PGIM MD Family Medicine key terms

The proportion of people who truly have a disease and are correctly identified as positive by a test. It reflects a test's ability to detect disease when present, and is calculated as true positives divided by all people with the disease.

The proportion of people without a disease who are correctly identified as negative by a test. It reflects how well a test excludes disease, calculated as true negatives divided by all people without the disease. High specificity means few false positives.

The probability that a person with a positive test result actually has the disease. Unlike sensitivity, it depends heavily on disease prevalence in the tested population, so it falls when the condition is rare.

The probability that a person with a negative test result genuinely does not have the disease. It rises as disease prevalence falls, making a negative result more reassuring in low-prevalence populations such as primary care screening settings.

A ratio comparing how likely a given test result is in people with disease versus those without. A positive likelihood ratio above 10 and a negative likelihood ratio below 0.1 substantially shift post-test probability and are useful at the bedside.

The number of patients who must receive an intervention for one additional person to benefit. It is the reciprocal of the absolute risk reduction; smaller values indicate a more clinically worthwhile treatment, though baseline risk matters.

The arithmetic difference in event rates between a control group and a treated group, expressed as a proportion or percentage. It conveys the true clinical impact of an intervention better than relative measures, which can exaggerate small effects.

A range of values, calculated from sample data, within which the true population parameter is expected to lie with a stated probability, usually 95 percent. Width reflects precision; intervals crossing the null value suggest no statistically significant effect.

The probability of observing a result at least as extreme as the one found, assuming the null hypothesis is true. It is not the probability that the null hypothesis is true, and it says nothing about the size or importance of an effect.

Falsely rejecting a true null hypothesis, that is, concluding there is an effect when none exists. Its probability is denoted alpha, conventionally set at 0.05. Multiple comparisons inflate this error unless adjustments are applied.

Failing to reject a false null hypothesis, meaning a real effect is missed. Its probability is beta, and statistical power equals one minus beta. Underpowered studies commonly commit this error and report falsely negative findings.

The proportion of a population that has a condition at a specified point or period in time. It reflects disease burden and strongly influences predictive values of diagnostic tests; chronic and slowly fatal diseases tend to show high prevalence.

The number of new cases of a disease arising in a defined population over a specified period. Incidence measures risk of developing disease and is preferred over prevalence for studying causation and evaluating preventive interventions.

The ratio of the risk of an outcome in an exposed group to the risk in an unexposed group. It is used in cohort studies and trials; a value of 1 indicates no association, above 1 increased risk, below 1 protection.

The ratio of the odds of exposure among cases to the odds among controls, or equivalently the odds of outcome between groups. It approximates relative risk when the outcome is rare and is the standard measure in case-control studies.

An experimental study in which participants are allocated by chance to intervention or control groups. Randomization balances known and unknown confounders, making it the strongest design for establishing causal effects of treatments.

An analysis that includes all randomized participants in the groups to which they were assigned, regardless of adherence or protocol deviations. It preserves randomization benefits and gives a pragmatic estimate of real-world effectiveness.

The process of hiding the upcoming treatment assignment from those enrolling participants, preventing them from influencing group allocation. It differs from blinding and protects against selection bias in randomized trials.

Distortion of the true relationship between an exposure and an outcome by a third variable associated with both. Confounders can create, exaggerate, or mask associations; randomization, restriction, matching, and statistical adjustment address them.

Systematic error arising when the studied groups differ in ways related to both exposure and outcome because of how participants were chosen, enrolled, or retained. It can invalidate comparisons even in large samples.

Testing apparently healthy people to detect unrecognized disease early, aiming to improve outcomes through earlier treatment. It requires a valid test, an accepted treatment, and evidence of benefit; harms include overdiagnosis and false positives.

Apparent improvement in survival after screening solely because disease is detected earlier, lengthening the time between diagnosis and death without actually postponing death. Mortality, not survival from diagnosis, is the appropriate outcome to assess screening benefit.

The tendency of screening to preferentially detect slowly progressive disease, which has a longer detectable preclinical phase and therefore better prognosis. This makes screened patients appear to survive longer even if screening confers no true benefit.

Indirect protection of unvaccinated individuals that arises when a sufficiently high proportion of a population is immune, interrupting chains of transmission. The threshold varies by pathogen and is higher for highly transmissible diseases such as measles.

The proportional reduction in disease risk among vaccinated compared with unvaccinated people, usually measured in a trial. It is calculated as one minus the risk ratio, and is expressed as a percentage.

The uninterrupted series of refrigerated storage and transport steps that keeps vaccines within their required temperature range from manufacture to administration. Breaks in the chain can render vaccines ineffective without any visible change.

A disease that health care providers are legally required to report to public health authorities, enabling surveillance, outbreak investigation, and control measures. Requirements differ by jurisdiction and typically include measles, tuberculosis, and cholera.

A patient's voluntary agreement to a proposed intervention after receiving and understanding information about its nature, benefits, risks, and alternatives, and after confirming the patient's decision-making capacity. It respects autonomy and must be documented appropriately.

A patient's ability to understand relevant information, appreciate the consequences of a decision, reason about options, and communicate a choice. Capacity is decision-specific and assessed clinically, unlike competence, which is a legal status.

The professional duty to protect patient information from unauthorized disclosure, except where law permits or requires sharing, such as with consent, for notifiable diseases, or when there is serious risk to others.

A clinical judgment that an intervention cannot achieve its intended physiologic goal or meaningful benefit for the patient. Futility discussions support appropriate limitation of treatment, though the concept is ethically contested and should be applied cautiously.

The process of distributing limited health care resources among competing needs, guided by criteria such as clinical need, cost-effectiveness, and equity. In primary care, gatekeeping and priority setting are common practical expressions of allocation decisions.

An economic evaluation comparing the costs of alternative interventions with their health outcomes, often expressed as cost per life-year or quality-adjusted life-year gained. It helps decision-makers compare value across different programs.

A composite measure combining length of life with health-related quality of life, where one year in perfect health equals 1.0 and death equals 0. It is widely used to compare the value of interventions across conditions.

The principle of distributing health resources fairly according to need rather than equally, so that disadvantaged groups receive proportionally more support to achieve comparable outcomes. It differs from equality, which means identical treatment.

A set of standard criteria, such as clinical features, time, place, and laboratory confirmation, used to classify whether a person has a particular disease for surveillance or outbreak investigation. Consistent case definitions allow valid comparison across settings and time.

A structured synthesis of all relevant studies addressing a focused question, using explicit search, selection, and appraisal methods to minimize bias. When statistically pooled, it becomes a meta-analysis and sits near the top of evidence hierarchies.

The statistical combination of results from multiple studies to produce a pooled estimate of effect. It increases precision but can be misleading if included studies are heterogeneous, biased, or selectively published.

The tendency for studies with positive or statistically significant results to be published more often and faster than negative ones. It distorts pooled estimates in systematic reviews and is assessed using funnel plots and related tests.