quality

1. QUALITY ASSURANCE
IN THE CLINICAL
LABORATORY
BY PEREZ PRINCE

2. Why do laboratory errors occur?
Quality
Control &
Assessment
Poor
Workload
Management
Understaffed
Non-validated
Tests
Inadequate
Attention
To Detail
Time
Pressures
Poor Results
Verification
Poor
Sample Control
Monitoring all areas of the work in the laboratory will decrease errors

3. Quality
 Quality is defined as:
o The degree to which a product or service meets requirements
 Laboratories need to provide quality to their
customers in many forms, most importantly the
following:
o Safe, comfortable phlebotomy experiences provided to all
patients
o Properly collected and labelled specimens provided for testing
o Timely, accurate test results and reports provided to
physicians and other healthcare personnel
o Informative and helpful consultation and answers to questions
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4. The laboratory’s path of workflow
 The laboratory’s path of workflow is the core business in
transforming a test order into the results report
 It begins with:
o The input of the clinician’s ordering of a test
o Through the activities of sample collection,
o Sample transport,
o Sample receiving and accessioning,
o Testing,
o Review,
o Report preparation,
o Report delivery and
o Ends with the output of accurate test results and interpretation
back to the clinician
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5. 5

6. Quality as a target
 The aspects of quality are:
o Quality control (QC),
o Quality assurance (QA) and
o Quality management system (QMS)
 When these are properly implemented and the
facility’s management and staff are effectively
involved in monitoring and maintaining the QMS,
true management has been achieved
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7. 7
QA: Part of QM focuses on
providing confidence that
quality requirements will be
fulfilled
QM
Coordinated activities to direct and
control an organization with regard
to quality
QC
Part of QM
focuses on
fulfilling
quality
requirements

8.  Quality Management
o Describes the activities that are necessary to
achieve quality objectives and requirements.
 Quality Management System
o Provides the organizational structure, processes,
procedures, and tools for implementing the
activities necessary to achieve the quality
objectives and requirements.
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9. Quality Control (QC)
 The quality control is the target
 It is the innermost circle of the target because the
target for each and every laboratory test is accurate
results
 QC provides a high degree of confidence that
testing and examination results are accurate for the
batch of samples being tested
 QC neither implies nor verifies that those accurate
results necessarily belong to the patient whose
name is on the sample
 QC will never prevent a patient misidentification or a
sample switch
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10. Quality Assurance (QA)
 The next outer ring of the target
 QA is a set of planned actions to provide confidence
that processes other than that influence the quality of
the laboratory’s results and reports are working as
expected
 QA answers the question, How does the laboratory
know it is delivering a high quality service to its
customers
 This is different from the question weather lab. test
results are accurate
 Therefore, QA is bigger than QC and covers all the
preanalytical, analytical and postanalytical processes
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11. Quality Management System (QMS)
 It is the outermost ring of the target, which includes the
management activities needed to ensure that the lab.
workflow proceeds smoothly to provide lab. services to
customers and patients
 Management activities including:
o safety requirements,
o staff training and competence assessment,
o equipment management,
o storing and managing reagents and supplies,
o lab. documents and records,
 All support the laboratory’s ability to meet regulatory and
accreditation requirement and fulfill the need for
accurate results in a timely manner
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12. Quality Assurance (QA)- Definition
 Quality assurance is the coordinate process of
providing the best possible service to the patient
and physician
 The components of a QA program include, but are
not limited to, the following:
o Staff qualifications and training (initial and in-service)
o Proficiency testing (internal and/or external)
o Sample collection, handling, and storage
o Documented, standardized, and validated procedures
o Reagent and instrument reliability
o Authenticated reference material
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13. Quality assurance has been defined by WHO as:
• The total process whereby the quality of the laboratory reports
can be guaranteed.
It has been summarized as:
• The Right result,
• At the Right time,
• On the Right specimen,
• From the Right patient,
• With the result interpretation based on Correct reference data,
• and at the Right price.
Quality Assurance (QA)- WHO Definition
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14. 1- Sources of Error
• Errors can occur at various stages in the process:
A. Pre-analytical, occurring outside the laboratory,
B. Analytical, occurring within the laboratory,
C. Post-analytical, whereby a correct result is generated
but is incorrectly recorded in the patient's record,
• Errors can be minimized by:
• Careful adherence to robust, agreed protocols at every
stage of the testing process
• This means a lot more than ensuring that the analysis is
performed correctly.
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62%
15%
23%

