Waiting times tracker: analysis of seasonal effects

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

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 (patients still on waiting lists, patients treated in putpatients and those treated as inpatients), and between years.

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

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.

Month-on-month percentage change in median waits: Patients treated in outpatients

The seasonal pattern for median waits for 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.

Month-on-month percentage change in median waits: Patients admitted as inpatients

The seasonal pattern for inpatients is similar to that for outpatients.

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

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.

Month-on-month percentage change in proportion of patients waiting more than 18 weeks: Patients still on waiting lists

Month-on-month percentage change in proportion of patients waiting more than 18 weeks: Patients admitted as inpatients

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

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

Some predictions for the future

On the basis of the seasonal pattern for median waits 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 to see if seasonal effects continue to be an important factor in changes to median waiting times, and whether they continue 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.

Source

All graphs adapted from Department of Health: Referral to Treatment Waiting Times Statistics