An important issue in understanding trends in waiting times - and what may be influencing changes since June - is seasonal variations.

A graph showing the month on month percentage change in median waits: Patients still on waiting lists

Month on month percentage change in median waits: Patients still on waiting lists

Figure 1: Median waits of patients still on waiting lists

Hospital activity, for example, has long shown peaks and troughs at certain times of the year - most notably at holiday (troughs) and post holiday (peaks) periods, especially in December/January and also at Easter and in August/September.

Similar patterns can also be seen in the way waiting times change over the year too.

Seasonal effects and median waiting times

For month on month changes in median waiting times, there is a noticeable seasonal pattern, although the timings and strength of the peaks and troughs vary between the three stages of waiting and between years.

For median waiting times for patients still on waiting lists there are notable peaks in August and December and troughs in September/October and February (see Figure 1).

The seasonal pattern for median waits for patients who attended outpatients is also clear from the figure below. However, the timing of the peaks and troughs is different, with notable peaks in January, April and September and troughs in December, February and October. The seasonal pattern for inpatients is similar to that for outpatients (see Figure 2 and 3).

The seasonal trend pattern that is evident visually is also clear statistically. The table below shows the correlations between pairs of years for each stage of waiting and shows strong positive associations - ie, changes up or down from month to month in one year move in a very similar way to changes in another year.

Table: Correlation coefficients (Pearson r1): Month on month percentage change in median waits between years

 Patients still on waiting listsPatients seen in outpatientsPatients admitted as inpatients
2007 vs 2008+0.75+0.91+0.87
2008 vs 2009+0.81+0.97+0.91
2009 vs 2010+0.78+0.92+0.87

1. Pearson r ranges from -1 (perfect negative correlation) to +1 (perfect positive correlation)

Seasonal effects and the proportion of patients waiting over 18 weeks

However, there is less evidence of a seasonal pattern for month on month changes in the proportion of patients waiting more than 18 weeks, as the more erratic pattern in the figures 4,5 and 6 show.

Statistically, the weaker and more erratic seasonal pattern is evident too, as the table below shows, with correlations varying between years and also changing sign.

Table: Correlation coefficients (Pearson r1): Month on month percentage change in proportion of patients waiting more than 18 weeks.

 Patients still on waiting listsPatients seen in outpatientsPatients admitted as inpatients
2007 vs 2008-0.22-0.47+0.28
2008 vs 2009+0.35+0.22-0.07
2009 vs 2010+0.14+0.79-0.40

1. Pearson r ranges from -1 (perfect negative correlation) to +1 (perfect positive correlation

Some predictions for November

On the basis of the seasonal pattern for median waist it is possible to offer a prediction for November’s median waits based on changes in median waits from October to November in previous years. For patients still on waiting lists the median wait is likely to rise very slightly to just over 5.9 weeks. Median waits for outpatients could also rise very slightly to just over 4.3 weeks. However, median waits for inpatients could fall from 9.1 to around 8.7 weeks in November.

As subsequent waiting times data are published we will update our analysis of the seasonal factor to see to what extent this continues to be an important factor in explaining changes in median waiting times and whether it continues to play a relatively small role in explaining changes in the proportion of patients waiting over 18 weeks. We will also see if our predictions for median waits turn out to be correct.