The Quality Strategy for Evaluating Laboratory Blood Glucose and Glycated Hemoglobin Results Using External Quality Assessment Survey Data
Objective Using External Quality Assessment(EQA)data,to establish a quality evaluation strategy suitable for the study of blood glucose(GLU)and glycated hemoglobin(HbA1c)based on big dataset.Methods A retrospective analysis of GLU and HbA1c EQA data participating in the EQA program of the National Health Commission was conducted.Acceptance rate and absolute percentage bias for GLU and HbA1c were calculated according to the biological variant(BV)quality specification,and we further established a quality strategy suitable for GLU and HbA1c.Results The acceptance rate of GLU and HbA1c were different.The GLU and HbA1c EQAs acceptance rates varied greatly,ranging from 0.00％to 100.00％.The mean percentage biases were 0.61％,1.00％,1.21％and 0.29％,0.60％,0.76％for GLU and HbA1c,respectively,which satisfied optimum,desirable,and minimum criteria.Conclusion The acceptance rate of GLU and HbA1c of different quality levels and the results of EQA are significantly different.The EQA is shown to be the lowest quality standard.Although it passes the EQA standard,this approach cannot guarantee that the laboratory test results are suitable for the quality requirements of big data research.The EQA can serve as a reference guide for the construction of big data studies.
GlucoseGlycated hemoglobinExternal quality assessmentBiasBiological variationQuality standard
万方数据
维普
