How to Interpret Diagnostic Tests
- 1). Understand the type and expected results of a specific diagnostic test. Some tests provide a positive or negative result, such as a pregnancy test.
Other tests report a number out of a continuous range of possible numbers. Blood levels of creatinine, for example, are measured as a test for kidney failure, but are not reported as positive or negative but as a number which can be compared to a range. - 2). Acquire diagnostic test results, and range of results possible. Compare diagnostic test results with normal test results or ranges. Age, gender and other differences also affect normal ranges and should be considered.
A test for pregnancy, for example, will display a positive or negative result. If the test is positive, the patient most likely is pregnant; if negative, the patient probably is not pregnant.
Other tests, such as blood creatinine, change with the severity or progression of disease. For example, creatinine blood levels usually increase with worsening kidney disease. A patient with mild kidney disease and a slightly increased blood creatinine level may at a later date have worsening kidney failure, and a higher blood creatinine level. - 3). If a laboratory test is done, compare results with normal ranges from the specific laboratory used. Normal ranges for comparison may vary for different laboratories and sometimes even within the same laboratory over time.
- 4). Determine the significance of the result in the context of other clinical tests. A condition such as pregnancy may initially be diagnosed on the basis of one test result.
Other cases, such as kidney failure, must be evaluated in the wider context of other tests. A patient with a high blood creatinine level, for example, should have other tests done such as a urinalysis to help determine whether kidney failure has actually occurred, and its severity. - 5). Consider the possibility of errors in test interpretation and results. Statistical data must often be considered when interpreting diagnostic tests.
For example, if interpreting a pregnancy test, consider the chance that a test may give a false positive result, in which a person who is not pregnant has a positive test. The chance of a false negative result, in which a pregnant person has a negative test, must also be considered. - 6). Determine the need for additional tests or repeated tests. For example, a positive result on a screening test with a low number of false negatives may be followed by a second test which gives few false positives. By doing additional tests, a clinician can be more certain of a diagnosis.
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