Reference-mean-centered statistical quality control

Clin Chem Lab Med. 2020 Jan 13;58(9):1517-1523. doi: 10.1515/cclm-2019-1034. Print 2020 Aug 27.

Abstract

Background: Statistical quality control (SQC) procedures generally use rejection limits centered on the stable mean of the results obtained for a control material by the analyzing instrument. However, for instruments with significant bias, re-centering the limits on a different value could improve the control procedures from the viewpoint of patient safety.

Methods: A statistical model was used to assess the effect of shifting the rejection limits of the control procedure relative to the instrument mean on the number of erroneous results reported as a result of an increase in the systematic error of the measurement procedure due to an out-of-control condition. The behaviors of control procedures of type 1ks (k = 2, 2.5, 3) were studied when applied to analytical processes with different capabilities (σ = 3, 4, 6).

Results: For measuring instruments with bias, shifting the rejection limits in the direction opposite to the bias improves the ability of the quality control procedure to limit the risk posed to patients in a systematic out-of-control condition. The maximum benefit is obtained when the displacement is equal to the bias of the instrument, that is, when the rejection limits are centered on the reference mean of the control material. The strategy is sensitive to error in estimating the bias. Shifting the limits more than the instrument's bias disproportionately increases the risk to patients. This effect should be considered in SQC planning for systems running the same test on multiple instruments.

Conclusions: Centering the control rule on the reference mean is a potentially useful strategy for SQC planning based on risk management for measuring instruments with significant and stable uncorrected bias. Low uncertainty in estimating bias is necessary for this approach not to be counterproductive.

Keywords: analytical quality; bias; quality control; quality control planning; risk management.

MeSH terms

  • Chemistry Techniques, Analytical / methods
  • Chemistry Techniques, Analytical / standards*
  • Data Interpretation, Statistical*
  • Humans
  • Quality Control*
  • Reference Values
  • Risk Management