Date of this Version

11-1-2016

Document Type

Journal Article

Publication Details

Submitted version

Liu, J., Tan, C. H., Loh, T. P., & Badrick, T. (2016). Verification of out-of-control situations detected by "average of normal" approach. Clinical Biochemistry, 49(16-17), 1248-1253.

Access the journal

Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved

ISSN

1873-2933

Abstract

OBJECTIVES:

"Average of normal" (AoN) or "moving average" is increasingly used as an adjunct quality control tool in laboratory practice. Little guidance exists on how to verify if an out-of-control situation in the AoN chart is due to a shift in analytical performance, or underlying patient characteristics.

DESIGN AND METHODS:

Through simulation based on clinical data, we examined 1) the location of the last apparently stable period in the AoN control chart after an analytical shift, and 2) an approach to verify if the observed shift is related to an analytical shift by repeat testing of archived patient samples from the stable period for 21 common analytes.

RESULTS:

The number of blocks of results to look back for the stable period increased with the duration of the analytical shift, and was larger when smaller AoN block sizes were used. To verify an analytical shift, 3 archived samples from the analytically stable period should be retested. In particular, the process is deemed to have shifted if a difference of >2 analytical standard deviations (i.e. 1:2s rejection rule) between the original and retested results are observed in any of the 3 samples produced. The probability of Type-1 error (i.e., false rejection) and power (i.e., detecting true analytical shift) of this rule are 0.9, respectively.

CONCLUSIONS:

The use of appropriately archived patient samples to verify an apparent analytical shift is preferred to quality control materials. Nonetheless, the above findings may also apply to quality control materials, barring matrix effects.

Share

COinS
 

This document has been peer reviewed.

 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.