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Welcome to Bio-Rad’s Blackboard Training. This is a series of short informal tutorials
brought to you by industry experts. Today we’ll cover Levey-Jennings Charts.
Let’s start with a definition. When plotting 1, 2, or 3 SD ranges in the Laboratory a graph
known as a Levey-Jennings (or LJ) chart is used. Levey-Jennings charts use a series of
horizontal lines to represent each SD range and the mean value.
Let’s take a look at an example.
The middle line is the mean value;
+1 SD is the first line above the mean line,
and -1 SD is the first line below the mean value;
+2 SD and -2 SD are above and below the +1 and -1 SD lines.
The 3 SD ranges are above and below the 2 SD ranges.
The results are plotted daily on this chart with day 1 at the extreme left of the chart.
If one month’s values are plotted, the last day would be the last result on the extreme
right.
This graphic presentation allows you to easily review how well you perform relative to the
mean value.
On this chart, the laboratory is demonstrating good precision by repeating the same basic
value. The general gauge of precision in a test system is the average distance from each
result to the average of all the results. If each control result is very close to the
others, then the test system is said to be precise.
This lab shows the potential for test errors due to the variation in QC results from day
9 through to day 19. Upon investigation it was determined this was due to mixing and
handling problems. This improper operator technique could have also adversely affected
patient values.
Every lab should try to recover control values as close to the mean as possible. When this
is achieved, the test system is functioning correctly.
Occasionally, however, the result will not be acceptable, and the analyst must determine
where the testing error is occurring.
There are generally two types of errors encountered in a test system: random and systematic.
Random errors usually affect the precision of the testing system. An example of random
error is poor pipetting technique.
Systematic errors usually affect the accuracy of the test system.
Sometimes the distinction between random and systematic error is not entirely clear, but
the overall objective is to develop a quality control program that will assure that the
results are not only reproducible (or precise – with a low random error), but also correct
(or accurate – low systematic error).
Levey-Jennings plots are used to detect long term changes (problems that manifest themselves
over a period of days, weeks, or months) within the testing system.
LJ plots allow you to detect when the control results show a tendency to migrate abnormally
across the acceptable ranges. Normally, results fall within two standard deviations around
the mean. Based on the Gaussian distribution, 5% of the results will ordinarily fall outside
the 2SD range.
Levey-Jennings plots are helpful with detecting shifts.
A shift is a sudden upward or downward change that lasts for four or more consecutive values.
Shifts are usually caused by either instument malfunction or by adjustments made to the
instrumentation.
Shifts should be monitored closely as there is a chance this change will be clinically
significant. If the results are very close to going out of range or are already out of
range, the situation should be corrected immediately.
Here’s another example of a shift.
It is important to identify and document the cause of a shift. For example, does the equipment
need maintenance? Did maintenance just occur? If you cannot determine the cause of the shift,
it may be necessary to call the service personnel to discuss the problem.
You should also be aware of results that gradually but consistently rise or fall, another clear
indicator that a problem is developing. This is called a trend.
A trend is the tendency of results to gradually increase or decrease over a period of time.
Trends are usually caused by contamination, reagent deterioration, or gradual equipment
failure.
When more than four consecutive points continue to gradually increase or decrease, a trend
may be developing.
Here’s is another example.
If the results are still within range, they should be monitored closely. If the trend
continues to develop, it should be corrected before becoming so significant that the patient
results are adversely affected.
In general, the cause of a trend is more difficult to determine than the cause of a shift. Consider
the following when troubleshooting.
Check the system for diluent background counts with blank runs.
Evaluate control materials.
Check dating of all disposables which could be near expiration.
Check the date of the last reagent changes.
Check the date the current control vial was opened. Open a new vial if necessary.
If the problem is still apparent, contact the manufacturer of the control product to
see if other users are experiencing the same problems.
If none of the above solves the problem, contact the instrument service personnel.
We hope you’re found this tutorial helpful.
For all of your QC needs, visit www.qcnet.com.