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Threshold analysis of decision tables.

P Glasziou·J Hilden
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Abstract

When a decision table is used to find a maximum expected utility testing strategy, it is based on a given prior probability distribution of diseases. In the two-disease situation, a threshold analysis over all prior probabilities can be done using threshold transformations of the points of indifference between treatments. This results in a set of prior probability intervals each with its own unique decision rule. The Boolean expression for the table indicates the acceptable testing strategies. A decision table analysis may then be extended to include invasive or costly investigations. The technique represents a saving in time and effort compared with standard decision tree approaches, especially where investigative recommendations are to be made for a broad range of prior probabilities, e.g., where initial symptoms and signs are considered before the investigations.

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Decision TheoryDiagnosisEconomics, MedicalHumansTherapeuticsJournal Article

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P Glasziou, J Hilden. Threshold analysis of decision tables.. https://doi.org/10.1177/0272989x8600600306

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