Evaluation of local hemoglobinopathy prevalence and promotion of accurate hemoglobin A1c testing using historical data retrieval.

OBJECTIVES: Heterozygous hemoglobin variants are known to cause method- and variant-specific interference with hemoglobin A1c (HbA1c) quantitation. Less attention has been paid to the role of other hemoglobin variants in confounding HbA1c testing. Here we evaluated the frequency with which enzymatic (ENZ) and immunoassay (IA) HbA1c quantitation methods, i.e., those unable to routinely detect the presence of hemoglobin variants, were used within our healthcare system for HbA1c analysis in patients with elevated fetal hemoglobin as well as compound heterozygous and homozygous variants. DESIGN & METHODS: This analysis was enabled by automated review of HbA1c result history, implemented to promote detection of variants prior to HbA1c result reporting. RESULTS: During a 54-week period, 319,290 HbA1c analyses were performed. We observed 110 unique patient cases (0.03% problem identification rate) in which HbA1c testing was ordered in the presence of either a homozygous or compound heterozygous hemoglobin variant or elevated hemoglobin F beyond the tolerance of the method. Among the 110 cases identified, 55 (50%) showed a compound heterozygous or homozygous hemoglobin variant while 55 (50%) showed elevated hemoglobin F. Of those cases involving a compound heterozygous or homozygous variant, 8/55 (15%) involved patients who had one or more ENZ or IA HbA1c results reported previously within our system. Of the 55 total compound heterozygous or homozygous variants identified, 37 (67%) were hemoglobin E, 10 (18%) hemoglobin S/C, 4 (7%) hemoglobin S, 2 (4%) hemoglobin C, 1 (2%) hemoglobin Camden, and 1 (2%) unidentified variant. CONCLUSIONS: Exclusive use of methods unable to routinely detect the presence of hemoglobin variants may lead to reporting of HbA1c results that are not clinically meaningful.

Optimizing testing for Clostridium difficile infection: A quality improvement project.

Overtesting for Clostridium difficile may result in increased health care facility-onset C difficile infection LabID events. Our quality improvement project optimized testing through standardization of laboratory processes, electronic health record clinical decision support, and real-time monitoring. Our intervention resulted in a 59% reduction in health care facility-onset C difficile infection LabID events.