Solution Found for Mislabeled Specimens in Clinical Laboratories

Laboratory scientists at the ARUP Laboratories (Salt Lake City, UT, USA) have examined the problem of misidentification and have suggested some possible solutions. One approach is the single piece flow and this concept has significant error-proofing potential for labeling tasks at relatively low cost. They suggest that to prevent errors during collection and processing, avoid having specimens from multiple patients in the active work area at the same time. Similarly, avoid using strips of labels from a label printer with labels for multiple patients that must be matched to specimens and if using an automated aliquoting device, be sure that the label exactly duplicates the barcode label from the primary tube to facilitate error detection.

Another tool that more laboratories are using is the portable barcode scanner. These scanners read wristband barcodes at point-of-collection and work well in conjunction with portable barcode label printers or point-of-care analytical devices. However, barcode devices make more errors than commonly believed. Display and layout inconsistency of the barcode can also leads to an increase in errors. It is recommended to implement the Clinical and Laboratory Standards Institute (Wayne, PA, USA) Standard AUTO12-A, Specimen Labels: Content and Location, Fonts, and Label Orientation.

The scientists have invented one high tech solution that they believe will bring their own error rate for mislabeled specimens to near zero and which, with further refinement, may become suitable for use on commercial automation systems. This is a robotic camera system that can lift a specimen tube from the transport carrier on an automated track, take four simultaneous photographs of the tube using four equidistantly spaced high resolution cameras, and precisely stitch the four photographs into a single photograph of the entire exterior of the tube. It then uses optical character recognition (OCR) to compare the patient name on the original label to the patient name in the laboratory information system (LIS), as identified by reading the barcode on the LIS label.

Since the robotic system was implemented in October 2012, the system has collected and analyzed some 2.4 million images and more than 300 mislabeled specimens have been detected, of which only 53% were found through our normal quality assurance processes. For the subset of specimens routed through this advanced automation, significantly fewer corrected reports have been issued.

Related Links:
College of American Pathologists
ARUP Laboratories 
Clinical and Laboratory Standards Institute