The measurement of internal quality-control samples (iQC) is the cornerstone of analytical quality assurance as implemented on a daily basis in medical laboratories.¹ For many tests, iQC is effective in ensuring that analytical performance is adequate. For other tests, however, using iQC alone is insufficient to assure appropriate analytical quality. Reasons include, firstly, the absence of (stable) quality-control materials, secondly, rapid-onset or temporary critical errors (between scheduled iQC measures), thirdly, quality-control materials with non-commutability issues and, fourthly, tests with a sigma value less than or equal to 4.^2,3 Although stable, preferably third-party, iQC materials are essential to perform iQC, it can be challenging or even impossible to obtain them for some tests, including those for serum indices, erythrocyte sedimentation rate or mean corpuscular volume (MCV). There may also be non-commutability issues with the iQC materials that do not properly represent for example, lot-to-lot variations of reagent or introduction of a new generation of a specific test. Such a case has been described by Hinge et al. for alkaline phosphatase,⁴ and the author has experienced these kinds of issues with several immunoassay-based tests, such as PSA, CEA and vitamin D. Another limiting factor is the scheduling frequency of iQC, which becomes relevant for tests with short turnaround times that may be reported before iQC confirmation of proper analytical performance. The high degree of automation and digitization of modern medical laboratories enables rapid turnaround times for many tests. Although this is extremely valuable for urgent medical diagnostics and patient-friendly healthcare by integrated care pathways, there is always a risk of a rapid-onset of critical error due to a technical failure. When applying iQC alone, there may be a significant delay before this failure is detected. Furthermore, temporary assay failure may be undetectable by iQC due to its scheduling frequency, as has been demonstrated.⁵ Finally, given its design, iQC is limited in detecting clinically relevant errors in tests with a low sigma performance value according to the sigma metrics approach.² Such tests, characterized by a low ratio of biological variation to analytical variation, generally require stringent control limits or rules and necessitate frequent analysis of iQC samples.^6,7 However, even with such a strict iQC set-up, the probability of detecting a clinically relevant error by iQC remains limited.^6,7 Despite all the efforts to improve the effectiveness of iQC, for example by introducing sigma-metrics-based iQC to reduce the false-alarm rate^6,8 and by designing iQC plans based on patient risk,^7,9 the abovementioned issues remain intrinsic limitations of iQC.² Furthermore, these more complex mathematical approaches used to increase the performance and efficiency of iQC are not only challenging to understand but also are complicated to implement in clinical practice. This is evident in the extremely low degree of adoption of these approaches, as observed in a recent survey in USA-based university hospitals.¹⁰ Finally, iQC requires the use of iQC materials and the performing of analytical tests and therefore brings significant costs.

中文翻译：

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当内部质量控制不足或效率低下时：考虑基于患者的实时质量控制！

内部质量控制样品（iQC）的测量是医学实验室每天实施的分析质量保证的基石。¹对于许多测试，iQC可有效确保足够的分析性能。但是，对于其他测试，仅使用iQC不足以确保适当的分析质量。原因包括：首先，缺少（稳定的）质量控制材料；其次，快速发作或暂时的关键错误（在计划的iQC措施之间）；其次，具有不可互换性问题的质量控制材料；其次，使用sigma值小于或等于^4。2,3尽管稳定的，最好是第三方的iQC材料对于执行iQC是必不可少的，但对于某些测试，包括血清指数，红细胞沉降率或平均红细胞体积（MCV）的测试，要获得它们可能是具有挑战性甚至是不可能的。iQC材料可能还存在不可交换性问题，这些问题不能正确地代表例如不同批次的试剂变化或新一代特定测试的引入。Hinge等人已经描述了这种情况。用于碱性磷酸酶，⁴并且作者在一些基于免疫分析的测试中遇到了这类问题，例如PSA，CEA和维生素D。另一个限制因素是iQC的调度频率，这与可能需要在iQC之前报告的周转时间短的测试有关。确认适当的分析性能。现代医学实验室的高度自动化和数字化可实现许多测试的快速周转时间。尽管这对于通过综合护理途径进行紧急医疗诊断和对患者友好的医疗非常有价值，但是由于技术故障，始终存在快速发生严重错误的风险。单独应用iQC时，在检测到此故障之前可能会有很大的延迟。此外，由于iQC的调度频率，临时检测失败可能无法被iQC检测到，⁵最后，根据其设计，根据sigma指标方法，iQC在检测低sigma性能值的测试中与临床相关的错误方面受到限制。²这种测试的特点是生物学变异与分析变异的比率低，通常需要严格的控制限或规则，并需要频繁分析iQC样品。^6,7然而，即使采用了如此严格的iQC设置，iQC检测到临床相关错误的可能性仍然有限。^6,7尽管已尽一切努力提高iQC的有效性，例如通过引入基于sigma-metrics的iQC来降低错误警报率^6,8，以及基于患者风险设计iQC计划，^7,9上述问题仍然是iQC的固有局限性。²此外，这些用于提高iQC的性能和效率的更复杂的数学方法不仅难以理解，而且在临床实践中实施起来也很复杂。正如最近在美国大学医院进行的一项调查所观察到的那样，这在采用这些方法的程度极低时很明显。¹⁰最后，iQC要求使用iQC材料并进行分析测试，因此会带来大量成本。