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Decision Making in Health and Medicine
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  • Cited by 29
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    This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Melo, Marcio Gusso, Gustavo D. F. Levites, Marcelo Amaro, Edson Massad, Eduardo Lotufo, Paulo A. Zeidman, Peter Price, Cathy J. and Friston, Karl J. 2017. How doctors diagnose diseases and prescribe treatments: an fMRI study of diagnostic salience. Scientific Reports, Vol. 7, Issue. 1,


    Clark, Claire D. Langkjaer, Staci Chinikamwala, Sara Joseph, Heather Semaan, Salaam Clement, Jillian Marshall, Rebekah Pevzner, Eric Truman, Benedict I. and Kroeger, Karen 2017. Providers’ Perspectives on Program Collaboration and Service Integration for Persons Who Use Drugs. The Journal of Behavioral Health Services & Research, Vol. 44, Issue. 1, p. 158.


    Shrime, Mark G. Alkire, Blake C. Grimes, Caris Chao, Tiffany E. Poenaru, Dan and Verguet, Stéphane 2017. Cost-Effectiveness in Global Surgery: Pearls, Pitfalls, and a Checklist. World Journal of Surgery, Vol. 41, Issue. 6, p. 1401.


    Barocas, Joshua A. and Linas, Benjamin P. 2017. Editorial Commentary: Decision Science at Work: The Case of Hepatitis C Virus Postexposure Prophylaxis. Clinical Infectious Diseases, Vol. 64, Issue. 1, p. 100.


    Royce, Trevor J. Punglia, Rinaa S. Chen, Aileen B. Patel, Sagar A. Thornton, Katherine A. Raut, Chandrajit P. and Baldini, Elizabeth H. 2017. Cost–Effectiveness of Surveillance for Distant Recurrence in Extremity Soft Tissue Sarcoma. Annals of Surgical Oncology, Vol. 24, Issue. 11, p. 3264.


    Bolbocean, Corneliu Robinson, Chessie Fleming, Neil and Hostin, Richard 2017. Adult Lumbar Scoliosis. p. 267.

    Luxardo, Natalia and Manzelli, Hernán 2017. Blurred logics behind frontline staff decision-making for cancer control in Argentina. Health Sociology Review, Vol. 26, Issue. 3, p. 224.


    Anderson, Barry F. and Misuraca, Raffaella 2017. Perceptual commensuration in decision tables. The Quarterly Journal of Experimental Psychology, Vol. 70, Issue. 3, p. 544.


    Demissie, Gizachew Tesfamariam, Solomon and Sadiq, Rehan 2017. Prediction of Pipe Failure by Considering Time-Dependent Factors: Dynamic Bayesian Belief Network Model. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, Vol. 3, Issue. 4, p. 04017017.


    Thall, Peter F. Nguyen, Hoang Q. and Zinner, Ralph G. 2017. Parametric dose standardization for optimizing two-agent combinations in a phase I-II trial with ordinal outcomes. Journal of the Royal Statistical Society: Series C (Applied Statistics), Vol. 66, Issue. 1, p. 201.


    Decroo, Tom Henríquez-Trujillo, Aquiles R. De Weggheleire, Anja and Lynen, Lutgarde 2017. Rational use of Xpert testing in patients with presumptive TB: clinicians should be encouraged to use the test-treat threshold. BMC Infectious Diseases, Vol. 17, Issue. 1,


    Negoescu, Diana M. Bimpikis, Kostas Brandeau, Margaret L. and Iancu, Dan A. 2017. Dynamic Learning of Patient Response Types: An Application to Treating Chronic Diseases. Management Science,


    Chen, Jack 2017. Textbook of Rapid Response Systems. p. 341.

    Bhise, Viraj Rajan, Suja S. Sittig, Dean F. Morgan, Robert O. Chaudhary, Pooja and Singh, Hardeep 2017. Defining and Measuring Diagnostic Uncertainty in Medicine: A Systematic Review. Journal of General Internal Medicine,


    Carroll, Noel and Richardson, Ita 2016. Software-as-a-Medical Device: demystifying Connected Health regulations. Journal of Systems and Information Technology, Vol. 18, Issue. 2, p. 186.


    Suen, Sze-chuan and Goldhaber-Fiebert, Jeremy D. 2016. An Efficient, Noniterative Method of Identifying the Cost-Effectiveness Frontier. Medical Decision Making, Vol. 36, Issue. 1, p. 132.


    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.


    van den Houten, M. M. L. Lauret, G. J. Fakhry, F. Fokkenrood, H. J. P. van Asselt, A. D. I. Hunink, M. G. M. and Teijink, J. A. W. 2016. Cost-effectiveness of supervised exercise therapy compared with endovascular revascularization for intermittent claudication. British Journal of Surgery, Vol. 103, Issue. 12, p. 1616.


    Khan, Arshia and Madden, Janna 2016. Mobile Devices as a Resource in Gathering Health Data: The Role of Mobile Devices in the Improvement of Global Health. p. 1010.

    Hobbs, Brian P. Thall, Peter F. and Lin, Steven H. 2016. Bayesian group sequential clinical trial design using total toxicity burden and progression-free survival. Journal of the Royal Statistical Society: Series C (Applied Statistics), Vol. 65, Issue. 2, p. 273.


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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.

Reviews

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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