Practical application of Sigma Metrics QC procedures in clinical chemistry

Schoenmakers, Christian H.H.; Naus, Andre J M; Vermeer, Henricus J.; Loon, Douwe van; Steen, Gerard J.

doi:10.1515/cclm.2011.249

Cited by 53 publications

(43 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[5] Schoenmaker et al described the importance of application of sigma metrics and preparation of rational QC design based on the sigma values with the help of westgard operational specifications chart (OPSpecs chart) in clinical biochemistry laboratories. [9] An example of QC design is shown in the Table 8. IJBR (2015) 6 (03) www.ssjournals.com IJBR (2015) 6 (03) www.ssjournals.com …”

Section: Discussionmentioning

confidence: 99%

Evaluation of sigma metrics in a Medical Biochemistry lab

Lakshman

Reddy

Bhulaxmi

et al. 2015

Int Jour of Biomed Res

View full text Add to dashboard Cite

Sigma metrics is calculated in our lab and evaluated from December 2013 to November 2014. It is observed that Triglycerides, Lactate, Uric acid, AST, Urea, Creatine kinase(CK), Phosphate, Total Bilirubin are the best performers and the sigma value is more than 6.0 in both in normal and abnormal levels. Iron and Creatinine are best performers in normal level and Prolactin and Vitamin B12 are best performers in abnormal level. Amylase and LDH are the poor performers at level 1 (normal), though they show sigma between 3 to 6 at level 2 which is clinically acceptable.

show abstract

Section: Discussionmentioning

confidence: 99%

Evaluation of sigma metrics in a Medical Biochemistry lab

Lakshman

Reddy

Bhulaxmi

et al. 2015

Int Jour of Biomed Res

View full text Add to dashboard Cite

show abstract

“…We used both precision and bias to generate several outcome metrics, including patient-weighted metrics, in-control percentage unreliable patient results, and maximum expected number of unreliable patient results due to an out-of-control condition [Max E(N uf )]. Sigma values are directly related to the predicted probability of producing unreliable patient results during stable operation, which may be expressed in terms of defects per million opportunities (DPMO) (7 ). A 6-method is associated with 3.4 DPMO and is classified as "world class quality."…”

Section: Discussionmentioning

confidence: 99%

“…This Equivalent QC option will be discontinued in 2016. Recently, the Centers for Medicare and Medicaid Services announced a new type of QC plan, the Individualized QC Plan (IQCP), 7 beginning January 2014, that allows laboratories to utilize risk management strategies to design a QC program. Laboratories will be able to choose either the traditional approach of testing 2 levels of QC per assay, per day of patient testing, or they may elect to develop the newly introduced IQCP, which determines analytical QC frequency by utilizing risk management principles.…”

mentioning

confidence: 99%

Utilization of Assay Performance Characteristics to Estimate Hemoglobin A1c Result Reliability

et al. 2014

View full text Add to dashboard Cite

show abstract

“…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

View full text Add to dashboard Cite

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.

show abstract

Practical application of Sigma Metrics QC procedures in clinical chemistry

Abstract: The use of the road map based on Sigma Metrics leads to fast and easy implementation of optimal Westgard QC rules.

Cited by 53 publications

References 5 publications

Evaluation of sigma metrics in a Medical Biochemistry lab

Evaluation of sigma metrics in a Medical Biochemistry lab

Utilization of Assay Performance Characteristics to Estimate Hemoglobin A1c Result Reliability

Selecting Statistical Procedures for Quality Control Planning Based on Risk Management

Contact Info

Product

Resources

About