Healthcare systems are complex, involving the interaction of multiple different subsystems. Whilst many processes may be documented, some may have evolved informally and therefore be challenging to unpick when investigating performance.

Much of the informal knowledge of such processes is hidden from those outside the system.

How can this be investigated? Studying the processes themselves might involve lengthy periods of observation or detailed interviews with staff to document the them. Much of information gained from such an investigation might not be particularly useful in managing performance problems. A cheaper way is to look at the effect such process have on the data.

The Fourier transform is a mathematical technique that can be used to examine the component frequencies in a signal. It can also be used to examine the components of time-series data to understand aspects which occur regularly and determine how frequently these occur.

The graph below shows the output of a fast Fourier transform of times during the day when hospital beds become available.

The graph demonstrates a pattern occurring every 12 and 24 hours. This is likely to be explained by nursing shift length being 12 hours and by beds being made available at a particular time each day, for example a particular area opening each morning.

In addition, there is a clear signal of something happening every 2, 4, 6 and 8 hours. This analysis alone cannot tell us what it occurring but it can be helpful in directly further investigations.

Fourier transform – Wikipedia