Arrow's Impossibility Theorem
Arrow's impossibility theorem is a welfare economics theorem proving no rule can pool rankings of three or more health options and meet five basic tests.
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.
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Arrow's impossibility theorem is a welfare economics theorem proving no rule can pool rankings of three or more health options and meet five basic tests.
Assumption structure is the full set of simplifying assumptions in a health economic model's design, such as its health states, events and extrapolation.
Asymptotic normality means an estimator's sampling distribution is approximately normal in large samples, the basis of Wald confidence intervals.
The Atkinson index measures inequality in health or income using a social welfare function with an explicit inequality aversion parameter, epsilon.
Attributable cost estimation measures the extra healthcare cost a disease or risk factor causes, against what the same patients would cost without it.
Auction theory in health economics studies how bidding rules in tenders set the price and supply of medicines, vaccines and medical equipment.
Autoregressive correlation is a structure for repeated measures in which correlation falls by a constant factor with each time step between measurements.
Available case analysis is a missing data method estimating each quantity from everyone with data for it, so costs and QALYs may use different patients.
Average cost is total cost divided by the number of units produced, such as patients treated or bed days, giving the cost per unit of a health service.
The average cost-effectiveness ratio (ACER) is an option's cost per unit of health effect, in total or against doing nothing, without comparing options.
Avoidable cost is the cost a budget holder would no longer pay if a health service stopped or a disease was prevented, within a stated time period.
Background mortality is the death rate a model's patients would face without the disease, usually taken from general population life tables by age and sex.
Bargaining theory explains how negotiating parties divide the gains from reaching agreement, as when a payer and a manufacturer agree a drug price.
The base case is a model's preferred set of inputs and assumptions and the primary results they produce, against which sensitivity analyses are compared.
Baseline risk is the probability of an event without the intervention under study; models apply relative treatment effects to it to give absolute benefit.
A bathtub hazard is a U-shaped hazard that is high soon after an event such as surgery, falls to a lower stable level, then rises again as patients age.
The Baumol effect is the rising relative cost of labour-intensive services such as health care as their pay tracks faster productivity growth elsewhere.
Bayesian analysis updates a prior distribution with data via Bayes' theorem to give a posterior, used in HTA for evidence synthesis and decision models.
Bayesian cost-effectiveness analysis updates prior evidence on costs and health effects with new data to estimate net benefit and decision uncertainty.
Bayesian information criterion (BIC) ranks models fitted to the same data, such as HTA survival curves, by fit with a penalty that grows with sample size.