Lab Med Qual Assur 2023; 45(3): 115-119
Published online September 30, 2023
https://doi.org/10.15263/jlmqa.2023.45.3.115
Copyright © Korean Association of External Quality Assessment Service.
Han Joo Kim1 , Yousun Chung2 , Hyungsuk Kim3 , Sang-Hyun Hwang1 , Heung-Bum Oh1 , and Dae-Hyun Ko1
1Department of Laboratory Medicine, Asan Medical Center, University of Ulsan College of Medicine; 2Department of Laboratory Medicine, Kangdong Sacred Heart Hospital; 3Department of Laboratory Medicine, Seoul National University Hospital, Seoul, Korea
Correspondence to:Dae-Hyun Ko
Department of Laboratory Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Songpa-gu, Seoul 05505, Korea
Tel +82-2-3010-4504
E-mail daehyuni1118@amc.seoul.kr
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background: External quality assessment (EQA) in transfusion medicine is conducted by the Korean Association of External Quality Assessment Service (KEQAS) for five programs covering 14 survey items. Results were annually analyzed and published in Laboratory Medicine and Quality Assurance, the official academic journal of KEQAS. Identifying trends in the transfusion medicine program is challenging due to remarkably low error rate. We aimed to analyze the error rates and types across recent 4-year results of general blood transfusion tests and suggest applicable solutions for laboratories.
Methods: The results and reports from participating laboratories in general blood transfusion tests of the EQA between 2019–2022 were analyzed. Specifically, we categorized the ‘unacceptable’ results and analyzed their patterns. Statistical analysis was performed using R ver. 4.0.0.
Results: A total of 6,277 reports with 193,152 results were analyzed. A total of 4,681 results were unacceptable. There were between 549–768 unacceptable results per round, with an average of 2.4%. Among them, majority (4,159 cases, 88.8%) of the results were attributed to incorrect interpretation of agglutination. When categorized by survey item, there was a significantly higher number of errors in interpreting agglutination in serum typing of an ABO group than in cell typing. Analyzing the error type by each year, agglutination interpretation error was the most frequent. Errors due to differences in test methods tend to be relatively decreasing.
Conclusions: Accurate interpretation of the test results, careful consideration for selection of test methods, and cross-validation to minimize clerical errors are necessary. Additionally, continuous education and making efforts towards improvements are essential.
Keywords: Transfusion medicine, Quality improvement, Laboratory proficiency testing
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