15. PROCESS POTENTIAL ERRORS
Test ordering
• Inappropriate test
• Handwriting not legible
• Wrong patients ID
• Special requirements not specified
Specimen
acquisition
• Incorrect tube or container
• Incorrect patient ID
• Inadequate volume
• Invalid specimen (hemolysed or diluted)
• Collected at wrong time
• Improper transport conditions
A- Preanalytical errors
• This includes all the activities performed before the actual
work (examination, analysis) is started

16. Analytical
Measurement
• Instrument not calibrated correctly
• Specimens mix – up
• Incorrect volume of specimen
• Interfering substances present
• Instrument precision problem
B- Analytical errors
PROCESS POTENTIAL ERRORS

17. Test interpretation
• Previous values not available for
comparison
Test reporting
• Wrong patient ID
• Report not legible
• Report delayed
• Transcription error
C- Post Analytical errors
PROCESS POTENTIAL ERRORS

18. 2- Aspects of a Good Quality Assurance
Program
A good quality assurance program has
three major aspects:
A. Preventive activities
B. Assessment Procedures
C. Corrective actions
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19. A- Preventive Activities
This helps to prevent error before it occurs
by:
o Improving accuracy and precision
o Method selection
o Careful laboratory design
o Hiring of competent personnel
o Development of comprehensive procedure
manuals
o Effective preventive maintenance programs
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20. B- Assessment Procedures
 Monitor the analytical process
 Determine the type of error
 Determine the amount of error
 Determine the change in accuracy and precision
 These activities include:
o The testing of quality control material
o Performing instrument function checks
o Participating in proficiency testing programs (e.g.
survey programs of accrediting agencies)
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21. C- Corrective Actions
 Correct errors after discovery
 Communication with the users of laboratory's
services
 Review of work
 Troubleshooting of instrument problems
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22. 3- Accuracy and Precision
 Accuracy is the measure of "truth" of a result
 Accurate results reflect the "true" or correct
measure of an analyte or identification of a
substance
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23. 3- Accuracy and Precision
 Precision is the expression of the variability of analysis,
reproducibility of a results, or an indication of the amount
of random error
 Precision is completely independent of accuracy or truth
 A procedure can be precise, as determined by repeat
analysis, but the result can be inaccurate
 Three terms are widely used to describe the precision of
a set of replicate data:
o standard deviation;
o variance;
o coefficient of variation
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24. Good Accuracy
Good Precision
Good Precision
Only
Neither
Good precision
Nor Accuracy
3- Accuracy and Precision
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25.  Both methods are
equally precise, but in
method D the mean
value differs from the
true value
 The mean for method
C is equal to the true
value
 Both methods are
equally precise, but
method C is more
accurate
3- Accuracy and Precision
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26. • The graph shows the
distribution of results for
repeated analysis of the
same sample by
different methods
• The mean value is the
same in each case, but
the scatter about the
mean is less in method
A than in method B
• Method A is, therefore,
more precise
3- Accuracy and Precision
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27. 4- Types of Errors
When Errors Occur ?
 Errors occur when there is a loss of accuracy
and precision
 A primary goal of quality assurance is to reduce
and detect errors or to obtain the best possible
accuracy and precision
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28. 4- Types of Errors
 Mistakes jeopardize patient care and must be
detected and avoided at all times
 An error is the difference between the result
obtained and the result expected
A. Random errors
B. Systematic errors
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29. A- Random Errors
 Occur without prediction or regularity
 Affect measurement of precision and causes
data to be scattered more
 Random errors occur as the result of:
o Carelessness,
o Inattention,
o when taking short cuts in procedures,
o Mislabeling specimens,
o Incorrect filing of reports,
o Reporting of wrong result to the wrong patient
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30. B- Systematic Errors
 Errors within the test system of methodology
 Affect the accuracy of results
o Causes the mean of a data set to differ from the
accepted value
 Examples include:
o Incorrect instrument calibration
o Unprecise or malfunctioning dilutors and pipettes
o Reagents that lost their activity
o Quantitative tests being read at an incorrect
wavelength
o Reagents are not prepared from sufficiently pure
chemicals
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31. B- Systematic Errors
Types of systematic errors
a) Proportional systematic error or bias
 It grows larger as the concentration of analyte grows
b) Constant systematic error "constant bias"
 A constant amount over the entire range of the
analysis process
 The magnitude of a constant error does not depend
on the size of the quantity measured
