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Traditional quality control materials used for monitoring the clinical laboratory test accuracy might be non-commutable with patient samples and may not detect systematic errors. The aim of this paper is to describe a method to monitor inter-instrument bias using result distributions that are independent of the control's commutability.

Serum calcium data collected within a laboratory network were assessed. A reference interval was calculated using a computerized, indirect Hoffmann's algorithm using all data across a laboratory network without excluding any results. Results outside the reference interval were considered as the zero-bias distribution. Three allowable bias levels were then calculated to determine the corresponding shift in abnormal results for each bias level in both directions from the zero-bias distribution. The observed result distributions in three laboratories within the network were compared for bias performance after one year of the reference interval study.

Performance levels for bias were: minimum allowable <1.27 percent; desirable <0.85 percent; and optimal <0.42 percent. Zero bias result distribution above and below the reference interval for calcium was 3.92 percent and 2.53 percent respectively. All three laboratories performed within the desirable allowable bias level.

Bias-monitoring process using patient result distributions allows managers to: assess systematic error between laboratory instruments; improve laboratory quality control; and strengthen patient risk management.