Quality Control

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Transcript Quality Control

Tabuk University
Faculty of Applied Medical Sciences
Department Of Medical Lab. Technology
3rd Year – Level 5 – AY 1434-1435
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Quality Assurance and
Automation in Hematology
By/
Dr WalidZAMMITI;
Phd; M.Sc; MLT
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Objectives
Describe the electrical impedance and light scatter principles for
performing cell counts.
 Utilize quality control procedures to determine if patient results are
acceptable.
 Explain histograms and their indications.
 Concentrate on some parameters and indices.
Identify the major components of a quality assurance program.
 Be able to distinguish between quality assurance & quality control.
Define and give examples of each of the following terms: AccuracyCalibration-Control-Standard-Precision.
Understand the concepts of internal & external control.

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Quality system begins and ends
with the patient
Quality Assurance vs. Quality Control
Quality Assurance
Quality Control
An overall
A series of analytical
management plan to
measurements used
guarantee the
to assess the quality of the
integrity of data
analytical data (The
(The “system”)
“tools”)
Quality Assurance in Hematology


QA includes all aspects of laboratory activities
that affects the results produced, from the
choice of methods, to the education of personnel,
to the handling of specimens and reporting results.
The real purpose of QA activities is to determine
how correct or incorrect the results emanating
from the lab are, and to allow those managing the
lab to determine whether or not the lab is
fulfilling its functions satisfactorily.
QA in Haematology Laboratory
 QA in haematology lab is intended to ensure the reliability of
the lab tests.
 The objective is to achieve precision and accuracy
 4 components of QA programme :
1 ) Internal Quality Control ( IQC )
2 ) External Quality Control ( EQC )
3 ) Standardization
4 ) Proficiency surveillance
Accuracy vs. Precision
Accuracy
How well a easurement agrees
with an accepted value: is
the closeness of the
agreement between the
result of a measurement
and a true value of the
measurand.
Precision
How well a series of
measurements agree with
each
other:
Is
the
closeness of agreement
between independent test
results obtained under
stipulated conditions.
Accuracy vs. Precision
Internal 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.
External Quality Control ( EQC )
 is the objective evaluation by an outside agency of the
performance by a number of laboratories on material which is
supplied specially for the purpose
 is usually organized on a national or regional basis
 analysis of performance is retrospective
 the objective is to achieve comparability with results of other
labs.
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Standardization



Refers to both materials and methods.
A material standard or reference preparation is used
to calibrate analytic instruments and to assign a
quantitative value to calibrators.
A reference method is an exactly defined technique
which provides sufficiently accurate and precise
data for it to be used to assess the validity of other
methods
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Proficiency surveillance


Implies critical supervision of all aspects of laboratory
tests: collection, labelling, delivery, storage of specimens
before the tests are preformed and of reading and
reporting of results.
Also includes maintenance and control of equipment and
apparatus.
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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 analyses being tested parallel
human ranges.
Manufacturers pool together many human blood samples to
create the large volume needed for a lot number of control
Tools for Validation of QC results
Control Charts: A Control Chart depend on the use of
IQC specimens and is developed in the following manner
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90
80
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10
0
+3 sd
+2 sd
+1 sd
Target value
-1 sd
-2 sd
-3 sd
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Assay Run
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Control Charts


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Samples of the control specimen are included in every batch
of patients’ specimens and the results checked on a control
chart
Check precision: it is not necessary to know the exact value
of the control specimen
Value has been determined reliably by a reference method,
the same material can be used to check accuracy or to
calibrate an instrument
Controls with high, low and normal values should be used
Advisable to use at least one control sample per batch even
if the batch is very small
The results obtained with the control samples can be plotted
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on a chart
How to calculate SD
1.
2.
3.
4.
5.
6.
Get the Mean.
Get the deviations. (each value minus the mean)
Square these.
Add the squares.
Divide by total numbers less one.
Square root of result is Standard Deviation
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Types Of Errors

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.
Systematic vs.Random Errors
Systematic Error
Avoidable error
due to controllable
variables in a
measurement.
Random Errors
Unavoidable
errors that are
always present in
any
measurement.
Impossible to
eliminate
Random Error

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
Automation in
Haematology
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Automated techniques of blood
counting

Semi-automated instruments
Require some steps, as dilution of blood samples
 Often measure only a small number of variables


Fully automated instruments
Require only that an appropriate blood sample is
presented to the instrument.
 They can measure 8-20 variables including some
new parameters which do not have any
equivalent in manual methods.

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

The accuracy of automated counters is
less impressive than their precision.
In general automated differential
counters are favourable to the manual
in 2 conditions


