Application of the Six Sigma concept in clinical laboratories: a review

Gras, Jeremie M.; Philippe, Marianne

doi:10.1515/cclm.2007.135

Cited by 75 publications

(45 citation statements)

References 4 publications

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“…a process variation of 6s, will create very few defects: 3.4 defects per million opportunities [DPMO]). 10 However, the data are less impressive when one considers the entire testing process of selecting, requesting, identifying patients, collecting and transporting specimens, analysing, reporting, interpreting and utilizing laboratory results. As stated by Mark Graber 11 'errors related to laboratory testing are too common and constitute a significant fraction of diagnostic errors in medicine today'.…”

Section: Types Of Errors In Laboratory Medicine and Their Prevalencementioning

confidence: 99%

The detection and prevention of errors in laboratory medicine

2009

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The last few decades have seen a significant decrease in the rates of analytical errors in clinical laboratories. Evidence demonstrates that pre-and post-analytical steps of the total testing process (TTP) are more error-prone than the analytical phase. Most errors are identified in pre-pre-analytic and post-post-analytic steps outside of the laboratory. In a patientcentred approach to the delivery of health-care services, there is the need to investigate, in the TTP, any possible defect that may have a negative impact on the patient. In the interests of patients, any direct or indirect negative consequence related to a laboratory test must be considered, irrespective of which step is involved and whether the error depends on a laboratory professional (e.g. calibration/testing error) or non-laboratory operator (e.g. inappropriate test request, error in patient identification and/or blood collection). Patient misidentification and problems communicating results, which affect the delivery of diagnostic services, are recognized as the main goals for quality improvement. International initiatives aim at improving these aspects. Grading laboratory errors on the basis of their seriousness should help identify priorities for quality improvement and encourage a focus on corrective/preventive actions. It is important to consider not only the actual patient harm sustained but also the potential worst-case outcome if such an error were to reoccur. The most important lessons we have learned are that system theory also applies to laboratory testing and that errors and injuries can be prevented by redesigning systems that render it difficult for all health-care professionals to make mistakes.

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Section: Types Of Errors In Laboratory Medicine and Their Prevalencementioning

confidence: 99%

The detection and prevention of errors in laboratory medicine

2009

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“…Since the introduction of the Six Sigma concept into clinical laboratories (12 ), several recommendations have been made for selecting optimal SQC procedures considering only the of the analytical process (13)(14)(15). Unless there is some exception (13 ), none of these recommendations take into account the QC frequency or the laboratory testing mode, but most of the SQC procedures recommended for control analytical processes with a certain show low Max E(N UF ) values (typically below 1 in the nomogram of Fig.…”

Section: Discussionmentioning

confidence: 99%

Selecting Statistical Procedures for Quality Control Planning Based on Risk Management

Yago¹,

Alcover²

2016

Clinical Chemistry

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BACKGROUND According to the traditional approach to statistical QC planning, the performance of QC procedures is assessed in terms of its probability of rejecting an analytical run that contains critical size errors (PEDC). Recently, the maximum expected increase in the number of unacceptable patient results reported during the presence of an undetected out-of-control error condition [Max E(NUF)], has been proposed as an alternative QC performance measure because it is more related to the current introduction of risk management concepts for QC planning in the clinical laboratory. METHODS We used a statistical model to investigate the relationship between PEDC and Max E(NUF) for simple QC procedures widely used in clinical laboratories and to construct charts relating Max E(NUF) with the capability of the analytical process that allow for QC planning based on the risk of harm to a patient due to the report of erroneous results. RESULTS A QC procedure shows nearly the same Max E(NUF) value when used for controlling analytical processes with the same capability, and there is a close relationship between PEDC and Max E(NUF) for simple QC procedures; therefore, the value of PEDC can be estimated from the value of Max E(NUF) and vice versa. QC procedures selected by their high PEDC value are also characterized by a low value for Max E(NUF). CONCLUSIONS The PEDC value can be used for estimating the probability of patient harm, allowing for the selection of appropriate QC procedures in QC planning based on risk management.

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“…That is, if we detect an error, we have to solve it and prevent it from affecting the process again. With this step, we continue to decrease the errors effectively until we obtain a desirable degree of quality (Westgard, 2006a;Gras, 2007). Six Sigma provides principles and tools that can be applied to any process as a means to measure defects and/or error rates.…”

Section: Six Sigma In Laboratory Medicinementioning

confidence: 99%