Patient results and laboratory test accuracy. Issue 1 (4th February 2014)

• Record Type: Journal Article
• Authors: Katayev, Alexander; K. Fleming, James
• Is Part Of: International journal of health care quality assurance. Volume 27:Issue 1(2014)
• Page Start: 65
• Page End: 70
• Publication Date: 2014-02-04
• Subjects: United States of America -- Quality control -- Bias -- Analytical performance -- Laboratory tests -- Reference interval; Medical care -- Quality control -- Periodicals; 362.1068
• DOI: 10.1108/IJHCQA-09-2012-0092
• Languages: English
• ISSNs: 0952-6862

Abstract

Abstract : Purpose: – 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. Design/methodology/approach: – 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. Findings: – 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. Originality/value: – 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.