Lab Med Qual Assur 2024; 46(3): 145-155
Published online September 30, 2024
https://doi.org/10.15263/jlmqa.2024.46.3.145
Copyright © Korean Association of External Quality Assessment Service.
Sang-Mi Kim1 , Kyunghoon Lee2 , Sollip Kim3 , Yong-Wha Lee4 , Sail Chun3 , and Hyung-Doo Park1,5
1Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul; 2Department of Laboratory Medicine, Seoul National University Bundang Hospital, Seongnam; 3Department of Laboratory Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul; 4Department of Laboratory Medicine and Genetics, Soonchunhyang University Bucheon Hospital, Soonchunhyang University College of Medicine, Bucheon; 5Department of Medical Device Management and Research, SAIHST, Sungkyunkwan University, Seoul, Korea
Correspondence to:Hyung-Doo Park
Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Korea
Tel +82-2-3410-0290
E-mail nayadoo@hanmail.net
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: The preanalytical phase is more vulnerable to errors. This study aimed to establish preanalytical quality indicators (QIs) suitable for Korean clinical laboratories and investigate the current status of preanalytical phase performance monitoring in Korea using these QIs.
Methods: We reviewed previous studies investigating preanalytical QIs including the International Federation of Clinical Chemistry (IFCC) model of QIs, to establish a set of QIs for Korean clinical laboratories. An e-mail survey consisting of this QI set was sent to 90 clinical laboratories. The collected data were analyzed, and performance measures were evaluated according to the quality specifications defined by the IFCC and the sigma-scale method.
Results: A model consisting of 23 preanalytical phase QIs was established. Approximately 47% (42/90) of clinical laboratories responded to the survey. The average result submission rate for each QI was 56% (standard deviation, 26%). The QIs with the highest and lowest result submission rates were “rejected samples due to hemolysis” (95%) and “recollected sample due to errors caused outside the laboratory” (17%). The QIs with the highest and lowest error rates were “hemolyzed sample detected by hemolytic index” (median, 0.546%; sigma performance level, “good”) and “samples not received” (median, 0.001%; sigma performance level, “very good”), respectively.
Conclusions: This survey findings on preanalytical phase QIs could serve as a foundation for developing an external quality assessment program for clinical laboratories in Korea.
Keywords: Pre-analytical phase, Quality indicators, Laboratory errors, Sigma metrics, Patient safety
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