Dr Medhat Eldeeb Lecturer of clinical pathology Al-Azhar University

1. Control of Analytical Quality Using
Stable Control Materials of Known
Concentration and Acceptable
Range
By
Dr. Medhat Eldeeb , MD
Lecturer of clinical pathology

2. What Do You Want to Learn?
Quality Control Basics
Calculations & Statistics
Westgard Rules
Levey-Jennings Charts
QC Product Awareness

3. Aim of Quality control
-To monitor the performance of
analytical methods.
-To detect analytical errors.

4. 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.

5. Types of analytical errors
Random error due to imprecision
Systematic error due to inaccuracy
Precision:” the repeatability, or reproducibility
of the measurement”
Accuracy: “Closeness of the agreement
between the result of a measurement and a
true value of the measurand”.

7. What is Random Error?
Random error (also called unsystematic error,
system noise or random variation) has no
pattern.
One minute your readings might be too small.
The next they might be too large.
You can’t predict random error and these errors
are usually unavoidable.
They are unpredictable and can’t be
replicated by repeating the experiment again.

8. CAUSES OF RANDOM ERRORS
• Bubbles in reagents;
• Instrument instability;
• Temperature variations; and
• Operator variability, such as variation in
pipetting.
• Uncalibrated pipets
• Mixing defect
• Timing defect

9. What is Systematic Error?
Systematic error (also called systematic bias)
is consistent, repeatable error.
Systematic Errors produce consistent errors,
either a fixed amount (like 1 mg/dL) or a
proportion (like 105% of the true value). If you
repeat the experiment, you’ll get the same
error.

10. Causes of systematic errors
• change in reagent lot;
• change in calibration;
• assigning the wrong calibrator values;
• reagents that were improperly prepared or are
deteriorating;
• pipettor maintenance error (not adjusted
correctly or misaligned); and/or
• a deteriorating photometric light source in the
instrument.

11. 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

12. Control solutions, control materials
The International Federation of Clinical
Chemistry defines a control solution or control
material as :
a "specimen or solution which is analyzed solely
for quality control purposes, not for
calibration“
Calibration.“The process of testing and adjustment of an instrument,
kit, or test system, to provide a known relationship between the
measurement response and the value of the substance being
measured by the test procedure.” [CLSI]

13. Quantitative QC - Module 7 13
Calibrators
A substance with a specific
concentration.
Calibrators are used to set
(calibrate) the measuring
points on a scale.
Controls
A substance similar to
patients’ samples that
has an established
concentration.
Controls are used to ensure
the procedure is working
properly.
1 2 3 4 5
1 2 3 4 5

14. Criteria of Control material
1. Stable, Known Concentration and Acceptable
Range.
2. Box Pricing (The product cost per mL).
3. Available in aliquotes or vials of suitable size,
it is necessary to know the approximate
volume of control to be used each day.
4. Shelf life, . Your quality control shelf life
should match or exceed the laboratory’s
normal usage rate or money will be wasted.

15. 5. Available at least for one year
6. Little vial to vial variability
7. Safe
8. Have a matrix similar to that of the test
specimens
9. Analyte conc. Should be in the normal and
abnormal ranges (similar to medical
situations)

16. Quantitative QC - Module 7 16
Choosing Control Materials
• values cover medical decision points
• similar to the test sample
• controls are usually available in high, normal, and low ranges

17. Types of Control Materials
Lyophilized or liquid
Human based or animal based
commercial products or Home-made
Assayed or unassayed

18. 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.

19. 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.

20. Quantitative QC - Module 7 20
Steps in Implementing Quantitative QC
• Obtain control material
• Run each control 20
times over 30 days
• Calculate mean and +/-1,2,3
Standard Deviations
• Draw L-J chat
• Apply WG rules Mean
1SD
1SD
2SD
3SD
2SD
3SD

21. The mean (or average) [x] :
Is the laboratory’s best estimate of
the analyte’s true value for a specific
level of control.

22. Formula 1: Calculating the Mean
X = Σ xn/n
Where:
Σ = sum
xn = each value in the data set
n = the number of values in the data set

23. Example
• Level I (Normal Control)
• Unassayed Chemistry Control, Lot No. 12345
• Test: K
• Instrument: ABC
• Units: mmol/L
• Control Values are:
• {4.0, 4.1, 4.0, 4.2,4.1, 4.1, 4.2}.

24. Answer
- The sum [Σ] is 28.7 mmol/L.
- The number of values is 7 (n = 7).
X = 28.7 / 7 = 4.1 mmol/L
X = 28.7 / 7 = 4.1
mmol/L

25. Standard Deviation [s]
Is a statistic that quantifies how close
numerical values (i.e., QC values) are
in relation to each other.

