Moving sum of number of positive patient result as a quality control tool

Author(s):  
Jiakai Liu ◽  
Chin Hon Tan ◽  
Tony Badrick ◽  
Tze Ping Loh

AbstractBackground:Recently, the total prostate-specific antigen (PSA) assay used in a laboratory had a positive bias of 0.03 μg/L, which went undetected. Consequently, a number of post-prostatectomy patients with previously undetectable PSA concentrations (defined as <0.03 μg/L in that laboratory) were being reported as having detectable PSA, which suggested poorer prognosis according to clinical guidelines.Methods:Through numerical simulations, we explored (1) how a small bias may evade the detection of routine quality control (QC) procedures with specific reference to the concentration of the QC material, (2) whether the use of ‘average of normals’ approach may detect such a small bias, and (3) describe the use of moving sum of number of patient results with detectable PSA as an adjunct QC procedure.Results:The lowest QC level (0.86 μg/L) available from a commercial kit had poor probability (<10%) of a bias of 0.03 μg/L regardless of QC rule (i.e. 1:2S, 2:2S, 1:3S, 4:1S) used. The average number of patient results affected before error detection (ANPed) was high when using the average of normals approach due to the relatively wide control limits. By contrast, the ANPed was significantly lower for the moving sum of number of patient results with a detectable PSA approach.Conclusions:Laboratory practitioners should ensure their QC strategy can detect small but critical bias, and may require supplementation of ultra-low QC levels that are not covered by commercial kits with in-house preparations. The use of moving sum of number of patient results with a detectable result is a helpful adjunct QC tool.

Irriga ◽  
2020 ◽  
Vol 25 (4) ◽  
pp. 719-727
Author(s):  
ABEL HENRIQUE SANTOS GOMES ◽  
Mayra Gislayne Melo de Lima ◽  
DENISE DE JESUS LEMOS FERREIRA ◽  
GLEYKA NÓBREGA VASCONCELOS ◽  
JUAREZ PAZ PEDROZA ◽  
...  

CONTROLE ESTATÍSTICO APLICADO A UNIFORMIDADE DE DISTRIBUIÇÃO EM UNIDADES GOTEJADORAS OPERANDO COM ÁGUA RESIDUÁRIA     ABEL HENRIQUE SANTOS GOMES1; MAYRA GISLAYNE MELO DE LIMA2; DENISE DE JESUS LEMOS FERREIRA3; GLEYKA NÓBREGA VASCONCELOS4; JUAREZ PAZ PEDROZA5 E VERA LÚCIA ANTUNES DE LIMA6   1 Doutor em Engenharia Agrícola: Departamento de Engenharia Agrícola, Programa de Pós-Graduação em Engenharia Agrícola, Universidade Federal de Campina Grande, Rua Aprígio Veloso, 882, Bairro Universitário, 58428-830, Campina Grande, Paraíba, Brasil, e-mail: [email protected]. 2 Doutoranda em Engenharia Agrícola: Departamento de Engenharia Agrícola, Programa de Pós-Graduação em Engenharia Agrícola, Universidade Federal de Campina Grande, Rua Aprígio Veloso, 882, Bairro Universitário, 58428-830, Campina Grande, Paraíba, Brasil, e-mail: [email protected]. 3 Professora doutora EBTT na área de Engenharia Agrícola: Instituto Federal de Educação, Ciência e Tecnologia Baiano – Campus Xique-Xique, Rodovia BA 052, Km 468, s/n – Zona Rural, CEP: 47.400-000, Xique-Xique, Bahia, Brasil, e-mail: [email protected]. 4 Mestranda em Engenharia Agrícola: Departamento de Engenharia Agrícola, Programa de Pós-Graduação em Engenharia Agrícola, Universidade Federal de Campina Grande, Rua Aprígio Veloso, 882, Bairro Universitário, 58428-830, Campina Grande, Paraíba, Brasil, e-mail: [email protected]. 5 Professor doutor: Departamento de Engenharia Agrícola, Programa de Pós-Graduação em Engenharia Agrícola, Universidade Federal de Campina Grande, Rua Aprígio Veloso, 882, Bairro Universitário, 58428-830, Campina Grande, Paraíba, Brasil, e-mail: [email protected]. 6 Professora doutora: Departamento de Engenharia Agrícola, Programa de Pós-Graduação em Engenharia Agrícola, Universidade Federal de Campina Grande, Rua Aprígio Veloso, 882, Bairro Universitário, 58428-830, Campina Grande, Paraíba, Brasil, e-mail: [email protected].     1 RESUMO   A ferramenta de controle estatístico de qualidade, desenvolvida para o setor industrial, ganhou espaço na agricultura como auxilio ao manejo adequado da irrigação. Objetivou-se com este projeto, através do auxílio do controle estatístico de qualidade, avaliar a uniformidade de distribuição de água em unidades de irrigação por gotejamento abastecidas por águas residuárias. O experimento foi conduzido em ambiente controlado pertencente ao Laboratório de Irrigação e Drenagem, da Unidade Acadêmica de Engenharia Agrícola, Universidade Federal de Campina Grande. Foram avaliados dois tipos de linhas laterais constituídas de gotejadores específicos, submetidos a fontes de água distintas, totalizando 31 ensaios. A maioria dos valores por ensaio situou-se dentro dos limites de controle, entretanto os valores de vazão não atingiram o valor de catálogo do fabricante para ambos modelos de fitas gotejadoras. Os dois modelos distintos de emissores funcionaram durante grande parte do período de estudo dentro dos limites de controle. A ferramenta de controle estatístico de qualidade se mostrou viável e imprescindível, possibilitando o uso eficiente das unidades de irrigação.   Palavras-chave: Irrigação, controle de qualidade, reúso de água.     GOMES, A. H. S.; LIMA, M. G. M. DE; FERREIRA, D. DE J. L.; VASCONCELOS, G. N.; PEDROZA, J. P.; LIMA, V. L. A. DE STATISTICAL CONTROL APPLIED TO DISTRIBUTION UNIFORMITY IN DRIPPING UNITS OPERATING WITH WASTE WATER 2 ABSTRACT   The statistical quality control tool, developed for the industrial sector, gained space in agriculture as an aid in the proper management of irrigation. The aim of the project was to assess, through the aid of statistical quality control, the uniformity of water distribution in drip irrigation units supplied by wastewater. The experiment was conducted in a controlled environment belonging to the Irrigation and Drainage Laboratory, of the Agricultural Engineering Academic Unit, Federal University of Campina Grande. Two types of lateral lines constituted of specific grippers were evaluated, submitted to different water sources, totaling 31 tests. Most of the values per test were within the control limits, however the flow values did not reach the manufacturer's catalog value for both drip strip models. The two models of emitters functioned during much of the study period within the control limits, the statistical quality control tool proved to be viable and essential, enabling the efficient use of the irrigation units.   Keywords: Irrigation, quality control, water reuse.


