Development and validation of effective real-time and periodic interinstrument comparison method for automatic...

Variability in hematology analyzer results can impact clinical decisions. Prior research has shown that standard interinstrument comparison methods may not fully capture real-time performance differences. No prior work had resolved how to set dynamic thresholds for acceptable variation. This gap motivated the development of a new method using statistical cutoffs. Existing methods often rely on fixed thresholds, which may not adapt to daily fluctuations. The need for a more responsive validation approach is clear. Researchers sought to improve accuracy without increasing false rejections. This paper introduces a novel approach to interinstrument comparison.

The aim was to develop and validate a real-time interinstrument comparison method for hematology analyzers. This method uses the 99th percentile coefficient of variation (CV) cutoff to assess performance. The study focused on both patient samples and quality control materials. Researchers wanted to determine optimal allowable total error (ATE) values. They also aimed to compare rejection rates between traditional and new methods. The goal was to reduce unnecessary recalibrations while maintaining accuracy. This approach could streamline quality assurance in labs. The findings may help standardize interinstrument monitoring.

The study used 120 patient samples collected over six months. The first three months provided data for calculating 99th percentile CV cutoffs. The last three months tested acceptable ranges and rejection rates. Identical analyses were performed using quality control (QC) materials. Two instrument comparisons were conducted to assess performance differences. Allowable total error (ATE) values were calculated using standard deviation (SD) thresholds. Researchers compared rejection rates between 3 SD and 4 SD cutoffs. The method evaluated both patient and QC data for consistency.

Rejection rates were 10.00% for patient samples and 9.30% for QC materials using the 99th percentile cutoff. QC material acceptable ranges were wider than those from the new method in most cases. In two-instrument comparisons, 34.8% of comparisons failed under standard methods. Applying 4 SD as an ATE value improved success rates to 87.0%. This suggests that 4 SD reduces unnecessary recalibrations. The new method showed consistent performance across sample types. It provided tighter acceptable ranges than traditional approaches. These results support the use of 99th percentile cutoffs for real-time monitoring.

The 99th percentile CV cutoff method can serve as a real-time interinstrument comparison tool. This approach works for both patient samples and QC materials. Applying 4 SD as an ATE value reduces unnecessary recalibrations. The study suggests that this method improves accuracy without increasing false rejections. It may help labs maintain quality while reducing workload. The findings align with the authors' goal of improving interinstrument monitoring. This method could be adopted in clinical settings for better performance tracking. The authors propose that it supports more consistent quality assurance practices.