Sample: Reading the waiting list figures like a scan
A sample article showing the contents list, margin notes, a table, a social post, sources and a correction note. Replace it with your own first piece.
Correction, : This is a sample correction note. Use it when you fix a mistake, e.g. “An earlier version gave the wrong year for the 18-week target.”
In this article 5 sections
This is a sample article. It shows every new feature in one place, so you can see how they look on your phone and on a computer. Delete it once you have published your own work. The figures below are invented for illustration only.
When a radiographer looks at a scan, they don’t start with the most dramatic thing on the screen. They start with the basics: is this the right patient, the right body part, the right settings? Only then do they look for what’s normal, what isn’t, and what needs a second opinion. Headlines about waiting lists deserve the same treatment.
What the headline number actually measures
Most stories quote a single figure: the number of people waiting. But that figure counts pathways, not people. One person waiting for two different things is counted twice. That doesn’t make the number wrong, but it does change what it means.
The second thing to check is the date. Monthly statistics are usually published around six weeks after the month they describe, so “today’s” waiting list is really a snapshot from late summer.
What looks normal
Seasonal patterns are normal. Waiting lists tend to rise over winter, when emergency pressures pull staff and beds away from planned care. Here is an invented example of what a quarter might look like:
| Month (example) | People waiting (millions) | Waiting over 18 weeks |
|---|---|---|
| July | 7.4 | 41% |
| August | 7.5 | 42% |
| September | 7.6 | 43% |
A rise of 0.1 million a month looks alarming in a headline, but on its own it tells you little. The useful question is whether it’s rising faster or slower than the same months last year.
What looks abnormal
The figure that rarely makes the headline is the long tail: people waiting a year or more. That number moves slowly and says more about how the system is coping than the overall total does.
Politicians on every side post about these numbers. Here is how a social post looks inside an article: readers see the text first, and the real post only loads if they choose to.
Incidental findings
Sometimes the most interesting detail is not the one anyone was looking for. In waiting list data, that is often the difference between regions. Two areas with the same total can have very different numbers of long waits.
What needs a second opinion
Before quoting any figure, it is worth checking the official source yourself and noting exactly which table and month you used. That is what the Sources box at the end of this article is for.
