Transcript The basic quality control statistics The mean

Quality Assurance
2
Quality Control
M. Zaharna Clin. Chem. 2015
What is Quality Control?
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Quality Control in the clinical laboratory
is a system designed to increase the
probability that each result reported by
the laboratory is valid and can be used
with confidence by the physician making a
diagnostic or therapeutic decision.
M. Zaharna Clin. Chem. 2015
Quality Control Programs
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The goal of a well-defined QC system is to detect
immediate errors in an analytical run while
minimizing the number of false rejections.
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The simplest type of QC procedure uses one rule
to reject the analysis based on QC results falling
outside of a range such as the 95% range.
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These facts are based on probability that the
correct decision was made 95% of the time when
results that fall within this range are accepted.
M. Zaharna Clin. Chem. 2015
Control Of The Analytical Quality
Using Stable Control Materials
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The performance of analytical methods can be
monitored by analyzing specimens whose
concentrations are known and then by comparing
the observed values with known values.
The known values are usually represented by an
interval of acceptable values, or upper and lower
limits for control (control limits)
When the observed values fall within the control
limits – analysis is working properly
When the observed value fall outside the control
limits the analyst should be alerted to the
possibility of problems in the analysis.
M. Zaharna Clin. Chem. 2015
Control Of The Analytical Quality
Using Stable Control Materials
QA includes analyzing known samples called
quality control (QC) samples along with
unknown (patient) samples to test for analytical
problems.
 When QC samples do not produce accurate
and precise results, it can be assumed that any
patient results obtained at the same time are
also erroneous.
 Following a set of guidelines for acceptance or
rejection of patient results based on the QC
results helps to assure reliability of the analysis.
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M. Zaharna Clin. Chem. 2015
Standards and Controls
 Standard
 A substance that has an exact known value
and that, when accurately measured, can
produce a solution of an exact concentration
 Not usually used on a daily basis
 Used to calibrate new instruments, recalibrate
instruments after repair, at manufacturer’s
recommended intervals, or if a method is out
of control
M. Zaharna Clin. Chem. 2015
Control
A solution that contains the same constituents
as those being analyzed in the patient sample
 Most are commercially produced from pooled
sera
 The manufacturer has analyzed each lot of
serum for a variety of test components and the
expected range of assay values for each
component is provided to the laboratory when
shipped
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M. Zaharna Clin. Chem. 2015
Control
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Controls are analyzed with each patient
test or batch of tests and the results are
compared with the manufacturer’s range
of values
For most tests, a “normal” control and an
“abnormal” control are analyzed with
each patient test or batch of tests
Results are plotted on a QC record
called a Levey-Jennings Chart
M. Zaharna Clin. Chem. 2015
Quality control (QC) procedures
Quality control (QC) procedures function by
detecting analytical errors;
◦ ideally any error large enough to invalidate the
medical usefulness of laboratory results should
be detected.
 The measurement of QC samples will detect
problems of precision and accuracy over time.
 Interpretation of control results is based on using
specific rules for acceptance and rejection of QC
results, documenting results and decisions, and
having a process for resolving problems that
result in rejection of results.
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M. Zaharna Clin. Chem. 2015
The basic quality control
statistics
Statistical Calculations
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The mean (X) is the sum of the control observations (x1,
x2, ... xi) divided by the number (n) of observations:
 Practice calculating the mean of the following five results: 45,
44, 45, 48, 39 (n = 5).
 Mean= (45 + 44 + 45 + 48 + 39)/5 = 221/5 = 44.2
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The standard deviation (SD or s) is the measure of the
dispersion of a group of values around the mean. It is
derived from the curve of normal distribution. It is used to
assess precision.
 Practice calculating the SD of the following results: 45, 44, 45, 48, 39
(n = 5).
SD (s) =
(44-44.2)2+(45-44.2)2+(45-44.2)2+(48-44.2)2+(39-44.2)2
= 3.3
Standard Deviation (SD)
It is the commonly used measure of
dispersion
 Gives a measurement of dispersion around
the mean
 Calculation:
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◦ X ± 1SD includes 68% observations
◦ X ± 2SD includes 95% observations
◦ The higher the SD, the more the observation
varies (deviates) from the mean.
