A utility-based model for comparing the cost-effectiveness of diagnostic studies.

The effective cost of a diagnostic test is the money spent per unit of diagnostic performance. The latter can be measured as diagnostic utility (DU), the probability-weighted sum of the utilities of the four test outcomes TP, TN, FP, and FN: DU = U(TP)P(TP) + U(TN)P(TN) + U(FP)P(FP) + U(FN)P(FN). DU (which also is called expected utility) incorporates the clinical decision analytic variables sensitivity (Se), specificity (Sp), equivocal fraction (EF), disease probability (P(D)), and outcome utility (U). DU is not an inherent property of a diagnostic test but of test-observer interactions in a clinical setting. The model sets the effective cost (EC) of a diagnostic test = actual direct cost (ADC)/DU. When DU = 1 (perfect test) EC = ADC and the patient benefits from the test dollar for dollar. When DU less than 1, EC exceeds ADC. If DU approaches O, EC becomes infinite; the test has no effectiveness at any cost. DU depends strongly on P(D) if Se and Sp differ significantly; then EC also depends on P(D), and the effective cost of a test performed in the wrong P(D) setting may be several times its actual direct cost. This model of comparing effective costs compares actual direct cost with clinical measures of test performance and utility values that allow expression of patient/doctor fears and preferences. It offers a more clinically realistic setting than models based on costs alone.