Posts Tagged ‘scheduling’
Previously I outlined why the ‘PTL’ approach to waiting times management is a labour-intensive way of achieving sub-optimal performance, and why it should be replaced with a rules-based approach to patient scheduling that optimises waiting times continuously without needing regular intervention from senior managers.
Here we will illustrate the point, taking a real NHS waiting list and (in a simulator) converting its management to the rules-based approach. We will see the 92nd centile waiting time fall from 14 weeks to 6 weeks, even though the size of the waiting list has not reduced. We will see how the biggest improvements are seen in the first month and how gains are sustained indefinitely (so long as the waiting is not allowed to grow).
So let us start by introducing our real waiting list. Here it is, and it’s the new outpatient list for one consultant orthopaedic surgeon.
Let’s take a quick tour of this image. The vertical grey stripe shows the date of this analysis, which in this example is the week beginning Monday 20th August 2012. To the left we have the waiting list; each blob is one patient, and they are sorted according to their referral date (so the longest-waiting patient at the far left has been waiting 36 weeks). If a patient does not have an appointment date (like the longest-waiting patient) then they appear hollow. When they are given an appointment they turn solid, and a copy of the patient is placed on the appointments diary; the appointments diary goes off to the right and into the future.
There are 121 patients on this waiting list, and the 92nd centile waiting time (i.e. how long the 112th patient has waited) is 14 weeks. So that is our starting point.
How are this consultant’s outpatients being scheduled?
Looking at the appointments diary (the grid to the lower right), there are plenty of empty clinic slots in the current week. Then for the next two weeks all slots are fully-booked, and after that there are plenty of empty slots again. So it is not clear, looking at the appointments diary, what the rules are for offering slots to patients.
Looking at the waiting list (to the top left), we can see that a majority of short-waiting patients are unbooked, then nearly all the longer-waiting patients are booked, and the few very-long-waiters are mostly unbooked.
So it looks on the face of it as if this is loosely a partially-booked system, booked about 3-4 weeks in advance, with efforts being made to book patients in date order. However slots are not being fully utilised, many short-waiting patients are being booked ahead of longer-waiters, and the very longest-waiting patients are not booked. So there should be scope for improving the management of this consultant’s list if we used all the available clinic slots and booked strictly in date order.
To mimic the possibility that patients are genuinely choosing not to take up offers of early appointments, we will assume that some 10 per cent of patients rearrange their appointments at short notice and put themselves back in the queue. (It is of course possible that the very-longest patients, who are unbooked, are choosing to delay their appointments by several months, but the delays are so long that it is surely legitimate to ask whether they should have been referred in the first place.)
So let’s hand this waiting list over to the computer and let it do the booking. (If you want to do this kind of analysis on your own waiting lists, the actual waiting list was loaded up into Gooroo SimActive, and then after clicking Save you can hand it over to the rules-based booking simulator.)
What’s changed in this picture? We’ve filled all available routine appointment slots (the blue ones) up to 4 weeks ahead, by booking patients in strict date order. Also, more patients have been referred, including a couple of urgent patients (shown in red); those urgent patients have been booked into urgent slots (the red ones). So we can already see how things are going to get better: over the next few weeks all our longest-waiting patients are going to be seen (unless they cancel).
Fast-forward a few weeks, and things are looking very different:
Most of the long-waiters have been seen already, and there’s just one patient from May still waiting. We did have a couple of cancellations who were put back on the list (they are shown with a double letter, to show that they’ve been cancelled). When we hold this week’s clinic, we’ll clear most of the remaining long-waiters and things should look a lot better.
One week later:
This is the new normal shape for our waiting list, under rules-based partial booking up to 4 weeks in advance. If we chose to run a fully-booked service instead, offering patients a choice of slots in up to 3 different weeks (which is compatible with Choose and Book rules), waits would be a week or two longer but otherwise in a similar position.
This is sustainable, so long as the size of the waiting list does not grow. Here is the same list a year later:
We’ve achieved a dramatic reduction in waiting times by implementing some relatively simple rules for booking patients, continuously as they come in. No weekly PTL meeting, no senior managers fire-fighting, just good clerk-level administration.
