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    Health Policy in Ageing Populations: Economic modeling of chronic disease policy options in Australia

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    Contributor(s)
    Walker, Agnes (editor)
    Butler, James R.G. (editor)
    Colagiuri, Stephen (editor)
    Language
    English
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    Abstract
    In a global environment of rapid increases in health expenditures, health policies in Australia and in many other countries are currently undergoing major reforms. To contain future cost increases, accurate tools able to identify and rank ‘best value for money’ health investments are essential. In Australia non-communicable chronic diseases – e.g. diabetes, heart disease, cancer, arthritis and mental disorders – affect the majority of the elderly, account for 70% of health expenditures, and cause poor health, deteriorating quality of life and premature death. This book focuses on how to identify ‘best value for money’ health investments within the context of on-going and future health reforms, and on quantifying the major benefits that would flow from such investments in terms of longer and better lives. This book will be of interest to general readers, social and economic researchers, and students interested in health care in ageing populations.
    URI
    https://library.oapen.org/handle/20.500.12657/76056
    Keywords
    Health Policy, Economic modeling, health and population ageing, socio-economic modelling, chronic disease prevention & treatment, cost-effectiveness of policy options, economics, social science, Socio-economic Modelling, public health, health economics
    DOI
    10.2174/97816080581671130101
    ISBN
    9781608058167, 9781608058174, 9781608058167
    Publisher
    Bentham Science Publishers
    Publication date and place
    2013
    Imprint
    Bentham Science Publishers
    Pages
    162
    Rights
    https://creativecommons.org/licenses/by/4.0/legalcode
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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