Understanding Run Charts for Quality Monitoring
Run charts are one of the most practical and frequently tested tools on the CPHQ exam. They display data over time and help quality professionals determine whether changes are leading to improvement.
Constructing a Run Chart
A run chart plots data points on the y-axis against time on the x-axis, with a horizontal line representing the median of the data. Unlike control charts, run charts do not include upper and lower control limits. This simplicity makes them accessible to frontline teams and useful for early-stage improvement projects where enough data for control limits may not yet be available. The median is preferred over the mean because it is not influenced by extreme values.
Rules for Detecting Non-Random Patterns
Four rules help determine whether observed patterns are likely due to non-random causes. A shift is six or more consecutive points above or below the median. A trend is five or more consecutive points going up or going down. Too many or too few runs (sequences of consecutive points on one side of the median) can indicate a non-random pattern. An astronomical data point is an obviously unusual value that anyone would agree is unusual. When any of these rules is triggered, the pattern likely reflects a real change rather than random variation.
Run Charts vs Control Charts
Run charts are simpler to create and interpret, making them ideal for teams new to quality improvement. Control charts provide more statistical power because they include control limits based on process variation. A common approach is to start with run charts during the early phases of an improvement project, then transition to control charts once the process has been improved and stabilized. The CPHQ exam may test your ability to choose the appropriate chart for a given situation.
Practical Applications
In healthcare, run charts are commonly used to track monthly infection rates, patient satisfaction scores, wait times, and other quality metrics over time. They help answer the fundamental question of quality improvement: "How do we know that a change is an improvement?"