A modified statistical approach for the detection of outlying values in external quality control: comparison with other techniques.
Laboratory results submitted to External Quality Assessment Schemes (EQAS) are evaluated against the arithmetic mean (m) and standard deviation (SD) of the result from other participants assuming a normal distribution of individual results. The sample statistics m and SD can only be reliable estimates of the theoretical mean (mu) and standard deviation (sigma), if they are not distorted by outlying values. Outliers are commonly detected by defining a confidence interval m +/- k SD, typically with k-values fixed at 3.0 or 3.2. The objective of our study was to prove the deficiency of the use of these fixed limits in large-scale EQAS, because it results in an unacceptable increase of outlier rate and hence in a serious distortion of the estimate of sigma. We have proposed a modified approach using a variable k-value which is dependent upon sample size and keeping the significance level constant at 5%. The influence of different decision limits on the number of outliers and on the sample statistics m and SD was compared using data from the Belgian National EQAS obtained in 6 consecutive surveys.
Thienpont
L M
LM
Laboratoria voor Medische Biochemie en voor Klinische Analyse, Rijksuniversiteit Gent (RUG), Belgium.
Steyaert
H L
HL
De Leenheer
A P
AP
D001774:Blood Chemical Analysis; D001786:Blood Glucose / Q000032:analysis; D006801:Humans; D006854:Hydrocortisone / Q000097:blood; D007501:Iron / Q000097:blood; D007753:Laboratories / Q000592:standards*; D011336:Probability; D011786:Quality Control
D001786:Blood Glucose; D007501:Iron; D006854:Hydrocortisone