR 2.78, 95% CI: 1.94–3.98, p < .0001) than those with no health condition. Conclusions: Recognising the multiple forms of disadvantage suffered by those with CVD provides a clearer picture of their living standards than just looking at their income alone and the high proportion of individuals with CVD that are suffering from multiple forms of disadvantage should make them a target for policy makers wishing to improve living standards
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