Multicenter evaluation of the hemolysis index in automated clinical chemistry systems.

BACKGROUND: In vitro hemolysis, the prevailing cause of preanalytical error in routine laboratory diagnostics, might influence the reliability of several tests, affect the quality of the total testing process and jeopardize patient safety. Although laboratory instrumentation is now routinely equipped with systems capable of automatically testing and eventually correcting for hemolysis interference, to our knowledge there are no reports that have compared the efficiency of different analytical platforms for identifying and classifying specimens with hemolysis. METHODS: Serum from a healthy volunteer was spiked with varying amounts of hemolyzed blood from the same volunteer, providing a serum free hemoglobin concentration ranging from 0.0 g/L to 2.0 g/L as measured by the reference cyanmethemoglobin assay. The spiked serum samples were shipped to seven separate laboratories and the hemolysis index (HI) was tested in triplicate on the following analytical platforms: Roche Modular System P (n=4) and Integra 400 Plus (n=1), Siemens Dimension RxL (n=3), ADVIA 2400 (n=1) and ADVIA 1800 (n=1), Olympus AU 680 (n=1) and Coulter DXC 800 (n=1). RESULTS: Satisfactory agreement of HI results was observed among the various analytical platforms, despite a trend toward overestimation by the ADVIA 2400 and 1800. After normalizing results according to the instrument-specific alert value, discrepancies were considerably reduced. All instruments except for the Dimension RxL gave values normalized to the instrument-specific alert value, <1.0 for the sample with 0.048 g/L free hemoglobin, and >1.0 for the sample with 0.075 g/L free hemoglobin. The results of the four Modular System P tests were also highly reproducible among the different facilities. When evaluating instruments that provided quantitative HI results, the mean intra-assay coefficient of variation (CV) calculated for the triplicate determinations was always between 0.1% and 2.7%. CONCLUSIONS: The results of this multicenter evaluation confirm that efficiency of different analytical platforms to correctly identify and classify unsuitable samples is satisfactory. However, more effort should be placed on the standardization of reporting HI. All the instruments that we tested provide either quantitative or qualitative results that are essentially comparable, but which should always be compared with the instrument-specific alert values to harmonize their efficiency.

Causes, consequences, detection, and prevention of identification errors in laboratory diagnostics.

Laboratory diagnostics, a pivotal part of clinical decision making, is no safer than other areas of healthcare, with most errors occurring in the manually intensive preanalytical process. Patient misidentification errors are potentially associated with the worst clinical outcome due to the potential for misdiagnosis and inappropriate therapy. While it is misleadingly assumed that identification errors occur at a low frequency in clinical laboratories, misidentification of general laboratory specimens is around 1% and can produce serious harm to patients, when not promptly detected. This article focuses on this challenging issue, providing an overview on the prevalence and leading causes of identification errors, analyzing the potential adverse consequences, and providing tentative guidelines for detection and prevention based on direct-positive identification, the use of information technology for data entry, automated systems for patient identification and specimen labeling, two or more identifiers during sample collection and delta check technology to identify significant variance of results from historical values. Once misidentification is detected, rejection and recollection is the most suitable approach to manage the specimen.

Haemolysis: an overview of the leading cause of unsuitable specimens in clinical laboratories.

Prevention of medical errors is a major goal of healthcare, though healthcare workers themselves have not yet fully accepted or implemented reliable models of system error, and neither has the public. While there is widespread perception that most medical errors arise from an inappropriate or delayed clinical management, the issue of laboratory errors is receiving a great deal of attention due to their impact on the quality and efficiency of laboratory performances and patient safety. Haemolytic specimens are a frequent occurrence in clinical laboratories, and prevalence can be as high as 3.3% of all of the routine samples, accounting for up to 40%-70% of all unsuitable specimens identified, nearly five times higher than other causes, such as insufficient, incorrect and clotted samples. This article focuses on this challenging issue, providing an overview on prevalence and leading causes of in vivo and in vitro haemolysis, and tentative guidelines on identification and management of haemolytic samples in clinical laboratories. This strategy includes continuous education of healthcare personnel, systematic detection/quantification of haemolysis in any sample, immediate clinicians warning on the probability of in vivo haemolysis, registration of non-conformity, completing of tests unaffected by haemolysis and request of a second specimen for those potentially affected.