Archive for September, 2011
Today we’re going to peek under the bonnet of Gooroo Planner at one of the new things we’re working on right now. We want to achieve two things:
Firstly, we want to make Gooroo Planner more interactive. When you’re doing your planning, most of the dozens or hundreds of services in your model can just be crunched through according to rules that you control, and Gooroo Planner already does that very straightforwardly. But there are some services, like Orthopaedic elective inpatients for example, where you want to take a much closer look and tweak your assumptions more carefully. Ideally, you want to do this tweaking interactively, with instant results on the same screen, rather than having to navigate around and re-run the model every time you want to try something new. So more interactivity is the first thing we’re building in.
Secondly, we want to bridge the divide between strategic and operational planning, by building in week-by-week profiling of your future plans. This of course will be done interactively, and backed up by powerful global functions that let you try out different profiling strategies at the touch of a button.
Here’s a spreadsheet mockup of the week-by-week profiling screen. (It looks a bit clunky in the mock-up, but when it’s integrated into Planner it will be professionally designed and look as gorgeous as everything else.)
This screen shows a single service, such as Orthopaedic elective inpatients.
The top chart is the interactive one, and you’ll be able to drag the blue columns up and down to change the amount of activity planned for each week. All the other activity columns will automatically adjust to preserve the overall total, and all the charts will immediately respond to show the new position.
Also in the top chart, the shorter red columns show the minimum activity needed to keep up with clinical priorities; they are there to stop you inadvertently creating clinical risk by planning too little activity to keep up with all the urgent patients coming in: vital in high-urgency specialties like Urology, Plastic Surgery, and elective Medicine. Planner already safeguards urgent patients across your modelling period, and this does it week by week.
The second chart, with the blue line on it, shows the waiting time you can sustain with good scheduling practices. It is calculated on the same basis as your waiting time target, e.g. 90 per cent of admissions within X weeks. The blue line always starts and ends in the same place, because overall activity for the future period is not changing, but it goes up and down in the middle in response to your activity profile. In this example you can see how it goes up a bit in the summer when staff tend to take their holidays, before falling again towards the target with another smaller hiccup at Christmas. If you are maintaining a target that has already been achieved, this line will help you keep out of trouble in-year by planning enough activity in the early weeks to prevent predictable breaches in the holiday season and winter.
The remaining charts show how much capacity you need: beds, theatres and clinics, week by week. The grey line shows the total, across either the whole specialty or the whole health economy (your choice), so that you can make sure your profile doesn’t bust the bed limit for the site at any time.
So that’s a quick introduction to the new profiling service. I’d like to offer a very big thank-you to everybody who participated in our consultation on how this profiling should work. If you have any further comments or suggestions about how we’re building this, please get in touch; we want to get it just right for you.
In a future post, we’ll look at something else we’re working on: automatic constant-capacity profiling. It wasn’t easy, but we think we’ve broken new ground in finding a better way to model this…
Lucky, lucky NHS: eight referral-to-treatment waiting time targets when just one would do a better job. All over England, Trusts are complaining about the irrelevance and perversity of the target regime, but their pleas are (mainly) falling on deaf ears. Higher up the system, performance managers want green boxes, only green boxes on the RAG (red-amber-green) ratings. You shall achieve the targets, they insist: all eight of them.
Here, then, is a little helping hand with that negotiation. You can offer them their green boxes, with pleasure. But it’s going to cost them, and we’re going to show how you can work out the bill.
1) 95th centile RTT waiting time for incomplete pathways (target: 28 weeks)
Let’s start with the only target that is actually sensible: the 95th centile referral-to-treatment (RTT) waiting time for incomplete pathways (or, in plainer English, the waiting time that the top 5 per cent of the waiting list has exceeded). It’s sensible because it delivers the third of the four key principles of good waiting list management, and (with good planning and monitoring) is relatively straightforward to implement without undermining the others.
The four principles are:
- treat patients with higher clinical priority first
- treat patients with similar clinical priority in turn
- treat the least-urgent patients within a reasonable time
- don’t waste capacity
But how do we actually work out the activity needed to achieve this particular target? It isn’t easy, and it took many years of research to find a good solution to this problem. The first step in the calculation is the hardest: working out the size of waiting list that is consistent with the waiting times target. When that’s done, the remaining steps aren’t too bad. For the sake of this post, we’ll assume you have a well-researched model that does all this for you.
