Biomedical Decision Making: Probabilistic Clinical Reasoning

Chapter

Abstract

After reading this chapter, you should know the answers to these questions:
  • How is the concept of probability useful for understanding test results and for making medical decisions that involve uncertainty?

  • How can we characterize the ability of a test to discriminate between disease and health?

  • What information do we need to interpret test results accurately?

  • What is expected-value decision making? How can this methodology help us to understand particular medical problems?

  • What are utilities, and how can we use them to represent patients’ preferences?

  • What is a sensitivity analysis? How can we use it to examine the robustness of a decision and to identify the important variables in a decision?

  • What are influence diagrams? How do they differ from decision trees?

Keywords

Cholesterol Arthritis Pneumonia Expense Stein 

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Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  1. 1.VA Palo Alto Health Care SystemPalo AltoUSA
  2. 2.Henry J. Kaiser Center for Primary Care and Outcomes Research/Center for Health PolicyStanford UniversityStanfordUSA
  3. 3.Dartmouth InstituteGeisel School of Medicine at Dartmouth, Dartmouth CollegeWest LebanonUSA

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