2020 ◽  
Vol 30 (2) ◽  
pp. 296-306
Author(s):  
Chun Yee Lim ◽  
Tony Badrick ◽  
Tze Ping Loh

Introduction: The capability of glucometer internal quality control (QC) in detecting varying magnitude of systematic error (bias), and the potential use of moving sum of positive results (MovSum) and moving average (MA) techniques as potential alternatives were evaluated. Materials and methods: The probability of error detection using routine QC and manufacturer’s control limits were investigated using historical data. Moving sum of positive results and MA algorithms were developed and optimized before being evaluated through numerical simulation for false positive rate and probability of error detection. Results: When the manufacturer’s default control limits (that are multiple times higher than the running standard deviation (SD) of the glucometer) was used, they had 0-75% probability of detecting small errors up to 0.8 mmol/L. However, the error detection capability improved to 20-100% when the running SD of the glucometer was used. At a binarization threshold of 6.2 mmol/L and block sizes of 200 to 400, MovSum has a 100% probability of detecting a bias that is greater than 0.5 mmol/L. Compared to MovSum, the MA technique had lower probability of bias detection, especially for smaller bias magnitudes; MA also had higher false positive rates. Conclusions: The MovSum technique is suited for detecting small, but clinically significant biases. Point of care QC should follow conventional practice by setting the control limits according to the running mean and SD to allow proper error detection. The glucometer manufacturers have an active role to play in liberalizing QC settings and also enhancing the middleware to facility patient-based QC practices.


2021 ◽  
Author(s):  
Carmen Seller Oria ◽  
Adrian Thummerer ◽  
Jeffrey Free ◽  
Johannes A. Langendijk ◽  
Stefan Both ◽  
...  

2016 ◽  
Vol 145 (3) ◽  
pp. 308-315 ◽  
Author(s):  
Patrick C. Mathias ◽  
Emily H. Turner ◽  
Sheena M. Scroggins ◽  
Stephen J. Salipante ◽  
Noah G. Hoffman ◽  
...  

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Suharto Suharto ◽  

Abstract This study aims to determine and identify the causes of defects in the production process of PT. Triteguh Manunggal Sejati and know the level of sigma level. This research uses the six sigma method with the DMAIC approach as a quality control tool, which includes the Define, Measure, Analyze, Improve and Control stages. Based on this study the results obtained are the level of sigma level at PT.Triteguh Manunggal Sejati is 4.96, which means that in the stage of sigma level the company has not reached the level of six sigma levels because in the production process at PT.Triteguh Manunggal Sejati still has product defects in the production process not yet achieved zero defect. The causes of product defects are based on cause and effect diagrams namely lid / seal defects are leaky lid, broken lid, and tilted lid. Kata kunci : Defect, Six Sigma, DMAIC, cause and effect diagram


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