Why do laboratory errors occur Quality Control amp Assessment Poor Workload Management Understaffed Nonvalidated Tests Inadequate Attention To Detail Time Pressures Poor Results ID: 737134
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Slide1
Quality Assurance in the clinical laboratory Slide2
Why do laboratory errors occur?
Quality
Control &
Assessment
PoorWorkload Management
Understaffed
Non-validatedTests
InadequateAttentionTo Detail
Time Pressures
Poor Results Verification
Poor Sample Control
Monitoring all areas of the work in the laboratory
will decrease errorsSlide3
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 patientsProperly collected and labelled specimens provided for testingTimely, accurate test results and reports provided to physicians and other healthcare personnelInformative and helpful consultation and answers to questions
3Slide4
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 andEnds with the output of accurate test results and interpretation back to the clinician4Slide5
5Slide6
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 achieved6Slide7
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
requirementsSlide8
Quality Management
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.
8Slide9
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 testedQC neither implies nor verifies that those accurate results necessarily belong to the patient whose name is on the sampleQC will never prevent a patient misidentification or a sample switch9Slide10
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 customersThis is different from the question weather lab. test results are accurateTherefore, QA is bigger than QC and covers all the preanalytical, analytical and postanalytical processes
10Slide11
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
11Slide12
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
storageDocumented, standardized, and validated proceduresReagent and instrument reliabilityAuthenticated reference material 12Slide13
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
13Slide14
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 processThis means a lot more than ensuring that the analysis is performed correctly.
14
62%
15%
23%Slide15
PROCESS
POTENTIAL ERRORS
Test ordering
Inappropriate test
Handwriting not legibleWrong patients IDSpecial requirements not specifiedSpecimen acquisition
Incorrect tube or containerIncorrect patient ID
Inadequate volumeInvalid 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 startedSlide16
Analytical Measurement
Instrument not calibrated correctly
Specimens mix – up
Incorrect volume of specimen
Interfering substances presentInstrument precision problem
B- Analytical
errors
PROCESS
POTENTIAL ERRORSSlide17
Test interpretation
Previous values not available for comparison
Test reporting
Wrong patient ID
Report not legibleReport delayed
Transcription error
C- Post
Analytical errors
PROCESS
POTENTIAL ERRORSSlide18
2- Aspects
of
a Good Quality Assurance Program
A good quality assurance program has three major aspects:Preventive activities Assessment Procedures Corrective actions
18Slide19
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 programs19Slide20
B- Assessment Procedures
Monitor the analytical process
Determine the type of error
Determine the amount of error Determine the change in accuracy and precisionThese activities include: The testing of quality control material Performing instrument function checks Participating in proficiency testing programs (e.g. survey programs of accrediting agencies)
20Slide21
C- Corrective Actions
Correct errors after discovery
Communication with the users of laboratory's services
Review of work Troubleshooting of instrument problems 21Slide22
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 substance22Slide23
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 truthA procedure can be precise, as determined by repeat analysis, but the result can be inaccurateThree terms are widely used to describe the precision of a set of replicate data:standard deviation;
variance;coefficient of variation23Slide24
Good
Accuracy Good Precision
Good Precision Only
Neither
Good
precision
Nor
Accuracy
3- Accuracy and Precision
24Slide25
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
25Slide26
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
26Slide27
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 precision27Slide28
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 expectedRandom errorsSystematic errors
28Slide29
A- Random Errors
Occur
without prediction or
regularityAffect measurement of precision and causes data to be scattered moreRandom 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 patient29Slide30
B- Systematic Errors
Errors within the test system of
methodology
Affect the accuracy of resultsCauses 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
wavelengthReagents are not prepared from sufficiently purechemicals
30Slide31
B- Systematic Errors
Types of systematic errors
Proportional
systematic error or bias It grows larger as the concentration of analyte growsConstant systematic error "constant bias"
A constant amount over the entire range of the analysis processThe magnitude of a constant error does not depend on the size of the quantity measured31Slide32
B- Systematic Errors
32Slide33
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. 33Slide34
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. 34Slide35
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
35Slide36
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 reportedvalue 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 withdiagnosis as does the constant bias: false negative results and false positive results.
36Slide37
37Slide38
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 38Slide39
39Slide40
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 methodThe 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 methodsPerforming blank determinationsVarying the Sample SizeAs 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.
40Slide41
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, oneor both of the samples are at fault and new samples must becollected. 41Slide42
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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