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首页> 外文期刊>Canadian journal of anesthesia: Journal canadien d'anesthesie >Statistical process control methods allow the analysis and improvement of anesthesia care: (Les methodes de controle statistique du processus permettent d'analyser et d'ameliorer les soins anesthesiques).
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Statistical process control methods allow the analysis and improvement of anesthesia care: (Les methodes de controle statistique du processus permettent d'analyser et d'ameliorer les soins anesthesiques).

机译：统计过程控制方法可以分析和改善麻醉护理：统计过程控制方法可以分析和改善麻醉护理。

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PURPOSE: Quality aspects of the anesthetic process are reflected in the rate of intraoperative adverse events. The purpose of this report is to illustrate how the quality of the anesthesia process can be analyzed using statistical process control methods, and exemplify how this analysis can be used for quality improvement. METHODS: We prospectively recorded anesthesia-related data from all anesthetics for five years. The data included intraoperative adverse events, which were graded into four levels, according to severity. We selected four adverse events, representing important quality and safety aspects, for statistical process control analysis. These were: inadequate regional anesthesia, difficult emergence from general anesthesia, intubation difficulties and drug errors. We analyzed the underlying process using 'p-charts' for statistical process control. RESULTS: In 65,170 anesthetics we recorded adverse events in 18.3%; mostly of lesser severity. Control charts were used to define statistically thepredictable normal variation in problem rate, and then used as a basis for analysis of the selected problems with the following results: -Inadequate plexus anesthesia: stable process, but unacceptably high failure rate; -Difficult emergence: unstable process, because of quality improvement efforts; -Intubation difficulties: stable process, rate acceptable; -Medication errors: methodology not suited because of low rate of errors. CONCLUSION: By applying statistical process control methods to the analysis of adverse events, we have exemplified how this allows us to determine if a process is stable, whether an intervention is required, and if quality improvement efforts have the desired effect.
机译：目的：麻醉过程的质量方面反映在术中不良事件发生率上。本报告的目的是说明如何使用统计过程控制方法分析麻醉过程的质量，并举例说明如何将此分析用于质量改善。方法：我们前瞻性地记录了所有麻醉药在五年内的麻醉相关数据。数据包括术中不良事件，根据严重程度分为四个级别。我们选择了代表重要质量和安全方面的四个不良事件进行统计过程控制分析。它们是：区域麻醉不足，全身麻醉难以出现，插管困难和药物错误。我们使用“ p-图”分析了基础过程，以进行统计过程控制。结果：在65,170例麻醉剂中，我们记录到的不良事件发生率为18.3％;而在所有麻醉剂中，不良事件的发生率均为18.3％。严重程度较小。控制图用于统计定义问题率的可预测正常变化，然后用作分析所选问题的基础，其结果如下：-麻醉不足：过程稳定，但失败率高到无法接受; -出现困难：由于质量改进工作，过程不稳定; -插管困难：过程稳定，速率可接受; -药物错误：由于错误率低，方法不适合。结论：通过将统计过程控制方法应用于不良事件的分析，我们已举例说明了这如何使我们能够确定过程是否稳定，是否需要干预以及质量改进措施是否具有预期的效果。

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