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INTRODUCTION: Use of fully automated solutions to perform analysis of immunohematology tests is highly desirable as it delivers an improved level of safety and security of results. However, full automation may not be feasible financially and practically in all circumstances. A solution that addresses most of the process step hazards of manual testing can assist in achieving a higher level of confidence in and safety of test results. METHODS: The study utilized a column agglutination technology (ORTHO BioVue ® System) to test a variety of samples on the ORTHO VISION ® Analyzer and compare to the reader capability of the ORTHO OPTIX™ Reader. Both direct agglutination and direct/indirect antiglobulin test methods were evaluated. The data was analysed for per cent agreement and for concordance at the lower bound 95% confidence interval. The acceptance criteria for concordance for direct agglutination was ≥ 99.4% and for indirect agglutination was ≥ 98.0% at a lower bound 95% confidence interval. RESULTS: There were 13,805 columns producing 5174 interpreted tests for direct agglutination and 5998 columns producing 2958 interpreted direct/indirect antiglobulin tests evaluated. Testing demonstrated that direct agglutination and direct/indirect antiglobulin testing generated greater than 99% concordance between the fully automated instrument system and the reader. CONCLUSIONS: The reader exceeded the approval criteria set for the study which demonstrates the capability to address the desire for a solution that moves manual testing to an enhanced level which achieves improved safety and security in immunohematology testing.

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CONCLUSIONS: Immunoglobulin therapy that interferes with pretransfusion testing may complicate the interpretation of test results and adversely affect patient management. Rh immune globulin (RhIG) should be considered an interfering immunoglobulin therapy when it is detected in an antibody detection test of a sample from a patient who has been treated with RhIG. Frequently, detection occurs in mother's or newborn's plasma. Because an antenatal injection of RhIG is indicated for pregnant Rh-negative women, anti-D is detected frequently by today's highly sensitive antibody screen methods when the mother's plasma is tested subsequently at delivery. Ascertaining the source of anti-D is complicated by the inability of routine clinical laboratory methods to distinguish anti-D due to RhIG from alloimmune anti-D. A combination of qualitative and quantitative test methods, as well as a complete clinical history, is necessary for accurate diagnosis and patient management.

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BACKGROUND: Protecting the safety of blood transfusion is the top priority of transfusion service laboratories. Pretransfusion testing is a critical element of the entire transfusion process to enhance vein-to-vein safety. Human error associated with manual pretransfusion testing is a cause of transfusion-related mortality and morbidity and most human errors can be eliminated by automated systems. However, the uptake of automation in transfusion services has been slow and many transfusion service laboratories around the world still use manual blood group and antibody screen (G&S) methods. STUDY DESIGN AND METHODS: The goal of this study was to compare error potentials of commonly used manual (e.g., tiles and tubes) versus automated (e.g., ID-GelStation and AutoVue Innova) G&S methods. Routine G&S processes in seven transfusion service laboratories (four with manual and three with automated G&S methods) were analyzed using failure modes and effects analysis to evaluate the corresponding error potentials of each method. RESULTS: Manual methods contained a higher number of process steps ranging from 22 to 39, while automated G&S methods only contained six to eight steps. Corresponding to the number of the process steps that required human interactions, the risk priority number (RPN) of the manual methods ranged from 5304 to 10,976. In contrast, the RPN of the automated methods was between 129 and 436 and also demonstrated a 90% to 98% reduction of the defect opportunities in routine G&S testing. CONCLUSION: This study provided quantitative evidence on how automation could transform pretransfusion testing processes by dramatically reducing error potentials and thus would improve the safety of blood transfusion.

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