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Quality Management in Clinical Pathology

Explore the process of quality management in clinical pathology, from test ordering to result evaluation, and learn about essential elements for quality assurance.

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Quality Management in Clinical Pathology

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  1. بسم الله الرحمن الرحيم

  2. Quality Management Kefaya El-Sayed Mohamed Professor of Clinical Pathology (Clinical Chemistry) Faculty of Medicine, Mansoura University

  3. The Laboratory test begins with a physician deciding which test to order and ends with that physician evaluating the test result. A process of brain to brain transmission of medical in formation.

  4. Problems arise primarily from imperfect processes, not from imperfect people. • The quality problems are primarily management problems because only management has the power to change work process.

  5. The total system for a health care organization involves the interaction of all of the following processes as well as many others:

  6. Physicians might view a health care organization as a provider of processes for: • Patient examination. • Patient testing. • Patient diagnosis. • patient treatment.

  7. Health care administrators might view the activities in terms of processes for : • Admitting • Patient services • Discharging patients • Billing for costs of service

  8. Laboratory directors might understand their responsibilities in terms of processes for: • Acquisition of specimens • Processing of specimens • Analysis of samples • Reporting of test results

  9. Laboratory analysts might view their work as processes for: • Acquiring samples • Analyzing samples • Performing quality control • Releasing patient test results

  10. Test request Interpretation Report Calculation Written order Measurement Specimen Specimen preparation Patient preparation

  11. Quality Assurance (Q.A)

  12. The five Q framework • Defines how quality can be managed using the scientific method or the PDCA cycle Plan do check Act: • Quality planning • QLP • Includes analytical process and the general policies, practices and procedures that define how all aspects of the work get done.

  13. Q.C. • Statistical. • Non statistical: • e.g.: Linearity checks , reagent and standard checks and procedure. • Q.A. quality assessment concerned with: • Measures and monitors of laboratory performance as: • Turaround • Specimen identification • Patient identification • Test utility • Q.I. quality improvement: • Provides a structural problem-solving process

  14. With better analytical quality a lab can eliminate repeat run requests for test (this work is waste). • If quality are improved waste will be reduced which reduce cost and provide a competitive advantage. • If quality means conformance to requirements, then quality costs must be cost of conformance and cost of non-conformance.

  15. To customer requirement PREVENTION (To prevent problem) For appraising performance For poor analytical performance For analytical quality

  16. Essential Elements for Q.A. • Commitment. • Facilities and Resources. • Technical Competence. • Technical Procedures. • Problem solving Mechanism. • Input from QC technologist or supervisors to initiate the mechanism. • In service training program. • Specialized trouble shooting skills. • Quality team responsible for problem solving (small groups).

  17. Essential elements for Q.A.

  18. Essential elements for Q.A.

  19. Essential elements for Q.A.

  20. Essential elements for Q.A.

  21. Technical procedures

  22. Technical procedures • Methodology

  23. Technical procedures • Standardization and calibration: • Reference calibrator material (RCM) (primary calibrator): by definitive method (absolute physical quantity such as mass) e.g. isotope dilution mass spectroscopy. • Test calibrator material (TCM) (secondary calibrator): by reference method and high quality staff.

  24. Structure of an accuracy-based measurement system showing relationships among reference methods and materials .

  25. Technical procedures • Documentation of analytical protocols and procedures. • Monitoring of critical equipment and materials.

  26. Technical procedures • The Monitoring of analytical quality by the use of: Q.C. SD, bias and 6 sigma • Levey – Jennings chart • Westgard multirules • Cum Sum P.T.

  27. Q.C. Levey Jennings control chart: • Analyze control 20 different days  mean ± SD. • Construct Control chart. • Control limits set as the mean ± 3s. Concentration is plotted on the y-axis versus time (run number) on the x- axis. • Introduce the control into each run & record the value.

  28. Control limit: • ± 2 SD when the number of observation (n) is one false rejection problem (Pfr). • ± 3 SD when n = 2 or more error detection (Ped is low).

