Categorizing and Establishing CD4 Service Equivalency: Testing of Residual, Archived External Quality Assessment Scheme Sample Panels Enables Accelerated Virtual Peer Laboratory Review

Abstract

BackgroundTesting of collated, curated residual archived external quality assessment (EQA) trial material, with pre‐established true (consensus) values collated into 25‐sample panels enables virtual peer review of a laboratory's proficiency. In this study, we introduce how archived EQAS samples/panels can establish equivalency of CD4 reporting across multiple laboratories in a national program.MethodsCurated unused trial material from archived EQAS CD4 trials were collated into 25‐sample panels comprising three sets of five‐sample replicates and at least three duplicate samples. Panel‐samples were tested using predicate methods of participating laboratories and proficiency determined by calculating a Standard Deviation Index (SDI) for each panel‐sample reported according to retrospective consensus pooled trial outcomes. All data were plotted using MS Excel and Graphpad‐Prism with SDI limits between −2 and +2 SDI to define acceptable performance. Percentage similarity analysis determined agreement. Bead‐count‐rate data was used to determine pipetting error.ResultsTight clustering of SDI outcomes predicted acceptable laboratory proficiency with acceptable accuracy and precision as evidenced by mean SDI < 0.5 and SD of SDI < 0.5. Random pipetting error was identified with aberrant BCR. Systematic under‐reading of results was noted in one lab with excellent precision but mean SDI > 1.6. Additional training requirements were evident where a respective laboratory's SD of SDI exceeded 0.7.ConclusionsArchival panel testing undertaken across a network of CD4 laboratories using the same CD4 method to simultaneously test the same panel prior to national implementation highlighted proficient laboratories and was useful for identifying sites with service deficiencies and immediate additional training needs. © 2019 International Clinical Cytometry Society

Practical application of mathematical calculations and statistical methods for the routine haematology laboratory

“…As an example, the study of Yoon et al calculated the SDI = [(measured value of the institution − average of the participating institutions)/standard deviation of the participating institutions] to show superior performance in haemoglobin analysis by accredited laboratories 9 . SDI is useful for interlaboratory comparison; for example, SDI has been used to establish equivalency of CD4 reporting in a large group of networked laboratories 10 …”

“…9 SDI is useful for interlaboratory comparison; for example, SDI has been used to establish equivalency of CD4 reporting in a large group of networked laboratories. 10 SD, CV and SDI are three calculated ways to establish QC limits, based on actual instrument/assay performance. Other sources for QC limits include precision goals from the manufacturer (from QC product monographs) and published precision goals.…”