预处理器
计算机科学
分析器
质量(理念)
控制图
下垂
控制(管理)
I类和II类错误
质量管理
数据挖掘
统计
人工智能
数学
工程类
运营管理
管理制度
哲学
化学
考古
认识论
色谱法
过程(计算)
历史
操作系统
作者
Dominic Man,Runqing Mu,Kun Zhang,Zhiwei Zhou,Hui Kang
标识
DOI:10.1016/j.cca.2023.117562
摘要
Patient-based real-time quality control (PBRTQC) has gained increasing attention in clinical laboratory management. Although its valuable characteristics complement traditional quality control measures, its performance and practical application have faced scrutiny. In this study, patient-based pre-classified real-time quality control (PCRTQC), an extended approach was devised to enhance real-time quality control protocols. PCRTQC distinguishes itself by incorporating an additional patient pre-classification step utilising the OPTICS algorithm, thus addressing interference from diverse patient types. The complete set of patient test results obtained from a clinical chemistry analyser at The First Hospital of China Medical University in 2021 was utilised. Constant error (CE) and proportional error (PE) were introduced as analytical errors. Four analytes were selected to evaluate the PCRTQC, measuring probability for false rejection (Pfr) and the average number of patient samples until error detection (ANPed). Relevant error detection charts were generated. The PCRTQC outperformed regression-adjusted real-time quality control (RARTQC) based on the ANPed by approximately 50% for both the CE and PE, compared to the RARTQC, particularly for the total allowable error threshold. The pre-classification step effectively reduced inter-individual variation and improved data preprocessing, filtering, and modelling. The PCRTQC is a robust framework for real-time quality control research.
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