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Decision Making in Health and Medicine
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    Anderson, Barry F. and Misuraca, Raffaella 2016. Perceptual commensuration in decision tables. The Quarterly Journal of Experimental Psychology, p. 1.

    Anthony, Kathryn E. and Sellnow, Timothy L. 2016. The Role of the Message Convergence Framework in Medical Decision Making. Journal of Health Communication, Vol. 21, Issue. 2, p. 249.

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    Wittenberg, Eve Bray, Jeremy W. Aden, Brandon Gebremariam, Achamyeleh Nosyk, Bohdan and Schackman, Bruce R. 2016. Measuring benefits of opioid misuse treatment for economic evaluation: health-related quality of life of opioid-dependent individuals and their spouses as assessed by a sample of the US population. Addiction, Vol. 111, Issue. 4, p. 675.

    McMeekin, Peter Flynn, Darren Ford, Gary A. Rodgers, Helen Gray, Jo and Thomson, Richard G. 2015. Development of a decision analytic model to support decision making and risk communication about thrombolytic treatment. BMC Medical Informatics and Decision Making, Vol. 15, Issue. 1,

    Molin, Adam Ramesh, Chithrupa Esen, Hasan and Johansson, Karl Henrik 2015. 2015 54th IEEE Conference on Decision and Control (CDC). p. 4163.

    Mushlin, Alvin I 2015. To (genetic) test or not to test, that is the question. Journal of Comparative Effectiveness Research, Vol. 4, Issue. 5, p. 429.

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    Elstein, Arthur S. 2001. Naturalistic decision making and clinical judgment. Journal of Behavioral Decision Making, Vol. 14, Issue. 5, p. 363.


Book description

Decision making in health care involves consideration of a complex set of diagnostic, therapeutic and prognostic uncertainties. Medical therapies have side effects, surgical interventions may lead to complications, and diagnostic tests can produce misleading results. Furthermore, patient values and service costs must be considered. Decisions in clinical and health policy require careful weighing of risks and benefits and are commonly a trade-off of competing objectives: maximizing quality of life vs maximizing life expectancy vs minimizing the resources required. This text takes a proactive, systematic and rational approach to medical decision making. It covers decision trees, Bayesian revision, receiver operating characteristic curves, and cost-effectiveness analysis, as well as advanced topics such as Markov models, microsimulation, probabilistic sensitivity analysis and value of information analysis. It provides an essential resource for trainees and researchers involved in medical decision modelling, evidence-based medicine, clinical epidemiology, comparative effectiveness, public health, health economics, and health technology assessment.


Review of previous edition:‘This is an impressively comprehensive approach to clinical decision-making with every angle considered, advantages and disadvantages tabulated … there is a great deal of knowledge and information in these chapters, presented with masses of detailed mathematical and statistical analysis.'

Source: Journal of the Royal Society of Medicine

Review of previous edition:‘… once I started to read the book, I was gripped. It is very readable, making a complex subject appear crystal clear and easy to understand … this book is a very useful addition to the literature on evidence-based health care, providing clear strategies for incorporating decision analysis into our daily decision making.'

Source: Family Practice

Review of previous edition:‘This book would be a useful acquisition for a statistician who needs the basics of decision-making, and it would certainly be a good book for a non-statistician.'

Source: Pharmaceutical Statistics

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