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Tools for Decision Making Sections
Author Bio
Introduction
Part I
Expected Value Decision Making
Case Study 2: Patient History
Currently selected section: Using a Decision Tree
Assigning Utility
Expected Value and QALYs
Sensitivity Analysis
Conclusions: Case Study 2
Part III

References


Chapter 14: Tools for Decision Making: Using a Decision Tree
        

The first step is to represent the problem by a decision tree. There are three key symbols in a decision tree:

  • A box represents a decision node. Lines from the box denote the decision alternatives (one line per decision alternative). The name of the decision alternative goes above the line.

  • A circle represents a chance node. Lines from the circle denote the events that could occur at the chance node. The name of the chance-driven event goes above the line. The probability of the event goes below the line. Since all probabilities at a chance node must sum to 1.0, one event is labeled simply as #, to denote "1 - the sum of the probabilities of the other events."

  • A horizontal rectangle represents a terminal node. A terminal node represents an outcome state, so there are no events that occur distal to a terminal node. The value of the outcome appears in the rectangle.


Below is a very simple decision tree for medical versus surgical treatment.

Figure 2.3.1: Simple Decision Tree for Medical Versus Surgical Treatment
Graphic depiction of simple decision tree for medical versus surgical treatment where the first decision is surgery or medication. For the medication choice, life expectancy equals 5. For the surgery choice, the options are either: OK where life expectancy equals 10; or die, where the life expectancy equals 0.  The number symbol is under OK on the surgery decision path. The value of the probability represented by # is 1 minus the sum of the probabilities of the other events at the chance node. In this case, it is 1 minus 0.05 or 0.95.

Question 2.3.1

What is the probability represented by the symbol #?

Selection AThe sum of the life expectancies (LE) of each outcome at the chance node, divided by the number of outcomes at that chance node
Selection B1 plus the sum of the probabilities of the other events at the chance node
Selection C1 minus the sum of the probabilities of the other events at the chance node


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