Basic Issues In Laboratory Quality Assurance Mohamed Hanafy .

Transcription

Basic Issues In Laboratory Quality Assurance Mohamed Hanafy .
Basic Issues In Laboratory
Quality Assurance
By
Mohamed Hanafy
M.B,B.Ch., M.Sc., M.D., Clin. Path.
Lecturer Of Hematology
Al-Azhar Faculty Of Medicine - Demiatte
Certificate OF Program Office for Laboratory Quality Management
Department of Pathology and Laboratory Medicine
University of British Columbia - Canda
MAIN POINTS
LABORATORY CYCLE
1
Quality control (QC)
2
3
Content
4
Internal Quality Control
Westgard Multirules
5 Types Of IQC Errors
6
What can we do about the errors?
Quality Control
Definition of Quality Control
Quality control (QC) is a system used to maintain a
determined level of accuracy and precision.
Proper quality control helps ensure that reported results of
patient laboratory testing are correct.
Quality control applies not only to specimen testing, but also
to collection, storage, and transportation .
Quality control procedures are performed in a clinical
laboratory to help the laboratorians ensure that patients'
results are reliable. Reliability refers both to accuracy
(how close a test is, on average, to patients' true results)
and precision (the consistency of tests performed at
different times).
Quality System
Quality Assurance
Quality Control
LABORATORY CYCLE
Quality system begins and ends
with the patient
Pre-examination Processes
Examination Processes
Post-examination Processes
Internal and External Quality
Control



Internal Quality Control Internal quality control is set up within a
laboratory to monitor and ensure the reliability of test results from that
laboratory.
The primary tool for internal quality control is called a control. A control
is a specimen with a predetermined range of result values, called control
values, that is processed in the same manner as a patient sample.
Control samples are processed with each series or run of patient
samples.
If the result of a test on a control sample is different from its known
value, this indicates a problem in the equipment or the methods being
used.
Internal Quality Control Program
An internal quality control program depend on the
use of internal quality control (IQC) specimens,
Shewhart Control Charts, and the use of statistical
methods for interpretation.
Internal Quality Control Specimens
IQC specimens comprises either (1) commercial
products or (2) Home-made
Quality Control
What is a Control?
QC programs require the same sample to be tested every day
testing is done.
This type of sample is called a control.
Controls, which are often purchased from manufacturers, use
a human base to ensure the analytes being tested parallel
human ranges.
Manufacturers pool together many human blood samples to
create the large volume needed for a lot number of control
Control Materials

Control materials are made to match patient samples in physical and
chemical characteristics. Control samples are often made with biological
material.
Control samples are tested in the same way as patient samples. If the
results from testing a control sample are not within the acceptable
ranges, we assume there has been a problem in the test procedure,
equipment, or the samples themselves. There are many criteria for
rejecting a test based on the control samples measurements.

Patient results are not reported until the cause of the problem has been
found, the problem resolved, and the controls re-run to verify that
everything is working normally.
Quality Control Methods


Assayed or Unassayed stabilized material
(Commercial)
Previously analyzed patient samples



Easily obtained
Cost effective
Results and samples readily available
QC Methods: Assayed or Unassayed
Stabilized Material





Commercially available
Known values (Assayed only)
Analyze low, normal and high control
Results stored in the instrument computer (Pentra
only)
Monitored with Levy-Jennings charts

- Easily illustrates trends and shifts
Assayed and Unassayed Controls

Commercially prepared controls come in either assayed
or unassayed forms. Assayed controls are tested by
multiple methods before sale, and are sold with the
results of the tests.
Assayed controls:

are more expensive than unassayed controls

are used to evaluate accuracy and precision

avoid laboratory errors in determining control values

may only be suitable for specific methods or conditions

While the manufacturer's control values can be used to
some extent to measure accuracy, the best measure of
accuracy
is
certified
reference
material.
Unassayed controls

are not tested by the manufacturer before they are sold. The
control values for these materials must be determined by the
individual laboratory. Unassayed controls:

are less expensive than assayed controls

are used to evaluate precision only

avoid manufacturer error in determining control values

control values are customized to the laboratory's own methods
and conditions

A final note: although commercially available control materials
are screened for hepatitis antigens and HIV antibodies, control
materials should still be handled with precautions, since they
contain biological materials and could contain infectious agents.
Use of Controls




