Quality Assurance in the clinical laboratory

1. Quality Assurance in the clinical laboratory

2. Why do laboratory errors occur? Inadequate Attention To Detail Understaffed Poor Sample Control Poor Results Verification Poor Workload Management 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. QM 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 • 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 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 onCorrect reference data, and at the Right price. Quality Assurance (QA)- WHO Definition

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- Preanalyticalerrors • This includes all the activities performed before the actual work (examination, analysis) is started

16. B- Analytical errors

17. C- Post Analytical errors

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

24. 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

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 • Unpreciseor malfunctioning dilutors and pipettes • Reagents that lost their activity • Quantitative tests being read at an incorrect wavelength • Reagents are not prepared from sufficiently purechemicals

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

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.

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 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.

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: • 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, ofloxacinand vancomycin are just some of the medications that require adjustment of dosage based on the creatinine and creatinine clearance values

39. 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.

40. C- Detection of Errors • Delta Checks • use measurements from two consecutive samples produced within fairly short time intervals. • The changes in concentration of the analytesare recorded. • If these changes exceed established limits (based on maximum expected physiological change between the sample collection times), then the analytemeasurement 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.

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.