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分析前阶段室间质量评价中的性能评估:实验室能否避免常见失误?

Evaluation of performance in preanalytical phase EQA: can laboratories mitigate common pitfalls?

作者信息

Linko-Parvinen Anna, Pelanti Jonna, Vanhelo Tanja, Eloranta Pia, Pallari Hanna-Mari

机构信息

Tyks Laboratories, Clinical Chemistry, Turku University Hospital, Turku, Finland.

Department of Clinical Chemistry, University of Turku, Turku, Finland.

出版信息

Clin Chem Lab Med. 2024 Dec 16;63(5):931-941. doi: 10.1515/cclm-2024-0990. Print 2025 Apr 28.

Abstract

OBJECTIVES

Preanalytical phase is an elemental part of laboratory diagnostics, but is prone to humane errors. The aim of this study was to evaluate performance in preanalytical phase external quality assessment (EQA) cases. We also suggest preventive actions for risk mitigation.

METHODS

We included 12 EQA rounds (Labquality Ltd.) with three patient cases (36 cases, 54-111 participants, 7-15 countries) published in 2018-2023. We graded performance according to percentage of correct responses in each case as ≥900 % excellent, 70-89 % good, 50-69 % satisfactory, 30-49 % fair and <30 % poor. Performance was simultaneously failed with ≥10 % of responses leading to harmful events.

RESULTS

Overall performance was excellent in 7, good in 12, satisfactory in 10, fair in 4 and poor in 3 cases. Additionally, 7 cases showed failed performance. Routine requests with incorrect sample tubes or incorrect sample handling were detected with good performance. Lower performance was seen with sudden abnormal results, with rare requests, with false patient identification (never-events) and with incorrect test requests. Information technology (IT) solutions (preanalytical checklists, autoverification rules and patient specific notifications) could have prevented 33 of 36 preanalytical errors.

CONCLUSIONS

While most common errors were detected with good performance, samples with rare requests or those requiring individualised consideration are vulnerable to human misinterpretation. In many instances, samples with preanalytical errors should have been identified and rejected before reaching the laboratory or being directed to analysis. Optimising IT solutions to effectively detect these preanalytical errors allows for focus on infrequent events demanding accessible professional consultation. EQA preanalytical cases may help in education of correct actions in these occasions.

摘要

目的

分析前阶段是实验室诊断的基本组成部分,但容易出现人为错误。本研究的目的是评估分析前阶段外部质量评估(EQA)案例中的表现。我们还提出了降低风险的预防措施。

方法

我们纳入了2018 - 2023年发布的12轮EQA(Labquality有限公司),其中包含三个患者案例(共36个案例,54 - 111名参与者,7 - 15个国家)。我们根据每个案例中正确回答的百分比对表现进行分级:≥90%为优秀,70 - 89%为良好,50 - 69%为满意,30 - 49%为中等,<30%为差。当≥10%的回答导致有害事件时,表现同时判定为不合格。

结果

总体表现优秀的有7个案例,良好的有12个案例,满意的有10个案例,中等的有4个案例,差的有3个案例。此外,有7个案例表现不合格。常规检测中,样本管不正确或样本处理不当的情况表现良好。对于突发异常结果、罕见检测请求、错误的患者识别(零失误事件)以及错误的检测请求,表现较差。信息技术(IT)解决方案(分析前检查表、自动验证规则和患者特定通知)本可预防36例分析前错误中的33例。

结论

虽然大多数常见错误的检测表现良好,但罕见检测请求的样本或需要个体化考虑的样本容易出现人为误解。在许多情况下,分析前有错误的样本在到达实验室或进行分析之前就应该被识别并拒收。优化IT解决方案以有效检测这些分析前错误,有助于关注需要专业咨询的罕见事件。EQA分析前案例可能有助于在这些情况下进行正确操作的培训。

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