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      Extended Cost-Effectiveness Analysis for Health Policy Assessment: A Tutorial

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          Abstract

          Health policy instruments such as the public financing of health technologies (e.g., new drugs, vaccines) entail consequences in multiple domains. Fundamentally, public health policies aim at increasing the uptake of effective and efficient interventions and at subsequently leading to better health benefits (e.g., premature mortality and morbidity averted). In addition, public health policies can provide non-health benefits in addition to the sole well-being of populations and beyond the health sector. For instance, public policies such as social and health insurance programs can prevent illness-related impoverishment and procure financial risk protection. Furthermore, public policies can improve the distribution of health in the population and promote the equalization of health among individuals. Extended cost-effectiveness analysis was developed to address health policy assessment, specifically to evaluate the health and financial consequences of public policies in four domains: (1) the health gains; (2) the financial risk protection benefits; (3) the total costs to the policy makers; and (4) the distributional benefits. Here, we present a tutorial that describes both the intent of extended cost-effectiveness analysis and its keys to allow easy implementation for health policy assessment.

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          Risk Aversion in the Small and in the Large

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            Differences in life expectancy due to race and educational differences are widening, and many may not catch up.

            It has long been known that despite well-documented improvements in longevity for most Americans, alarming disparities persist among racial groups and between the well-educated and those with less education. In this article we update estimates of the impact of race and education on past and present life expectancy, examine trends in disparities from 1990 through 2008, and place observed disparities in the context of a rapidly aging society that is emerging at a time of optimism about the next revolution in longevity. We found that in 2008 US adult men and women with fewer than twelve years of education had life expectancies not much better than those of all adults in the 1950s and 1960s. When race and education are combined, the disparity is even more striking. In 2008 white US men and women with 16 years or more of schooling had life expectancies far greater than black Americans with fewer than 12 years of education-14.2 years more for white men than black men, and 10.3 years more for white women than black women. These gaps have widened over time and have led to at least two "Americas," if not multiple others, in terms of life expectancy, demarcated by level of education and racial-group membership. The message for policy makers is clear: implement educational enhancements at young, middle, and older ages for people of all races, to reduce the large gap in health and longevity that persists today.
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              Priority setting of health interventions: the need for multi-criteria decision analysis

              Priority setting of health interventions is often ad-hoc and resources are not used to an optimal extent. Underlying problem is that multiple criteria play a role and decisions are complex. Interventions may be chosen to maximize general population health, to reduce health inequalities of disadvantaged or vulnerable groups, ad/or to respond to life-threatening situations, all with respect to practical and budgetary constraints. This is the type of problem that policy makers are typically bad at solving rationally, unaided. They tend to use heuristic or intuitive approaches to simplify complexity, and in the process, important information is ignored. Next, policy makers may select interventions for only political motives. This indicates the need for rational and transparent approaches to priority setting. Over the past decades, a number of approaches have been developed, including evidence-based medicine, burden of disease analyses, cost-effectiveness analyses, and equity analyses. However, these approaches concentrate on single criteria only, whereas in reality, policy makers need to make choices taking into account multiple criteria simultaneously. Moreover, they do not cover all criteria that are relevant to policy makers. Therefore, the development of a multi-criteria approach to priority setting is necessary, and this has indeed recently been identified as one of the most important issues in health system research. In other scientific disciplines, multi-criteria decision analysis is well developed, has gained widespread acceptance and is routinely used. This paper presents the main principles of multi-criteria decision analysis. There are only a very few applications to guide resource allocation decisions in health. We call for a shift away from present priority setting tools in health – that tend to focus on single criteria – towards transparent and systematic approaches that take into account all relevant criteria simultaneously.
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                Author and article information

                Contributors
                verguet@hsph.harvard.edu
                Journal
                Pharmacoeconomics
                Pharmacoeconomics
                Pharmacoeconomics
                Springer International Publishing (Cham )
                1170-7690
                1179-2027
                4 July 2016
                4 July 2016
                2016
                : 34
                : 913-923
                Affiliations
                [1 ]Department of Global Health and Population, Harvard T.H. Chan School of Public Health, 665 Huntington Avenue, Boston, MA 02115 USA
                [2 ]Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA USA
                [3 ]Global Health Sciences, University of California, San Francisco, CA USA
                [4 ]Department of Global Health, University of Washington, Seattle, WA USA
                Article
                414
                10.1007/s40273-016-0414-z
                4980400
                27374172
                da5b9e5d-ec7d-4e44-9d30-946fbe531ffc
                © The Author(s) 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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                Practical Application
                Custom metadata
                © Springer International Publishing Switzerland 2016

                Economics of health & social care
                Economics of health & social care

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