20 research outputs found

    Affordability of Complementary Health Insurance in France : A Social Experiment.

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    Inequalities in access to health care are well documented in France. They are mainly explained by inequalities in access to complementary health insurance. Even if the poorest 7% of French residents are covered for most of the out-of-pocket payments by the "free complementary health insurance plan" (Couverture maladie universelle complémentaire, CMUC) since 2000, 8% of the French population remains without any complementary health insurance and this proportion is higher among households whose resources are just above the CMU eligibility threshold. In order to improve financial access to complementary health insurance and reduce the threshold effect induced by the CMUC, a complementary health insurance voucher has been introduced in 2005 for this specific population. Despite a regular increase in uptake, four years after being set up the system concerned only a little over 490,000 people. This result is far below the 2 million people initially targeted. Several hypotheses can explain this evidence : 1. unaffordability of health insurance despite this financial aid, considering that beneficiaries have to pay almost 50% of the price of the contract after the voucher ; 2. lack of information on the take-up administrative process ; 3. voluntary trade-off between private consumption and health coverage. In order to evaluate these different hypotheses, we develop an experiment with the National Health Insurance Fund. Three groups of 1680 eligible households living in urban area in North of France have been randomly selected: a control group benefiting of the current financial aid, a group benefiting of a 50% voucher increase, and a last group benefiting of a 50% voucher increase and a social take-up support. The three groups have been followed-up during 6 months to observe their health insurance purchase. The comparison of the health coverage rate among the three groups will provide some indications on the respective effects of financial incentives and informal barriers on health insurance demand. The experimental data will then be merged with administrative data from the Public Health Insurance Fund to have information on income, supports received, health expenditures of the 2 previous years and health insurance status. A survey is also being conducted among the 3 groups and among a subsample of individuals which previously benefit from the ACS to explore: 1. the determinants of their health insurance status, 2. the determinants of ACS adherence. Finally, the health insurance purchase and the health expenditures will be followed during one year to explore the efficacy of the experiment. Findings from this study will enhance the understanding of the determinants of health insurance demand among the poorest population and help design better public policies to promote access of the poor to health insurance in order to tackle horizontal inequity in access to health care.Subsidized Health insurance; randomized experiment; low-income population; uninsured; France;

    The development of nations conditions the disease space

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    Using the economic complexity methodology on data for disease prevalence in 195 countries during the period of 1990-2016, we propose two new metrics for quantifying the relatedness between diseases, or the ‘disease space’ of countries. With these metrics, we analyze the geography of diseases and empirically investigate the effect of economic development on the health complexity of countries. We show that a higher income per capita increases the complexity of countries’ diseases. Furthermore, we build a disease-level index that links a disease to the average level of GDP per capita of the countries that have prevalent cases of the disease. With this index, we highlight the link between economic development and the complexity of diseases and illustrate, at the disease-level, how increases in income per capita are associated with more complex diseases

    The development of nations conditions the disease space

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    Using the economic complexity methodology on data for disease prevalence in 195 countries during the period of 1990-2016, we propose two new metrics for quantifying the relatedness between diseases, or the ‘disease space’ of countries. With these metrics, we analyze the geography of diseases and empirically investigate the effect of economic development on the health complexity of countries. We show that a higher income per capita increases the complexity of countries’ diseases. Furthermore, we build a disease-level index that links a disease to the average level of GDP per capita of the countries that have prevalent cases of the disease. With this index, we highlight the link between economic development and the complexity of diseases and illustrate, at the disease-level, how increases in income per capita are associated with more complex diseases

