1. Quality Assurance in the clinical laboratory

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

3. Quality Quality is defined as:
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:
Safe, comfortable phlebotomy experiences provided to all patients
Properly collected and labelled specimens provided for testing
Timely, accurate test results and reports provided to physicians and other healthcare personnel
Informative and helpful consultation and answers to questions

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:
The input of the clinician’s ordering of a test
Through the activities of sample collection,
Sample transport,
Sample receiving and accessioning,
Testing,
Review,
Report preparation,
Report delivery and
Ends with the output of accurate test results and interpretation back to the clinician

6. Quality as a target The aspects of quality are:
Quality control (QC),
Quality assurance (QA) and
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

7. Part of QM focuses on fulfilling quality requirements
Coordinated activities to direct and control an organization with regard to quality
QA: Part of QM focuses on providing confidence that quality requirements will be fulfilled QC
Part of QM focuses on fulfilling quality requirements

8. Quality Management System
Describes the activities that are necessary to achieve quality objectives and requirements.
Quality Management System
Provides the organizational structure, processes, procedures, and tools for implementing the activities necessary to achieve the quality objectives and requirements.

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

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

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:
safety requirements,
staff training and competence assessment,
equipment management,
storing and managing reagents and supplies,
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

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:
Staff qualifications and training (initial and in-service)
Proficiency testing (internal and/or external)
Sample collection, handling, and storage
Documented, standardized, and validated procedures
Reagent and instrument reliability
Authenticated reference material

13. Quality Assurance (QA)- WHO Definition
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.

14. 1- Sources of Error Errors can occur at various stages in the process:
Pre-analytical, occurring outside the laboratory,
Analytical, occurring within the laboratory,
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.
62%
15%
23%

15. A- Preanalytical errors
This includes all the activities performed before the actual work (examination, analysis) is started
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

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

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

18. 2- Aspects of a Good Quality Assurance Program
A good quality assurance program has three major aspects:
Preventive activities
Assessment Procedures
Corrective actions

19. A- Preventive Activities
This helps to prevent error before it occurs by:
Improving accuracy and precision
Method selection
Careful laboratory design
Hiring of competent personnel
Development of comprehensive procedure manuals
Effective preventive maintenance programs

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:
The testing of quality control material
Performing instrument function checks
Participating in proficiency testing programs (e.g. survey programs of accrediting agencies)

21. C- Corrective Actions Correct errors after discovery
Communication with the users of laboratory's services
Review of work
Troubleshooting of instrument problems

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

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:
standard deviation;
variance;
coefficient of variation
 coefficient of variation: standard deviation divided by the mean and expressed as a percentage

24. Good Accuracy Good Precision
3- Accuracy and Precision
Neither
Good precision
Nor Accuracy
Good Accuracy Good Precision
Good Precision Only

25. 3- Accuracy and Precision
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

26. 3- Accuracy and Precision
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 26

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

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
Random errors
Systematic errors

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:
Carelessness,
Inattention,
when taking short cuts in procedures,
Mislabeling specimens,
Incorrect filing of reports,
Reporting of wrong result to the wrong patient

30. B- Systematic Errors Errors within the test system of methodology
Affect the accuracy of results
Causes the mean of a data set to differ from the accepted value
Examples include:
Incorrect instrument calibration
Unprecise or malfunctioning dilutors and pipettes
Reagents that lost their activity
Quantitative tests being read at an incorrect wavelength
Reagents are not prepared from sufficiently pure chemicals

31. B- Systematic Errors Types of systematic errors
Proportional systematic error or bias
It grows larger as the concentration of analyte grows
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

32. B- Systematic Errors
Recovery Experiment: proportional systematic error
Interference Experiment: constant systematic errors

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.

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.
Thus, if the upper limit for creatinine in the reference interval were 106 μmol/L = 1.2

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

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.

38. 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:
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;
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

40. C- Detection of Errors Analyzing standard samples
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
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
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.

41. C- Detection of Errors Delta Checks
use measurements from two consecutive samples produced within fairly short time intervals.
The changes in concentration of the analytes are recorded.
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.
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.

42. 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.