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Quality Assurance in the clinical laboratory Quality Assurance in the clinical laboratory

Quality Assurance in the clinical laboratory - PowerPoint Presentation

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Quality Assurance in the clinical laboratory - PPT Presentation

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

errors quality mol error quality errors error mol results precision accuracy bias creatinine analytical systematic true constant sample test

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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.

42