NHS Education for Scotland: Charts and graphs

Summary

Charts are useful for collecting and charting data over time, you can find trends or patterns in the process. NHS Education for Scotland has provided resources and guidance on a number of different charts you could use for quality improvement.

Content

Run charts – is a line graph showing a measure in chronological order, with the measure on the vertical (y) axis and time or observation number on the horizontal (y) axis. The median of the data points (the middle value) is added once 10 or so data points are available. Changes made to a process, and other useful annotations, are also often marked on the graph so that they can be connected with the impact on the process.

Statistical Process Control (SPC) charts – simple graphical tools that enable process performance monitoring. There are different types of SPC chart depending on the type of data you have. The most common ones are:

• P chart – for classification data expressed as a % or proportion
• I chart (or Xmr chart) – for individual measurements
• C chart – count data – for numbers of incidents (or U chart if expressed as a rate)
• Xbar & S chart – for measurements data where an average can be calculated at each time point.

Scatter plot graph – A graph in which the values of two variables are plotted along two axes, the pattern of the resulting points revealing any correlation present. Use a scatter plot if you want to investigate whether or not two variables are related to each other, and also when you want to communicate the nature of a relationship between two measures.

Funnel plots – a chart that helps to understand variation within a system. A funnel plot is a useful way to show comparisons between different units to identify where there may be special cause variation. It is helpful if you have data relating to different teams, hospitals, schools, NHS boards, Local Authorities for example, which are of different sizes and you want to avoid misleading ranking that doesn’t account for this. The measure you plot would have a denominator (e.g. rate, proportion or average).

Histogram – a plot that lets you discover, and show, the underlying frequency distribution (shape) of a set of continuous data. It is useful to look at the distribution of data if you have collected a lot of data (at least 30 data items) to see whether there are any patterns occurring. For example, you might spot errors or anomalies in the data. Sometimes it is also useful to understand whether the data follows a typical ‘bell shape’ or if it is skewed or asymmetrical. When investigating your data it can also be really useful to split it into different groups and compare histograms. For example, you might be interested to see whether different teams involved in the above project have similar distributions of happiness scores. This might help you to decide whether to focus in on specific teams or take some other approach.