Quality Control.pptx for laboratory uses

Laboratory quality control theory

1. Quality Control Quality control in clinical biochemistry laboratory refers to the reliability of investigative service. Any error in the laboratory will jeopardize the lives of patients. It is therefore utmost important that the laboratory errors are identified and rectified. Quality control comprises of four interrelated factors namely precision, accuracy, specificity and sensitivity.

2. Precision refers to the reproducibility of the result when the same sample is analysed on different occasions (replicate measurements) by the same person. For instance, the precision is good, if the blood glucose level is 78, 80 and 82 mg/dl on replicates. Accuracy means the closeness of the estimated result to the true value e.g., if true blood urea level is 50 mg/dl, the laboratory reporting 45 mg/dl is more accurate than the one reporting 35 mg/dl. Specificity refers to the ability of the analytical method to specifically determine a particular parameter e.g., glucose can be specifically estimated by enzymatic glucose oxidase method. Sensitivity deals with the ability of a particular method to detect small amounts of the measured constituent

3. Contd … Recall is also called sensitivity Precision is also called Positive Predictive Value (PPV). The difference between the  mean of the measurements and the reference value is the  bias . Establishing and correcting for bias is necessary for calibration. Precision includes: repeatability   — the variation arising when all efforts are made to keep conditions constant by using the same instrument and operator, and repeating during a short time period; and reproducibility   — the variation arising using the same measurement process among different instruments and operators, and over longer time periods.

4. METHODS OF QUALITY CONTROL: Internal quality control refers to the analysis of the same pooled sample on different days in a aboratory , the results should vary within a narrow range. External quality control deals with the analysis of a sample received from outside, usually from a national or regional quality control centre . The results obtained are then compared

5. Westgard Multirules & L-J Chart.

6. BIOCHEMISTRY QUALITY CONTROL PROCEDURE Following Procedure is followed in Biochemistry: A. Regular use of QC material of renowned QC kit manufacturer B. Participation in EQAS / inter-laboratory comparison C. Replicate testing of retained sample (same day) D. Retesting of retained sample (previous day) E. Correlation of results F. Lot Verification of Reagents. G. Precision Check H. Linearity Check I. Carry Over Check J. Harmonization

7. A. REGULAR USE OF QC MATERIAL OF RENOWNED QC KIT MANUFACTURER: Laboratory runs QC as per Quality Control Plan (IQCITY/FM/76). Laboratory interprets QC results by using statistical technique such as L-J chart. Where any control value is found to deviate from Westgard’s Multi QC rules, cause is identified & corrective action is taken. Consultant Biochemist reviews it and records are maintained accordingly. 1. PLAN FOR RUNNING COMMERCIAL CONTROL : Dimension EXL: Two levels of control once daily in morning & one more level in evening for all the parameters under the scope of accreditation. Dimension RXL: Two levels of control once daily in morning & one more level in evening for all the parameters under the scope of accreditation Advia Centaur CP: Two levels of control once on the day of testing for all the parameters under the scope of accreditation. Hb Vario : Two levels of control once on the day of testing for all the parameters under the scope of accreditation

8. PROCEDURE FOR HANDLING INTERNAL COMMERCIAL CONTROL : Receive the sample and confirm Lot No. and Expiry Date with reference values specific to the machine. Make a note of the storage temperature. Controls are stored at 2-8 o C in specified Biochemistry Refrigerator. Controls vials are kept at room temperature for a maximum period of 1 hour. Record sample validity period after opening or reconstitution. Prepare aliquots (if applicable) and store in recommended temperature. Prepare aliquots (if applicable) and store in recommended temperature. Internal Controls are run on a daily basis as per Quality Control Plan. Only authorized personnel in each department run controls. Values observed are recorded and plotted in L-J charts. Observe for any violation of the Multi QC Deviation Rule and proceed accordingly

9. 3. INTERPRETATION OF QUALITY CONTROL DATA QC Results are reviewed & if any of the parameters run out of 3SD or do not follow any of the MULTI QC RULES described below, then a QC Level is run for the second time. If the results still do not fall within the expected range, then the test parameter is calibrated, QC checked & samples run. All the QC values are checked and filled and reviewed by the Consultant Biochemist. Calculation of CV %: The standard deviation (SD) of a set of results divided by the mean result is expressed as a percentage CV. In automated analyzer percentage CV is auto calculated along with L-J chart. CV% is inversely proportional to the precision level of the instrument, i.e., higher the CV% lower the precision level and vice versa. CV% is calculated using the formula: CV % = (SD / MEAN) X 100 Where SD = Standard Deviation

10. The rules to be followed when 1 level QC material are used: Reject QC if: 1 2S Rule = A warning to trigger careful inspection of the control data. Westgard Rejections : 1 3S - When a single control measurement exceeds the ± 3SD control limit. 2 2S - Reject the run when 2 consecutive control measurements exceed the same side of ± 2SD control limit. R 4S - Reject the run when 1 control measurement exceed the +2SD and the other exceeds the -2SD control limit. 4 1S - Four consecutive QC results for one level of control of outside ± 1 SD control limit

11. Procedure to be followed when QC results are “out of control”: Follow step wise till QC results are “in control” 1. Repeat with same aliquot of QC. 2. Repeat with new aliquot of QC. 3. Reconstitute new QC. 4. Calibrate with current calibration pack and same reagent. 5. Calibrate with new calibration pack and same reagent. 6. Check generation no. of slide/ lot no. Cartridge/ reagent expiry / on board reagent expiry. 7. Use new reagent. 8. Calibrate with new calibration pack and new reagent 9. Contact respective Application Specialist

