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Chapter 3 Levey-Jennings Charts & Westgard Rules
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Welcome to Chapter 3: Levey-Jennings Charts & Westgard Rules.
Standard deviation is commonly used for preparing Levey-Jennings (L-J or LJ) charts.
The Levey-Jennings chart is used to graph successive (run-to-run or day-to-day) quality
control values.
A chart is created for each test and level of control.
The first step is to calculate decision limits.
These limits are ±1s, ±2s and ±3s from the mean.
Let’s begin with the data set from the previous module.
The mean for the Level I potassium control is 4.1 mmol/L and the standard deviation is
0.1 mmol/L.
This is an illustration of how ±1s, ±2s and ±3s quality control limits are calculated
using that mean and standard deviation.
The Levey-Jennings chart we have developed can be overlaid onto a bell-shaped curve to
illustrate the overall distribution of quality control values.
When an analytical process is within control, approximately 68% of all QC values fall within
±1 standard deviation (1s).
Likewise 95.5% of all QC values fall within ±2 standard deviations (2s) of the mean.
About 4.5% of all data will be outside the ±2s limits when the analytical process is
in control.
Approximately 99.7% of all QC values are found to be within ±3 standard deviations (3s)
of the mean.
As only 0.3%, or 3 out of 1000 points, will fall outside the ±3s limits, any value outside
of ±3s is considered to be associated with a significant error condition and patient
results should not be reported.
Some laboratories consider any quality control value outside its ±2s limits to be out of
control.
They incorrectly decide that the patient specimens and QC values are invalid.
An analytical run should not be rejected if a single quality control value is outside
the ±2s QC limits but within the ±3s QC limits.
Approximately 4.5% of all valid QC values will fall somewhere between ±2 and ±3 standard
deviation limits.
Laboratories that use a ±2s limit frequently reject good runs.
That means patient samples are repeated unnecessarily, labor and materials are wasted, and patient
results are unnecessarily delayed.
The laboratory needs to document that quality control materials are assayed and that the
quality control results have been inspected to assure the quality of the analytical run.
This documentation is accomplished by maintaining a QC Log and using the Levey-Jennings chart
on a regular basis.
The QC Log can be maintained on a computer or on paper.
The log should identify the name of the test, the instrument, units, the date the test is
performed, the initials of the person performing the test, and the results for each level of
control assayed.
Optional items for the log include: method and the assay temperature (usually included
for enzymes).
There should be room to write in actions taken to resolve any situation which is identified
as “out-of-control” or unacceptable and a place for documentation of supervisory review.
Once the QC results are entered into the QC Log, they should be plotted on the Levey-Jennings
chart.
When the results are plotted, an assessment can be made about the quality of the run.
The technologist/technician performing the test should look for systematic error and
random error.
Systematic error is evidenced by a change in the mean of the control values.
The change in the mean may be gradual and demonstrated as a trend in control values
or it may be abrupt and demonstrated as a shift in control values.
A trend indicates a gradual loss of reliability in the test system.
Trends are usually subtle.
Causes of trending may include: Deterioration of the instrument light source.
Gradual accumulation of debris in sample/reagent tubing.
Gradual accumulation of debris on electrode surfaces Aging of reagents.
Gradual deterioration of control materials.
Gradual deterioration of incubation chamber temperature (enzymes only).
Gradual deterioration of light filter integrity.
Gradual deterioration of calibration.
Abrupt changes in the control mean are defined as shifts.
Shifts in QC data represent a sudden and dramatic positive or negative change in test system
performance.
Shifts may be caused by: Sudden failure or change in the light source.
Change in reagent formulation.
Change of reagent lot.
Major instrument maintenance.
Sudden change in incubation temperature (enzymes only).
Change in room temperature or humidity.
Failure in the sampling system.
Failure in reagent dispense system.
Inaccurate calibration/recalibration.
Technically, random error is any deviation away from an expected result.
For QC results, any positive or negative deviation away from the calculated mean is defined as
random error.
There is acceptable (or expected) random error as defined and quantified by standard deviation.
There is unacceptable (unexpected) random error that is any data point outside the expected
population of data (e.g., a data point outside the ±3s limits).
In 1981, Dr. James Westgard of the University of Wisconsin published an article on laboratory
quality control that set the basis for evaluating analytical run quality for medical laboratories.
The elements of the Westgard system are based on principles of statistical process control
used in industry nationwide since the 1950s.
There are six basic rules in the Westgard scheme.
