Quality management in European screening laboratories in blood establishments: A view of current approaches and trends

Pereira, Paulo; Westgard, James O.; Encarnação, Pedro; Seghatchian, Jerard; Sousa, Gracinda de

doi:10.1016/j.transci.2015.02.014

Cited by 16 publications

(11 citation statements)

References 11 publications

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“…Pereira et al, 2015 [179,180] Determination of polybrominated diphenyl ethers in water by a simple dispersive liquid-liquid microextraction-gas chromatography-mass spectrometry method. Validation parameters, including the calculation of the expanded uncertainty associated to the results in the range of quantification is included.…”

Section: Paoloni Et Al 2016 [176]mentioning

confidence: 99%

A Practical Way to ISO/GUM Measurement Uncertainty for Analytical Assays Including In-House Validation Data

González¹,

Herrador²,

GarcíaAsuero³

et al. 2018

Quality Control in Laboratory

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In this contribution, we outline the estimation of measurement uncertainty of analytical assays in a practical way, according to the so-called reconciliation paradigm, by considering the heritance of uncertainties according to the ISO Guide to the expression of uncertainty in measurement (ISO/GUM) approach and the accuracy (bias and precision) study coming from the in-house method validation. A cause and effect analysis is performed by using the Ishikawa diagram or fishbone plot, consisting of a hierarchical structure reaching a final outcome that is the analytical result. The procedure is illustrated with a case study. This procedure may be very suitable for processing data in accreditation of routine assays.

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Section: Paoloni Et Al 2016 [176]mentioning

confidence: 99%

A Practical Way to ISO/GUM Measurement Uncertainty for Analytical Assays Including In-House Validation Data

González¹,

Herrador²,

GarcíaAsuero³

et al. 2018

Quality Control in Laboratory

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show abstract

“…If you remove one of these steps, for example the monitoring part (Check), the whole system of improvement collapses. The EN-ISO 15189 standard requests laboratories to improve quality in a similar way (11), by demanding them to develop plans to implement improvement and to monitor and document the quality of pre-examination-, examination and post-examination procedures (57). Based on a quote of Robert S. Kaplan, the inventor of the Balanced Scorecard, one could summarize: you cannot manage/improve what you don't measure.…”

Section: Where Are We Now?mentioning

confidence: 99%

How do we use the data from pre-analytical quality indicators and how should we?

Cadamuro¹,

Gaksch²,

Mrazek³

et al. 2018

J. Lab. Precis. Med.

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It is impossible to imagine a modern medical laboratory without a structured quality management system in place. Nevertheless, this system usually focuses mostly on the analytical part of the total testing process (TTP), despite being aware of the fact that most errors occur in the pre-and post-analytical phases. There are many reasons possibly explaining this fact, one of them being that extra-analytical processes are hard to grasp, since they occur mostly outside of the laboratory and include many different parties. Despite these obstacles, it is mandatory to keep all steps of TTP, potentially influencing the analytical test result or their interpretation, under meticulous quality control and to improve them as much as possible, involving all health care workers contributing to sample quality. Additionally, it is necessary to collect and evaluate all data in a standardized manner, not only within one laboratory, but nationwide and internationally. This is a perquisite for valid data comparison over time (trend analysis) and benchmarking, the basis for threshold definition and continuous improvement. A widely accepted method to meet all these requirements is the concept of quality indicators (QIs). In this review, we provide an overview over this topic and we discuss an easy to use and freely available tool, aiming to aid laboratories in data collection and comparison: The QIs project of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Working Group on "Laboratory errors and patient safety" (WG-LEPS). Additionally, we provide practical suggestions on how to successfully implement QIs within any laboratory.

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“…Currently, the determination of measurement uncertainty is required in ISO/IEC 17025 and ISO 15189 [17]. It is mandatory in Australia, Latvia, and France after November 1, 2016.…”

Section: Introduction To the "Guide To The Expression Of Uncertainty mentioning

confidence: 99%

Uncertainty of Measurement in Medical Laboratories

Pereira¹

2016

New Trends and Developments in Metrology

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The Guide to the Expression of Uncertainty in Measurement GUM is not systematically used in medical laboratories, for what the laboratorian should understand the Uncertainty "pproach and its importance to recognize the level of realism of results. This chapter presents, discusses, and recommends the models fulfilling GUM principles. "n example is given to a single test for an easier understanding of the determination of measurement uncertainty. "ll the practice uses a freeware. Results with larger measurement uncertainty intervals have a significant probability of being unrealistic, arising a high risk of the uncorrected clinical decision. " flow chart to the selection of models for the determination of measurement uncertainty in a medical laboratory is recommended.

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Quality management in European screening laboratories in blood establishments: A view of current approaches and trends

Cited by 16 publications

References 11 publications

A Practical Way to ISO/GUM Measurement Uncertainty for Analytical Assays Including In-House Validation Data

A Practical Way to ISO/GUM Measurement Uncertainty for Analytical Assays Including In-House Validation Data

How do we use the data from pre-analytical quality indicators and how should we?

Uncertainty of Measurement in Medical Laboratories

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