  29. Q.C. Levey Jennings chart M+3SD M+2SD M+1SD Mean Concentrations M M-1SD M-2SD M-3SD 1 2 3 4 5 6 7 8 9 10 Run number

  30. Q.C. Westgard Multirules Chart If the control is within mean ± 2SD  in control: • I2s one excced mean ± 2SD ( warning that initiate testing of other control rules). • I3s one excced mean ± 3SD ( Random error ) • 22s2consecutive control excced mean ±2SD(systemic error) • R4s 2 consecutive excced mean plus and minus 2SD) • ( Random error) • 41s 4consecutive excced mean ± 1SD ( syst. errors ) • 10x` consecutive deviation Less than 1SD on one side (system errors)

  31. Q.C Westgard chart 13s (random) M+3SD 22s systemic 12s (warning ) 4s (Random) M+2SD 41s systemic M+1SD Mean Concentrations M M-1SD M-2SD M-3SD 1 2 3 4 5 6 7 8 9 10 Run number

  32. Westgard Multirule Chart Pfr is kept low Ped is improved

  33. Q.C Westgard chart Introduce two control specimens into each analytical run : • When both fall with 2slimits accept the analytical run and report the patient results. • When one exceeds 2s limit hold the patients results and inspect the control data using l3s, R45, 22s and 10x- • When one of these rules is out of control, reject the analytical run & don’t report the analytical results . • When all of these rules indicate that the run is in control , accept the analytical run and report the patient results

  34. Q.C Westgard chart • R4s is applied only within a run –between Run interpritted as RE • Rule may be applied "across" materials one observations can be on the low, concentration and the other on the high concentration as long as they are within the same run . • Rules 22s, 41s and 10x rules can be applied across runs and materials. This effectively increases n and improve the Ped of the procedure

  35. Q.C. Systemic error: caused by variations in: • Instruments • Technique • Reagents or other material Random error: • Appear despite, Tightly Controlled, Analytical method • Sample piptting • Dissolving reagent • Mixing sample and reagents • Baths temp instability.

  36. Q.C. • The overall objective of these rules is to obtain a high probability of error detection and a low frequency of false rejection of runs: If the rules are violated it must:

  37. QC performance characteristics • Different QC procedures have different sensitivities or capabilities for detecting analytical errors. • The best is that with lowest Pfr and highest Ped.

  38. QC Cumulative sum CUSUM chart • Calculate difference between mean & the result (e.g. mean 100 , result 110 the diff = 10) -add this difference to the following each day. • Interpret the chart data . • Steep slope of the Cusum Line, suggest systemic errors and the run is out of control.

  39. QC CUSUM

  40. QC CUSUM The Same as before but the difference is calculated between the estimated control value and k1 or ku (mean ±SD): The cusum calculation do not start until a control value exceeds a certain threshold above (Ku) or below (K1) of the expected mean (X).

  41. QC CUSUM • This difference summated for 2 weeks • If the summation exceed the control Limit  the method out of control • If the sign changed (+  - or the reverse  the calculation stopped  the method is in – control changed to

  42. QC CUSUM Calculations and Tabular Record for Decision Limit Cusum For Control Material. With X=100, S=5.0, kU = 105 , K1 =95,hu=13.5,h1=13,5).

  43. Q.C using patients data (Its efficiency is relatively low) • Clinical correlation: • Correlate clinical diagnosis with laboratory test results e.g. impossible test result such as normal serum bilirubin in a highly jaundiced patients. • Correlation with other laboratory tests e.g. T4 and TSH, urea and creatinine.

  44. Q.C using patients data • Inter laboratory duplicate: • Divide sample into 2 aliquots and do analysis. This is a simple Q.C. procedure used in absence of stable control material.

  45. Q.C using patients data • Delta checks with previous test: • To detect certain errors e.g. identification or labelling. • Compare laboratory test results with value obtained on previous specimens from the same patients. Delta check limit based on 3-day interval in term % of change from the initial value e.g. Na+ 5%, CK 99%.

  46. Q.C using patients data • Limit checks: • Patients test results should be reviewed to check that they are within the physiological ranges compatible with life.

  47. External Q.C. • Analyze the same Lot of control material: • N. ± 1-1.5. • > 2 Indicate that the Lab is not in agreement with the test of other Laboratories in the program. • Must correct any test method instrum. trouble shooting.

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