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

Abstract

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. 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. 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%). 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.