Once you have a suitable model, the calculation is easy: you just specify the target and let the model take care of everything. In Gooroo Planner, for instance, you can either load up targets for every service separately, or not bother and just set up default values like this:
To give an indication of how tough each of the targets is, we will use a benchmark waiting list that is well-managed according to the four principles above, and show how it has to get smaller and smaller as each new target is applied (keeping all other attributes of this benchmark list constant: addition rate, cancellations, urgency, etc).
To achieve 95 per cent of incomplete pathways within 28 weeks, sustainably and safely, without taking any of the other targets into account at this stage, our benchmark list starts out with 200 patients on it. We need two copies of this benchmark list now, one for admitted and one for non-admitted pathways, and we will track the fates of those two benchmark lists below.
2) 95th centile RTT waiting time for admitted patients (target: 23 weeks)
The next six targets we are going to look at are all based on those patients who were lucky enough to be treated or discharged over the chosen time period, as opposed to those patients who are still waiting. The trouble with these targets is that Trusts can achieve them by being selective about which patients they choose to treat.
For instance, any Trust could achieve 95 per cent of admissions within 23 weeks, cost-free, simply by picking 19 short-waiting patients for admission before picking an over-23-week waiter. This would violate the second principle: that patients with similar clinical priority should be treated in turn.
But on the assumption that you want to do the job properly, by actually achieving short waits on the waiting list as well as in your admissions profile, this target is easy to model in Gooroo Planner. Just set the data up like this:
It turns out that this target is more challenging to achieve sustainably than the incomplete pathways target above, and our benchmark waiting list (applied now to admitted patient pathways) must have no more than 155 patients on it.
That means we can now ignore the incomplete pathways target above because, if we achieve this admitted patient target while following the principles of good waiting list management, then we will have a small enough waiting list to automatically achieve the incomplete pathways target too.
3) Percentage admitted within 18 weeks RTT, adjusted basis (target: 90 per cent)
This is the best-known of all the RTT waiting time targets, though it too suffers from the problem that it is easy to achieve if you abandon patients who have already exceeded 18 weeks.
If you want to achieve it safely and sustainably, it is similarly easy to model:
Now our benchmark admitted-pathway list must not exceed 132 patients, if well-managed, and we can forget about the previous target too as it will automatically be met if we achieve this one.
4) 95th centile RTT waiting time for non-admitted patients (target: 18.3 weeks)
This target has all the same perverse incentives as the admitted patient targets above. If, again, we assume that we will do the job properly and manage the waiting list well, it is easy to model safely and sustainably:
If our benchmark list is now a non-admitted pathway, it must not exceed 129 patients.
5) Percentage non-admitted within 18 weeks RTT (target: 95 per cent)
This target duplicates the target above, but with a slightly tougher limit of 95 per cent within 18 weeks instead of 18.3 weeks. Originally this target (together with the percentage admitted within 18 weeks) was going to be dropped, but they had to be reinstated as they are both laid down in law.
You can model this target easily, just like the previous target but with 18 weeks instead of 18.3. Our benchmark non-admitted list now must shrink a little further to 127 patients.
6) Median RTT waiting time for admitted patients (target: 11.1 weeks)
The median targets make things a little more complicated to model, and to understand. But we are looking for ways to have a sensible discussion about the costs of achieving green boxes right across our 8 RTT targets, so let’s dive in and find a way to do it.
What is meant by this median target? If we look at the waiting times experienced by patients admitted over a period of time, the median admitted waiting time is the waiting time that half of them exceeded. If we were managing our waiting list well, according to the four principles, what would the median be then?
In all the main surgical specialties, only a minority of patients are clinically urgent. The remaining majority, who are non-urgent, should be admitted in turn and therefore all of them should experience roughly the same waiting time. The median patient and the 95th centile patient are both among this majority, and should therefore experience similar waiting times; so it follows that the median waiting time should be close to the 95th centile waiting time if we are managing our waiting list well.
But, for admitted patients, the targets are asking for a 95th centile of 23 weeks, and a median of only 11.1 weeks. How can we achieve that? Quite easily, as it turns out, although it does require us to violate the principles of good waiting list management. All we need to do is pick a lot of non-urgent (i.e. routine) patients and expedite them, for no other reason than to meet the target. Yes, that is brutally unfair on the other routine patients, who will wait longer as a result, and we can put that argument to the people who enforce the targets. But if they want all their boxes to be green, that is what they are going to get.
