## QUALITY CONTROL SIMPLIFIED
Quality control is a subject which is mainly
difficult to digest, because of the mathematical figures and formulas contained
in the calculations, and hence is many a times ignored by the
pathologists. As an honest and sincere
laboratory worker, everybody will be interested in providing correct
results. In this connection, we should
know the following words :
1.
Imprecision : Errors of scatter. 2. Inaccuracy : Errors of bias. To understand these, the following experiment was done. Three different technicians were given a plasma to perform 20 tests on the same sample. They carried out glucose estimation on the same sample, with the same pipets and the autoanalyser, and the results were tabulated ( Tables A , B, & C ). In each case, the mean, bias and scatter were calculated. Bias is the difference between the actual level and the mean. Scatter means the standard deviation as calculated in the tables.
Total of
columns 2 & 4 . Mean 133 Bias 0 Scatter 4.5 <img
src=images/p1.gif>
## SD = 380 / 19 = 20 =
4 . 5 2 SD = 9
CV = ( 4 . 5 / 133 ) X 100 = 3.38
TOTAL 2460 20 MEAN 123 BIAS - 10 SCATTER 1.02 2 SD = 2.04 <img
src=p2.gif> _______ _____ SD = CV =- (1.02 / 123 ) X 100= 0.83 ## TABLE C
: GLUCOSE ESTIMATION BY C
TOTAL 2660
36 MEAN 133 BIAS 0 SCATTER 1.37 2 SD 2.74 <img
src=p3.gif> SD = 36 / 19 =
1.89 = 1.37 CV =( 1.37 / 133 ) X 100 = 1.03 Thus, to summerise,
<img src=p4.gif> A
has ideal mean, good bias , but
large scatter. B has very low mean ( due to common pipeting error ), large bias and very low scatter.
C has all the factors ideal.
So his performance is the best.
When this experiment is repeated, the technicians come to know their
errors, which are persistently reduced.
Thus, this is the best practical experiment done constantly in my lab,
especially when I get only one sample for glucose estimation ( because of cheapness of the reagent
).
1. Faulty
technique : incorrect and variable pipeting,
inadequate mixing of samples with reagents, incubation of tests at inconsistent temperatures or
for incorrect length of time. Reliable test
results can only be achieved if the methods are written clearly,
and
insufficient details, and
followed exactly by all the members of staff. 2. Dirty
glassware. 3. Too heavy a workload resulting in faulty
technique, mistakes being made, or short cuts being utilized. 4. Too low a workload resulting in loss of
concentration. 5. Faults in colorimeter / spectrophotometer / analyzer, and unreliable
main supply. 6. Use of dirty or finger marked cuvettes, air
bubbles in sample, vapor present in cuvettes. 7. Incomplete removal of interfering substances in serum, like RBCs,
or protein.
1. Use of unsatisfactory reagents :
impure chemicals, -
wrong preparation, -
improper storage, -
use beyond working life / expiry
date, -
improper balance, -
bad quality of distil water, -
uncalibrated volumetric
apparatus. 2. Incorrect or infrequent calibration of a test
method. 3. Poor controls / standards : wrongly prepared or stored controls or
standards or used after expiry. 4. Readings on incorrect filter.
1. Training laboratory workers to perform tests
correctly, 2. Establishing performance standards for each
test method, 3. Charting the results for bias and scatter, 4. Taking part in external quality control
programmes, 5. Reporting results clearly and with minimum
delay, 6. Making sure that equipment such as balance,
colourimeters / spectrometers / autoanalysers, water baths are being used
correctly and maintained adequately.
1.
Collect at least 2 ml clear
plasma / serum, the value of which is around 130 160 mg / dl. 2.
Perform 20 measurements on the
sample very carefully. 3.
Tabulate the results ( column 2 ). 4.
Calculate the mean. 5.
Calculate the difference from
mean for each value and tabulate in column 3. 6.
Square this value in column 3
and write in column 4. 7. The total of
column is made. 8. Standard
Deviation is then calculated
from the following formula : Total of column 4 SD =
------------------------ n - 1 where n = number of readings 9. Coefficient of Variation (
CV ) is calculated from S D as SD CV =
--------- x 100.
Mean 10. The results are charted on graph paper as
follows : GRAPHS SHOWING 2 SD
VALUES & THE MEAN : <img
src=p5.gif> <img
src=p6.gif> <img
src=p7.gif>
^{ }2 SD limits. If the
values are beyond these limits, the results should be discarded. If so, check for-
reagent deterioration, -
incorrect preparation of the
reagents, -
faulty equipment, especially the
temperatures, -
proper filters, dust over them.
A
control will detect errors in reagents
and standards, but not individual pipetting or calculating errors in one or
more of the patients specimens.
1. Collect any unused tested sera at the end of
days work. Exclude from them i.
those with moderately to highly abnormal values, ii. icteric, cloudy or hemolysed sera and iii
sera of patients with hepatitis or HIV. 2.Transer
all the remaining sera in one screw-capped container. Freeze. 3. Add the next days samples
till the bottle fills. 4 .Allow the serum to thaw completely. Transfer to another larger bottle and mix
properly. Test for hepatitis and
HIV. Add Sodium Fluoride, 100 mg / dl
of serum. 5. Centrifuge to remove any fibrin or other debris. 6..
Analyse with maximum care for all values. 7.
Disperse the supernate in 1 ml. amounts in penicillin bulbs and keep in deep
freeze. 8. Remove one bulb at each time, thaw completely and use. ----------------------------------------------------------------------------------------- I hope this will help to understand the
subject. In the next article, I will give some practical hints to achieve
Quality Control in Biochemistry. Dr. Pramod Vaman Purohit Consulting Pathologist 347, E , Opp Railway Station Kolhapur, 416 001 ( Maharashtra ) E-mail: kpr_pathpuro@sancharnet.in |
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