1. Internal Quality Control (QC) for Medical Laboratories: An introduction Dr. Otto Panagiotakis and Dr. Alexander Haliassos ESEAP – Greek Proficiency Testing Scheme for Clinical Laboratories http://www.eseap.gr info@eseap.gr

2. Analytical Quality Control The most important tool for ensuring the quality of laboratory results through the identification and reduction of errors It includes two parallel mechanisms: Internal (intra-laboratory) quality control External quality control, or External quality assessment (EQA) or Proficiency Testing (PT)

3. Correct result: There is not a value, but a range from repeated measurements We need a tool to compare the reported with the expected result. What means a value of total cholesterol 245mg/dL reported for the analysis of an QC control? 235 245255 240 250260 265 It is the control chart Levey-Jennings

4. Central horizontal line: expected mean value Dotted horizontal lines: control limits (mean ± nSD) Control charts Levey-Jennings: +2s mean +1s -1s -2s +3s -3s

5. Their design is based on the assumption that: The values resulting from previous measurements are subject to random variation This variation follows a uniform (normal) distribution Control charts Levey-Jennings:

6. How we draw the control charts? We select a parameter (p.ex. Cholesterol) we measure this parameter in a control material for 20 days using the method (assay) and the instrument (analyzer) that we evaluate from those values we calculate the mean and the SD p.ex. mean = 200 mg/dL and SD = 4 mg/dL subsequently, the control limits at the level of 2s, 3s mean ± 2s: 200 ± 2(4)=200 ± 8  from 192 to 208 mean ± 3s: 200 ± 3(4)=200 ± 12  from 188 to 212

7. Cholesterol (mg/dL), Lot No: xxx, January 2015 216 212 208 200 192 188 184 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 x-3s x+3s x-2s x+2s mean

8. Interpretation of control charts (1) The control charts reflect the distribution resulting from the initial measurements of the control materials In the charts we draw the values of each measurement Evaluation: depending on their position in the chart 1) If the analytical procedure is correct, the new measurements will have the same distribution with the originals: Extremely rare (0,3%) a value> mean ± 3s Unlikely (5%) a value> mean ± 2s Very likely (32%) a value> mean ± 1s (limits without a value)

9. Control Rules Rules to decide whether a series of measurments is under control or out of control Control rules control limits 1 2s mean ± 2s 1 3s mean ± 3s Single rule methods Multiple rules methods

10. 2) If the analytical procedure has a problem, it increases the probability of a value exceeding the control limits This can happen : Either with the appearance of a constant error (bias) (shifting of the mean of the distribution to or values) or by increasing the random error (enlargement of the distribution) Situation out of control / Unacceptable results Interpretation of control charts (2)

11. Situation under control (normal) Systematic error (bias) Distribution enlargement

12. The QC methods are detection systems The detection systems have some characteristics: The frequency of true warnings, true alarms The frequency of erroneous warnings, false alarms In the QC methods they are called respectively : Error detection probability (Ρ) Probability of false rejection (Ρο) The ideal on a single rule QC method would be: Ρ=1,0 (100%) and Ρο=0 (0%) However, for each control rule: Ρ 0 A realistic goal is : Ρ=0,90 and Ρο=0,05 The problem of erroneous rejects

13. Rule 1 2s : high Ρ and high Ρο For Ν=1 Ρο=5% For Ν=2 Ρο=9% For Ν=3 Ρο=14% The single rule QC method using the 1 2s rule should only be used with Ν=1. If Ν=2, almost a false rejection in 10 This is not a problem of the analytical procedure. This is an intrinsic problem of the QC method and related to the selected control threshold.

