CLINICAL LAB SCIENEC

246
ESSENTIALS OF CLINICAL LABORATORY SCIENCE
A
FIGURE 10-3 (A) Accuracy versus (B) precision.
Source: Delmar/Cengage Learning.
B
control materials. However, the new limits must be within the range given by the
manufacturer, which would always be the case as the range would grow smaller
as the number of data points from testing of controls increases.
Unassayed controls are controls tested by the laboratory at a specified frequency
and time period to establish the acceptable limits or range. To establish
the acceptable limits or range, new lots of control material should be analyzed
for each analyte in parallel with the assayed control material in current use.
Once the SDs are established for the unassayed control when both the assayed
and unassayed controls are performed together, the laboratory may convert to
using only unassayed controls and therefore using its own established values.
At least 20 sets of data and preferably more than 20 separate runs should be
obtained. The common practice is to set the limits or range at 2 SDs. As a general
rule, the SDs as stated before should become smaller as the laboratory produces
more sets of test results for the various procedures being performed.
For quality assurance and as part of the laboratory’s QC program, the laboratory
must have a plan or procedure for accepting the results obtained from QC
materials, as well as the course of action to be taken when results fall outside
acceptable limits. QC rules should be incorporated into the laboratory’s procedure
or plan, to determine if the QC results are within an acceptable range.
These rules can be designed to detect inappropriate bias or imprecision that may
affect the quality of patient test results. A variety of control rules have been used
to monitor the quality of laboratory testing. These rules generally use Gaussian
statistics and assume a Gaussian-type distribution of data. Control limits are
usually the mean (x – ) of individual control values obtained over various periods
of time, and the limits are customarily based on multiples of the SD.
Due to such large number of control rules and their various ramifications,
Westgard developed a shorthand notation for the representation of these rules.
Most of these rules are incorporated into the computerized equipment, where
the instrument operator enters data for analysis and the compilation and storage
of QC data. Many of these instruments will “flag” results outside the acceptable
range, and will give a cautionary message if results from a patient’s values
would be a critical value or if some malfunction was noted by the instrument
during the procedure. In general, only approximately 4.5% of control results
should be found outside the ±2 SD limits as seen on the distribution curve shown
earlier. The lower control limits are calculated from the formula x – – 2 SDs and
the upper limit from x – ±2 SDs. For QC purposes,
a value that is too high is no worse than one that
is too low. Whenever a new control observation is
obtained, it is compared to the mean ±2 SD control
limits. If an observation is outside these limits, it
may indicate an accuracy or precision problem. As
you can see from the “targets” in Figure 10-3, accuracy
and precision are two different things; accuracy
indicates whether the true measurement of a
component has been achieved, whereas precision
indicates reproducibility.
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