To model this target, we can pretend that half our patients are urgent and need admission within 11.1 weeks. They aren’t, but that is what the target demands. We just leave our long-wait target at the most demanding level we discovered above (for admitted patients, 90 per cent of admissions within 18 weeks). So that means we set our model up like this (we’ll show the data in data entry style this time):
|Data code||Data description||Value|
|FutPCWaiting1||Future percent waiting at time 1||50%|
|FutWaitTime1||Future waiting time for time-limited patients 1||11.1|
|TgtMaxWait||Future target waiting time||18|
|TgtMaxWaitPC||Future percentage within future target waiting time||90%|
|TgtMaxWaitType||Flag whether target max wait is flux or snapshot based||f|
With 50 per cent of admissions within 11.1 weeks, and 90 per cent of admissions within 18 weeks, our benchmark waiting list for an admitted pathway must not exceed 112 patients. That is 15 per cent smaller than before we introduced the median waiting time target, and that is the extra financial cost of the median target.
(To model this more precisely, it would be better to specify two levels of urgency, with the first one being the true clinical urgency of the service; if urgency rates are significant then the waiting list will need to be even smaller than this.)
7) Median RTT waiting time for non-admitted patients (target: 6.6 weeks)
Exactly the same process applies to the median for non-admitted patients, except that now 50 per cent are non-admitted within 6.6 weeks, and our target is specified as 95% within 18 weeks. Now our benchmark waiting list for non-admission must not exceed 97 patients, which is 24 per cent smaller than the well-managed non-admitted list when no median target was applied.
8) Median RTT waiting time for incomplete pathways (target: 7.2 weeks)
This last target is the trickiest of all. To be honest, we have not worked out a way of incorporating it directly into the model. Nor can we think of any purpose to this target that is not already achieved much better by the 95th centile for incomplete pathways.
However we have done some side calculations to work out whether, in a well-managed waiting list, this target would be more or less challenging than the “median + longwait” targets we have just considered. If it’s less challenging, that is good news because we know that, if we met the admitted and non-admitted targets above, then the median incomplete pathway would be met too. If it’s more challenging, then we need to work it out specially. So which is it?
Good news: it turns out to be less challenging, and that conclusion holds under all reasonable scenarios for surgical clinical priorities and for the management of expedited routine patients. That means we can neglect this target, knowing that in a well-managed list everything should turn out alright for our median incomplete pathways, so long as our waiting list is small enough for the other targets to be met.
So, in summary, this is how we should set up our planning models to achieve eight green boxes on our RAG ratings.
For admitted patient pathways, we should specify the level of clinical urgency in the casemix, and then add a second level of urgency so that only 50 per cent of patients remain on the list at 11.1 weeks. The waiting time target is 90 per cent within 18 weeks on a flux basis.
For non-admitted patient pathways, we specify the level of clinical urgency, and then our second level of urgency has 50 per cent of patients remaining at 6.6 weeks. The waiting time target is 95 per cent within 18 weeks on a flux basis (as opposed to a waiting list snapshot basis).
Given those inputs, the model will work out the activity, capacity and money needed to deliver the specified targets, provided we manage the waiting list well. If we achieve all that, then the other targets should simply fall into place, as they are all less demanding and would be achieved even with a larger waiting list.
In practice we would want to work out some other things too. Firstly, we might repeat the calculation without the median targets, just to show the extra costs that are pointlessly incurred in achieving a less-fair waiting list. Secondly, and particularly for the admitted patient pathway, we would want to model the pathway stages separately in order to work out capacity and money.
It’s been a long slog, but worth it. Now we know how to offer eight green boxes. Who knows, one day we might get a sensible target regime that means we don’t have to?
Waiting times across England
Waiting time pressures have turned the corner and are now getting worse. One in ten patients on the waiting list had waited over 17.6 weeks at the end of July, up from 17.2 weeks in June and worse than July 2010 at 17.3 weeks. You can see the trend in the dotted blue line below.
As we head towards the winter, we are starting from a worse base than last year. We might even see the dotted line breaching 18 weeks in next month’s figures, which would be a whole three months earlier than in 2010.
