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Content – Annex. Content. Checklists Glossary of terms References. Annex – Checklists. Checklists. IQC software Administrative capabilities -Easy set-up and modification -Online (real time) connection with LIS -Full sample & IQC traceability -“Accreditation-conform” documentation

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  1. Content – Annex Content • Checklists • Glossary of terms • References Statistics & graphics for the laboratory

  2. Annex – Checklists Checklists • IQC software • Administrative capabilities • -Easy set-up and modification • -Online (real time) connection with LIS • -Full sample & IQC traceability • -“Accreditation-conform” documentation • -Up-to-date data safety • “IQC”-capabilities • -Transparent & efficient data presentation • -Great variety of rules • -Rule selection logic • -Automatic release • -Automatic “flags” and remedial action • (but with open decision logic) • IQC-sample • Nature • Correspond with patient sample • Compatible with the test • Concentration: medically relevant • Number of levels • Stability (liquid versus lyophilized) • Lyophilized • Variation in fill content • Accuracy of reconstitution • Target mean • Sufficient digits • System specific • Uncertainty • Target SD/CV • Representative for system • Uncertainty Statistics & graphics for the laboratory

  3. Annex – Checklists Checklists • “Stable” imprecision • Instrument stability (general system robustness), e.g.: • Pipetting • Temperature • Photometer (wavelength/intensity/sensor) • Test stability & reproducibility (individual test robustness) • Total/within-day CV (CVa,tot/CVa,w ratio) • Calibration tolerance (within/between lot), -function • Reagent (within/between lot) • Test robustness • Note: Ideally, a GUM-type variance analysis of all elements should be available. •  Decide about approaching the variation by IQC and/or quality assurance Statistics & graphics for the laboratory

  4. Annex – Checklists Checklists • IQC-measurement-frequency and location • Minimum: 2 samples per run • Desirable: ~1-2% of patient samples • -Make a cost/benefit calculation • Frequency should be related to test stability: requires knowledge of instrument and test • Consider “dummy” measurements before 1st IQC • Frequency may depend on the control rule • Block: Maximizes chance of assignable cause of variability between subgroups • Continuous: Maximizes chance of assignable cause of variability within subgroups • Basic statistics • Calculations • Mean • SD • CV • Gaussian (normal) distribution • Graphic of the usual & the cumulated distribution • Probabilities within certain distances (s) of the mean • Probabilities outside certain distances (s) of the mean • 1-sided and 2-sided probabilities • Important values for s • Convention on “rare events” • Possibility of wrong decisions • The 1st IQC principle: monitoring the outsides • Metrology, knowledge of • The total error concept (TE, SE, RE) • Concept of maximum allowable total error (TEa) (process specifications) • Critical error Statistics & graphics for the laboratory

  5. Annex – Checklists Checklists • TEa • Apply TEa values from the following hierarchy • • 1. Clinical models (e.g., cholesterol; glucose) • • 2. Biological variation (obtain the database) • -Bottom-line values • No numbers from 1-2: 3. Expert models • No numbers from 1-3: 4. Regulation • No numbers from 1-4: 5. Better state-of-the-art • Note: Critically review the proposed numbers. • Rule selection • Statistical basis: A rule is chosen based on Pfr and Ped. SD-limits are taken from stable performance. • TEa basis: From a specification for TEa, critical error values can be calculated. • From the critical error values, adequate IQC rules can be selected, naturally, on statistical basis. • Selection tools: power functions, OPSpecs, the TEa/CVa,tot ratio; the IQC decision tool • Power of control rules • Ped should be 90% • Realistic errors to be detected by IQC are • D SE = >2 • D RE = >3 • REstable • Ped AND Pfr increase with • lower s-limits (2s > 3s) • n (note, some rules are connected to the number of materials: multiples of 2, 3 with 2 or 3 materials) • Generally, do not consider rules with Pfr >1% • Ped increases by combination of rules • Ped of mean and variance rules > than single or combined rules • Ped for SE > RE • Pfr at non-zero can be minimized by movement of the power curve • The power curve should have a good steepness Statistics & graphics for the laboratory

