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This textbook offers a comprehensive analysis of medical decision making under uncertainty by combining Test Information Theory with Expected Utility Theory. The book shows how the parameters of Bayes’ theorem can be combined with a value function of health states to arrive at informed test and treatment decisions. The authors distinguish between risk-neutral, risk-averse and prudent decision makers and demonstrate the effects of risk preferences on physicians’ decisions. They analyze individual tests, multiple tests and endogenous tests where the test outcome is chosen by the decision maker. Moreover, the topic is examined in the context of health economics by introducing a trade-off between enjoying health and consuming other goods, so that the extent of treatment and thus the potential improvement in the patient’s health becomes endogenous. Finally, non-expected utility models of choice under risk and uncertainty (i.e. ambiguity) are presented. While these models can explain observed test and treatment decisions, they are not suitable for normative analyses aimed at providing guidance on medical decision making.

This book presents an innovative framework for enhancing creativity in decision-making by applying systems thinking principles and tools. It is based on the premise that creativity is not a fixed trait that some people have and others don't, but a skill that can be learned and improved with practice and guidance. The book also argues that decision-making is not a linear or mechanical process that can be reduced to simple rules or formulas, but a dynamic and creative process that requires holistic and systemic thinking.

The 21st century promises to be an era dominated by international response to c- tain global environmental challenges such as climate change, depleting biodiversity and biocapacity as well as general atmospheric, water and soil pollution problems.

This book develops a general theory of managerial decision making on the basis of a few elementary postulates. It employs logic as the method of reasoning, systems science in general and the systemic YoYo Model in particular, as the intuitive playground. By doing so, the authors take individually background-based guesswork out of processes of decision making. All established conclusions are expected to be generally employable in real-life applications. At the same time, the book is user friendly to a wide range of audience, coincides with people's intuition, and provides applicable results and insights for practical purposes.

This textbook offers a comprehensive theory of medical decision making under uncertainty, combining informative test theory with the expected utility hypothesis. The book shows how the parameters of Bayes’ theorem can be combined with a value function of health states to arrive at informed test and treatment decisions.