Quality Control in a Medical Testing Laboratory

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Basic QC and its need in a Medical testing Laboratory

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  • 8-5
  • Quality Control in a Medical Testing Laboratory

    1. 1. 1.Quality Control 2.Quality Assurance 3.Quality Assessment
    2. 2. → Quality control in the medical laboratory is a statistical process used to monitor and evaluate the analytical process that produces patient results. → Quality control refers to the measures that must be included during each assay run to verify that the test is working properly
    3. 3. → Quality Assurance is defined as the overall program that ensures that the final results reported by the laboratory are correct. i. Quality assurance means quality enhancement ii. Quality assurance aims at ensuring that the data provided are reliable and relevant iii. Quality assurance involves all measures that can be taken to improve laboratory efficiency and effectiveness. iv. It ensures laboratory performance with minimum risk for laboratory workers and gives maximum benefit to the individual and community
    4. 4. The Quality Assurance Cycle Patient/Client Prep Sample Collection Reporting •Data and Lab Management •Safety •Customer Service Personnel Competency Test Evaluations Sample Receipt and Accessioning Record Keeping Quality Control Testing Sample Transport
    5. 5. Quality Assurance vs. Quality Control Quality Assurance An overall management plan to guarantee the integrity of data (The “system”) Quality Control A series of analytical measurements used to assess the quality of the analytical data (The “tools”) “The aim of quality control is simply to ensure that the results generated by the test are correct. However, quality assurance is concerned with much more: that the right test is carried out on the right specimen, and that the right result and right interpretation is delivered to the right person at the right time”
    6. 6. → Also known as proficiency testing → Quality Assessment is a means to determine the quality of the results generated by the laboratory → Quality Assessment is a challenge to the QA and QC programs → Quality Assessment may be external or internal, examples of external programs include EQAS, RIQAS, etc
    7. 7. • Support provision of high quality health-care → Reduce morbidity → Reduce mortality → Reduce economic loss • Ensure credibility of lab • Generate confidence in lab results
    8. 8. Sample Transport Sample handling Sample Collection Sample receiving Analysis Patient preparation Outside laboratory Within laboratory Requisition Results Patient Doctor Reports
    9. 9. → Specimen → Collection technique → Storage and transportation → Quantity → Labeling → Mismatch of sample → Laboratory : No necessary test capacity
    10. 10. PROFICIENCY OF PERSONNEL: Education, Training, Aptitu de, Competence, Commitm ent, Adequate number, CME, Supervision, Motivation USE OF APPROPRIATE CONTROLS: • Internal: Labs, Calibrated against national • External: Supplied by manufacturer, National, International Assessment REAGENTS STABILITY, INTEGRITY AND EFFICIENCY: Stable, Efficient, Desired quality, Continuously available, Validated DOCUMENTATION: All the written policies, plans, procedures, inst ructions and records, quality control procedures and recorded test results involved in providing a service or the manufacture of a product EQUIPMENT RELIABILITY: Meet technical needs, Compatible, User & maintenance friendly, Cost effective, Validated SPECIFICITY & SENSITIVITY OF SELECTED TEST: Adequate ST, Sufficient SP, cost effective, compatible with, available infrastructure and expertise, interpretable, meets the needs/ objectives, validated Procedural reliability using Standard Operating Procedures
    11. 11.  If you have not documented it, you have NOT done it …  If you have not documented, it is a RUMOUR !!!
    12. 12. • Ensures processes and outcomes are traceable • Processes can be audited, thus external assessments can take place • Tool for training • Reminds you what to do next
    13. 13. It is a comprehensively written document that describes the laboratory procedure and all other related issues  Essential for ensuring uniformity in laboratory procedures 
    14. 14.  Right recording and reporting  Right interpretation  Range of normal values  Right turnaround time  Report to right user
    15. 15. True Value The known, accepted value of a quantifiable property Measured Value The result of an individual’s measurement of a quantifiable property
    16. 16. Accuracy Precision How well a measurement agrees with an accepted value How well a series of measurements agree with each other
    17. 17. • The degree of fluctuation in the measurements is indicative of the “precision” of the assay. • The closeness of measurements to the true value is indicative of the “accuracy” of the assay. • Quality Control is used to monitor both the precision and the accuracy of the assay in order to provide reliable results.
    18. 18.  True value - The known, accepted value of a quantifiable property  Accepted true value - the value approximating the true value, the difference between the two values is negligible.  Error - the discrepancy between the result of a measurement and the true (or accepted true value).
    19. 19. • Input data required - such as standards used, calibration values, and values of physical constants. • Inherent characteristics of the quantity being measured • Instruments used - accuracy, repeatability. • Observer fallibility - reading errors, blunders, equipment selection, analysis and computation errors. • Environment - any external influences affecting the measurement. • Theory assumed - validity of mathematical methods and approximations.
