Bargaining Theory
Bargaining theory explains how negotiating parties divide the gains from reaching agreement, as when a payer and a manufacturer agree a drug price.
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Bargaining theory explains how negotiating parties divide the gains from reaching agreement, as when a payer and a manufacturer agree a drug price.
A barrier to implementation is a factor, such as cost or staffing, that limits uptake of an effective health intervention, so health gains go unrealised.
Barthel Index (BI) is a ten-item rating of independence in self-care and mobility, scored 0 to 100, used as an outcome in stroke and rehabilitation trials.
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.
Base rate is the standard payment per unit of case weight in prospective hospital payment, adjusted for local costs and multiplied by a stay's DRG weight.
Baseline risk is the probability of an event without the intervention under study; models apply relative treatment effects to it to give absolute benefit.
The basic reproduction number (R0) is the average number of infections one typical case causes in a fully susceptible population, used in vaccine models.
The basket of countries is the set of foreign markets whose drug prices a regulator compares in external reference pricing to set a domestic price.
A basket trial tests one targeted treatment in several diseases, usually tumour types, that share the same biomarker, with each disease forming a basket.
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.
Bayes theorem is the rule that updates a prior probability with new evidence to give a posterior probability, used for diagnostic tests and model inputs.
Bayesian adaptive design is a clinical trial design in which pre-set rules on posterior or predictive probabilities trigger changes such as early stopping.
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.
Bayesian meta-analysis combines prior distributions with results from several studies to give posterior and predictive distributions for an effect.
Bayesian optimisation seeks the inputs that optimise a costly function, such as a model's fit to calibration targets, using a surrogate to pick each run.
Bed capacity is the number of staffed hospital beds immediately available for admitted patients, often reported per 1,000 population as a supply measure.
Bed turnover is the number of discharges, including deaths, per available hospital bed over a period, using the average number of beds available.