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Tools for Decision Making Sections
Author Bio
Introduction
Probability Theory
Case Study 1: Patient History
Bayes' Theorem
Methods for Estimating Pre-test Probability
Estimating Likelihood Ratios
Sensitivity and Specificity
Interpreting Test Results
Calculating Post-test Probabilities
Post-test Probabilities in Clinical Practice
Currently selected section: Conclusions: Case Study 1
Part II
Part III
References


Chapter 14: Tools for Decision Making: Conclusions - Case Study 1
        

This case study began as an examination of how to express certainty and uncertainty of a diagnosis. Think back to your original estimate of the probability that the case study patient's symptoms were due to myocardial ischemia.

Now, considering the heuristics of subjective estimates, the usefulness and limitations of disease prevalence estimates, and the application and interpretation of clinical prediction rule scores, what do you feel is gained by framing this diagnostic problem in terms of probability?

The author suggests these benefits:

  • We gain respect for the imperfections of tests, since neither examined in this case study leads to diagnostic certainty for this patient.

  • We make a rational decision to get a somewhat more expensive test because we have proved to ourselves that it would be more useful.





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