    Cost Effectiveness Analysis: Methodology for the Food Chain Area

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    This report provides a methodological guidance on cost-effectiveness analysis in the view of future evaluations of the EU interventions currently funded under the Common Financial Framework of the food chain area (CFF, Regulation (EU) No 652/2014). The report was commissioned by DG SANTE. Under the CFF, the EU is either funding or co-funding eligible costs faced by Member States when implementing phytosanitary and veterinary programmes, official control activities, and veterinary and phytosanitary emergency measures. These interventions aim at contributing to a high level of health for humans, animals and plants along the food chain, by preventing and eradicating diseases and pests and by ensuring a high level of protection for consumers and the environment, while enhancing the competitiveness of the Union food and feed industry. This report presents a methodology on how to address relevant policy questions such as: “Should more funding be awarded to prevention measures or to control measures to reduce the risk of outbreaks of classical swine fever in pigs?” or “is the introduction of new e-learning tools for official staff more effective in increasing the quality of the official controls compared to workshops?” This report provides evaluation methods to answer this type of questions and illustrates the methodology introduced for specific CFF related policy questions. These methods are based on disaggregated data and regression techniques. Economic evaluation is a systematic analysis tool to assess and quantify whether the interventions produce the expected effects, and to help draw conclusions on the cost-effectiveness of the different EU funded programmes. Thus, economic evaluation is a funding allocation tool that allows decision makers with a budget constraint to make informed choices on which interventions to allocate funding to. When performing economic evaluation, three main challenges need to be addressed; (i) how to measure the costs, (ii) how to quantify the effects, and (iii) how to identify the causal impact of the intervention under evaluation.JRC.I.1-Monitoring, Indicators & Impact Evaluatio

    Health Care Access of Low-Income Populations in France : micro-econometric Studies of the Take-up of Complementary Health Insurance Program and the Use of Health Care

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    L’objet de ce travail de recherche est d’étudier l’accĂšs financier Ă  la complĂ©mentaire santĂ© et aux soins des populations modestes en France. Nous nous intĂ©ressons plus particuliĂšrement au dispositif d’Aide complĂ©mentaire santĂ© (ACS) introduit afin d’inciter les mĂ©nages dont les ressources se situent juste au-dessus du plafond d’attribution de la Couverture maladie universelle (CMUC), Ă  acquĂ©rir une complĂ©mentaire santĂ©. À partir notamment d’une expĂ©rimentation sociale et d’un Ă©chantillon inĂ©dit de mĂ©nages Ă©ligibles Ă  ces dispositifs, nous sommes en mesure d’éclairer les connaissances sur trois questions : (i) La comprĂ©hension et la rĂ©duction du non-recours Ă  l’ACS. (ii) Les comportements de recours Ă  la complĂ©mentaire santĂ© et aux soins. (iii) L’existence d’un effet de seuil de la CMUC. Les rĂ©sultats de cette thĂšse permettent ainsi de nourrir la rĂ©flexion afin d’amĂ©liorer l’efficacitĂ© de ces dispositifs et plus gĂ©nĂ©ralement celle des politiques publiques futures visant Ă  amĂ©liorer l’équitĂ© dans l’accĂšs aux soins.The purpose of this research is to study the financial access to complementary health insurance (CHI) and to health care of low-income populations in France. We are particularly interested in evaluating a subsidized health insurance program (ACS) introduced to encourage households whose resources are just above the free means-tested complementary health insurance program (CMUC), to purchase a CHI plan. In implementing a randomized experiment and in using a sample of eligible households for these programs, we are able to enhance the knowledge base on three issues: (i) Understanding and reducing the ACS non-take-up. (ii) The take-up of CHI plan and the health care use of low-income populations. (iii) The existence of a CMUC threshold effect. Results of this thesis provide some important tracks to improve the effectiveness of these programs and more generally that of future public policies aiming to improve equity in access to health care

    Loneliness among older adults in Europe: The relative importance of early and later life conditions.

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    The aim of this paper is to study the association between childhood circumstances and loneliness in older adults in Europe. Based on rich information collected by the Survey on Health, Ageing, and Retirement in Europe (SHARE) on childhood characteristics and individual characteristics at age 50+, the study is able to control for personality traits, socioeconomic and demographic factors, social support and health in later life, and country-specific characteristics. The analyses show strong correlations between life circumstances in childhood and feeling lonely in older age; these correlations remain significant after adjusting for covariates. While ill health is the main factor correlated with loneliness at 50+, as expected, the analysis of the relative importance of the determinants reveals that personality traits account for more than 10% of the explained variance and that life circumstances during childhood account for 7%. Social support at older ages is the second highest category of factors, accounting for 27%-with, interestingly, support at home and social network characteristics contributing about 10% each, engaging in activities and computer skills accounting for 7% of the explained variance. Demographic and socioeconomic factors account for 6% and country-level characteristics contribute 5%. This paper points out the relevance of early life interventions to tackling loneliness in older age, and it shows that early interventions and interventions aiming at increasing social support in later life need to be adapted to all personality types. Thus, the role of childhood circumstances and the mechanisms explaining the association between loneliness in childhood and loneliness in later life deserve more attention in future research
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