Quality Monitoring Approach for Optimizing Antinuclear Antibody Screening Cutoffs and Testing Work Flow.

ABSTRACT

BACKGROUND: An antinuclear antibody (ANA) testing strategy involving enzyme immunoassay (EIA) screening that reflexed to immunofluorescence assay (IFA) was implemented, monitored, and optimized for clinical utility. METHODS: The clinical utility, test performance, and workload implications of various ANA testing strategies were compared during the following study phases (a) Preimplementation (n = 469) when IFA was used for all ANA screening, (b) Verification (n = 58) when EIA performance was confirmed, (c) Implementation (n = 433) when a reflexive strategy (EIA screen/IFA confirmation) was implemented, and (d) Postimplementation (n = 528) after the reflexive strategy was optimized. Sequential samples were captured in the Preimplementation, Implementation, and Postimplementation phases for clinical performance evaluation. RESULTS: Clinical performance of the EIA screen, per ROC analysis yielded area under the curve (AUC) of 0.846 in the Implementation phase and increased to 0.934 Postimplementation (P < 0.01); AUC for IFA similarly increased, from 0.678 to 0.808 (P = 0.05). The reflexive testing strategy increased screening sensitivity from 61% Preimplementation (IFA) to 98% (EIA) at Implementation and was maintained after optimization (98%, Postimplementation). Optimization decreased the false-positive rates for both EIA (from 40% to 18%) and IFA (18% to 8%) and was associated with reductions in daily full-time equivalent (by 33%) and IFA slide use (by 50%). CONCLUSIONS: Continuous quality monitoring approaches that incorporate sequential data sets can be used to evaluate, deploy, and optimize sensitive EIA-based ANA screening methods that can reduce manual IFA work without sacrificing clinically utility.