    20. 20. Systematic Error Random Errors Avoidable error due to controllable variables in a measurement. Unavoidable errors that are always present in any measurement. Impossible to eliminate
    21. 21. • An error which, in the course of a number of measurements of the same value of a given quantity, remains constant when measurements are made under the same conditions, or varies according to a definite law when conditions change. • Systematic errors create a characteristic bias in the test results and can be accounted for by applying a correction. • Systematic errors may be induced by factors such as variations in incubation temperature, blockage of plate washer, change in the reagent batch or modifications in testing method.
    22. 22. • The standard deviation (SD) is the square root of the variance • it is the square root of the average squared deviation from the mean • SD is commonly used (rather than the variance) since it has the same units as the mean and the original observations • SD is the principle calculation used in the laboratory to measure dispersion of a group of values around a mean
    23. 23. S (x x ) N 1 1 2 mg/dl variance
    24. 24. For a set of data with a normal distribution, a value will fall within a range of: • +/- 1 SD 68.2% of the time • +/- 2 SD 95.5% of the time • +/- 3 SD 99.7% of the time X Frequency • 68.2% 95.5% 99.7% -3s- 2s -1s Mean +1s +2s +3s
    25. 25. • In general, laboratories use the +/- 2 SD criteria for the limits of the acceptable range for a test • When the QC measurement falls within that range, there is 95.5% confidence that the measurement is correct • Only 4.5% of the time will a value fall outside of that range due to chance; more likely it will be due to error
    26. 26. +3SD +2SD +1SD 115 110 105 Mean 100 -1SD -2SD -3SD 95 90 85 80 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Day
    27. 27. • Ideally should have control values clustered about the mean (+/-2 SD) with little variation in the upward or downward direction • Imprecision = large amount of scatter about the mean. Usually caused by errors in technique • Inaccuracy = may see as a trend or a shift, usually caused by change in the testing process • Random error = no pattern. Usually poor technique, malfunctioning equipment
    28. 28. • Use Levey-Jennings chart • Plot control values each run, make decision regarding acceptability of run • Monitor over time to evaluate the precision and accuracy of repeated measurements • Review charts at defined intervals, take necessary action, and document
    29. 29. • Consider using Westgard Control Rules • Uses premise that 95.5% of control values should fall within ±2SD • Commonly applied when two levels of control are used • Use in a sequential fashion
    30. 30. • “Multirule Quality Control” developed by Dr. James O. Westgard based on statistical concepts • Uses a combination of decision criteria or control rules • Allows determination of whether an analytical run is “in-control” or “out-of-control” Dr. Westgard
    31. 31.  12S rule  13S rule  22S rule  R4S rule  41S rule  10X rule Used when 2 levels of control material are analyzed per run.
    32. 32. • “warning rule” • One of two control results falls outside ±2SD • Alerts tech to possible problems • Not cause for rejecting a run • Must then evaluate the 13S rule
    33. 33. +3SD +2SD +1SD 12S rule violation Mean -1SD -2SD -3SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Day
    34. 34. • If either of the two control results falls outside of ±3SD, rule is violated • Run must be rejected • If 13S not violated, check 22S
    35. 35. +3SD +2SD +1SD Mean 13S rule violation -1SD -2SD -3SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Day
    36. 36. • 2 consecutive control values for the same level fall outside of ±2SD in the same direction, or • Both controls in the same run exceed ±2SD • Patient results cannot be reported • Requires corrective action
    37. 37. 22S Rule = Reject the run when 2 consecutive control measurements exceed the same +2SD or -2SD control limit +3SD +2SD +1SD Mean 22S rule violation -1SD -2SD -3SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Day
    38. 38. • One control exceeds the mean by –2SD, and the other control exceeds the mean by +2SD • The range between the two results will therefore exceed 4 SD • Random error has occurred, test run must be rejected
    39. 39. +3SD +2SD +1SD Mean R4S rule violation -1SD -2SD -3SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Day
    40. 40. • Requires control data from previous runs • Four consecutive QC results for one level of control are outside ±1SD, or • Both levels of control have consecutive results that are outside ±1SD
    41. 41. +3SD +2SD +1SD Mean -1SD 10x rule violation -2SD -3SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Day
    42. 42. • Warning rule = use other rules to inspect the control points • Rejection rule = “out of control” • Stop testing • Identify and correct problem • Repeat testing on patient samples and controls • Do not report patient results until problem is solved and controls indicate proper performance • Solving “out-of-control” problems  Policies and procedures for remedial action  Troubleshooting  Alternatives to run rejection
    43. 43.  It is a process of inspection of laboratories and their licensing by a third party to ensure conformity to pre-defined criteria  Very very long task (it may take around 2-3 years to follow the roadmap)  Last step of the entire process  Quality assurance (procedures, way of working)  IQC  EQC  Networking of the laboratories  … and then only accreditation if 1-4 completed
    44. 44. • Quality is a lousy idea …if its only an Idea • Quality assurance measures what a lab can do to improve reliability • Validate all test accuracy and reliability • ALWAYS, ALWAYS, ALWAYS: DOCUMENT THE PROBLEM TAKEN!!!!! AND CORRECTIVE ACTIONS

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