Exam of normal blood samples
Flagging of abnormal samples
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
CBC : Complete Blood Count
The complete blood count is performed as an automated procedure. A
sample of blood is placed in an analyzer and the cells are sorted by a
laser according to size, granularity, and shape.
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23.
Parameters :
WBC= Total white blood cells
RBC= Red blood cell count
HGB= Hemoglobin concentration
HCT= Hematocrit (PCV)
MCV= Mean Cell Volume
MCH= Mean Cell Hemoglobin
MCHC= Mean Cell Hemoglobin Concentration
PLT= Platelets count
NEUT%= Percentage Neutrophil count
LYMPH%= Percentage Lymphocyte count
MONO%= Percentage Monocyte count
EO%= Percentage Eosinophil count
BASO%= Percentage Basophil count
NEUT#= Absolute Neutrophil Count
LYMPH#= Absolute Lymphocyte Count
MONO#= Absolute Monocyte Count
EO#= Absolute Eosinophil Count
BASO#= Absolute Basophil Count
RDW-SD= Red cell Distribution Width – Standard Deviation
RDW-CV= Red cell Distribution Width – Coefficient Variation
MPV= Mean Platelet Volume
PDW = Platelet Distribution Width
Some times other parameters are included; e.g.: Reticulocytes.
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Examples of Haematology analysers
1.
2.
3.
4.
AcT 5diff (Beckman Coulter )
SE 9000, KX21, XE 2100 (Sysmex)
Advia 60 (Bayer)
Cell-Dyn 3500 ( Abott)
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When to Calibrate
You should calibrate your instrument:
1. At installation.
2. After the replacement of any
component that involves dilution
characteristics or the primary
measurements (such as the
apertures).
3. When advised to do so by your service
representative.
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Flagging


Condition flags
• Describes cell population
normal
abnormal
WBC Suspect flags
 Blasts
 Immature Grans/Bands 1
 Immature Grans/Bands 2
 Variant lymphocytes
 Review Slide
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More Flagging


Check S
lide
RBC Suspect flags
 NRBCs
 Macrocytic RBCs
 Dimorphic RBC population
 Micro RBCs/RBC fragments
 RBC agglutination
Definitive Flagging
 Based on predetermined lab limits
 Provide information for review
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Histograms



RBC, PLT, and
WBC plotted on
histogram
X-Axis
 Cell size in
femtoliters (fL)
Y-Axis
 # of cells
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RBC Histogram As A Quality Control Tool
INDICATOR
Left of curve does
not touch baseline
Right portion of
curve extended
Left shift of curve
PROBABLE CAUSE
Schistocytes and
extremely small red
cells
Transfused cells,
therapeutic response
Red cell
autoagglutination
Microcytes
Right shift of curve
Macrocytes
Bimodal peak
COMMENT
Review smear CBC
and Platelet
histogram
Review Smear
Review CBC &
Smear
Review smear &
CBC
Review smear &
CBC
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Platelet Histogram As A Quality Control
Tool
INDICATOR
Peak or spike at left
end of histogram (28 fl)
Spike towards right
end of histogram
PROBABLE CAUSE
Cytoplasmic
fragments
COMMENT
Review smear
Schistocytes,
microcytes, giant
platelets
Bimodal peak
Cytoplasmic
fragments
Review smear + CBC
( MCV &  RDW)
( MPV &  PDW)
Review smear
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Histograms - WBCs
 WBC: Distribution with three individual peaks
and valleys at specific regions representing
the lymphocytes, monocytes, and
granulocytes.
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WBC Histogram As A Quality Control Tool
INDICATOR
Trail extending downward
at extreme left, or lymph
peak not starting at
baseline
Peak to the left of lymph
peak or widening of
lymph peak towards left
Widening of lymph peak
to right
Wider mono peak
PROBABLE CAUSE
COMMENT
NRBC, Plt clumping,
unlysed RBC,
cryoproteins, parasites
Review smear and correct
WBC for NRBC
NRBC
Review smear & correct
WBC for NRBC
Atypical lymphs, blasts,
plasma cells, hairy cells,
eosinophilia, basophilia
Monocytosis, plasma
cells, eosinophilia,
basophilia, blasts
Review smear
Review smear
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WBC Histogram As A Quality Control Tool
INDICATOR
Elevation of left
portion of
granulocyte
Elevation of right
portion of
granulocyte peak
PROBABLE CAUSE
COMMENT
Left Shift
Review smear
Neutrophilia
Review smear
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RDW-SD
RDW is an actual measurement of the width of the erythrocyte
distribution curve.
It is a measurement of Anisocytosis.
May increase before MCV becomes abnormal
Reference values:
female: 36.4 – 46.3 fL
male: 35.1 – 43.9 fL
It is increased in many types of anemias to indicate the variation in red
cell sizes.
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RDW-CV
The coefficient of variation (CV) is defined as the % ratio of the
standard deviation (x), to the mean (µ)
Cv = x/µ
Sometimes known as relative standard deviation.
Reference values:
female: 11.7 – 14.4%
male:
11.6 – 14.4 %
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MCV = MEAN Cell VOLUME


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
M.C.V. = Hematocrit%
X 10
RBC in millions/µl
Normal values: Men & women
82 – 97 fl (femtoliters) = cubic microns
Increased : Macrocytes
Decreased : Microcytes
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MCH = Mean Cell
Hemoglobin




M.C.V. = Hemoglobin g/dl
X 10
RBC in millions/µl
Normal values: Men & women
27 – 32 pg (pico grams)
Increased : Hyperchromic
Decreased : Hypochromic
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MCHC = Mean Cell Hb
Concentration

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M.C.V. = Hemoglobin g/dl
X 100
Hematocrit%
Normal values: Men & women
30 – 34 g/dl
Increased : Hyperchromic
Decreased : Hypochromic
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Other Hematology Machines
Coagulometers :
- Used in Hemostasis

studies, and the Endpoint
Detection depends on Mechanical, Optical (Photooptical , Nephelometric , Chromogenic or
Immunologic), Electrochemical principles.


ESR machines : in 30 minutes.
Leucocytes automated Differential
Counters :
Using cytochemical or image recognition methods.
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Thank you
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