Understanding Negative Predictive Value of Diagnostic Tests Used in Clinical Practice

Abstract

Nurses review, evaluate, and use diagnostic test results on a routine basis. However, the skills necessary to evaluate a particular test using statistical outcome measures is often lacking. The purpose of this article is to examine and interpret the underlying principles for use of the statistical outcomes of diagnostic screening tests (sensitivity, specificity, and positive (PPV) and negative (NPV) predictive values, with a discussion about use of SpPIn [Specificity, Positive test = rule in], and SnNOut [Sensitivity, Negative test = rule out]) in advanced nursing clinical practice. The authors focus on NPVs because test results with high NPV are useful to practitioners when considering unnecessary, costly, and possibly risky treatments, whether using clinical assessment tool, test, or procedure or using polymerase chain reaction analysis of DNA test results. In this article, the authors emphasize the use of NPV in treatment decisions by providing examples from critical care, neonatal, and advanced forensic nursing, which become a framework for assessing decisions in the clinical arena. This commentary stresses the importance of the NPV of tests in preventing, detecting, and ruling out disease, where PPV may not be relevant for that purpose. Negative predictive value percentages inform treatment decisions when the provider understands the biology, chemistry, and foundation for testing methods used in clinical practices. The art of diagnosis, confirmed in a test's high NPV (meaning the patient probably does not have the disease when the test is negative), reassures provider treatment stewardship to do no harm.

Publication Title

Dimensions of Critical Care Nursing

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