A false positive describes a test result where a pathology or out of range result is indicated by the test but the pathology does not actually exist in the patient. They are a frequent problem in diagnostic medicine and, as a result, physicians have to learn not to take results at face value and to confirm a diagnosis by ensuring the patient has other symptoms of the pathology.

No medical test is perfect and most common tests have a well established error rate. There are several reasons why a false result may occur ranging from improper handling of a sample to other naturally occurring substances in the sample that also react to whatever substances are used to run the test.

Because of the counter-intuitive nature of statistical analysis, the chance that a patient actually has a pathology given a positive test result depends more on the likely percentage of the population that has the disease more than the sensitivity of the test. For example, a test that is 90% accurate for a disease that exists in 10% of the population results in a false positive rate of about 45% (8 false positives and 9 true positives in 100 tests). However, a test that is 99% accurate for a disease that exists in .1% of the population will result in a false positive rate of about 90% (10 false positives for 1 real positive in 1000 tests)

False positives and false negatives at Wikipedia

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