Improvement of the quality of work in a biochemistry laboratory via measurement system analysis.
An adequate and continuous monitoring of operational variations can effectively reduce the uncertainty and enhance the quality of laboratory reports. This study applied the evaluation rule of the measurement system analysis (MSA) method to estimate the quality of work conducted in a biochemistry laboratory. Using the gauge repeatability & reproducibility (GR&R) approach, variations in quality control (QC) data among medical technicians in conducting measurements of five biochemical items, namely, serum glucose (GLU), aspartate aminotransferase (AST), uric acid (UA), sodium (Na) and chloride (Cl), were evaluated. The measurements of the five biochemical items showed different levels of variance among the different technicians, with the variances in GLU measurements being higher than those for the other four items. The ratios of precision-to-tolerance (P/T) for Na, Cl and GLU were all above 0.5, implying inadequate gauge capability. The product variation contribution of Na was large (75.45% and 31.24% in normal and abnormal QC levels, respectively), which showed that the impact of insufficient usage of reagents could not be excluded. With regard to reproducibility, high contributions (of more than 30%) of variation for the selected items were found. These high operator variation levels implied that the possibility of inadequate gauge capacity could not be excluded. The analysis of variance (ANOVA) of GR&R showed that the operator variations in GLU measurements were significant (F=5.296, P=0.001 in the normal level and F=3.399, P=0.015 in the abnormal level, respectively). In addition to operator variations, product variations of Na were also significant for both QC levels. The heterogeneity of variance for the five technicians showed significant differences for the Na and Cl measurements in the normal QC level. The accuracy of QC for five technicians was identified for further operational improvement. This study revealed that MSA can be used to evaluate product and personnel errors and to improve the quality of work in a biochemical laboratory through proper corrective actions.
Department of Healthcare Administration, Oriental Institute of Technology, New Taipei 22061, Taiwan, Republic of China.
Ming-Shu
MS
Chen
Department of Applied Statistics and Information Science, Ming Chuan University, Taoyuan 33352, Taiwan, Republic of China.
Chen-Mao
CM
Liao
Department of Laboratory Medicine, Min-Sheng General Hospital, Taoyuan 33044, Taiwan, Republic of China.
Ming-Hsun
MH
Wu
Department of Healthcare Information and Management, Ming Chuan University, Taoyuan 33352, Taiwan, Republic of China.
Chih-Ming
CM
Lin
D064790:Clinical Laboratory Services / Q000592:standards / Q000706:statistics & numerical data*; D058996:Quality Improvement
clinical biochemistry; measurement system analysis; quality control; repeatability; reproducibility