Analyzing quality-control trends with moving slope charts

We have developed and evaluated a new procedure for detecting trends in quality-control measurements and applied it to laboratory data. The method requires the use of sequential or "moving" slope estimates to identify trends. Formulae are derived to estimate the regression error for the moving slope directly from the standard deviation of the analytical measurements obtained during characterization runs. Control limits for the moving slope depend only on this regression error, the span of the slope, and the desired statistical level of control. The moving slope can be plotted with control limits to determine out-of-control points. The statistical power of the moving slope is found to be much greater than that of an often-used test for trends. An example of the use of the moving slope is shown for quality-control measurements for total cholesterol obtained over several years. We conclude that the moving slope procedure has considerably more statistical power than trend rules and that it yields more useful information to the analyst.