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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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Content – Annex


  • Checklists

  • Glossary of terms

  • References

Statistics & graphics for the laboratory

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Annex – 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

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Annex – 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

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Annex – 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

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Annex – 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

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Annex – 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


  • 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

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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

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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

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Annex – 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



  • Software for laboratory statistics




  • IQC-websites



  • IQC-software

  • QC-today:

  • Unity: Bio-Rad

  • EZ Runs: Westgard

  • QC Validator. EZ-rules. Westgard Quality Corporation.

  • Useful links

  • Regulation



  •, and



Statistics & graphics for the laboratory

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Annex – 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

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Annex – 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

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Annex – 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):

  • 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.

  • QC - THE REGULATIONS. Sharon S. Ehrmeyer, Ph.D.

  • 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

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Annex – 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.

  • 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.


  • 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

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  • Dietmar Stöckl, PhD

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  • B-9667 Horebeke, Belgium

  • e-mail: [email protected]

  • Tel + FAX: +32/5549 8671

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