Guidelines to Westgard Rules - pSMILE



|Westgard Rules - Guidelines |Guideline Number |Pro50-10-G |

| | | |

|Author Heidi Hanes | | |

| |Effective Date |12/18/06 |

|Subject |Page |1 of 2 |

|Westgard Rules Guidelines | | |

|Review by |Heidi Hanes |Review date |1 April 2020 |

|pSMILE Comments: This document is provided as an example only. It must be revised to accurately reflect your lab’s specific |

|processes and/or specific protocol requirements. Users are encouraged to ensure compliance with local laws and study protocol |

|policies when considering the application of this document. If you have any questions contact SMILE. |

What are Westgard Rules?

Westgard Rules are multirule QC rules to help analyze whether or not an analytical run is in-control or out-of-control. It uses a combination of decision criteria, usually 5 different control rules to judge the acceptability of an analytical run.

Westgard Rules are generally used with 2 or 4 control measurements per run, which means they are appropriate when two different control materials are measured 1 or 2 times per material, which is the case in many chemistries application.

For hematology, coagulations, and immunoassays applications some alternate control rules are more suitable when three control materials are analyzed.

Explanation of Individual Rules

12s

One control measurement exceeding 2 standard deviations of control limits either above or below the mean.

This rule is used a warning rule to trigger careful inspection of the control data.

13s

This rule is commonly used with a Levey-Jennings chart when the control limits are set as the mean +3 standard deviations of control limits. A run is rejected when a single control measurement exceeds the mean +3 control limits.

22s

The control run is rejected with 2 consecutive control measurements 2 standard deviations of control limits on the same side of mean with this rule.

R4s

This rule rejects a run if two control measurements in a group exceed the mean with a 4 standard deviation difference between the 2 controls

41s

This rule rejects a run with the 4th consecutive control measurement exceeding 1 standard deviation on the same side of the mean.

10x

This rule rejects a control run when there are 10 consecutive controls on the same side of the mean.

How to perform multirule QC

To perform multirule QC collect your control measurements in the same way as you would for a regular Levey-Jennings control chart; establish means and standard deviations for the control materials; then create a Levey-Jennings chart with the mean +3, +2, and +1 standard deviations. The only difference is the interpretation of the data.

The 12s rule is used as a warning to trigger application of the other rules. Any time a single measurement exceeds a 2 standard deviation control limit, you respond by inspecting the control data using the other rules. This doesn’t mean stop, it just means to look carefully at the data before proceeding.

By using the following diagram you should be able to decide what if any action is required.

[pic]

Why use a multirule QC procedure?

The advantages of multirule QC procedures are that false rejection can be kept low while at the same time maintaining high error detection. This is done by selecting individual rules that have very low levels of false rejection, then building up the error detection by using these rules together. It is like running two liver function tests and diagnosing a problem if either one of them is positive. A multirule QC procedure uses two or more statistical test, (control rules) to evaluate the QC data, and then rejects a run if any one of these statistical tests is positive.

Other common multirules used for analyzing 3 different controls

2of32s

For this rule reject a control if 2 out of 3 control measurements exceed the same mean +2 or -2 control limits.

31s

For this rule reject when 3 consecutive control measurements exceed the same mean +1 or -1 control limits.

6x

For this rule reject when 6 consecutive control measurements of one control fall on one side of the mean.

Reference

Westgard JO, Barry PL, Quam EF, Shrmeyer SS, Plaut D, Statland BE. Chapter 6 in Basic QC Practices, Training in Statistical Quality Control for Healthcare Laboratories, 2nd Edition, Westgard QC, Inc, Madison, WI, 2002, pp77-88.

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Control Data

12s

In-control

Report Results

In-Control Report Results

13s

22s

R4s

41s

10x

Out-of-control, Reject analytical run

No

yes

yes

yes

yes

yes

Yes

no

no

no

no

no

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