Lab Med Qual Assur 2023; 45(3): 107-114
Published online September 30, 2023
https://doi.org/10.15263/jlmqa.2023.45.3.107
Copyright © Korean Association of External Quality Assessment Service.
Yong Hun Jo* , Sooin Choi*
, Jae Joon Lee
, Jeong Gwon Kim
, and Yong-Wha Lee
Department of Laboratory Medicine and Genetics, Soonchunhyang University Bucheon Hospital, Soonchunhyang University College of Medicine, Bucheon, Korea
Correspondence to:Yong-Wha Lee
Department of Laboratory Medicine and Genetics, Soonchunhyang University Bucheon Hospital, Soonchunhyang University College of Medicine, 170 Jomaru-ro, Wonmi-gu, Bucheon 14584, Korea
Tel +82-32-621-5943
E-mail lywmd@schmc.ac.kr
*These authors equally contributed to this study.
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: While glucose point-of-care testing (POCT) is widely utilized, it is often carried out by clinical staff who may lack specific test-related training, potentially leading to inadequate quality control (QC) procedures. This study aimed to establish a comprehensive quality management system for glucose POCT.
Methods: We implemented a systematic approach encompassing quality assurance, equipment maintenance, operator training, and competency assessment in alignment with the Clinical and Laboratory Standards Institute guidelines POCT12-A3. To facilitate structured internal QC, the results of glucose POCT were automatically analyzed within the laboratory information system (LIS). An adjusted acceptable range was defined as mean±2 standard deviations (SD) based on 1 month of QC result analysis operator performance was enhanced through a tailored training program, and proficiency tests were conducted on all glucometers to assess competency.
Results: Leveraging the LIS allowed the application of quality control rules to glucose POCT, enabling swift error identification and response. Analysis of one month’s QC results revealed that for high-concentration samples, the warning rate using the adjusted range was significantly higher than that using the provided range (1.1% vs. 2.7%, P<0.01). A maintenance schedule was established, encompassing monthly upkeep for glucometers and collective replacement of all QC materials every 3 months. Operator training was facilitated through both face-to-face education and instructional videos. During proficiency testing, four devices initially exhibited deviations beyond 3SD, which were subsequently rectified upon re-examination.
Conclusions: The implementation of a systematic and efficient quality control system, as demonstrated in this study, holds the potential to yield accurate and dependable glucose POCT results.
Keywords: Point-of-care testing, Glucometer, Glucose, Quality assurance, Quality control, Laboratory information system, CLSI POCT12-A3
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