An internal quality control program must monitor results in
the normal range, and in the abnormal range. For each test,
there is one control in the normal range and one or two
abnormal controls. Abnormal controls may be in the
unhealthy but physiologically possible range, or outside what
is physiologically possible, or both. Testing in many ranges
ensures that the procedures are accurate for a wide range of
patient results. Controls are run at least as often as specified
by the instrument manufacturer. Controls should also be run
whenever there is:concern about the quality of results or
stability of the testing system, or
if the results of previous controls were not acceptable,
If a problem is discovered, the samples in previous runs of the
instrument may also have been affected. Once the problem(s)
are corrected, it may be necessary to go back and re-run
previous samples working in reverse order, until the retested
results match the original results.
Tools for Validation of QC
results
Shewhart Control Charts
A Shewhart Control Chart depend on the use of IQC
specimens and is developed in the following manner
Shewhart Chart
100
90
80
70
60
50
40
30
20
10
0
+3 sd
+2 sd
+1 sd
Target value
-1 sd
-2 sd
-3 sd
1
2
3
4
5
6
7
8
9
Assay Run
10 11
12 13
14 15
16
Westgard multirules





The formulation of Westgard rules were based on statistical
methods. Westgard rules are commonly used to analyse data in
Shewhart control charts.
Westgard rules are used to define specific performance limits for a
particular assay and can be use to detect both random and systematic
errors.
There are six commonly used Westgard rules of which three are
warning rules and the other three mandatory rules.
The violation of warning rules should trigger a review of test
procedures, reagent performance and equipment calibration.
The violation of mandatory rules should result in the rejection of the
results obtained with patients’ serum samples in that assay.
Warning rules

Warning 12SD : It is violated if the IQC value exceeds the
mean by 2SD. It is an event likely to occur normally in less
than 5% of cases.

Warning 22SD : It detects systematic errors and is violated
when two consecutive IQC values exceed the mean on the
same side of the mean by 2SD.

Warning 41SD : It is violated if four consecutive IQC values
exceed the same limit (mean  1SD) and this may indicate the
need to perform instrument maintenance or reagent calibration.
Mandatory rules

Mandatory 13SD : It is violated when the IQC value exceeds
the mean by 3SD. The assay run is regarded as out of control.

Mandatory R4SD : It is only applied when the IQC is tested in
duplicate. This rule is violated when the difference in SD
between the duplicates exceeds 4SD.

Mandatory 10x : This rule is violated when the last 10
consecutive IQC values are on the same side of the mean or
target value.
Westgard Rules: 1 3SD
100
90
80
70
60
50
40
30
20
10
0
+3 sd
+2 sd
+1 sd
Target value
-1 sd
-2 sd
-3 sd
1
2
3
4
5
6
7
8
9
Assay Run
10 11
12 13
14 15
16
Westgard Rules: 10X
Antibody Units
100
90
80
70
60
50
40
30
20
10
0
+3 sd
+2 sd
+1 sd
Target value
-1 sd
-2 sd
-3 sd
1
2
3
4
5
6
7
8
9
10 11
12 13
Assay Run
VZV IgG ELISA: Target Value = 49 U/ml
14 15
16
Follow-up action in the event of a
violation
There are three options as to the action to be taken in the event of a
violation of a Westgard rule:



Accept the test run in its entirety - this usually applies when
only a warning rule is violated.
Reject the whole test run - this applies only when a
mandatory rule is violated.
Enlarge the greyzone and thus re-test range for that particular
assay run - this option can be considered in the event of a
violation of either a warning or mandatory rule.
Types Of Errors
Random Error

An error which varies in an unpredictable manner, in magnitude
and sign, when a large number of measurements of the same
quantity are made under effectively identical conditions.

Random errors create a characteristic spread of results for any test
method and cannot be accounted for by applying corrections.
Random errors are difficult to eliminate but repetition reduces the
influences of random errors.

Examples of random errors include errors in pipetting and changes
in incubation period. Random errors can be minimized by training,
supervision and adherence to standard operating procedures.
Random Errors
x
x
x
x
True
x
Value
x
x
x
x
x
x
x
x
x
x
x
x
x
Systematic Error

An error which, in the course of a number of measurements of
the same value of a given quantity, remains constant when
measurements are made under the same conditions, or varies
according to a definite law when conditions change.

Systematic errors create a characteristic bias in the test results
and can be accounted for by applying a correction.

Systematic errors may be induced by factors such as variations in
incubation temperature, blockage of plate washer, change in the
reagent batch or modifications in testing method.
Systematic Errors
x
x
True
Value
x
x
x
x
x
x
x
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