CLINICAL LAB SCIENEC

CHAPTER 10: QUALITY ASSURANCE 259
usually involve human or instrument failure, and sometimes are caused by the
quality or condition of the standards and reagents used to calculate the results for
the procedures. Disturbances to the electrical supply for the equipment, weakening
of instrument components due to age, and failure of the laboratory worker to
detect malfunctions are common areas that result in poor or negative results. Even
during the best instrument operation and when everything seems to be running
smoothly, and even if all instructions have been followed, a random error may
occur. Although the result from a random error is the type of error most difficult
to determine, in most cases a laboratory procedure that shows an abnormality
will be accompanied by other abnormal results. An astute technologist should
be able in most instances to review all the results and look for supporting tests
to support the value or to determine if a result is a random error. An unresolved
random error may cause unwarranted delay in treatment or treatment for a condition
that does not exist.
Postanalytical
An example of a postanalytical error is when the correct result was obtained but
was incorrectly recorded or was applied to the wrong patient. This may cause the
wrong treatment or failure to treat a patient who needed therapy. Many of these
problems have been eliminated by more specific identification of the patient and
linking of the results by numerical means rather than by names. This does not
eliminate the human error in which a report is placed on the wrong chart and the
physician or other clinician reads the results but does not verify the name.
Interpretation of Results
A postanalytical error with correct results may affect the patient’s well-being
but is beyond the purview of the laboratory. The clinician (usually a physician)
makes a determination as to whether the results are normal or expected based
on the patient’s clinical condition. Changes in test values that are significantly
different from previous results indicate that a patient’s condition is changing. If
results are inconsistent with clinical findings, physical assessments, and signs and
symptoms, it is possible that either the diagnosis was in error or the results are in
error. This requires follow up by the clinician responsible for the patient’s care,
but may require that a medical laboratory worker do some research to determine
if a problem occurred in the performance of the test(s).
Determining if Results Are Normal
A Gaussian distribution curve is a bell-shaped curve divided into equal halves
on the upper and lower sides of the mean. Each side is then divided into 1 SD,
2 SD, and 3 SD values. Results within 2 SDs should include 95% of tested subjects
(1 of 20 patients would be outside normal range) even if clinically normal.
The normal range may have limitations, e.g., a patient with cholesterol within
the normal range may suffer from coronary heart disease or a patient with an
elevated serum cholesterol may have no level of coronary disease. So it can be
assumed that a normal range does not mean an “ideal” range.
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