If you have access to YouTube (i.e. probably not from an NHS computer) you can see this scenario running as a video here:
Also new in Gooroo SimActive: there is now a download button that downloads all the data including the meta-data about additions, removals, etc. So now you can build up a library of files for your subspecialties and consultants, without having to type in the meta-data every time you upload something.
A fiddly little annoyance has been fixed for anyone using Gooroo SimActive to diagnose their waiting times pressures.
One of Excel’s little “features” is that it often tries to guess what you want, and reformats things even if you didn’t want it to. For example, if you have a date that is correctly formatted ccyy-mm-dd for upload into SimActive, and you open the file in Excel, then Excel thinks “a-ha, this is a date, so you probably want me to reformat it as dd/mm/ccyy”. And it goes right ahead and does it without asking.
This used to mean that SimActive got confused because it wasn’t expecting dates in that format, but no longer, because now it will detect and accept dates in dd/mm/ccyy format. It’s a small issue, and it wasn’t hard to work around in Excel, but it was a little bit fiddly and so we’ve fixed it.
So you don’t need to force Excel to deliver ccyy-mm-dd formats any more; the default dd/mm/ccyy is just fine (and ccyy-mm-dd and ccyymmdd are both fine too).
The first Gooroo user group is being set up for the East Midlands and surrounding areas, where we have a growing cluster of NHS organisations using Gooroo’s planning and scheduling software.
Meetings will be held three times a year, and attendance is free of charge. The first will be on Monday 1st October from 2pm to 4:30pm in Teaching Room 5 of the Education Centre at Derby Hospital. If you’re a current or potential Gooroo user and would like to come along, then you are very welcome, and should email email@example.com to add your name to the mailing list.
The second user group is already being set up in Scotland, and again if you’d like to come then please email us. The first meeting will probably be in late October in Stirling.
If you are a Gooroo user somewhere else in the country, and would like a user group to be established in your area, then please let us know and we’ll see what we can do.
In a parallel post I explain why PTLs should now change, and evolve into “active PTLs” which work continuously to minimise waiting times for all patients. This blog post explains how in a bit more detail, describing the rules for operating active PTLs.
I’ll also take the opportunity to sketch out briefly the origins of PTLs, because they were a tremendous achievement in their day. It is easy to forget just how unmanaged the NHS’s waiting lists were in the 1980s, and the originators of PTLs deserve credit for their roles in making today’s shorter NHS waiting times possible.
Let’s start with the active PTL rules.
There are only five rules, and they aren’t particularly complicated. The difficult part was excluding all the alternatives, and quantifying the behaviour of the system to allow the calculation of booking rules and waiting times; this took two years of PhD-level research, and the study of over a billion simulated patient bookings. If you want to find out more about the simulator research, you can download the research papers here, and you can try the simulator by logging in here and clicking SimView (registration and use is free to NHS).
The purpose of laying out the rules in this blog post is to stimulate interest in the next stage, which is to take the active PTL rules beyond the simulator and into the real world. If you are interested in joining those hospitals who have already expressed an interest then you can email me at firstname.lastname@example.org
Before implementing an active PTL, you will first need to:
a) know, at subspecialty and stage-of-pathway level, the size of waiting list that is consistent with your waiting times targets;
b) ensure that enough slots will be delivered through your available capacity to achieve and sustain a waiting list that is no bigger than that; and
c) carve out the right number of slots for urgent and cancelled patients.
A free booking rules calculator that helps with all this is available after login at nhsgooroo.co.uk.
The active PTL rules
The rules work differently for fully-booked and partially-booked services. In a fully-booked service, which should include all services using direct Choose & Book, all patients are invited to make an appointment. In a partially-booked service, which only works when the provider has control over all appointments, slots are only available a limited number of weeks ahead (typically 6 or 4 weeks) to minimise disruption caused by staff taking leave. The rules work for both clinics and theatres.
