When individuals at risk of a condition are administered a diagnostic or screening test for a condition of interest, the positive predictive value (PPV) is proportion of those who test positive who indeed have the condition (true positives). This may also be called diagnostic precision. This statistic is influenced both by the sensitivity and specificity of the test itself and the prevalence of the condition in those tested. If the pre-test probability is the same as the prevalence, then the PPV is numerically the same as the post-test probability. PPV is important in economic modelling of diagnostic tests as it indicates the proportion of those who receive further tests or an intervention who can potentially benefit. Those who text positive without the disease (false negatives) may experience side effects of further tests or interventions without benefit. In information retrieval PPV is sometimes called the precision of the search strategy. PPV is closely related to negative predictive value (NPV).

How to cite: Positive Predictive Value [online]. (2016). York; York Health Economics Consortium; 2016. https://www.yhec.co.uk/glossary/positive-predictive-value/

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