控制图
风险管理
计算机科学
风险评估
图表
风险分析(工程)
贝叶斯定理
控制(管理)
质量(理念)
统计
可靠性工程
医学
数学
工程类
人工智能
贝叶斯概率
过程(计算)
操作系统
哲学
经济
管理
计算机安全
认识论
作者
Yuping Zeng,Shiyun Peng,Lingwei Meng,He Huang
标识
DOI:10.1177/00045632221086468
摘要
Risk management strategies have been proposed for applications in clinical laboratories to reduce patient risks; however, effective and visual risk-monitoring tools are currently lacking in medical laboratories. In this study, we constructed a risk quality control (QC) chart based on risk management strategies.We calculated the risk levels of QC materials based on Bayes' theorem by combining the total allowable error, QC results, and the maximum number of unacceptable errors in the laboratory. Then, we constructed a risk QC chart by presenting the Z values and corresponding risk levels of QC materials simultaneously. Finally, we evaluated the risk-monitoring capabilities of the risk QC charts by simulating different long-term errors in the laboratory.The risk levels of QC materials increased as the QC results moved further away from the set mean. Larger sigma values led to fewer risks obtained for the same QC results. The constructed risk QC charts intuitively showed specific risk levels and could warn lab staff out-of-control, without the need for QC rules to make judgments. The risk levels of erroneous results differed for items with different sigma performance.Risk-based QC charts allowed visualization of the QC results and specific risk levels simultaneously, providing more intuitive results than those obtained from traditional QC charts.
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