M. Zaharna Clin. Chem. 2015
Percentage Coefficient of Variation
(%CV)
Measures level of imprecision
 Assess the reliability of a given method
based on preset values
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S tan dard Deviation
100
% CV =
Mean
M. Zaharna Clin. Chem. 2015
Gaussian Probability Distribution
It is very important in
statistics
 When the distribution of
values around the mean are
plotted graphically and are
symmetrical this is referred
to as a Gaussian curve.
 Statistical procedures are
based on Gaussian probability
distribution.
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M. Zaharna Clin. Chem. 2015
68-95-99.7 Rule
• In a random distribution and in a
correctly operating test system
approximately:
◦ 65% of the values will be between
the ± 1s ranges and will be evenly
distributed on either side of the
mean
◦ 95% of the values should fall between
the ± 2s ranges
◦ and 99% between the ± 3s limits
•
This means that one data point in 20 should be placed between
either of the 2s and 3s limits
• One data point placed outside of the 3s limits will occur once in
100 analyses
M. Zaharna Clin. Chem. 2015
M. Zaharna Clin. Chem. 2015
How Are These Values Used?
Mean and SD are calculations that assess the
accuracy and precision of the analysis statistically.
 Errors of accuracy may be assessed by examining
changes in the measured concentration of the
control over time and comparing these
concentration values to mean and SD ranges of
the control.
 By contrast, an imprecision problem will be
demonstrated by an increase in the SD and %CV
of results of the control concentration over time.
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General Principles Of Control
Charts
Control charts are simple graphical displays
in which the observed values are plotted
versus the time when the observations are
made.
 The control limits are calculated from the
mean (x) and standard deviations (s)
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General Principles Of Control
Charts
The most commonly used charts indicate day
or run number on the X-axis and observed QC
concentration, indicating mean, and SD ranges
on the Y-axis
 One example of a QC chart is the LeveyJennings control chart.
 By plotting the daily QC results, one can
visualize the deviation of the results from the
mean, typically noting when the results are
greater than 2 SD from the mean on a daily
basis.
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Control Rules
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The criteria used to determine acceptability of
each control measurement are termed control
rules, or QC rules.
Westgard defined QC rules based on the
earlier work of Shewhart, Levey, and Jennings.
Use of multiple control rules (commonly
referred to as Westgard rules) can improve the
performance of the control system.
Control Rules
Individual rules have different capabilities for
detecting different types of analytical error.
 A control rule or control decision is used to
judge whether analysis is performing well.
 Ranges can be tighter if clinical requirements
are more demanding, but the SD limit should
not be set so narrow that excessive time and
resources are wasted checking false rejections.
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M. Zaharna Clin. Chem. 2015
M. Zaharna Clin. Chem. 2015
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Errors in Laboratory Testing
 Random or Systematic
 Random Errors – cannot be absolutely
identified (Ex. Differences in techniques
between workers, specimen characteristics,
etc.) - precision
 Systematic Errors – variation that may make
results consistently higher or lower than the
mean value for a control (Ex. Trouble with the
instrument, deteriorated reagents, etc.) accuracy
Types of Quality Control
QC can be achieved through:
Internal Quality Control (IQC)
 External Quality Assessment (EQA)
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Internal Quality Control Program
• An internal quality control program depend
on the use of:
• internal quality control (IQC) specimens,
• LJ Control Charts,
• and the use of statistical methods for
interpretation.
M. Zaharna Clin. Chem. 2015
Impact of Internal Quality Control
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Continuous detection and rectification of
the Analytical Process.
◦ Reagent-Equipment-Personnel-Specimen
◦ Ensure the degree of both precision & accuracy
of your results
◦ Assure the quality and clinical applicability of
your laboratory reports
◦ Generate objective evidence of your analytical
performance.
External Quality Assessment (EQA)
Inter laboratory
 Complimentary to IQC
 Maintain the long-term accuracy of the
analytical process.
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Impact of External Quality Assessment
Continuous quality improvement
 Independent laboratory audit
 Objective evidence of a laboratory
analytical performance
 Assess the results which the laboratory
delivers
 Encourages the search for the root cause
of unacceptable performance.
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