Consumers, public officials, and even managers of health care and insurance are unhappy about care quality, access, and costs. This book shows that is because efforts to do something about these problems often rely on hope or conjecture, not rigorous evidence of effectiveness. In this book, experts in the field separate the speculative from the proven with regard to how care is rendered, how patients can be in control, how providers should be paid, and how disparities can be reduced - and they also identify the issues for which evidence is currently missing. It provides an antidote to frustration and a clear-eyed guide for forward progress, helping health care and insurance innovators make better decisions on deciding whether to go ahead now based on current evidence, to seek and wait for additional evidence, or to move on to different ideas. It will be useful to practitioners in hospital systems, medical groups, and insurance organizations and can also be used in executive and MBA teaching.

Geometry processing, or mesh processing, is a fast-growing area of research that uses concepts from applied mathematics, computer science, and engineering to design efficient algorithms for the acquisition, reconstruction, analysis, manipulation, simulation, and transmission of complex 3D models. Applications of geometry processing algorithms already cover a wide range of areas from multimedia, entertainment, and classical computer-aided design, to biomedical computing, reverse engineering, and scientific computing.

Over the last several years, triangle meshes have become increasingly popular, as irregular triangle meshes have developed into a valuable alternative to traditional spline surfaces. This book discusses the whole geometry processing pipeline based on triangle meshes. The pipeline starts with data input, for example, a model acquired by 3D scanning techniques. This data can then go through processes of error removal, mesh creation, smoothing, conversion, morphing, and more. The authors detail techniques for those processes using triangle meshes. A supplemental website contains downloads and additional information.

Consumers, public officials, and even managers of health care and insurance are unhappy about care quality, access, and costs. This book shows that is because efforts to do something about these problems often rely on hope or conjecture, not rigorous evidence of effectiveness. In this book, experts in the field separate the speculative from the proven with regard to how care is rendered, how patients can be in control, how providers should be paid, and how disparities can be reduced - and they also identify the issues for which evidence is currently missing. It provides an antidote to frustration and a clear-eyed guide for forward progress, helping health care and insurance innovators make better decisions on deciding whether to go ahead now based on current evidence, to seek and wait for additional evidence, or to move on to different ideas. It will be useful to practitioners in hospital systems, medical groups, and insurance organizations and can also be used in executive and MBA teaching.

Addresses the question of how potential insurance buyers make decisions like these by considering the conceptual and empirical evidence that address the following theoretical and behavioral issues: the extent that consumers tend to follow the multiperiod decision rules based on expected utility [E(U)] maximization; and the factors that influence their choices when they do not behave as if they are maximizing E(U). The principal contribution of this monograph is to demonstrate that emotions play a role in predicting departures from expected utility maximization for making insurance purchasing decisions over time. The authors highlight the conceptual issues and alternative theories of behavior about repeat insurance purchasing over time and the empirical literature on the proportion of consumers that buy coverage after loss-producing events only to cancel their insurance as those events become more distant in time. The monograph then details the findings from novel web-based experiments that seek to determine whether people change their insurance decisions after experiencing a loss when offered a relatively high, medium or low premium relative to the expected loss. Section 2 reviews the empirical evidence on deviations from rational thinking, especially as they relate to choices about repeated purchase over time. It also discusses the interplay between cognitive biases generated by intuitive thinking and emotions in changing insurance purchase decisions over time. Section 3 details an experiment in the context of hypothetical hurricane damage where individuals are told that loss probabilities and premiums remain the same from period to period. Section 4 details an experiment where participants must choose between high-deductible health insurance at a given premium and low-deductible health insurance at a higher premium, and explores whether they will switch from one policy to the other over time. Section 5 draws together the findings, and provides guiding principles of insurance and recommendations for public-private partnerships to address the cognitive biases noted in Section 2 via a behavioral risk audit that encourages more deliberative thinking with respect to insurance-related choices.