Analysis of inadequate cervical smears using Shewhart control charts

Abstract

Background: Inadequate cervical smears cannot be analysed, can cause distress to women, are a financial burden to the NHS and may lead to further unnecessary procedures being undertaken. Furthermore, the proportion of inadequate smears is known to vary widely amongst providers. This study investigates this variation using Shewhart's theory of variation and control charts, and suggests strategies for addressing this.

The impact of the introduction of liquid based cytology on the variation in the proportion of inadequate samples between GP practices

“…A study we undertook in South Staffordshire in 2000–01 identified two sources of variation in the proportion of inadequate smears; that associated with laboratories and that associated with GP practices [3]. Our study showed that there was wide variation in the proportion of inadequate smears amongst 100 general practices, with 23% showing evidence of special cause variation which merited further investigation to identify possible causes.…”

“…Our original study noted a wide variation in the proportion of inadequate samples between all 156 English laboratories [3]. More recently a study has compared the variability of inadequacy rates in eleven Welsh laboratories following the introduction of LBC using longitudinal control charts [9].…”

“…Diagnostic accuracy is also important. In our original study we found no relationship between the proportion of smears reported as inadequate and the positive predictive value of a smear in data from English laboratories [3]. We have not had the opportunity to measure any change in the detection of abnormalities in the current data, though recent reports from two large medium quality studies (based on the criteria used by Davey et al [8]) have indicated that LBC has been associated with an increase in diagnostic accuracy [10,11].…”

Using Poisson Regression to Compare Rates of Unsatisfactory Pap Smears Among Gynecologists and to Evaluate a Performance Improvement Plan

“…[4][5][6] One report found adequacy unrelated to rates at which abnormalities are detected. 7 Despite this, all observers agree that reducing unsatisfactory rates is desirable. A wide array of attempts to reduce unsatisfactory rates are available to the interested reader.…”

Business indicators of healthcare quality: Outlier detection in small samples

“…To avoid unauthorised disclosure and hospital identification without loosing the information relevant for our study, the actual quantities defining the numerator and the denominator are masked. It is essential to note that funnel plots, which have rightfully been promoted for monitoring cross-sectional performance indicators in health care [6][7][8][9] and also in education [10], may not be the appropriate choice for such data. The reason is that virtually all points would get labelled as outliers in such plots because of huge denominators (thousands of square metres, millions of Euro) yielding excessively narrow CIs for the average proportion (even at 99% confidence level).…”