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RLO Transcript: Sensitivity and specificity
This is a transcript of the Reusable Learning Object (RLO) entitled "sensitivity and specificity",
online at:
http://www.nottingham.ac.uk/nursing/sonet/rlos/ebp/sensitivity_specificity/
Introduction
Diagnosis is an essential step in medical care. Usually this involves ‘diagnostic tests’ of some
description. A health check is also a group of diagnostic tests. Decisions about medical treatment
are made on the basis of test results.
If disease is present an ideal, or truly accurate, test will always give a positive result, whilst if
disease is not present, the test will always give a negative result. This is not the case for all tests.
The properties of the test that tell us about test accuracy are called sensitivity and specificity.
Sensitivity is defined as the proportion of people with disease who have a positive test result.
Specificity is defined as the proportion of people without disease who have a negative test result.
Tests
In a group of 100 people, 60 have disease, 40 do not have disease. Our ideal test applied to all
these people will give 60 positive results in those who have disease and 40 negative results in
those without disease. This test therefore has a sensitivity of 100% and a specificity of 100%.
Most tests are not 100% accurate for a variety of reasons. In this case the test gives a positive
result in 48 out of the 60 who have disease. What is the sensitivity?
The test gives a negative result in 28/40 who do not have disease. What is the specificity?
False results
Those people who have been misclassification as false positive and false negative still have a test
result. If patients have disease and the test has not identified them, then they are labeled as
negative, but the test is wrong so this is a false negative. Similarly, the group with no disease that
did not have a negative result, must have had a positive result, so they are false positive.
Hence the population with disease includes those who have true positive test results and false
negative test results.
The population without disease includes those who have true negative test results and false
positive test results.
Accuracy Table
Information on the accuracy of a diagnostic test can be put into a table. Disease presence or
absence must be determined by some means and this is usually called the 'gold' or 'reference'
standard.
Sensitivity (the proportion of patients with disease who have a positive test) = true positive
divided by true positive plus false negative.
© 2006 School of Nursing and Academic Division of Midwifery, University of Nottingham
Specificity (the proportion of patients without the disease who have a negative result) = true
negative divided by true negative plus false positive.
Activity
50 people were given a diagnostic test for asthma. (20 with disease, 30 without.) 15 people with
asthma had a positive test, whilst 5 people with asthma had a negative test. A negative test result
was also found in 28 people without asthma. 2 people without asthma had a positive test result.
Put these numbers into the table and answer box to work out the sensitivity and specificity.
Assessment
A diagnostic test has a sensitivity of 85% and a specificity of 95%. How many false positive and
false negative results will there be if the test is used on 100 patients with disease and 100
without?
Glossary
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Sensitivity: the proportion of people with disease who have a positive test result.
Specificity: the proportion of people without disease who have a negative test result.
Reference standard: the presence or absence of disease determined by approved methods.
False positive: a positive test result in a patient without disease.
False negative result: a negative test result in a patient with disease.
© 2006 School of Nursing and Academic Division of Midwifery, University of Nottingham