Stochastic Frontier Analysis
Stochastic frontier analysis (SFA) is a regression method that scores hospital or health system efficiency, separating inefficiency from random noise.
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Stochastic frontier analysis (SFA) is a regression method that scores hospital or health system efficiency, separating inefficiency from random noise.
Stochastic programming is optimisation that includes parameter uncertainty, used in health care to choose a vaccination policy before outcomes are known.
Stochastic simulation represents a system in which at least one event, transition, time or outcome is generated probabilistically.
A stock and flow model tracks health quantities, such as people with a disease, as stocks that change over time only through inflow and outflow rates.
Stop-loss is insurance that reimburses health claims above an agreed attachment point, limiting what a self-funded employer pays for one member or a group.
Strict dominance in cost-effectiveness analysis is when one option both costs less and gives more health than another, so the other option is ruled out.
A structural equation model (SEM) is a set of linked regression equations, often with latent variables, that tests hypothesised paths to health outcomes.
Structural uncertainty is doubt about how a health economic model represents a decision problem, such as its health states, pathways or extrapolation.
Structural validity of a measurement instrument is how far a health questionnaire's scores reflect the dimensions of the construct it is meant to measure.
Subgroup analysis estimates treatment effects, costs or cost-effectiveness separately for defined groups of patients to test whether they differ.
SUCRA, the surface under the cumulative ranking curve, is a 0 to 1 score of how highly a treatment ranks across all ranks in a network meta-analysis.
The Suits index measures how progressive a tax or health financing source is by comparing cumulative payment shares with cumulative income shares.
The Sullivan method estimates health expectancy, such as healthy life expectancy, by weighting life-table person-years by age-specific health prevalence.
A summary ROC (SROC) curve pools diagnostic accuracy studies to show how a test's sensitivity trades off against specificity across positivity thresholds.
Supplier-induced demand (SID) is use of health care that providers create through their information advantage, beyond what informed patients would choose.
Supply is the amount of a good or service, such as health care, that producers are willing and able to provide at each price over a given period.
A surrogate endpoint is a biomarker or intermediate outcome used in trials and HTA to stand in for and predict a patient-relevant outcome such as survival.
Survival analysis is the statistical study of time to an event such as death when follow-up is incomplete, giving survival curves for economic models.
The survival function, S(t), is the probability that a patient stays alive or free of a defined event beyond time t, used to model life years and QALYs.
Survival regression estimates how treatment and patient characteristics change the hazard of, or time to, death or progression in censored data for HTA.