Patient Care under Uncertainty

Princeton University Press
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How cutting-edge economics can improve decision-making methods for doctors

Although uncertainty is a common element of patient care, it has largely been overlooked in research on evidence-based medicine. Patient Care under Uncertainty strives to correct this glaring omission. Applying the tools of economics to medical decision making, Charles Manski shows how uncertainty influences every stage, from risk analysis to treatment, and how this can be reasonably confronted.

In the language of econometrics, uncertainty refers to the inadequacy of available evidence and knowledge to yield accurate information on outcomes. In the context of health care, a common example is a choice between periodic surveillance or aggressive treatment of patients at risk for a potential disease, such as women prone to breast cancer. While these choices make use of data analysis, Manski demonstrates how statistical imprecision and identification problems often undermine clinical research and practice. Reviewing prevailing practices in contemporary medicine, he discusses the controversy regarding whether clinicians should adhere to evidence-based guidelines or exercise their own judgment. He also critiques the wishful extrapolation of research findings from randomized trials to clinical practice. Exploring ways to make more sensible judgments with available data, to credibly use evidence, and to better train clinicians, Manski helps practitioners and patients face uncertainties honestly. He concludes by examining patient care from a public health perspective and the management of uncertainty in drug approvals.

Rigorously interrogating current practices in medicine, Patient Care under Uncertainty explains why predictability in the field has been limited and furnishes criteria for more cogent steps forward.

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About the author

Charles F. Manski is Board of Trustees Professor of Economics at Northwestern University and a member of the National Academy of Sciences. His books include Public Policy in an Uncertain World, Identification for Prediction and Decision, and Social Choice with Partial Knowledge of Treatment Response (Princeton).
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Additional Information

Publisher
Princeton University Press
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Published on
Sep 10, 2019
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Pages
184
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ISBN
9780691195360
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Language
English
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Genres
Business & Economics / Econometrics
Business & Economics / Insurance / Health
Health & Fitness / Health Care Issues
Medical / Health Care Delivery
Medical / Health Policy
Medical / Public Health
Political Science / Public Policy / General
Political Science / Public Policy / Social Services & Welfare
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Content Protection
This content is DRM protected.
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Eligible for Family Library

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From a giant of health care policy, an engaging and enlightening account of why American health care is so expensive—and why it doesn't have to be

Uwe Reinhardt was a towering figure and moral conscience of health care policy in the United States and beyond. Famously bipartisan, he advised presidents and Congress on health reform and originated central features of the Affordable Care Act. In Priced Out, Reinhardt offers an engaging and enlightening account of today's U.S. health care system, explaining why it costs so much more and delivers so much less than the systems of every other advanced country, why this situation is morally indefensible, and how we might improve it.

The problem, Reinhardt says, is not one of economics but of social ethics. There is no American political consensus on a fundamental question other countries settled long ago: to what extent should we be our brothers' and sisters' keepers when it comes to health care? Drawing on the best evidence, he guides readers through the chaotic, secretive, and inefficient way America finances health care, and he offers a penetrating ethical analysis of recent reform proposals. At this point, he argues, the United States appears to have three stark choices: the government can make the rich help pay for the health care of the poor, ration care by income, or control costs. Reinhardt proposes an alternative path: that by age 26 all Americans must choose either to join an insurance arrangement with community-rated premiums, or take a chance on being uninsured or relying on a health insurance market that charges premiums based on health status.

An incisive look at the American health care system, Priced Out dispels the confusion, ignorance, myths, and misinformation that hinder effective reform.

Sample data alone never suffice to draw conclusions about populations. Inference always requires assumptions about the population and sampling process. Statistical theory has revealed much about how strength of assumptions affects the precision of point estimates, but has had much less to say about how it affects the identification of population parameters. Indeed, it has been commonplace to think of identification as a binary event - a parameter is either identified or not - and to view point identification as a pre-condition for inference. Yet there is enormous scope for fruitful inference using data and assumptions that partially identify population parameters. This book explains why and shows how. The book presents in a rigorous and thorough manner the main elements of Charles Manski's research on partial identification of probability distributions. One focus is prediction with missing outcome or covariate data. Another is decomposition of finite mixtures, with application to the analysis of contaminated sampling and ecological inference. A third major focus is the analysis of treatment response. Whatever the particular subject under study, the presentation follows a common path. The author first specifies the sampling process generating the available data and asks what may be learned about population parameters using the empirical evidence alone. He then ask how the (typically) setvalued identification regions for these parameters shrink if various assumptions are imposed. The approach to inference that runs throughout the book is deliberately conservative and thoroughly nonparametric. Conservative nonparametric analysis enables researchers to learn from the available data without imposing untenable assumptions. It enables establishment of a domain of consensus among researchers who may hold disparate beliefs about what assumptions are appropriate. Charles F. Manski is Board of Trustees Professor at Northwestern University. He is author of Identification Problems in the Social Sciences and Analog Estimation Methods in Econometrics. He is a Fellow of the American Academy of Arts and Sciences, the American Association for the Advancement of Science, and the Econometric Society.
A New York Times bestseller/Washington Post Notable Book of 2017/NPR Best Books of 2017/Wall Street Journal Best Books of 2017 

"This book will serve as the definitive guide to the past and future of health care in America.”—Siddhartha Mukherjee, Pulitzer Prize-winning author of The Emperor of All Maladies and The Gene  

At a moment of drastic political upheaval, An American Sickness is a shocking investigation into our dysfunctional healthcare system - and offers practical solutions to its myriad problems.

In these troubled times, perhaps no institution has unraveled more quickly and more completely than American medicine. In only a few decades, the medical system has been overrun by organizations seeking to exploit for profit the trust that vulnerable and sick Americans place in their healthcare. Our politicians have proven themselves either unwilling or incapable of reining in the increasingly outrageous costs faced by patients, and market-based solutions only seem to funnel larger and larger sums of our money into the hands of corporations. Impossibly high insurance premiums and inexplicably large bills have become facts of life; fatalism has set in. Very quickly Americans have been made to accept paying more for less. How did things get so bad so fast?

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