The active PTL rules are driven by five different events:
1) An urgent patient needs booking
Find out how long the patient can safely wait because of their clinical condition. Book them into the latest empty urgent or routine slot within that time. If no empty slots are available, create one by cancelling the routine patient who will be least inconvenienced.
2) In a fully-booked service: a routine patient has had their appointment cancelled and needs rebooking
Offer the patient a choice of any empty urgent or routine slot in the first three weeks in which empty slots are available.
3) In a fully-booked service: a new routine patient is added to the waiting list
Offer the patient a choice of any empty routine slot in the first three weeks in which empty routine slots are available.
4) In a partially-booked service: empty routine slots become available
Select routine patients for booking in the following order: cancelled patients first (starting with the longest-waiters), then new patients (again starting with the longest-waiters). Book each patient into the soonest empty routine slot, until all available routine slots are filled.
5) There is an empty urgent or routine slot at very short notice which is at risk of being wasted
Fill the slot, ideally with an urgent patient or by bringing forward a long-waiting patient, or alternatively with a new routine patient.
Tactics that are not in the rules
Avoid holding extra slots in reserve. Avoid running services that neither offer bookings to all patients (if fully-booked), nor fill all available routine slots (if partially-booked). Avoid “rippling”.
A short history of PTLs
According to Anthony McKeever (who was there at the time), PTLs all came about in the mid to late 1980s.
The thought leader was Professor John Yates who studied in great detail the influences that led to long waiting times. By analysing the available data he identified that if you increased the focus on the back of the queue then long waits could be greatly reduced.
Mersey RHA, under Sir Duncan Nichol and Sir Donald Wilson, turned this into a policy to achieve 2 year maximum inpatient waits, which sounds long today but was ground-breaking at the time.
This policy was developed into practical methods by Kevin Cottrell and Anthony McKeever. First they developed the concept of Personal Treatment Plans, which were individualised for each long-waiting patient and agreed with their consultant. These developed into provider-led Patient Treatment Lists, and these were the first PTLs. As other NHS organisations picked up the techniques, the PTL abbreviation stuck but came to stand for a variety of different words.
First published at HSJ blogs
They’ve been a mainstay of waiting list management for a quarter century, and seen the NHS through the most spectacular reductions in waiting times in its history. They are breathtakingly simple in concept, and easy to implement in practice. They are already understood and embedded throughout the NHS. Why, then, do patient tracking lists need to change?
PTLs are also known by various other names that share the same initial letters (primary, patient, priority, tracking, treatment, targeted or targeting are common substitutes). They work like this. Draw up a list of all the patients who are going to breach your waiting times target in the next few weeks. Then you make sure they are treated before they do. Simple as that. What could possibly go wrong?
Well, quite a lot actually. Let’s say your target is 18 weeks, but your waiting list (at subspecialty level) is small enough to achieve 12. What waiting time do you achieve in practice? If you rely on PTLs then you’ll probably stay at 18 weeks, with managers firefighting imminent breaches week by week. Why? Because PTLs only work at the margins, so non-PTL patients (most of them) are not being managed systematically. Some patients get treated quickly, while others end up on the PTL.
Things get worse if the waiting list grows. If 18 weeks is achievable, but only just, then it becomes really hard to find slots for all your PTL patients: too many short-notice slots are already filled with non-PTL patients being booked out of turn (even if they aren’t urgent). So you end up on the familiar trail of begging consultants to squeeze PTL patients onto lists, buying extra sessions on a Saturday, persuading patients to transfer to the private hospital down the road, and even (though you hope it will never come to this) finding it difficult to treat urgent patients safely. Failure remains likely despite the effort and expense.
What if your PTL is too big to sustain 18 weeks? Much the same, except that now sustaining the targets is impossible. But you can’t tell from the PTL.
It isn’t all doom and gloom with PTLs. They’re a lot better than having no system at all. That is pretty much what was happening before PTLs were invented in the late 1980s, when inpatients waited years for treatment. But it’s pretty clear that we can do a lot better.