Very-long-waits are up too. There are 19,939 over-52-week-waiters on the waiting list, the highest since August 2010. However, as we will see below, this apparently huge increase (up from 13,259 last month) is explained by two Trusts submitting data after a prolonged absence from the series.
The government, unfortunately, prefers not to follow the waiting list. Instead it watches those patients lucky enough to be treated, and you can see how long the top ten per cent of admitted patients had waited in the solid blue line below. This is a lagging indicator, as you can see by looking at what happened last winter: pressure built up on the waiting list in November and December (when the dotted waiting-list line went up), and then the NHS cleared that backlog in February and March (the dotted line came down, and the solid admitted-patient line went up as the long-waiters appeared in the admission statistics).
So if you hear Ministers cheering that 90.6 per cent of inpatients and daycases were admitted within 18 weeks, up from 90.2 per cent in June, ask yourself this: if long-wait pressures are growing, is it really a good thing that more short-waiters (and fewer long-waiters) are being admitted? And you’d be right to question; the politicians have the whole thing backwards.
The total waiting list is possibly even more of a leading indicator. At least, it was last year: the total number of patients on the waiting list peaked in the height of summer and then fell (even as the longest waiting times rose). So far, the pattern is repeating again this year, giving no comfort that we are going to avoid a repeat of last year’s long-waiters.
What about activity? Well, the NHS seems to be working just as hard as last year, with no sign of any drop caused by limited finances. Admissions are following the same pattern as 2010, and if you compare admissions with the number of working days in the month (not shown in the chart below) then last year’s pattern is being followed closely.
For more detail on the English figures you can download our RTT waiting times fact checker, which contains complete time series for all the main English waiting time measures, here:
Waiting times by Trust
Everything in healthcare is characterised by gross and inexplicable variation, and waiting times are no exception.
In the following chart, each English Trust is represented by two dots: a red one and a blue one. The red dots show how long the top ten per cent of the waiting list is still waiting (i.e. based on incomplete pathways). The blue dots show how long the top ten per cent of patients admitted during the month had waited before they were treated (adjusted admitted pathways). As usual, we can see over on the right a number of Trusts that are “achieving the target” that 90 per cent of admissions should be under 18 weeks, even though they have plenty of long-waiters.
The proportion of Trusts, where at least 90 per cent of patients on the waiting list are under 18 weeks, has improved slightly since June, showing that the rise in long-waiters is increasingly concentrated in a minority of Trusts. At 71 per cent, this is the best since July 2010. The next chart shows the trend; this chart is related to the one above because it tracks the point where the red line (in the chart above) crosses 18 weeks.
Which Trusts have the longest-waiting patients on their waiting lists? Here’s the top 20: they’re the 20 red dots to the far right of the blue & red dot chart above. This time I’ve added a new column to the far right, so that you can see who is “meeting the target” while their long-waiters languish on the waiting list.
|Trust||Position in July||Top 10% of waiting list over||Change||Position in June||90% of admissions within|
|Kingston Hospital NHS Trust||#1||52.5 weeks||no change||from #1||17.8 weeks|
|St George’s Healthcare NHS Trust||#2||52.1 weeks||new entry||no data||29.2 weeks|
|Wirral University Teaching Hospital NHS Foundation Trust||#3||34.6 weeks||down 1||from #2||23.4 weeks|
|University College London Hospitals NHS Foundation Trust||#4||32.1 weeks||up 1||from #5||17.1 weeks|
|Shrewsbury and Telford Hospital NHS Trust||#5||29.5 weeks||up 1||from #6||36.2 weeks|
|Surrey and Sussex Healthcare NHS Trust||#6||28.4 weeks||down 2||from #4||35.5 weeks|
|Great Ormond Street Hospital for Children NHS Trust||#7||28.0 weeks||down 4||from #3||17.8 weeks|
|United Lincolnshire Hospitals NHS Trust||#8||25.7 weeks||no change||from #8||21.8 weeks|
|South London Healthcare NHS Trust||#9||22.9 weeks||up 11||from #20||24.7 weeks|
|Maidstone and Tunbridge Wells NHS Trust||#10||22.8 weeks||up 22||from #32||17.8 weeks|
|Yeovil District Hospital NHS Foundation Trust||#11||22.6 weeks||up 4||from #15||17.7 weeks|
