Negative Predictive Value - the probability that a negative test identifies a true negative. These points are extremely important yet often misunderstood. Basic knowledge of these concepts is important to understand how tests are evaluated and how they affect the decisions that follow the application of a test in the field. The sensitivity, specificity, and predictive values of a test used in any given program will play a major role in the success or failure of that program. Accuracy is most commonly expressed in terms of sensitivity and specificity.
Sensitivity is the ability of a test to identify true positives.
A highly sensitive test will have few false negatives. Specificity, on the other hand, is the ability of a test to identify true negatives. A highly specific test will have few false positives. Therefore decisions and actions based on such test results are no better than the accuracy of test. However, while these are not mutually exclusive in most instances, a test cannot have both high sensitivity and high specificity because an increase in one often leads to a decrease in the other.