Westgard rules

Figure 2.8 Example of a control chart with two control levels. The marked control sample indicates that the system may be out of control by use of the Westgard rules (Christensen et a ., 1993).

Internal, i.e., within department, quality control utilizing material of known concentration is used to assess the precision and bias of the assay. Inadequate analytical performance in internal schemes will result in rejection of the results from the analyzed samples. Performance criteria may simply be assessed as >2 standard deviations from the mean or by more complex bias and imprecision estimates such as Westgard rules. Rejection of quality control may require analyses to be rejected, corrective action to be taken, and the analyses repeated. 

It is recommended that several different control samples be used simultaneously in the quality control, e.g., control materials at low and high concentration levels. In this case, it is recommended that the six control rules commonly known as Westgard rules be used [34]. These control procedures provide simple data analysis with low probability for false rejection or false alarms and indications of the type of analytical error occurring when a run is rejected. 

Westgard jo, Barry PL, Hunt MR (1981) A multi-rule Shewhart chart for quality control in clinical chemistry. Clin Chem 27 493-501. 

Figure 19-10 Power functions for l2s control rule. A, Random error. B, Systematic error. (From Westgard JO, Groth T. Power functions for statistical control rules. Clin Chem 1979 25 863-9.)...

Obtain power function graphs for the control rules and n s of interest, or OPSpecs charts for the defined TE . Power function graphs and OPSpecs charts for commonly used QC procedures with n s of 2, 3, 4, and 6 are available in the scientific literature, in workbook format, and also from computer programs (EZ Rules and QC Validator 2,0, Westgard QC, Inc., Madison, Wis.— http //vmw.westgard.com). 

The multirule procedure developed by Westgard and associates uses a series of control rules for interpreting control data. The probability for false rejections is kept low by selecting only those rules whose individual probabilities for false rejection are very low (0.01 or less). The probability for error detection is improved by selecting those rules that are particularly sensitive to random and systematic errors. The procedure requires a chart having lines for control limits drawn at the mean 1 s, 2 s, and 3 s, and is adapted to existing Levey-Jennings charts by the addition of one or two sets of control limits. 

Westgard JO, Ehrmeyer SS, Darcy TP. CLIA final rules for quahty systems Quality assessment issues and answers. Madison WI Westgard QC, Inc., 2004. 

Westgard JO, Falk H, Groth T. Influence of a between-run component of variation, choice of control limits, and shape of error distribution on the performance characteristics of rules for internal quality control. Clin Chem 1979 25 394-400. 

Westgard JO, Groth T. Power functions for statistical control rules. Clin Chem 1979 25 863-9. 

Westgard JO, Groth T, Aronsson T> et al. Performance characteristics of rules for internal quality control Probabhities for false rejection and error detection. Clin Chem 1977 23 1857-67. 

J. O. Westgard, P. L. Barry, and M. R. Hunt, A Multi-Rule Shewhart Chart for Quality Control in Clinical Chemistry, Clin. Chem., 27 (1981) 493. 

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