Now we can put an end to managing at the margins and in batches, to tying up managers’ time in endless firefighting, and to limboing under the target when much shorter waits are possible. Now we can move towards systematically managing all waiting list patients continuously by the booking clerks and via choose and book, to create an “active PTL”.
The active PTL rules aren’t complicated. In summary: urgent patients are booked as late as is safe (cancelling a routine patient if necessary); cancelled patients who need rebooking are booked into the next available slots (and in a fully booked service have access to urgent slots to avoid them going all the way to the back of the queue); new routines are offered the next routine slots; and if a short-notice slot is at risk of being wasted, then fill it.
By getting the booking right, the active PTL will consistently achieve the shortest waiting time possible. That waiting time might be eight weeks, or 18 weeks, or even 28 weeks. It all depends on the size of the list.
Ah, the poor waiting list. Her younger sister, waiting times, has been the sexy one these past few years and the fusty old waiting list hasn’t had much attention. So let us remind ourselves that the size of the waiting list is absolutely key: if it’s too big, then short waiting times are impossible, no matter how good your booking practices.
It’s about time waiting lists came back into fashion. Every subspecialty should know, for each stage of the pathway, how small their waiting list needs to be to sustain their waiting times targets. If the waiting list gets too big then it is time to take action.
That’s the funny thing about waiting times. Tackle them directly and you get all sorts of unintended consequences. But do it indirectly, via the list size and booking rules, and you’ll have them nailed.
First published in the Health Service Journal
Treat your long-waiting patients!
Don’t treat your long-waiting patients!
You can forgive the NHS for being confused. A Trust with a long-wait backlog gets clobbered whatever it does: with fines under the NHS Contract if it treats its long-waiters, and via performance management if it doesn’t.
There is a way through the conundrum, but it’s messy. (At least the NHS can console itself with the thought that it didn’t make the mess in the first place.)
The key point is that, from April 2013, the target regime is expected to focus on the waiting list (when 92% of incomplete pathways must be below 18 weeks). So if you work at a Trust with lots of long-waiters then, whatever you do this year, you need to tackle that 18-week backlog.
Unfortunately, when you treat those long-waiters you will probably breach the admitted and non-admitted targets which live on, zombie-like, in the NHS Contract. If your PCT Cluster is sensible about it, they will voluntarily refrain from enforcing these zombie targets. (And, even if they don’t, being “performance managed” is perhaps more likely to keep you awake at night than the prospect of a fine.)
So in operational terms, if you have an 18-week backlog, the right thing to do is to treat your long-waiting patients, preferably with blessings from your PCT Cluster. This is more than just good tactics; it is consistent with the four principles of good waiting list management:
- Treat more urgent patients more quickly
- Treat patients with similar priority broadly in turn
- Keep the longest waits to a reasonable level
- In doing all this, don’t waste the available capacity
So that’s the operational approach. What about planning?
Here things get a little trickier, because you have two completely different kinds of target to juggle: the zombie targets based on patients as they are being treated, and the new ones based on patients who are still waiting. Happily it turns out that this conflict is easy to resolve.
In a well-managed waiting list (following the four principles above), it turns out to be easier to achieve the incomplete pathways target than the zombie targets. So the solution is simply to plan your activity and capacity to achieve the more difficult (i.e. the zombie) targets. In practical terms this means that, when you are running your planning model, you should set the waiting times targets to sustainably achieve 90% of admissions and 95% of non-admissions within 18 weeks; you do not need to model the 92% incomplete pathways target because it will automatically follow.
If all goes well then this muddle of targets should only last for a year. Then we can all focus on what is really important: stopping long-wait backlogs from building up in the first place.
In the meantime it is within the gift of PCT Clusters to resolve the confusion locally by choosing not to enforce the zombie targets in the NHS Contract, and so clear the way for performance management to bear down on the backlogs.
At dawn on the 17th of November, Andrew Lansley and I appeared together on Radio 5 Live for the Government’s pre-announcement of its new waiting times target. It was a friendly affair rather than a duel, because the new target is very welcome and so we were in the happy position of agreeing with each other.
