Design, Use, and Performance of Statistical Control Charts for Clinical Process Improvement

Background: The utility of statistical process control (SPC) methods has received growing interest in the healthcare community to help improve clinical and administrative processes. SPC charts are chronological graphs of process data that are used in many other industries to help understand, control, and improve processes and that, although based in statistical theory, are easy for practitioners to use and interpret. Objectives: The objective of this article is to provide an overview of SPC charts, the different types and uses of control charts, when to use each chart type, their statistical performance, and simple methods for determining appropriate sample sizes. The intended audience includes practitioners and healthcare researchers seeking either an introduction to these methods or further insight into their design and performance. Methods for dealing with rare events and low occurrence rates also are discussed. Methods: Recent empirical examples are used to illustrate appropriate applications of each chart type, sample size determination, and chart performance. Sensitivities are calculated and tabulated for a wide range of scenarios to aid practitioners in designing control charts with desired statistical properties. Conclusions: Control charts are valuable for analyzing and improving clinical process outcomes. Different types of charts should be used in different applications and sample size guidelines should be used to achieve the desired sensitivity and specificity. SPC is both a data analysis method and a process management philosophy, with important implications on the use of data for improvement rather than for blame, the frequency of data collection, and the type and format of data that should be collected. When dealing with low rates, it also can be advantageous to collect data on the number of cases or the amount of time between adverse events, rather than monthly rates.