A set of health states, or events, and the probabilities of transitioning from one state to others during a specified period of time (“transition probabilities”) are the fundamental building blocks of decision models. These are often not available in the published literature in a format directly suitable for use in decision models.

Procedures for estimating transition probabilities from published evidence, including deriving probabilities from other types of summary statistics and modifying the time frame to which a probability applies, have been discussed in disparate places in the literature.

This tutorial article aggregates this information in one location, to serve as a stand-alone resource for the decision modeler. The information is meant to assist decision modelers in the practical tasks of building high-quality decision models.