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Decision Making in Health and Medicine
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  • Cited by 43
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    This book has been cited by the following publications. This list is generated based on data provided by CrossRef.

    He, Kai Maillart, Lisa M. and Prokopyev, Oleg A. 2018. Optimal sequencing of heterogeneous, non-instantaneous interventions. Annals of Operations Research,

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    Engel, Connie L. Rasanayagam, M. Sharima Gray, Janet M. and Rizzo, Jeanne 2018. Work and Breast Cancer: Recommendations to Address Research Needs. NEW SOLUTIONS: A Journal of Environmental and Occupational Health Policy, Vol. 28, Issue. 1, p. 79.

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    Graves, Nicholas Barnett, Adrian G. Burn, Edward and Cook, David 2018. Smaller clinical trials for decision making; using p-values could be costly. F1000Research, Vol. 7, Issue. , p. 1176.

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    Kappen, Teus H. van Klei, Wilton A. van Wolfswinkel, Leo Kalkman, Cor J. Vergouwe, Yvonne and Moons, Karel G. M. 2018. Evaluating the impact of prediction models: lessons learned, challenges, and recommendations. Diagnostic and Prognostic Research, Vol. 2, Issue. 1,

    Odmell, Chipungu Mamimine, Patrick Walter Kudakwashe, Chitindingu and Coetzee, Willem 2018. A situational analysis of health tourism for appropriation of indigenous herbal sexual stimulants and fertility enhancers in Zimbabwe: A situational analysis paper. Cogent Social Sciences, Vol. 4, Issue. 1,

    Soklaridis, Sophie Bernard, Carrie Ferguson, Genevieve Andermann, Lisa Fefergrad, Mark Fung, Kenneth Iglar, Karl Johnson, Andrew Paton, Morag Whitehead, Cynthia and Laws, M Barton 2018. Understanding health advocacy in family medicine and psychiatry curricula and practice: A qualitative study. PLOS ONE, Vol. 13, Issue. 5, p. e0197590.

    Yet, Barbaros Constantinou, Anthony Fenton, Norman and Neil, Martin 2018. Expected Value of Partial Perfect Information in Hybrid Models Using Dynamic Discretization. IEEE Access, Vol. 6, Issue. , p. 7802.

    Krijkamp, Eline M. Alarid-Escudero, Fernando Enns, Eva A. Jalal, Hawre J. Hunink, M. G. Myriam and Pechlivanoglou, Petros 2018. Microsimulation Modeling for Health Decision Sciences Using R: A Tutorial. Medical Decision Making, Vol. 38, Issue. 3, p. 400.

    Hong, Traci and Beaudoin, Christopher E. 2018. A Behavioral Function Approach in Predicting Contribution of User-Generated Content. Communication Research, Vol. 45, Issue. 5, p. 764.

    Negoescu, Diana M. Bimpikis, Kostas Brandeau, Margaret L. and Iancu, Dan A. 2018. Dynamic Learning of Patient Response Types: An Application to Treating Chronic Diseases. Management Science, Vol. 64, Issue. 8, p. 3469.

    Lughofer, Edwin 2018. Human and Machine Learning. p. 177.

    Bhise, Viraj Rajan, Suja S. Sittig, Dean F. Morgan, Robert O. Chaudhary, Pooja and Singh, Hardeep 2018. Defining and Measuring Diagnostic Uncertainty in Medicine: A Systematic Review. Journal of General Internal Medicine, Vol. 33, Issue. 1, p. 103.

    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.

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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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