Increased instrument intelligence--can it reduce laboratory error?

Abstract

Recent literature has focused on the reduction of laboratory errors and the potential impact on patient management. This study assessed the intelligent, automated preanalytical process-control abilities in newer generation analyzers as compared with older analyzers and the impact on error reduction. Three generations of immuno-chemistry analyzers were challenged with pooled human serum samples for a 3-week period. One of the three analyzers had an intelligent process of fluidics checks, including bubble detection. Bubbles can cause erroneous results due to incomplete sample aspiration. This variable was chosen because it is the most easily controlled sample defect that can be introduced. Traditionally, lab technicians have had to visually inspect each sample for the presence of bubbles. This is time consuming and introduces the possibility of human error. Instruments with bubble detection may be able to eliminate the human factor and reduce errors associated with the presence of bubbles. Specific samples were vortexed daily to introduce a visible quantity of bubbles, then immediately placed in the daily run. Errors were defined as a reported result greater than three standard deviations below the mean and associated with incomplete sample aspiration of the analyte of the individual analyzer Three standard deviations represented the target limits of proficiency testing. The results of the assays were examined for accuracy and precision. Efficiency, measured as process throughput, was also measured to associate a cost factor and potential impact of the error detection on the overall process. The analyzer performance stratified according to their level of internal process control The older analyzers without bubble detection reported 23 erred results. The newest analyzer with bubble detection reported one specimen incorrectly. The precision and accuracy of the nonvortexed specimens were excellent and acceptable for all three analyzers. No errors were found in the nonvortexed specimens. There were no significant differences in overall process time for any of the analyzers when tests were arranged in an optimal configuration. The analyzer with advanced fluidic intelligence demostrated the greatest ability to appropriately deal with an incomplete aspiration by not processing and reporting a result for the sample. This study suggests that preanalytical process-control capabilities could reduce errors. By association, it implies that similar intelligent process controls could favorably impact the error rate and, in the case of this instrument, do it without negatively impacting process throughput. Other improvements may be realized as a result of having an intelligent error-detection process including further reduction in misreported results, fewer repeats, less operator intervention, and less reagent waste.