Huang Yun, Loveday Callie, Vincent Anne
Kingston Health Sciences Center, Kingston, ON, Canada.
Department of Pathology and Molecular Medicine, Queen's University, Kingston, ON, Canada.
Heliyon. 2024 Aug 22;10(17):e36651. doi: 10.1016/j.heliyon.2024.e36651. eCollection 2024 Sep 15.
This study applied Six Sigma metrics to facilitate the quality control (QC) review for hospital glucose meters.
QC data from a period of six months on all hospital glucose meters were extracted from the data management system. Sigma values for each meter at two QC levels were calculated and evaluated each month by combining the imprecision, the absolute bias between the meter mean and all-meter mean, and the standards from ISO 15179:2013. The effectiveness of using Sigma values in identifying meters with possible quality problems for further Levey-Jennings QC chart review was assessed.
More than 80 % of the meter's Sigma values within the six months were greater than 4 at either QC level. At the high QC level, twice as many Sigma values were below 4 than the low QC level. Including Sigma values 4, 3.5 or 3 in the criteria for the QC review reduced the number of chart review to 32.8 %, 11.2 % or 3.5 %, respectively.
The majority of the glucose meters examined in this study demonstrated optimal Sigma values. The Sigma metrics-based approach could be a valuable tool to guide an effective QC review of glucose meters for quality improvement.
本研究应用六西格玛指标促进医院血糖仪的质量控制(QC)审查。
从数据管理系统中提取所有医院血糖仪六个月期间的QC数据。计算每个血糖仪在两个QC水平下的西格玛值,并每月通过结合不精密度、血糖仪均值与所有血糖仪均值之间的绝对偏差以及ISO 15179:2013标准进行评估。评估使用西格玛值识别可能存在质量问题的血糖仪以进行进一步的Levey-Jennings QC图审查的有效性。
在六个月内,超过80%的血糖仪在任一QC水平下的西格玛值大于4。在高QC水平下,西格玛值低于4的数量是低QC水平下的两倍。将西格玛值4、3.5或3纳入QC审查标准分别将图表审查数量减少至32.8%、11.2%或3.5%。
本研究中检查的大多数血糖仪显示出最佳西格玛值。基于西格玛指标的方法可能是指导对血糖仪进行有效QC审查以提高质量的有价值工具。