Why is it so welcome? If you’ve been following this blog for a while, you will know that I am a longstanding critic of the main existing target (that 90 per cent of admitted patients must have waited less than 18 weeks since referral). The reason, quite simply, is that if you have lots of long-waiters then the target restricts your ability to treat them.
The new target is much better because it stops the backlog of long-waiters from building up in the first place. The target, which is confirmed in the new Operating Framework (para. 2.31), is:
that 92 per cent of patients on an incomplete pathway should have been waiting no more than 18 weeks. The referral to treatment (RTT) operational standards should be achieved in each specialty by every organisation and this will be monitored monthly.
The NHS has never actually achieved this level of performance, although it did come very close last year, achieving 91.9 per cent of the waiting list within 18 weeks at the time of the General Election. How hard will it be to achieve?
The statement issued to the media by the Department of Health estimated that “In practice, the new standard will mean the NHS will have to trim about 50,000 from its waiting lists”. I couldn’t quite replicate this figure, but as we’ll see in a moment it is as good an estimate as any. At 2 per cent of the waiting list, or 4 per cent of monthly activity, it doesn’t sound too hard.
There are various ways of looking at the numbers. If we simply take the total size of the waiting list (2,586,583) and the current number waiting over 18 weeks (242,540), then to achieve the target by cutting the backlog we need to reduce the list size by 38,710 (bearing in mind that both the total list and the over-18-week waiters are being reduced at the same time).
That calculation assumes that we can net-off the under-achieving services against the over-achieving ones. In practice, though, the target must be met in every service. If we tackle the target by brute force by treating the backlog, without netting-off pressures between one service and another, we find that a heftier 90,000 extra activity would be needed to bring the existing backlogs down to target level. This still doesn’t look too bad, at only 0.6 per cent of annual (admitted and non-admitted) activity.
But, as usual with NHS pressures, the challenge is not spread evenly around the NHS. It is clustered. Taking all specialties together, here is a map showing the waiting time exceeded by the top 8% of patients on the list (all data is for September 2011 from DH):
We can get a better picture by going right down to specialty level; there are 1,330 services (by Trust, by specialty) that have more than 50 admissions per month. Some 61 per cent of them are already achieving the new target. We estimate that about 22 per cent more could achieve the target safely with good scheduling alone, without needed to reduce the size of the waiting list. That leaves just 17 per cent that would need to reduce the size of the waiting list (in addition to good scheduling).
(You might guess from those proportions that the England-wide target could be met with good scheduling alone, and you would be right. In fact, if every service implemented good scheduling then we estimate the target could be met nationally even if the English waiting list grew by 50,000.)
When analysing the pressures in each service, we really want to know how many working days it will take to clear the backlog. We want to draw attention to those services that have the biggest pressures. Ideally, we also want to know whether we can get part-way there by scheduling patients in a better order.
The next chart has a go at this. The size of each bubble shows the number of over-18-week waiters at each Trust (considering all specialties together, for now). Its position along the horizontal (x-) axis shows how many working days it would take to achieve the new target, if each Trust simply tackled its backlog starting with the longest-waiting patients (and did so at the rate the Trust currently treats both admitted and non-admitted patients). For comparison, the bubble’s position up the vertical (y-) axis shows how many working days it would take to achieve the target, if good scheduling were also put in place (and, because the necessary details are not published for each Trust, we have had to make a few assumptions about what good scheduling might look like).
Most of the Trusts are piled in a heap around where the axes cross; they don’t need to do much, if anything, to achieve the new target. Then we have a few going out along the horizontal axis, who could achieve the target just by scheduling their patients in a better order; no extra activity is required. Then, rising up the chart, come the big blobs with the biggest problems; these are Trusts where good scheduling isn’t going to save them; somehow they need to cut their waiting lists in a fairly serious way. The four biggest ones from the top right are: Kingston, Taunton, Wirral, and St George’s; all currently have 8 per cent of their waiting list over 26 weeks, and will face a challenge to get that down to 18 weeks.
