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利用异常事件监测检验周转时间。

Using outlier events to monitor test turnaround time.

作者信息

Steindel S J, Novis D A

机构信息

Centers for Disease Control and Prevention, Public Health Practice Program Office, Division of Laboratory Systems, Laboratory Performance Assessment Branch, Chamblee, GA, USA.

出版信息

Arch Pathol Lab Med. 1999 Jul;123(7):607-14. doi: 10.5858/1999-123-0607-UOETMT.

Abstract

OBJECTIVES

To determine the causes of excessive test turnaround time (TAT) and to identify methods of improvement by studying reasons for those tests reported in excess of 70 minutes from the time the test was ordered (ie, outliers).

DESIGN

Self-directed data-gathering of stat outlier TAT events from intensive care units and emergency departments, with descriptive parameters associated with each event and additional descriptive parameters associated with the participant.

PARTICIPANTS

Laboratories enrolled in the 1996 College of American Pathologists Q-Probes program.

MAIN OUTCOME MEASURES

Components associated with outlier TAT events and outlier TAT rates.

RESULTS

Four hundred ninety-six hospital laboratories returned data on 218 551 stat tests, of which 10.6% had TATs in excess of 70 minutes. Ten percent of stat emergency department tests and 14.7% of stat intensive care unit tests were outliers. Major areas in which delays occurred were test ordering, 29.9%; within-laboratory (analytic) phase, 28.2%; collection of the specimen, 27.4%; postanalytic phase, 1.9%; and undetermined, 12.5%. The type of test performed was a significant factor and was independent of location: Chemistry-Multiple Test appeared most frequently ( approximately 40%), followed closely by Hematology-Complete Blood Count (approximately 20%) and Chemistry-Single Test ( approximately 18%). Factors of outlier TAT components for intensive care unit specimens were identified using statistical modeling and included hour of day, type of health care personnel collecting specimen, performing the test in a stat laboratory, and reason for delay. Outlier rates were not associated with any identified factors. The practice parameters of laboratories with outlier rates in the lowest 10th percentile significantly differed from those with rates in the top 10th percentile in test request computerization, report methods, and ordering methods.

CONCLUSIONS

We observed that outlier analysis yields new information, such as type of test and reason for delay, concerning test delays when compared with TAT determination alone. Laboratories experiencing stat test TAT problems should use this tool as an adjunct to routine TAT monitoring for identifying unique causes of delay.

摘要

目的

通过研究那些从医嘱开出后报告时间超过70分钟的检验(即异常值)的原因,来确定检验周转时间(TAT)过长的原因,并找出改进方法。

设计

对重症监护病房和急诊科的急诊异常值TAT事件进行自主数据收集,记录与每个事件相关的描述性参数以及与参与者相关的其他描述性参数。

参与者

参加1996年美国病理学家学会Q-Probes项目的实验室。

主要观察指标

与异常值TAT事件相关的组成部分和异常值TAT率。

结果

496家医院实验室返回了218551次急诊检验的数据,其中10.6%的检验TAT超过70分钟。急诊科室10%的急诊检验和重症监护病房14.7%的急诊检验为异常值。出现延迟的主要环节包括:医嘱开出,占29.9%;实验室内部(分析)阶段,占28.2%;标本采集,占27.4%;分析后阶段,占1.9%;原因不明,占12.5%。所进行的检验类型是一个重要因素,且与地点无关:多项化学检验出现频率最高(约40%),其次是全血细胞计数血液学检验(约20%)和单项化学检验(约18%)。通过统计建模确定了重症监护病房标本异常值TAT组成部分的因素,包括日期时间、采集标本的医护人员类型、在急诊实验室进行检验以及延迟原因。异常值率与任何已确定因素均无关联。异常值率处于最低十分位数的实验室与处于最高十分位数的实验室在检验申请计算机化、报告方法和医嘱开出方法等实践参数方面存在显著差异。

结论

我们观察到,与仅进行TAT测定相比,异常值分析能得出有关检验延迟的新信息,如检验类型和延迟原因。遇到急诊检验TAT问题的实验室应将此工具作为常规TAT监测的辅助手段,以识别延迟的独特原因。

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