Reduced bracketed control concept for automated biochemistry analyzers: A reliable and cost-effective setup

IF 3.2 3区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY
Helle Glud Binderup, Trine Rennebod Larsen, Steen Antonsen
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引用次数: 0

Abstract

Objectives

Today, most biochemical analytes are produced on automated analysers in continuous mode, and internal quality control (IQC) protocols often include a “critical control” analysed after maintenance and a “bracketed control” (BC) analysed periodically along with patient samples. As quality control materials and reagents are costly, the BC might be reduced to one level of IQC and include only selected analytes, covering testing principles and essential technical parts of the analyser. This study aimed to investigate whether such a reduced BC (rBC) is reliable for detecting clinically relevant analytical problems.

Methods

Over 8 months, we compared an rBC with nine analytes and one IQC level with a full BC (fBC) with 65 analytes and two IQC levels regarding the analytical problems revealed.

Results

A total of 1,463,512 patient results were produced. With the fBC and rBC, respectively, 1669 and 996 patient samples were reanalysed due to an IQC result outside acceptance limits, resulting in the correction of 311 and 222 patient results. The rBC overlooked 89 (0.061 ‰) patient results outside our correction limits, only two of which were judged to be of potentially serious clinical importance. The extra annual cost of identifying these errors in our setting is approximately 220,000 €.

Conclusions

In our setup, the rBC overlooked only very few errors of clinical importance. This rate might be further reduced by including in the rBC any critical tests that are not prone to patient-based real-time quality control, which should be used for remaining, relevant tests.
减少了自动化生物化学分析仪的括号控制概念:一个可靠的和具有成本效益的设置
目前,大多数生化分析都是在连续模式下的自动分析仪上产生的,内部质量控制(IQC)方案通常包括在维护后分析的“关键控制”和定期与患者样本一起分析的“括号控制”(BC)。由于质量控制材料和试剂昂贵,BC可能会降低到IQC的一个级别,只包括选定的分析物,涵盖测试原理和分析仪的基本技术部件。本研究旨在探讨这种减少的BC (rBC)是否可靠地用于检测临床相关的分析问题。方法在8个月的时间里,我们比较了含有9个分析物和1个IQC水平的红细胞与含有65个分析物和2个IQC水平的全BC (fBC)的分析问题。结果共获得1463512例患者结果。由于IQC结果超出可接受范围,分别对1669例和996例患者的fBC和rBC样本进行了重新分析,导致311例和222例患者的结果被更正。rBC忽略了89例(0.061‰)患者的结果超出了我们的校正范围,其中只有2例被认为具有潜在的严重临床重要性。在我们的环境中,识别这些错误的额外年度成本约为22万欧元。结论在我们的研究中,rBC只忽略了很少的临床重要错误。通过在红细胞中纳入不容易进行基于患者的实时质量控制的任何关键测试,这一比率可能会进一步降低,这些测试应用于剩余的相关测试。
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来源期刊
Clinica Chimica Acta
Clinica Chimica Acta 医学-医学实验技术
CiteScore
10.10
自引率
2.00%
发文量
1268
审稿时长
23 days
期刊介绍: The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.
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