Prospective Risk Adjustment
Prospective risk adjustment adjusts health plan or provider payments for a coming period using diagnoses and demographics from an earlier base period.
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Prospective risk adjustment adjusts health plan or provider payments for a coming period using diagnoses and demographics from an earlier base period.
Provider payment is how health purchasers pay doctors and hospitals, for example by budget, salary, fee-for-service, per diem, case (DRG) or capitation.
A pseudo-random number is a value produced by a deterministic algorithm whose sequence is designed to exhibit specified statistical properties of random draws.
The process of computing quality-adjusted life years by multiplying time spent in a health state by its utility value, then summing across states.
QALY shortfall is the expected QALY gap between a matched general population and patients on current care, which NICE reads as absolute or proportional.
Quality of care is the extent to which health services raise the chance of desired health outcomes and follow current professional knowledge.
Quality of evidence is a judgement, rated high to very low in GRADE, of how far a review, guideline or HTA can trust that an effect estimate is correct.
A quality score is a single number summing checklist items to rate a study's methodological quality, now discouraged in favour of risk of bias judgements.
A quality-adjusted life year (QALY) combines length and quality of life in one measure: a year in full health counts as one QALY and death counts as zero.
Quality-adjusted time without symptoms (Q-TWiST) sums cancer survival time with toxicity, free of symptoms and after relapse, each weighted for quality.
A quasi-experimental design estimates the causal effect of a health policy or treatment without randomisation, using a comparison group or period instead.
A queuing model is a mathematical representation of how arrivals, service times, capacity, and service rules generate waiting, congestion, and throughput in a service system.
A random effects model is a meta-analysis model that lets true treatment effects differ between trials and estimates their mean and between-study variance.
Random number generation supplies the uncertain draws used in probabilistic sensitivity analysis, microsimulation, discrete-event simulation, bootstrap procedures, and other stochastic analyses.
A random parameter model, or mixed logit, is a discrete choice model in which preference weights vary across people, estimated as a mean and a spread.
Random sampling selects members of a population by chance, giving each a known, non-zero probability of selection, so sample estimates can be generalised.
A randomised controlled trial (RCT) is a study that assigns people to an intervention or comparator by chance, HTA's preferred source of relative effects.
Randomisation assigns participants to treatments by chance, balancing known and unknown prognostic factors on average so effects used in HTA are unbiased.
Rate-to-probability conversion turns an event rate, such as deaths per person-year, into the probability of the event within one cycle of a Markov model.
Ratio scale is a level of measurement with equal intervals and a true zero, such as cost or survival time, so a claim of twice the cost is meaningful.