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Many Americans believe that people who lack health insurance somehow get the care they really need. Care Without Coverage examines the real consequences for adults who lack health insurance. The study presents findings in the areas of prevention and screening, cancer, chronic illness, hospital-based care, and general health status. The committee looked at the consequences of being uninsured for people suffering from cancer, diabetes, HIV infection and AIDS, heart and kidney disease, mental illness, traumatic injuries, and heart attacks. It focused on the roughly 30 million-one in seven-working-age Americans without health insurance. This group does not include the population over 65 that is covered by Medicare or the nearly 10 million children who are uninsured in this country. The main findings of the report are that working-age Americans without health insurance are more likely to receive too little medical care and receive it too late; be sicker and die sooner; and receive poorer care when they are in the hospital, even for acute situations like a motor vehicle crash.
Healthcare for all at affordable prices is still a major but universally elusive goal. Everyone spends money on healthcare, and it is the most impoverishing consumption item. Thus, most governments (and the United Nations) promote Universal Health Coverage — each country's unique blend of tools for healthcare financing, including taxes, subsidies and market controls.Most people in low- and middle-income countries (LMICs) have no health insurance of any kind. And most LMIC governments lack the political will, information, or resources to require their citizens to buy health insurance themselves or to subsidize insurance for all who cannot afford the price. This book deals with financing voluntary and contributory health insurance for resource-poor and rural groups in LMICs.This book addresses three issues. The first is how to catalyse demand for health insurance and develop insurance literacy among the largely illiterate and innumerate target population, using training programs to build an enabling consensus, allowing locals to create and administer such schemes. The second involves the process of developing simplified methods for risk assessment, which can help to underwrite risks, price the micro health insurance schemes, and ensure proper implementation. The third issue is formulating a compelling business case which would make this health insurance affordable, financially sustainable, and operationally scalable.This book develops insurance education and financial literacy for students of economics, business administration, insurance, development studies, and social work to prepare them for practical work as implementers, policymakers, or evaluators. A supplementary section for teachers and students includes comprehension questions.
Addressing the challenge of covering heath care expenses—while minimizing economic risks. Moral hazard—the tendency to change behavior when the cost of that behavior will be borne by others—is a particularly tricky question when considering health care. Kenneth J. Arrow’s seminal 1963 paper on this topic (included in this volume) was one of the first to explore the implication of moral hazard for health care, and Amy Finkelstein—recognized as one of the world’s foremost experts on the topic—here examines this issue in the context of contemporary American health care policy. Drawing on research from both the original RAND Health Insurance Experiment and her own research, including a 2008 Health Insurance Experiment in Oregon, Finkelstein presents compelling evidence that health insurance does indeed affect medical spending and encourages policy solutions that acknowledge and account for this. The volume also features commentaries and insights from other renowned economists, including an introduction by Joseph P. Newhouse that provides context for the discussion, a commentary from Jonathan Gruber that considers provider-side moral hazard, and reflections from Joseph E. Stiglitz and Kenneth J. Arrow. “Reads like a fireside chat among a group of distinguished, articulate health economists.” —Choice
A valuable overview of the most important ideas and results in statistical modeling Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linearstatistical models. The book presents a broad, in-depth overview of the most commonly usedstatistical models by discussing the theory underlying the models, R software applications,and examples with crafted models to elucidate key ideas and promote practical modelbuilding. The book begins by illustrating the fundamentals of linear models, such as how the model-fitting projects the data onto a model vector subspace and how orthogonal decompositions of the data yield information about the effects of explanatory variables. Subsequently, the book covers the most popular generalized linear models, which include binomial and multinomial logistic regression for categorical data, and Poisson and negative binomial loglinear models for count data. Focusing on the theoretical underpinnings of these models, Foundations ofLinear and Generalized Linear Models also features: An introduction to quasi-likelihood methods that require weaker distributional assumptions, such as generalized estimating equation methods An overview of linear mixed models and generalized linear mixed models with random effects for clustered correlated data, Bayesian modeling, and extensions to handle problematic cases such as high dimensional problems Numerous examples that use R software for all text data analyses More than 400 exercises for readers to practice and extend the theory, methods, and data analysis A supplementary website with datasets for the examples and exercises An invaluable textbook for upper-undergraduate and graduate-level students in statistics and biostatistics courses, Foundations of Linear and Generalized Linear Models is also an excellent reference for practicing statisticians and biostatisticians, as well as anyone who is interested in learning about the most important statistical models for analyzing data.
Non-life insurance pricing is the art of setting the price of an insurance policy, taking into consideration varoius properties of the insured object and the policy holder. Introduced by British actuaries generalized linear models (GLMs) have become today a the standard aproach for tariff analysis. The book focuses on methods based on GLMs that have been found useful in actuarial practice and provides a set of tools for a tariff analysis. Basic theory of GLMs in a tariff analysis setting is presented with useful extensions of standarde GLM theory that are not in common use. The book meets the European Core Syllabus for actuarial education and is written for actuarial students as well as practicing actuaries. To support reader real data of some complexity are provided at www.math.su.se/GLMbook.
This book is devoted to intelligent models and algorithms as the core components of cyber-physical systems. The complexity of cyber-physical systems developing and deploying requires new approaches to its modelling and design. Presents results in the field of modelling technologies that leverage the exploitation of artificial intelligence, including artificial general intelligence (AGI) and weak artificial intelligence. Provides scientific, practical, and methodological approaches based on bio-inspired methods, fuzzy models and algorithms, predictive modelling, computer vision and image processing. The target audience of the book are practitioners, enterprises representatives, scientists, PhD and Master students who perform scientific research or applications of intelligent models and algorithms in cyber-physical systems for various domains.
Recent developments in parallel computing for various fields of application are providing improved solutions for handling data. These newer, innovative ideas offer the technical support necessary to enhance intellectual decisions, while also dealing more efficiently with the huge volumes of data currently involved. This book presents the proceedings of ICAPTA 2022, the International Conference on Advances in Parallel Computing Technologies and Applications, hosted as a virtual conference from Bangalore, India, on 27 and 28 January 2022. The aim of the conference was to provide a forum for the sharing of knowledge about various aspects of parallel computing in communications systems and networking, including cloud and virtualization solutions, management technologies and vertical application areas. The conference also provided a premier platform for scientists, researchers, practitioners and academicians to present and discuss their most recent innovations, trends and concerns, as well as the practical challenges encountered in this field. More than 300 submissions were received for the conference, from which the 91 full-length papers presented here were accepted after review by a panel of subject experts. Topics covered include parallel computing in communication, machine learning intelligence for parallel computing and parallel computing for software services in theoretical and practical aspects. Providing an overview of recent developments in the field, the book will be of interest to all those whose work involves the use of parallel computing technologies.