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Updated: Dec 9, 2025

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
Published on: August 29, 2025
The costs and benefits of cross-level quality control rules
Robert L Schmidt1, Ryleigh A Moore2, Lauren N Pearson1
1Department of Pathology, University of Utah, Salt Lake City, UT, United States; ARUP Laboratories, Salt Lake City, UT, United States.
Background:
Quality is often monitored by multi-rule schemes that are applied at each level of QC material. Cross Level (CL) quality control rules have been proposed but have not been investigated.
Methods:
We used computer simulation to study the impact of CL rules on time to detection and the false positive rate in a system using multirules (3-1s, 2-2s, 4-1s, and 10x) with 2 levels of QC material We also studied the effect of correlation between shifts at each level. The performance of QC policies was compared using simulation analysis. We also compared the detection rates of QC policies (with and without QC rules) using laboratory QC data.
Results:
Implementing the CL rule increased the false positive rate and increased the detection rate for small shifts (around 1 standard deviation). CL rules had a greater impact when the correlation of shifts between levels was high.
Conclusions:
CL rules have the potential to increase detection rates, but also increase false positive rates. It is difficult to identify the circumstances where the benefits of increased detection outweigh the costs of false positives. Alternative approaches to QC should be explored.
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