  6. Annex – Checklists Checklists • Input elements for a successful IQC policy • The guiding rule (regulation) • Knowledge • Basic statistics • Power functions • TE error concept (metrology) • TEa (critical errors, specifications) • Selection of TEa values (and problems) • IQC Software • Additional: rule selection tools • Adequate samples • Adequate frequency (and location) policy • Cost/benefit calculations • Instrument stability data • Test stability and reproducibility data • Integrated rule selection (TEa; statistics; costs) • Release of patient data • Process control • Remedial actions policy • Release of patient data • Process control • Integration of IQC in the overall quality management • Dedicated personnel Review your current practice Which~ • Tests • Stable performance~ • Known? • Compared to manufacturer claim/Peers? • Compared to medical requirements? • Materials~ • Sort and concentration • Targets (mean & CV) • Frequency (run-length) • Rules (& software) • Remedial actions policy~ • Responsible for interpretation • % of non-billable tests (calibration, IQC, repeat) • Remedial actions: success-rate Statistics & graphics for the laboratory

  7. Annex – Glossary of terms Glossary (and abbreviations) of terms – IQC • Ped: probability of error detection • Pfr: probability of false rejection • TEa: total allowable error • DSEcrit, critical systematic error: the amount of systematic error that places 5% of results outside TEa • DREcrit, critical random error: the amount of random error that places 5% of results outside TEa • ARL, average run length: the average number of runs that occur before a run is rejected by the IQC procedure • Glossary of terms – IQC rules • Control rules with a fixed limit  • a) Control rules in the form of Nz•s (N is the number of observations, z•s is a certain number of standard deviations of the Gaussian distribution, commonly used are 2s, 2.5s, or 3s). • 13s: refers to a control rule where action is taken when one measurement falls outside the ±3s range around the target value. • 22s: refers to the situation where action is taken when two consecutive measurements exceed the same limit, either the +2s or -2s range. • b) Range rules • R4s: refers to a situation where action is taken when the absolute difference between the highest and the lowest result exceeds 4 • s (Westgard interpretation: one >+2s, the other <-2s). • c) Others  • 7X(mean): 7 consecutive measurements lie on one side of the target • 7t : 7 consecutive measurements show a trend (increasing/decreasing) Statistics & graphics for the laboratory

  8. Annex – Glossary of terms Glossary of terms – IQC rules • Control rules with variable limit (depending on the number of observations N), however, a fixed probability of false rejections (Pfr): XPfr • 10.05: 1 control measurement in a group of N measurements exceeds a limit based on a Pfr of 0.05. The limit widens when N increases (tables are available). • X0.05 : The mean of a group of N measurements exceeds a limit based on a Pfr of 0.05 (also called "mean" rules). The limit decreases when N increases (tables are available). • R0.05: The range in a group of N measurements exceeds a limit based on a Pfr of 0.05. The limit increases when N increases (tables are available). • Chi20.05: The ratio s2obs(N-1)/s2 exceeds the critical chi-square value at a Pfr of 0.05 (sobs is the standard deviation calculated from the control measurements, s is the intrinsic standard deviation) (also called "variance" rules). The limit increases when N increases (tables are available). • CS ("CUSUM"): The difference between individual results and the mean is summed up and plotted. Interpretation is either graphical ("V" mask) or with a numerical limit. Statistics & graphics for the laboratory

  9. Annex – References References • Statistical textbooks • Basic • Miller JC, Miller JN. Statistics for analytical chemistry. 3rd ed. Chichester (UK): Ellis Horwood, 1993. • Advanced • Sokal RR, Rohlf FJ. Biometry. 3rd ed. New York: W. H. Freeman and Company, 1995. • Altman DG. Practical Statistics for medical research. Chapman & Hall, London, 1991. • Electronic textbook • www.statsoft.com/textbook/stathome.htm • http://faculty.vassar.edu/lowry/VassarStats.html • Software for laboratory statistics • www.cbstat.com • www.medcalc.be • www.marquis-soft.com • IQC-websites • www.westgard.com • www.marquis-soft.com • IQC-software • QC-today: www.ilww.com • Unity: Bio-Rad • EZ Runs: Westgard • QC Validator. EZ-rules. Westgard Quality Corporation. www.westgard.com. • Useful links • Regulation • www.iph.fgov.be • www.baek.de • www.cms.hhs.gov/clia/, and www.phppo.cdc.gov/clia/regs/toc.asp • www.cenorm.be • www.iso.ch Statistics & graphics for the laboratory

