Value of Information for Healthcare Decision-Making introduces the concept of Value of Information (VOI) use in health policy decision-making to determine the sensitivity of decisions to assumptions, and to prioritise and design future research. These methods, and their use in cost-effectiveness analysis, are increasingly acknowledged by health technology assessment authorities as vital. Key Features: Provides a comprehensive overview of VOI Simplifies VOI Showcases state-of-the-art techniques for computing VOI Includes R ...
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Value of Information for Healthcare Decision-Making introduces the concept of Value of Information (VOI) use in health policy decision-making to determine the sensitivity of decisions to assumptions, and to prioritise and design future research. These methods, and their use in cost-effectiveness analysis, are increasingly acknowledged by health technology assessment authorities as vital. Key Features: Provides a comprehensive overview of VOI Simplifies VOI Showcases state-of-the-art techniques for computing VOI Includes R statistical software package Provides results when using VOI methods Uses realistic decision model to illustrate key concepts The primary audience for this book is health economic modellers and researchers, in industry, government, or academia, who wish to perform VOI analysis in health economic evaluations. It is relevant for postgraduate researchers and students in health economics or medical statistics who are required to learn the principles of VOI or undertake VOI analyses in their projects. The overall goal is to improve the understanding of these methods and make them easier to use.
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Add this copy of Value of Information for Healthcare Decision-Making to cart. $136.60, new condition, Sold by Ria Christie Books rated 5.0 out of 5 stars, ships from Uxbridge, MIDDLESEX, UNITED KINGDOM, published 2024 by CRC Press.
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New. Print on demand Sewn binding. Cloth over boards. 292 p. Contains: Unspecified, Illustrations, black & white, Line drawings, black & white, Tables, black & white. Chapman & Hall/CRC Biostatistics.
