HealthEconomics.wiki · Interactive explorer

Economic Evaluation Study Design Explorer

Answer a few questions about a study. The explorer will distinguish a full economic evaluation from a partial evaluation and identify the most likely analytical method.

Choose a study to classify

Select a practice case or use the explorer with a study of your own. Read the case, then answer each question using the information provided.

Question 1 of 425% complete
25%

Study design questions

Does the study compare two or more alternatives?

An alternative might be current care, another intervention, no intervention or a clearly defined comparator.

Classification guide

This table provides the same core information without requiring the interactive questions.

DesignAlternativesCostsConsequencesTypical conclusion
Cost-effectiveness analysisTwo or moreYesNatural health unitsFull economic evaluation
Cost-utility analysisTwo or moreYesPreference-based units such as QALYsFull economic evaluation
Cost-benefit analysisTwo or moreYesMonetary benefitsFull economic evaluation
Cost-consequence analysisTwo or moreYesSeveral outcomes presented separatelyFull economic evaluation
Cost-minimisation analysisTwo or moreYesAdequately demonstrated equivalent outcomesFull economic evaluation if equivalence is justified
Cost descriptionOne or noneYesNoPartial economic evaluation
Outcome descriptionOne or noneNoYesPartial economic evaluation
Method and limitations

A full economic evaluation compares at least two alternatives and examines both costs and consequences. The method label also depends on how consequences are measured and reported. This explorer is a study-design classifier, not a substitute for reviewing the complete study protocol, evidence or jurisdiction-specific methodological guidance.

Cost-of-illness studies and budget impact analyses can provide important evidence, but neither alone establishes the comparative value of alternatives. Cost minimisation requires adequate evidence that relevant outcomes are equivalent; similarity should not be assumed merely because no statistically significant difference was observed.