Control of Analytical Variables

1. Control of Analytical Variables Dr. RoulaHamid MScClinBiochem Central Puplic Health Laboratory QC Chemistry

2. Today is not the golden age of quality in healthcare laboratories. We can & should be doing the better. James O Westgard 2003

3. Introduction“Nice to Know”

4. Total Quality Management framework for management of quality in healthcare laboratories Goals, Objectives, Quality Riquirements

5. The “five-Q” framework defines how quality is managed objectively with the “scientific method” or the PDCA cycle

6. Control of Analytical Variables

7. Analytical Variables must be controlled carefully to ensure accurate measurements by analytical methods

8. Documentation of analytical protocols • Monitoring technical competency • Statistical control of analytical methods • EQA • New quality initiatives

9. Documentation of Analytical Protocols • CLSI defines a process as a set of interrelated or interacting activities that transform input into output.

10. CLSI document describes the following section to be included in a laboratory procedure : • Title: clear & concise • Purpose or principle: e.g. this process describes how …., • Procedure instructions: how to do • Related documents:listing of other procedure • References: source of information • Appendixes or attachments • Auther(s): author(s) of document • Approved signatures

11. Monitoring Technical Competency • Proper training of laboratory personnel to establish uniformity in technique is important.

12. Statistical control of analytical methods • Control materials • General principles of control chart • Performance characteristics of a control procedures • Westgardmultirule chart • Identifying sources of analytical errors

13. Control materials • Specimens that are analyzed for QC purposes are known as control materials • They need to be available • In a stable form • In vial or aliquots • & for analysis over an extended period of time

14. General principles of control chart • A common method used to compare the values observed for control materials with their known values is the use of control charts

15. Figure: Gaussian frequency distribution

16. c) Precision problem; increase in standard deviation b) Accuracy problem; shift in mean a)Stable performance Control limit Control limit Figure: Conceptual basis of control charts. Frequency distributions of control observations for different error conditions

17. Figure: Conceptual basis of control charts. Frequency distributions of control observations for different error conditions

18. Performance characteristics of a control procedures The knowledge of performance characteristics of control procedures is necessory to select the control rules that detect relevent laboratory problems without causing too many false alarms

19. Westgardmultirule chart • The probability of false rejection is kept low through selection of only those rules with low • The probabilities for error detection is improved through selection of those rules that are particularly sensitive to random & systemic errors. • The use of multirule procedure is similar to the use of a Levey-Jennings chart, but the data interpretation is more structured.

20. Figure: Decision path for QC program

21. To use the multirule procedure, the following steps are used :

22. D-

24. E-

25. Figure : Westgardmultirule chart with control limit drawn at the mean ± 1s, 2s & 3s. Chart for high concentration

26. Figure : Westgardmultirule chart with control limit drawn at the mean ± 1s, 2s & 3s. Chart for low concentration

27. Identifying sources of analytical errors

29. EQA Procedures used to compare the performance of different laboratories (EQA)

30. IQC & EQA are complementary

31. Features of External Quality Assessment Programs • EQA program available to the clinical laboratories by professional societies & manufactures of control materials • All the participating laboratories analyzing the same lot of control material • Results are tabulated periodically & sent to the sponsering group for data analysis • The reports often includes extensive data analysis, statesical sumaries & plots

32. The mean of values of all laboratories is taken as the true or correct value & is used for comparision with the indivisual laboratory’s mean • Different approaches for data anaalysise.g. t-test, SDI,Youden plots & Levey-Jennings plots

33. New quality initiatives The six sigma process Lean production ISO 9000

34. The six sigma process • The six sigma control is an evolution in quality management • 6 sigma or 6 SD of process variation should fit within the tolerance limits for the process

35. - Tolerance specification + Tolerance specification Target -6s -5s -4s -3s -2s -1s 0s 1s 2s 3s 4s 5s 6s Figure : Six sigma goal for process performance “ tolerance specification” represents the quality requirements

36. Lean production • It is a quality process that is focused on creating more value by eliminating activities that are considered waste • e.g. Lean team at Saint Mary’s Hospital used lean production to improve the efficiency of its paper ordering system for lab work in their ICU.

38. ISO 9000 • The International Standard Organization (ISO) has developed the ISO 9000 standards • It is a set of 4 standards (ISO 9001-9004) enacted to ensure quality management & QA. • ISO 9000 represents an international consequence on the essential features of a QS to ensure the effective operation of an organization

39. Joint Committee for traceability in Laboratory Medicine The traceability of values assigned to calibrators &/or control materials must be assured through available reference measurement procedures &/or available reference materials of a higher order

40. True value Definitive method Primary reference material Method validation Reference method traceability Method validation, external quality control Secondary reference method Observed value Field method Figure: Structure of an accuracy based measurement system showing relationships among reference methods & materials Control material IQC

41. References Burtis,C.A., Ashwood,E.R. & Br uns,D.E. Fundamentals of Clinical Chemistry. 2008. .6th.ed. SAUNDERS ELSEVIER. P:249-262. Arneson,W. & Brichell,J. Clinical Chemistry ‘A Laboratory Perspective’. 2007. F. A. Davis Company. P:53-72. Westgard,J.O. Internal Quality Control: Planning & Implementation Strategies. 2003. Ann ClinBiochem. 40; 593-611.

42. Thank you