Abstract
Preanalytic errors, including specimen labeling errors and specimen loss, occur frequently during specimen collection, transit, and accessioning. Radio-frequency identification tags can decrease specimen identification and tracking errors through continuous and automated tracking of specimens. To implement a specimen tracking infrastructure to reduce preanalytic errors (specimen mislabeling or loss) between specimen collection and laboratory accessioning. Specific goals were to decrease preanalytic errors by at least 70% and to simultaneously decrease employee effort dedicated to resolving preanalytic errors or investigating lost specimens. A radio-frequency identification specimen-tracking system was developed. Major features included integral radio-frequency identification labels (radio-frequency identification tags and traditional bar codes in a single printed label) printed by point-of-care printers in collection suites; dispersed radio-frequency identification readers at major transit points; and systems integration of the electronic health record, laboratory information system, and radio-frequency identification tracking system to allow for computerized physician order entry driven label generation, specimen transit time tracking, interval-based alarms, and automated accessioning. In the 6-month postimplementation period, 6 mislabeling events occurred in collection areas using the radio-frequency identification system, compared with 24 events in the 6-month preimplementation period (75% decrease; P = .001). In addition, the system led to the timely recovery of 3 lost specimens. Labeling expenses were decreased substantially in the transition from high-frequency to ultrahigh frequency radio-frequency identification tags. Radio-frequency identification specimen tracking prevented several potential specimen-loss events, decreased specimen recovery time, and decreased specimen labeling errors. Increases in labeling/tracking expenses for the system were more than offset by time savings and loss avoidance through error mitigation.
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