12. " within run" and "across run" In a biochemistry lab, the terms "within run" and "across run" refer to different types of variability or precision assessments in experimental or analytical procedures, particularly in assays or measurements (e.g., enzyme activity, protein quantification, or other biochemical tests). Here's a concise explanation:

13. Within Run: Definition : Refers to the variability or precision of measurements taken within a single experimental run or batch. This assesses how consistent the results are when the same sample is tested multiple times under identical conditions in one session. Context : For example, if you measure the concentration of a protein in a sample 10 times in one go using the same equipment, reagents, and conditions, the variability in those measurements is the "within-run" variability. Purpose : Evaluates the repeatability of the assay, i.e., how consistent the method is when performed in a single setting. Example : Running a standard curve for an ELISA assay and measuring the absorbance of a single sample multiple times in one plate. Statistical Measure : Often expressed as the coefficient of variation (CV) , calculated as (standard deviation / mean) × 100 for the replicate measurements.

14. Across Run: Definition : Refers to the variability or precision of measurements taken across multiple experimental runs or batches, typically conducted on different days, with different reagent preparations, or by different operators. Context : For example, if you measure the same protein sample’s concentration on three different days with freshly prepared reagents, the variability in those results is the "across-run" variability. Purpose : Evaluates the reproducibility of the assay, i.e., how consistent the method is over time or under slightly varying conditions. Example : Repeating the same ELISA assay on different days or with different batches of reagents to check consistency. Statistical Measure : Also uses the coefficient of variation (CV) but calculated across the means of multiple runs.

15. Practical Importance in Biochemistry: Within-run precision ensures the assay is reliable in a single experiment, critical for immediate results. Across-run precision ensures the assay is robust and reproducible over time, which is essential for longitudinal studies, quality control, or clinical diagnostics . Both are critical for validating analytical methods, ensuring reliable data, and meeting regulatory standards (e.g., in clinical labs).

16. Small Laboratory:  Receives samples of up to 100 subjects per day.  Medium Laboratory:  Receives samples of 101-400 subjects per day.  Large Laboratory:  Receives samples of more than 401-1000 subjects per day.  Very Large Laboratory:  Receives samples of more than 1000 subjects per day. 

17. Westgard’s Multirules : Rule 1 2s : (see next slide) This is a warning rule that is violated when a single control observation is outside the ± 2s limits. Remember that in the absence of added analytical error , about 4.5% of all quality control results will fall between the 2s and 3s limits. This rule merely warns that random error or systematic error may be present in the test system. The relationship between this value and other control results within the current and previous analytical runs must be examined . If no relationship can be found and no source of error can be identified , it must be assumed that a single control value outside the ± 2s is an acceptable random error & patient results can be reported . Caution: using the 1 2s rule as a rejection rule will generate 4.5% false rejections .

18. Figure: 1 2s rule: Fig.

19. Rule 1 3s : This rule identifies unacceptable random error or possibly the beginning of a large systematic error. Any QC result outside ± 3s violates this rule and should be rejected . (see next figure)

20. Figure: 1 3s rule: Fig.

21. 2 2s Rule: This rule identifies systematic error only. The criteria for violation of this rule are: Two consecutive QC results: 1) Greater than 2s ( i.e outside/crosses the 2s) & 2) On the same side of the mean. There are two applications to this rule : within-run and across-runs . The within-run application affects all control results obtained for the current analytical run . For example, if a normal (level 1) and abnormal (level 2) control are assayed in this run and both levels of control crosses 2s on the same side of the mean, this run violates the within-run application for systematic error.

22. The across-run application of this rule affects only 1 control level. If the current and previous run are both crosses 2s, the across-run application for systematical error is violated and the results should be rejected . Violation of the within-run application indicates that systematic error is present and that it affects potentially the entire analytical curve. Violation of the across run application indicates that only a single portion of the analytical curve is affected by the error. ( see next 2 figures)

23. Figure: 2 2s rule in within-Run: Figure:

24. Figure: 2 2s rule in Across-Run: Fig.

25. 2/3 2s Rule: For three (3) level controls the 2 2s rule is also expressed as 2/3 2s . Whenever any two (2) of the three level (3) of controls violate the criteria for this rule within the run , unacceptable systematic error may be present and must be resolved.

26. Figure 2/3 2s rule in Within-Run : Fig.

27. R 4s Rule: This rule identifies random error only and is applied only within the current run (not across the run). If there is at least a 4s difference between control values within a single run , the rule is violated for random error . For example, assume both level 1 and level 2have been assayed within the current run. Level 1 is +2.8s above the mean and level 2 is -1.3s below the mean. The total difference between the two control levels is greater than 4s (e.g. [+2.8s – (-1.3s)] = 4.1s).

28. Figure R 4s Rule: Fig.

29. Violation of any of the following rules does not necessarily require rejection of the analytical run. These violations typically identify smaller systematic error or analytical bias that is not often clinically significant or relevant. Analytical bias may be eliminated by performing calibration or instrument maintenance.

30. 31s Rule The criteria which must be met to violate this rule are: ■ Three consecutive results ■ Greater than 1s ■ On the same side of the mean