26. Formula 2: Calculating a
Standard Deviation [s]

27. • Level I (Normal Control)
• Unassayed Chemistry Control, Lot No. 12345
• Test: K
• Instrument: ABC
• Units: mmol/L
• Control Values are:
• {4.0, 4.1, 4.0, 4.2,4.1, 4.1, 4.2}.

28. - The sum [Σ] is 28.7 mmol/L.
- The number of values is 7 (n = 7).
X = 28.7 / 7 = 4.1 mmol/L

30. • Level I (Normal Control)
• assayed Chemistry Control, Lot No. 12345
• Test: K
• Instrument: ABC
• Units: mmol/L
• Range of control :
• {3.9 - 4.3}.

31. - The sum [Σ] is 8.2mmol/L.
- The number of values is 2(n = 2).
X = 8.2/ 2= 4.1 mmol/L

32. Calculating a Standard Deviation
Upper limit = X + 2 SD
4.3 = 4.1 + 2 SD
4.3 - 4.1 = 2 SD
0.2 = 2 SD
SD = 0.1

33. Calculating Quality Control Limits
• These ranges are used with the mean to construct the
Levey-Jennings chart
• ±1s range is 4.0 to 4.2 mmol/L
• 4.1 – (0.1)(1) = 4.0
• 4.1 + (0.1)(1) = 4.2
• ±2s range is 3.9 to 4.3 mmol/L
• 4.1 – (0.1)(2) = 3.9
• 4.1 + (0.1)(2) = 4.3
• ±3s range is 3.8 to 4.4 mmol/L
• 4.1 – (0.1)(3) = 3.8
• 4.1 + (0.1)(3) = 4.4

34. Creating a Levey-Jennings Chart
• 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.
• The mean for the Level I potassium control is 4.1
mmol/L and the standard deviation is 0.1 mmol/L. Next
slide provides examples on how ±1s, ±2s and ±3s
quality control limits are calculated.

35. Levey-Jennings Chart

36. Quantitative QC - Module 7 36
Number of Controls
Interpretation depends on number of controls
run with patients’ samples.
• Good: If one control:
– accept results if control is within ± 2SD
unless shift or trend
• Better: If 2 levels of controls
– apply Westgard multirule system

37. Westgard Rules
12s
• This is a warning rule that is violated when a
single control observation is outside the ±2s
limits.

38. 12s Rule

39. 13s
• This rule identifies unacceptable random error
or possibly the beginning of a large systematic
error. Any QC result outside ±3s violates this
rule.

40. 13s

41. 22s
• This 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.

42. 22s within-run

43. 22s across runs

44. R4s
• This 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.

45. R4s

46. 41s
• The criteria which must be met to violate this
rule are:
• •• Four consecutive results
• •• Greater than 1s
• •• On the same side of the mean

47. 41s
• There are two applications to the 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).

48. 41s within control material

49. 41s Across control materials

50. 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.

51. • 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).

52. 10X Within control material

53. 10X Across control materials

54. Systematic 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.
– shift–control on one side of the mean 6 consecutive days
– trend–control moving in one direction– heading toward an
“out of control” value

56. Quantitative QC - Module 7 56
Levey-Jennings Chart
Shift
MEAN
+1SD
+2SD
-1SD
-2SD
-3SD
+3SD
Days
190.5
192.5
194.5
196.5
188.5
186.5
184.6

57. Quantitative QC - Module 7 57
Levey-Jennings Chart
Trend
MEAN
+1SD
+2SD
-1SD
-2SD
-3SD
+3SD
Days
190.5
192.5
194.5
196.5
188.5
186.5
184.6

58. A trend indicates a gradual loss of reliability in the
test system.
Causes of trend:
• 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

59. Shift: 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.

60. 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

61. Quantitative QC - Module 7 61
If QC is out of control
• STOP testing
• identify and correct problem
• repeat testing on patient
samples and controls after correction
• Do not report patient results until
problem is solved and controls
indicate proper performance

62. Coefficient of Variation [CV]
Is the ratio of the standard deviation
to the mean and is expressed as a
percentage.

63. Formula 4: Calculating the
Coefficientof Variation [CV]

64. Applications of CV
The CV allows easier comparisons of the
overall precision.
The Coefficient of Variation can also be used
when comparing instrument performance.

65. The Coefficient of Variation can also be used
when comparing instrument performance.
Imprecision Differences Due to Instrument or Reagent
Level I (Normal Control)
Chemistry Control
Lot No. 12345
Level I (Normal Control)
Chemistry Control
Lot No. 12345
Instrument #1 / Reagent #1 Instrument #2 / Reagent #2
CV CV
Calcium 6.1% 5.9%
Phosphorus 5.2% 9.9%
Glucose 4.4% 4.2%