14. resulting in non detected large errors As the control limits are extended erroneous rejections (Po) decrease, but also P decreases If a rule with high P is selected will have also high Ρο Single rule QC methods have serious drawbacks Need to find other QC methods Rule 1 3s : low Ρο and low Ρ

15. Multiple rules methods They do not use a single control rule but a combination of rules (at least 2) Advantage: Low Po and simultaneously high P The most well known Westgard method: 6 control rules 2 control sera (N=2) resulting to 2 Levey-Jennings control charts L-J, one for each serum (control material) Control limits at three levels(±1s, ±2s, ±3s)

16. 216 212 208 200 192 188 184 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 x-3s x+3s x-2s x+2s x+1s x-1s 204 196 Cholesterol (mg/dL), Lot No: xxx, January 2015

17. The 6 control rules according to Westgard 1 2S 1 3S 2 2S R 4S 4 1S 10 x

18. 1 2 3 4 5 6 7 8 9 10 +3s +2s +1s mean - 1s - 2s - 3s Not a rejection but warning for a potential problem Further control is required based on the other criteria Rule 1 2S One value (measurement) > 2s limit

19. 1 2 3 4 5 6 7 8 9 10 +3s +2s +1s mean - 1s - 2s - 3s Applied in a series for each of the two sera Sensitive to random errors Rule 1 3S One value (measurement) > 3s limit

20. 1 2 3 4 5 6 7 8 9 10 +3s +2s +1s mean - 1s - 2s - 3s Rule 2 2S 2 consequent values > the same limit of 2s In the last 2 series for each serum In the same series for both

21. 1 2 3 4 5 6 7 8 9 10 +3s +2s +1s mean - 1s - 2s - 3s +3s +2s +1s mean - 1s - 2s - 3s +3s +2s +1s mean - 1s - 2s - 3s 1 2 3 4 5 6 7 8 9 10 In the last 2 series for each serum In the same series for both Sensitive to systematic errors Rule 2 2S 2 consequent values > the same limit of 2s

22. 1 2 3 4 5 6 7 8 9 10 +3s +2s +1s mean - 1s - 2s - 3s In the last 2 series for each serum In the same series for both Rule R 4S The difference in value of the two sera> 4s

23. 1 2 3 4 5 6 7 8 9 10 +3s +2s +1s mean - 1s - 2s - 3s +3s +2s +1s mean - 1s - 2s - 3s +3s +2s +1s mean - 1s - 2s - 3s 1 2 3 4 5 6 7 8 9 10 In the last 2 series for each serum In the same series for both Sensitive to systematic error Rule R 4S The difference in value of the two sera> 4s

24. 1 2 3 4 5 6 7 8 9 10 +3s +2s +1s mean - 1s - 2s - 3s In the last 4 series for each serum In the last 2 series for both Rule 4 1S 4 consecutive values > the same limit of 1s

25. 1 2 3 4 5 6 7 8 9 10 +3s +2s +1s mean - 1s - 2s - 3s +3s +2s +1s mean - 1s - 2s - 3s +3s +2s +1s mean - 1s - 2s - 3s 1 2 3 4 5 6 7 8 9 10 In the last 4 series for each serum In the last 2 series for both Sensitive to systematic errors Rule 4 1S 4 consecutive values > the same limit of 1s

26. 1 2 3 4 5 6 7 8 9 10 +3s +2s +1s mean - 1s - 2s - 3s In the last 10 series for each serum In the last 5 series for both Rule 10 Χ 10 consecutive values at the same side of the mean

27. 1 2 3 4 5 6 7 8 9 10 +3s +2s +1s mean - 1s - 2s - 3s +3s +2s +1s mean - 1s - 2s - 3s +3s +2s +1s mean - 1s - 2s - 3s 1 2 3 4 5 6 7 8 9 10 In the last 10 series for each serum In the last 5 series for both Sensitive to systematic errors Rule 10 Χ 10 consecutive values at the same side of the mean

28. values 1 2s Situation out of control - Series Rejected Situation under control - Series Accepted Flowchart according to Westgard 1 3s 2 2s R 4s 41s41s 10 x yes no control

29. Differences of Internal and External QC Internal QC performed daily in the laboratory uses samples (control materials) of known concentration it is always required External QC performed periodically (weekly, monthly …) uses samples (control materials) of unknown concentration useful in conjunction with the internal Q C

30. External QC does not replace the Internal QC the inter-laboratory comparisons are infrequent the results are reported deferred (not in real time) and therefore it is not possible the immediate intervention with corrective measures even if the performance is satisfactory, it assures the proper functioning of the laboratory only on the day of the inspection (participation) These programs do not lead to quality improvement of the laboratory if it is not performed daily the internal QC.