  10. Annex – References References • IQC-general • National Committee for Clinical Laboratory Standards (NCCLS).C24-A2. Statistical quality control for quantitative measurements: Principles and definitions; Approved Guideline – 2nd ed (1999). • Westgard JO, Barry PL. Cost-effective quality control. AACC Press, 1995 • Shewart WA. Economic control of manufactured products. Van Nostrand: 1931. • Levey S, Jennings ER. The use of control charts in the clinical laboratory. Am J Clin Pathol 1950;20:1059-66. • Westgard JO, Groth T, Aronsson T, Falk H, de Verdier C-H. Performance characteristics of rules for internal quality control: probabilities for false rejection and error detection. Clin Chem 1977;23:1857-67. • Hyltoft Petersen P, Ricós C, Stöckl D, Libeer J-C, Baadenhuijsen H, Fraser CG, Thienpont LM. Proposed guidelines for the internal quality control of analytical results in the medical laboratory. Eur J Clin Chem Clin Biochem 1996;34:983-99. • Linnet K. Mean and variance rules are more powerful or selective than quality control rules based on individual values. Eur J Clin Chem Clin Biochem 1991;29:417-24. • IQC-practice surveys • Steindel SJ, Tetrault G. Quality control practices for calcium, cholesterol, digoxin, and hemoglobin. A College of American Pathologists Q-probes study in 505 hospital laboratories. Arch Pathol Lab Med 1998;122:401-8: Recommend 2.5 – 2.7s rule • Tetrault GA. QC in the clinical lab: 6 questions for the pathologist. CAP Today 1995 (April):60-1: Recommends 3.5 s rule • Steindel SJ. Quality control systems in the clinical laboratory. A survey on implementation in 505 hospital laboratories. Labmedica Int 1999;16:8-12: Recommends 2.5 – 2.7s rule • Krishnan S, Webb S, Henderson AR, Cheung CM, Nazir DJ, Richardson H. An overview of quality control practices in Ontario with particular reference to cholesterol analysis. Clin Biochem 1999;32:93-9. Statistics & graphics for the laboratory

  11. Annex – References References • Quality management • ISO 8402: 1994. Quality management and quality assurance - Vocabulary • National Committee for Clinical Laboratory Standards (NCCLS). HS1-A (replaces GP26-A). A quality system model for health care; Approved guideline (2002). • ISO/DIS 15189.2 Medical laboratories - Particular requirements for quality and competence. • Burnett D. Understanding accreditation in laboratory medicine. ACB Venture Publications. London: Association of Clinical Biochemists, 1996. • Stewart CE, Koepke JA. Basic quality assurance practices for clinical laboratories. Philadelphia (USA): J. B. Lippincott Company, 1987. • Garfield FM. Quality assurance principles for analytical laboratories. AOAC International: 1994. • St John A. Critical care testing. Quality assurance. Mannheim: Roche Diagnostics, 2001. • Nilsen CL. Managing the analytical laboratory: plain and simple. Buffalo Grove (IL): Interpharm Press, 1996. • Metrology • ISO VIM. Vocabulaire international des terms fondamentaux et généraux de métrologie. • ISO GUM. Guide to the expression of uncertainty in measurement • ISO 5725-1. Accuracy (trueness and precision) of measurement methods and results. • Stöckl D. Metrology and analysis in laboratory medicine: a criticism from the workbench. Scand J Clin Lab Invest 1996;56:193-7. Statistics & graphics for the laboratory

