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In statistics, verification bias is a type of measurement bias in which the results of a diagnostic test affect whether the gold standard procedure is used to verify the test result. This type of bias is also known as "work-up bias" or "referral bias".^[1]^[2]

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.^{[citation needed]}

In cohort studies, 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.^{[citation needed]}

In most situations, verification bias introduces a sensitivity estimate that is too high and a specificity that is too low.^[3]

References

^ O'Sullivan, JW; Banerjee, A; Heneghan, C; Pluddemann, A (April 2018). "Verification bias". BMJ Evidence-Based Medicine. 23 (2): 54–55. doi:10.1136/bmjebm-2018-110919. PMID 29595130.
^ Begg CB, Greenes RA (1983). "Assessment of diagnostic tests when disease verification is subject to selection bias". Biometrics. 39 (1): 207–215. doi:10.2307/2530820. JSTOR 2530820. PMID 6871349.
^ Zhou XH (1998). "Correcting for verification bias in studies of a diagnostic test's accuracy". Statistical Methods in Medical Research. 7 (4): 337–353. doi:10.1191/096228098676485370. PMID 9871951.

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