Much of the variation in breast pathology quality assurance data in the UK can be explained by the random order in which cases arrive at individual centres, but some true outliers do exist

作者：Cross Simon S^*; Stephenson Timothy J; Harrison Robert F

来源：Histopathology, 2011, 59(4): 594-599.

DOI：10.1111/j.1365-2559.2011.03919.x

• binomial distribution
• breast screening
• computer simulation
• control limits
• decision tools
• pathology quality assurance

Aims: To investigate the role of random temporal order of patient arrival at screening centres in the variability seen in rates of node positivity and breast cancer grade between centres in the NHS Breast Screening Programme.
Methods and results: Computer simulations were performed of the variation in node positivity and breast cancer grade with the random temporal arrival of patients at screening centres based on national UK audit data. Cumulative mean graphs of these data were plotted. Confidence intervals for the parameters were generated, using the binomial distribution. UK audit data were plotted on these control limit graphs. The results showed that much of the variability in the audit data could be accounted for by the effects of random order of arrival of cases at the screening centres. Confidence intervals of 99.7% identified true outliers in the data.
Conclusions: Much of the variation in breast pathology quality assurance data in the UK can be explained by the random order in which cases arrive at individual centres. Control charts with confidence intervals of 99.7% plotted against the number of reported cases are useful tools for identification of true outliers.

• 出版日期2011-10