North Kansas City Hospital North Kansas City, Missouri, United States
Background/Case Studies: Accurate patient identification and specimen labeling are crucial in transfusion medicine to ensure safe blood product administration. Misdrawn or mislabeled samples can lead to serious clinical consequences. Investigating wrong blood in tube events is essential to track trends and identify root causes for process improvements.
Traditional serologic methods may be time-consuming and labor-intensive for investigating patient identity discrepancies. Automated red cell phenotyping offers a high-throughput, objective approach to antigen profiling and can help investigate wrong blood in tube errors. It provides faster turnaround times and quality control for multiple antigen types compared to manual methods. Instrument printed reports display reaction grades and interpretations for quality assurance.
This study explores using automated phenotyping in the blood bank to resolve suspected sample misidentification, enhancing transfusion safety and supporting root cause analysis.
Study
Design/Methods: A 30-year-old female in active labor had unknown prenatal care status. Routine labs, including a type and screen (TS), were collected but initially rejected due to missing witness documentation. Blood bank policy requires a second witness for identification. The RN noted the patient was a difficult stick, delaying recollection.
An hour later, the RN contacted the blood bank for help with Positive Patient Identification (PPID) label printing. A full 6.0 mL tube was received quickly. The technologist confirmed proper PPID scanning but noted the unusually fast collection turnaround.
Automated hemagglutination testing flagged a questionable ABORh result. Follow up tube testing showed sticky reactions; after washing, the result was AB+. A confirmation sample collected by a lab staff typed B+. A third collection from the patient also typed B+.
Further investigation revealed two AB+ patients were in the unit at the time, raising concern for a misidentified blood collection. Automated phenotyping and cross-checking confirmed the initial TS belonged to another patient, ensuring accurate identification and transfusion safety.
Results/Findings: Automated antigen typing was employed to investigate the phenotyping of the unknown blood sample in comparison with other patients of the same AB+ blood type in proximity to the Labor and Delivery unit. Table 1 shows the results of the phenotyping.
Conclusions: FDA approved automated red cell phenotyping proved to be instrumental in expediting the investigation of a mislabeled specimen. In this case, the extended phenotyping supported the trends of delayed specimen labeling which led to a baby’s cord blood being labeled as the mother’s type and screen specimen. Consequently, an immediate process change was proposed to use a different colored stopper test tube exclusively for cord blood samples.