  12. Annex – References References • Regulation • Praktijkrichtlijn voor het opzetten van een kwaliteitshandboek in erkende klinische laboratoria werkzaam binnen het kader van het RIZIV. • Royal Decree from December 3 1999 regarding the authorization of clinical chemical laboratories. Moniteur Belge. December 30, 1999. Implementation document: Praktijkrichtlijn (Practice guideline): www.iph.fgov.be/Clinbiol/NL/index.htm. • Guidelines of the German Medical Association (Bundesärztekammer) regarding the quality assurance in medical laboratories (RILIBÄK). Deutsches Ärzteblatt 2001;98, 42:A 2747-59 + 2002;99, 17: A 1187. www.bundesaerztekammer.de/30/-Richtlinien/Richtidx/Labor2002/index.html. • QC - THE REGULATIONS. Sharon S. Ehrmeyer, Ph.D. www.westgard.com/guest8.htm. • Directive 98/79/EC of the European Parliament and of the Council of 27 October 1998 on in vitro diagnostic medical devices. Official Journal of the European Communities 1998 (Dec 7):L 331/1-L 331/37. • CEN prEN ISO 17511 (draft Dec 2000) in vitro diagnostic medical devices - Measurement of quantities in samples of biological origin - Metrological traceability of values assigned to calibrators and control materials (ISO/DIS 17511:2000). • CEN prEN 13612 (final draft September 2001) Performance evaluation of in vitro diagnostic medical devices. • ISO/DIS 15198 (April 2001). Clinical laboratory medicine - Validation of manufacturer´s recommendations for user quality control. • CEN EN 591 (2001) Instructions for use for in vitro diagnostic instruments for professional use. • CEN EN 375 (2001) Information supplied by the manufacturer with in vitro diagnostic reagents for professional use. • CEN prEN 14136 (draft March 2001) Use of external quality assessment schemes in the assessment of the performance of in vitro diagnostic procedures. • ISO/IEC 17025: 1999 - General requirements for the competence of testing and calibration laboratories (former EN 45001). • ISO/DIS 15189.2 Medical laboratories – particular requirements for quality and competence • ISO/AWI 22869 Clinical laboratory testing -- Guidance on application of ISO 15189. • NCCLS EP11-P Uniformity of claims for in vitro diagnostic tests; Proposed guideline (1996). • NCCLS EP15-P User demonstration of performance for precision and accuracy; Proposed guideline (1998). Statistics & graphics for the laboratory

  13. Annex – References References • Dignostic value of tests • Büttner J. Diagnostic validity as a theoretical concept and as measurable quantity. Clin Chim Acta 1998;260:131-43. • Linnet K. A review on the methodology for assessing diagnostic tests. Clin Chem 1988;34:1379-86. • National Committee for Clinical Laboratory Standards. Assessment of clinical accuracy of laboratory tests using receiver operating characteristics (ROC) plots; approved guideline. NCCLS publication GP10-A. Wayne, PA: NCCLS 1995. • The Bayes Library of Diagnostic Studies and Reviews. 2nd edition 2002. http://www.ispm.unibe.ch/files/file/261.Bayes_library_handbook.pdf • Henderson AR. Assessing test accuracy and its clinical consequences: a primer for receiver operating characteristic curve analysis [Review]. Ann Clin Biochem 1993;30:521-39. • Performance specifications • Stöckl D, Baadenhuijsen H, Fraser CG, Libeer J-C, Hyltoft Petersen P, Ricós C. Desirable routine analytical goals for quantities assayed in serum. Eur J Clin Chem Clin Biochem 1995;33:157-69. • Stöckl D. Desirable Performance criteria for quantitative measurements in medical laboratories based on biological analyte variation - hindrances to reaching some and reasons to surpass some. Clin Chem 1993;39:913-4. • www.westgard.com • Strategies to set global analytical quality specifications in laboratory medicine. Consensus Statement, Stockholm 1999. Scand J Clin Lab Invest 1999;59:585. • Hyltoft Petersen, P. Quality specifications based on analysis of effects of performance on clinical decision making. Scand J Clin Lab Invest 1999;59:517-22. • ISO 15196/CD Identification and determination of analytical and clinical performance goals for laboratory methodologies Statistics & graphics for the laboratory

  14. Annex • STT Consulting • Dietmar Stöckl, PhD • Abraham Hansstraat 11 • B-9667 Horebeke, Belgium • e-mail: dietmar@stt-consulting.com • Tel + FAX: +32/5549 8671 Statistics & graphics for the laboratory

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