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32. B- Systematic Errors
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33. B- Systematic Errors
 In the analytical phase, calibrators do not always
translate the signal into exactly the same set of
values that a purified standard would.
 What makes a matrix material different from a
standard is the analyte of interest plus other
analytes are bound or complexed with naturally
occurring constituents.
 The naturally occurring constituents may alter the
way the analytical method interacts with the analyte
of interest, altering the signal from the sensor.
 The mistranslation results in a systematic error.
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34. B- Systematic Errors
 If the error, for example for creatinine, were high or low and
did not depend on the value for creatinine over the entire
range of results, then the error is constant.
 To illustrate the constant error, take a value of 115 μmol/L of
creatinine.
 If there is a constant error or bias of 27 μmol/L, then the
reported value would be 88 μmol/L instead of 115 μmol/L.
 Further, if the true value of creatinine were 71 μmol/L, then
the reported value would be 44 μmol/L; and if the true value of
creatinine were 398 μmol/L, then the reported value would be
371 μmol/L.
 The deviation from the true value would always be the same,
what differs in the error for each of these examples is the
percentage of error that occurs.
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35. B- Systematic Errors
 For the 115 μmol/L the percentage error is a negative 23
%, for the 71 μmol/L, the percentage error is a negative
37 % and for the 398 μmol/L of creatinine, the
percentage error is a negative 7 %.
 The impact of a constant bias decreases with an
increasing true value of the analyte.
 More important is the effect that the error has on the
interpretation of the laboratory result.
 If the bias is negative and the true value falls within the
reference interval and values below the reference
interval have no clinical impact, then
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36. B- Systematic Errors
 For a proportional bias of 10 % and creatinine, at 71 μmol/L
true value, the reported value would be 78 μmol/L.
 At a creatinine concentration of 106 μmol/L, the reported
value would be 117 μmol/L; while at a creatinine
concentration of 398 μmol/L, the reported value would be 438
μmol/L, and so on.
 The proportional bias demonstrates a constant percentage of
error over all the values of the reportable range.
 The percentage bias can be positive or negative.
 Typically the proportional bias is reported as a slope.
 A positive bias of 10% would have a slope of 1.1, while a
negative bias of 10 % would have a slope 0.9.
 The proportional bias can cause the same problems with
diagnosis as does the constant bias: false negative results
and false positive results.
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37. B- Systematic Errors
 For example, if pharmacy needed to adjust the dosage
of a drug based on the patient’s renal clearance of that
drug, then:
o if the reported creatinine value was 20 % higher than the
true concentration, the calculated dosage would be too low
and the patient would not receive a sufficient amount of
drug;
o likewise, if the reported creatinine value was 20 % lower
than the true value, the patient would be overdosed on the
drug and run the risk of becoming drug toxic.
 Ciprofloxacin, digoxin, gentamicin, lithium, ofloxacin and
vancomycin are just some of the medications that
require adjustment of dosage based on the creatinine
and creatinine clearance values
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39. C- Detection of Errors
 Analyzing standard samples
o The best way to estimate the bias of an analytical method is by
analyzing standard reference materials, materials that contain one
or more analytes at well-known or certified concentration levels
 Using an independent analytical method
o The independent method should differ as much as possible from
the one under study to minimize the possibility that some common
factor in the sample has the same effect on both methods
 Performing blank determinations
 Varying the Sample Size
o As the size of a measurement increases, the effect of a constant
error decreases. Thus, constant errors can often be detected by
varying the sample size.
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40. C- Detection of Errors
 Delta Checks
o use measurements from two consecutive samples produced within
fairly short time intervals.
o The changes in concentration of the analytes are recorded.
o If these changes exceed established limits (based on maximum
expected physiological change between the sample collection
times), then the analyte measurement is repeated on both
samples.
o If the second measurement set also exceeds the change limit, one
or both of the samples are at fault and new samples must be
collected.
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41. 5- Benefits of an Effective quality
Assurance Program
 Correct and timely presentation of data to the physician
 Improvement of precision and accuracy
 Early detection of mistakes
 More efficient and cost effective use of materials and
personnel
 Meeting the requirements of inspection and accreditation
agencies
 Development of accurate and concise procedures and
manuals
 Measure of productivity of personnel and
instrumentation.
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