Novel Internet-based Tool for Correcting Apparent Sensitivity and Specificity of Diagnostic Tests to Adjust for Referral (Verification) Bias

Abstract

Referral (verification) bias-the selective sampling of a population under evaluation for definitive confirmation of disease status-has been recognized as affecting the measured sensitivity and specificity of diagnostic tests. The authors developed an Internet-based Java applet to correct the apparent (measured) values of sensitivity and specificity of diagnostic tests to adjust for referral (verification) bias. The applet was applied to the diagnosis of coronary artery disease by means of exercise stress testing. Referral rates for coronary arteriography can be adjusted separately for patients with positive and negative test results. The more complicated situation, in which the results are stratified in terms of exercise heart rate, was also investigated.

False Positives and Referral Bias: Content for a Quantitative Literacy Course

“…This non-invasive procedure can help doctors identify those patients who should be referred for more-definitive testing. The following example is based extensively on Danias and Parker (2002).…”