INTRODUCTION
TEACHING TIP 1: UNDERSTANDING THE STRUCTURE OF A DECISION TREE
When to use this Tip
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Understand the components that make up a decision tree
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Learn how to identify the optimal choice through calculations of probabilities of events and their outcome after constructing a decision tree
Preparing to Teach
Outcomes | Probability |
---|---|
Probability of foot saved using antibiotics | 0.50 |
Probability of full recovery after foot saved | 0.80 |
Probability of recovery with limp after foot saved using antibiotics | 0.20 |
Probability of death after infection is not controlled by antibiotics | 0.10 |
Probability of above the knee amputation if infection not controlled by antibiotics | 0.80 |
Probability of below the knee amputation if infection not controlled by antibiotics | 0.10 |
Probability of survival after immediate below knee amputation | 1.00 |
Possible outcome | Utility* |
---|---|
Recovery with a limp | 0.98† |
Recovery with foot amputation | 0.70 |
Recovery with leg amputation | 0.60† |
Entire limb saved and no limp | 1.00 (assumed) |
Death | 0.00 (assumed) |
The Script
The Bottom Line
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Decision analysis may be used to help patients objectify their own values and preferences in the context of complex decision making.
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The analysis begins by identifying the important choices available to the patient.
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Stumbling block: Understanding how the decision tree is folded back to arrive at the best alternative.
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The analysis of the completed decision tree moves from right to left as partial utilities are developed for each chance node.
TEACHING TIP 2: UNDERSTANDING SENSITIVITY ANALYSIS
When to use this Tip
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Understand how uncertainty regarding the estimates used in a decision tree can be addressed.
The script
Additional Comments
The Bottom Line
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A sensitivity analysis is the process of repeatedly folding back the decision tree using different values for probabilities and value consequences to test of the stability of the decision tree result.