|Guy’s and St Thomas’ NHS Foundation Trust||#12||22.6 weeks||up 4||from #16||19.3 weeks|
|Sheffield Teaching Hospitals NHS Foundation Trust||#13||22.2 weeks||up 11||from #24||17.8 weeks|
|St Helens and Knowsley Hospitals NHS Trust||#14||22.2 weeks||up 5||from #19||17.2 weeks|
|Derby Hospitals NHS Foundation Trust||#15||21.9 weeks||down 1||from #14||19.5 weeks|
|Warrington and Halton Hospitals NHS Foundation Trust||#16||21.5 weeks||up 12||from #28||17.3 weeks|
|South Warwickshire NHS Foundation Trust||#17||21.5 weeks||up 19||from #36||17.4 weeks|
|Southampton University Hospitals NHS Trust||#18||21.5 weeks||up 4||from #22||25.9 weeks|
|Pennine Acute Hospitals NHS Trust||#19||21.4 weeks||down 6||from #13||27.0 weeks|
|Central Manchester University Hospitals NHS Foundation Trust||#20||21.4 weeks||up 5||from #25||30.8 weeks|
Both Kingston and St George’s are new entrants to the table, in June and July respectively. Both hospitals reported very large numbers of patients waiting 52 weeks and longer: 4,483 at Kingston; 3,193 at St George’s. The total, 7,676 at the two hospitals, is larger than the national increase of 7,409 seen for English 52-week-plus waiters since May (which was the last month when neither hospital submitted data). I don’t have local knowledge of what is happening at these Trusts, but I expect there are serious data quality issues involved.
Data for all Trusts
You can find full details of the position at every English Trust, including time trends and peer comparison, via the interactive maps below: choose a specialty and click on it, then click on a pin to get a balloon showing a summary of any Trust’s data, and then click on the Trust name in the balloon to get a full analysis with charts.
There are separate maps for each specialty (all maps based on incomplete pathways):
Here’s a thumbnail of the interactive Orthopaedics map to whet your appetite:
If you have a particular Trust in mind, you can directly look up its detailed reports here.
All the above analysis comes with a caveat: in many parts of England there are restrictions on hospital referrals that have the effect of blocking or holding up patients before they arrive on the hospital waiting list. Those patients are not included in the reported figures, and so they are missing from this analysis.
The August 2011 RTT waiting time figures are due out at 9.30am on Thursday 13th October.
This post first appeared at HSJ blogs.
Every month, the Department of Health publishes 18-week waiting times data for England. The publication timetable is here (look for “Referral to treatment waiting times statistics”), and the data itself is published here. This is a quick guide to help journalists find their way around the data.
As the term “referral to treatment” (or “RTT”) suggests, a patient’s waiting time “clock” starts ticking when the patient is referred by their GP to a consultant (it doesn’t apply to referrals to non-consultants such as physiotherapists). For as long as the clock is still ticking, their clinical pathway is called “incomplete”. The clock only stops ticking when the patient starts receiving definitive treatment (or when it’s agreed that they shouldn’t be treated). The detailed rules for all this are found under “Methodology, Rules and FAQ” on the main statistics page.
The waiting times statistics page has lots of different data on it, so it’s worth understanding what the different kinds are.
- If you want total figures for the whole of England, then use Commissioner Data. When you’ve downloaded and opened a spreadsheet, click the worksheet called “National” and look for a row near the bottom of the table where, in the Treatment Function column, it says “Total”; that’s the all-specialties data.
- If you want detail for individual NHS Trusts, then use the Provider Data. When you’ve downloaded and opened a spreadsheet, click the Provider worksheet to get the detail.
All these spreadsheets are large, and contain lots of hidden columns that you will want to reveal by clicking the + symbol in the grey area just above the table. Then you’ll need to freeze the headers so that you don’t lose your place when scrolling around in the spreadsheet: click on the first actual number in the table (just under the header “>0-1″) and select Freeze Panes from the Window menu (more on Freeze Panes here). Now you can scroll around more easily, or if you’re looking for Trusts you can search for them by name using Find in Excel (more on Find here).
One other technical point: when you open one of these spreadsheets, Excel might ask if you want Macros enabled, or cells updated from another spreadsheet. Just say no.
