Measures of Accuracy in Screening

The accuracy of a public health screening program is essential in determining its effectiveness in identifying individuals with a specific condition or disease. Several key measures help assess this accuracy: sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

Sensitivity measures the proportion of true positive cases among individuals with the condition, reflecting the test's ability to correctly identify those affected. Specificity, on the other hand, measures the proportion of true negative cases among those without the condition, gauging the test's ability to correctly identify healthy individuals. PPV indicates the probability that an individual with a positive test result truly has the condition, while NPV represents the probability that an individual with a negative test result is indeed healthy. Balancing these measures is crucial to minimize false positives and false negatives, ensuring the screening program effectively identifies at-risk individuals and allocates resources appropriately.

References

• This text was originally generated on 28 March 2023 by ChatGPT4.0 and reviewed by Arnold Bosman.
• Wilson, J. M. G., & Jungner, G. (1968). Principles and practice of screening for disease. World Health Organization. Public Health Papers, No. 34. [Link: http://apps.who.int/iris/bitstream/10665/37650/17/WHO_PHP_34.pdf]
• Pepe, M. S. (2003). The Statistical Evaluation of Medical Tests for Classification and Prediction. Oxford University Press. [ISBN: 0198565828]
• Zweig, M. H., & Campbell, G. (1993). Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clinical Chemistry, 39(4), 561-577. [Link: https://academic.oup.com/clinchem/article/39/4/561/5642662]

(this text was not part of the original 2017 FEMWIKI)