statistics Statistics (from German: '' Statistik'', "description of a state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, indust ...

, verification bias is a type of measurement

bias Bias is a disproportionate weight ''in favor of'' or ''against'' an idea or thing, usually in a way that is closed-minded, prejudicial, or unfair. Biases can be innate or learned. People may develop biases for or against an individual, a group ...

in which the results of a diagnostic test affect whether the

gold standard A gold standard is a monetary system in which the standard economic unit of account is based on a fixed quantity of gold. The gold standard was the basis for the international monetary system from the 1870s to the early 1920s, and from th ...

procedure is used to verify the test result. This type of bias is also known as "work-up bias" or "referral bias". In clinical practice, verification bias is more likely to occur when a preliminary diagnostic test is negative. Because many gold standard tests can be invasive, expensive, and carry a higher risk (e.g. angiography, biopsy, surgery), patients and physicians may be more reluctant to undergo further work-up if a preliminary test is negative. In

cohort studies A cohort study is a particular form of longitudinal study that samples a cohort (a group of people who share a defining characteristic, typically those who experienced a common event in a selected period, such as birth or graduation), performing ...

, obtaining a gold standard test on every patient may not always be ethical, practical, or cost effective. These studies can thus be subjected to verification bias. One method to limit verification bias in clinical studies is to perform gold standard testing in a random sample of study participants. In most situations, verification bias introduces a sensitivity estimate that is too high and a specificity that is too low.

References

{{Biases Epidemiology Medical statistics Bias