Expected Value Analysis
Expected value analysis compares health care options under uncertainty by their probability-weighted average outcomes, such as expected costs and QALYs.
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Explore comprehensive, evidence-informed explanations of key health economics concepts, including their development, application and relationships to other concepts. Published entries are validated through human expert review.
Concepts, entries and ontology terms
A concept page is a published entry on the wiki. Some concepts also have a full encyclopaedia article. The Health Economics Ontology (HEO) holds every concept, including dictionary terms without an article, so it is larger than the list of published pages. The knowledge graph shows how concepts relate to each other.
Expected Value Criterion
The expected value criterion is a decision rule that chooses the option with the highest probability-weighted mean outcome, such as expected net benefit.
Expected Value of Partial Perfect Information
Expected value of partial perfect information (EVPPI) is the expected gain in net benefit from knowing selected model parameters exactly before deciding.
Expected Value of Perfect Information
Expected value of perfect information (EVPI) is the expected gain from removing all uncertainty in a funding decision, the upper limit on research value.
Expected Value of Sample Information
Expected value of sample information (EVSI) is the expected net benefit gained by deciding after a specific proposed study reports instead of deciding now.
Experience Rating
Experience rating sets health insurance premiums from the insured group's or person's own past claims, so buyers with costlier claims histories pay more.
Experimental Design
Experimental design is the planning of how a trial or choice experiment assigns interventions or attributes so their effects can be estimated without bias.
Explanatory Trial
An explanatory trial is a randomised trial run under ideal, tightly controlled conditions to test whether a treatment can work, so it measures efficacy.
Exploratory Factor Analysis
Exploratory factor analysis is a latent-variable method that examines whether correlations among observed variables can be represented by a smaller, initially unspecified set of common factors.
Exponential Distribution
The exponential distribution models time to an event under a constant hazard, used for survival curves and simulated event times in health economic models.
Exponential Model
A survival model assuming time-to-event data follow an exponential distribution, implying a constant hazard rate throughout the modelled time horizon.
Extended Cost-Effectiveness
Extended cost-effectiveness analysis (ECEA) is an economic evaluation that reports a policy's health gains, financial protection and costs by income group.
Extended Dominance
Extended dominance excludes an option in cost-effectiveness analysis when a blend of a less and a more effective option gives its health gain for less.
External Reference Pricing
A medicine-pricing policy that uses prices for the same or comparable product in other jurisdictions as benchmarks for a domestic price or reimbursement decision.
Externality
An externality is a cost or benefit, such as antimicrobial resistance or herd immunity, that falls on third parties and is ignored by the person deciding.
Extra-Welfarism
Extra-welfarism is a branch of welfare economics that judges health policies by outcomes such as health or capability, not by individual utility alone.
Extrapolation
Extrapolation is the projection of survival, treatment effects or costs beyond trial follow-up so an economic model can estimate lifetime outcomes.
F-Distribution
The F distribution describes the ratio of two independent variance estimates and underlies F tests on cost and outcome regressions in health economics.
FACT-G
FACT-G is a 27-item cancer quality of life questionnaire used as a trial outcome, whose scores need mapping or the FACT-8D before they can inform QALYs.
Factor Analysis
Factor analysis explains correlations among observed variables using a smaller number of unobserved latent factors.