These rules are used individually or in combination to evaluate the quality of analytical runs.
Westgard devised a shorthand notation for expressing quality control rules.
Most of the quality control rules can be expressed as NL where N represents the number of control
observations to be evaluated and L represents the statistical limit for evaluating the control
observations.
Thus 1-3s represents a control rule that is violated when one control observation exceeds
the ±3s control limits.
The 1-2s rule is a warning rule that is violated when a single control observation is outside
the ±2s limits.
Remember that in the absence of added analytical error, about 4.5% of all quality control results
will fall between the 2s and 3s limits.
This rule merely warns that random error or systematic error may be present in the test
system.
The relationship between this value and other control results within the current and previous
analytical runs must be examined.
If no relationship can be found and no source of error can be identified, it must be assumed
that a single control value outside the ±2s limits is an acceptable random error.
Patient results can be reported.
The 1-3s rule identifies unacceptable random error or possibly the beginning of a large
systematic error.
Any QC result outside ±3s violates this rule.
The 2-2s rule identifies systematic error only.
The criteria for violation of this rule are: Two consecutive QC results.
Greater than 2s.
On the same side of the mean.
There are two applications to this rule: within-run and across runs.
The within-run application affects all control results obtained for the current analytical
run.
For example, if a normal (Level I) and abnormal (Level II) control are assayed in this run
and both levels of control are greater than 2s on the same side of the mean, this run
violates the within-run application for systematic error.
If however, Level I is -1s and Level II is +2.5s (a violation of the 12s rule), the Level
II result from the previous run must be examined.
If Level II in the previous run was at +2.0s or greater, then the across run application
for systematic error is violated.
Violation of the within-run application indicates that systematic error is present and that
it affects potentially the entire analytical curve.
Violation of the across run application indicates that only a single portion of the analytical
curve is affected by the error.
The R-4s rule identifies random error only, and is applied only within the current run.
If there is at least a 4s difference between control values within a single run, the rule
is violated for random error.
For example, assume both Level I and Level II have been assayed within the current run.
Level I is +2.8s above the mean and Level II is -1.3s below the mean.
The total difference between the two control levels is greater than 4s (e.g. [+2.8s – (-1.3s)]
= 4.1s).
Violation of any of the following rules does not necessarily require rejection of the analytical
run.
These violations typically identify smaller systematic error or analytical bias that is
not often clinically significant or relevant.
Analytical bias may be eliminated by performing calibration or instrument maintenance.
The following criteria must be met for a 3-1s rule violation: Three consecutive results.
Greater than 1s.
On the same side of the mean.
The following criteria must be met for a 4-1s rule violation: Four consecutive results.Greater
than 1s.
On the same side of the mean.
There are two applications to the 31s and 41s rule.
These are within control material (e.g. all Level I control results) or across control
materials (e.g., Level I, II, and III control results in combination).
Within control material violations indicate systematic bias in a single area of the method
curve while violation of the across control materials application indicates systematic
error over a broader concentration
These rules are violated when there are: 7 or 8, or 9, or 10, or 12 control results,
On the same side of the mean regardless of the specific standard deviation in which they
are located.
Each of these rules also has two applications: within control material (e.g., all Level I
control results) or across control materials (e.g. Level I, II, and III control results
in combination).
Within control material violations indicate systematic bias in a single area of the method
curve while violation of the across control materials application indicates systematic
bias over a broader concentration.
We have reached the end of this module.
Let’s review some basic points before we check your understanding.
The Levey-Jennings chart is used to graph successive (run-to-run or day-to-day) quality
control values.The first step in creating a Levey-Jennings chart is to calculate decision
limits.
These limits are ±1s, ±2s and ±3s from the mean.Some laboratories consider any quality
control value outside its ±2s limits to be out of control.
They incorrectly decide that the patient specimens and QC values are invalid.Approximately 4.5%
of all valid QC values will fall somewhere between ±2 and ±3 standard deviation limits.The
laboratory needs to document that quality control materials are assayed and that the
quality control results have been inspected to assure the quality of the analytical run.Systematic
error is evidenced by a change in the mean of the control values.
The change in the mean may be gradual and demonstrated as a trend in control values
or it may be abrupt and demonstrated as a shift in control
values.
A trend indicates a gradual loss of reliability in the test system.
Trends are usually subtle.Abrupt changes in the control mean are defined as shifts.
Shifts in QC data represent a sudden and dramatic positive or negative change in test system
performance.
For all your laboratory QC needs go to www.qcnet.com.
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