What’s the difference between Adjusted Admitted Pathways, Incomplete Pathways, and so on? Each spreadsheet contains a Glossary sheet with all the definitions, but here’s a quick run-down:
- Incomplete pathways are what everybody used to call “The Waiting List”. This is the most important data of all. These patients may have been seen in clinic by a hospital doctor, and they may even have had a load of diagnostic tests, or none of those things may have happened; the important thing is they haven’t yet started definitive treatment (or been discharged) and so they have an “incomplete pathway”. The data shows how long these people have waited so far, up to the end of the month that the data relates to.
- Adjusted Admitted Pathways are what most people usually focus on (wrongly, in my view). These are patients who started receiving treatment during the month as an inpatient or day case (but not outpatient). The data shows how long they waited before their treatment began. The word “Adjusted” means that if a patient says they don’t want their treatment just yet (for instance, a teacher might want to wait for the school holidays before having an operation), then the delay they asked for is deducted from their waiting time.
- Admitted Pathways are the same as the Adjusted Admitted Pathways, except that no time is deducted when patients ask for a delay.
- Non Admitted Pathways are patients who started treatment during the month as outpatients, plus those patients who decided not to be treated (which includes “watchful waiting” to see if the condition gets worse).
We provide detailed commentary on each month’s RTT waiting times data, usually on the same day it is released. Our report appears first on HSJ blogs here, and then a few days later on our open blog site here.
In August 2007 there were 578,826 over-one-year waiters on the English waiting list. In May 2010, the time of the General Election, there were only 18,458. This colossal reduction in the longest waiting times was a huge achievement by the NHS under Labour.
The curious thing is how, after a steep descent, this particular plane never landed. Look at the trend through 2008 and you might expect it to hit the ground sometime in 2009. But it never did. The long-waiters, albeit in much smaller numbers, are still with us.
The next chart takes a closer look at this enduring tail.
Since the Election, the number of over-one-year waiters fell a little further, reaching 13,442 in September 2010. And since then, no real change. On the latest (June) figures, it stands stubbornly at 13,259.
13,259 patients. Is that a lot?
In June 2011, the NHS in England recorded a million and a quarter patients who were treated or discharged from the waiting list during the month. If that is a month’s worth of work for the NHS, then 13,259 patients is only 100 minutes.* How long does it take to do 100 minutes’ work? And why is the NHS not doing it?
The simple answer is that long-waiting patients aren’t a national priority. They should be. The longer patients wait, the less we know about them; some of them (nobody knows how many) will be in very real need of treatment. This isn’t about money, it’s about swapping one 100-minute task for another. The NHS has achieved far more difficult things before. So let’s finish this job, and make year-long waiting a thing of the past.
*You may be thinking that surely these are all waiting for an inpatient or day case admission. Then it would be about six and a half hours’ work. But I’m not sure you’d be right about that; many of the very-long-waiters are incorrectly-coded watchful-waiters in outpatients and wouldn’t actually require any clinical time at all to remove. Even if they are all waiting for admission, it still isn’t very much work to clear.
This post first appeared in HSJ blogs
Why do elective admissions go up and down like a yo-yo? And why is the pattern apparently so seasonal? It’s a big effect, as this chart of English RTT admissions shows:
It’s pretty striking: a trough-to-peak variation of around 25 per cent. And the pattern repeats fairly regularly, rising and falling in the same months every year. What is happening?
Fortunately, a smoking gun is lying in plain view. Take a look at this:
The orange line (using the left hand scale) is the number of patients admitted each month (from the Department of Health RTT site). It has an upward trend because the NHS is treating more patients each year; the trend is 1.5 per cent per year, and shows no sign of reversing in the age of austerity.
The blue line (using the right hand scale) is the number of working days each month (from work-day.co.uk). Working days, of course, do not have a year-on-year trend, though they do vary a lot from month to month. In April 2011, for instance, there were only 18 working days. That’s 30 days in total, minus 9 weekend days (the 30th April was a Saturday), Good Friday, Easter Monday, and the Royal Wedding.
And look. When you adjust the left and right hand scales carefully, as in the chart above, the lines are pretty close. From March to June 2011 they sit absolutely on top of each other.
There are some exceptions in the pattern. There are fewer admissions than you might expect in December, which is almost entirely explained by the NHS not running elective lists between Christmas and New Year (which knocks off another 3 days); no need to look for factors such as extreme weather and influenza putting pressure on the NHS. Also August sees an extra dip, because so many staff take their summer holidays then. But otherwise, the number of admissions looks as predictable as a calendar.