An all-specialties view is all very interesting, but in practice a gynaecologist isn’t going to be much help with the gastro backlog. So here is the same style of chart for each specialty; one blob per Trust, with the specialty name shown in the bottom right corner of each chart:
As we found previously with one-year-waiters, some of the biggest pressures are found in gastroenterology and “other specialties”. Neurosurgery is also an area for concern, because there are large pressures and because not many Trusts provide this highly-specialised service. You may be wondering if your Trust is one of the pressured ones, so the highest clearance times in the charts above (according to backlog clearance time alone) are:
In conclusion, the new target is within reach for the NHS as a whole. Things may slip over the winter but, come the spring, the target should be achievable nationally as Trusts improve their waiting management and recover the winter backlog.
Looking in greater detail, there are many Trusts and specialties (we estimate around 17 per cent) where some backlog clearance will be required. Within that, some have very challenging positions and may need help from their neighbours with their backlog clearance. In all cases good planning, using an advanced planning tool that models waiting time dynamics, will help Trusts and Commissioners to ensure that recurring and non-recurring resources are deployed to achieve the new target sustainably.
This post first appeared at 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.
PTLs have been around since the early 2000s as a tried-and-trusted way of achieving waiting time targets.
What are they? The name doesn’t tell you much (depending on who you ask, PTL stands for Patient/Primary Targeted/Targeting/Tracking/Treatment List) but the concept is easy enough to explain:
Pretend it’s the 1st of February. In 4 weeks time, on the 1st of March, you want to have no patients waiting longer than 18 weeks since referral. All the patients who could possibly breach that target have already waited over 14 weeks. You know who they are, and the “PTL” is the list of their names. If you book everybody on the PTL in for treatment during February, then (so long as you don’t cancel any) you are guaranteed to achieve the target. Simple.
But this deceptively simple approach creates problems of its own.
Firstly, if you have a serious waiting time problem, then it is very difficult to find slots for all those patients. You might end up using slots that should really be kept aside for urgent patients who haven’t arrived yet. If urgent patients end up being delayed as a result, then you have created a clinical risk that could result in patients being harmed. This is a serious matter which a good booking system should be designed to avoid.
Secondly, when booking the PTL, your main concern is to find slots in February. Exactly which patient goes into which slot may be considered less important. But if you book routine patients out of order then the maximum waiting time goes up: those lucky patients who squeeze in for treatment at 14 and 15 weeks are jumping the queue on those waiting longer, and we know that queue-jumping pushes up maximum waiting times. So at next week’s meeting you will have more difficulty clearing your PTL, even though your underlying waiting time pressures have not changed.
PTLs manage long-waits in batches and at the margins
These problems arise because you are managing your long-wait problem in batches and at the margins, and your actions have unintended consequences for the rest of the system. It would be better to manage the whole system continuously in the right way, and so achieve the best possible waiting times safely and consistently.
If this holistic approach means that you can achieve 12 weeks, then you will. (You might not have realised it was possible using PTLs.) If the best you can achieve is 20 weeks, then you have a problem; but your planning and monitoring systems should have picked up this pressure already and pointed to solutions for relieving it (perhaps by moving resources from those services that can achieve 12 weeks).
What if your waiting list is just too huge to achieve 18 weeks safely and continuously? Then your problem is not so much waiting list management, but a mismatch between supply and demand that needs to be tackled together with commissioners.
While you’re dealing with that, you need to ask yourself how you want to fail in the meantime. You are faced with three main choices:
- carry on treating routine patients in turn even if they all wait over 18 weeks;
- drip-feed your long-waits through the system so that at least you’re achieving the headline target (90% of admissions within 18 weeks) while the backlog gets worse; or
- squeeze so hard that urgent patients end up being delayed.
The first is the high moral ground, and the holistic approach; the second is understandable; the third is surely indefensible. PTLs, unfortunately, are most likely to lead you towards the third.
This post first appeared at HSJ blogs
What should you do if you have a large and growing waiting list backlog, and no way to clear it?
You could devote as much capacity as possible to treating the longest-waiting patients. That would keep maximum waiting times as short as possible, and keep to the principle that patients of similar clinical priority should be treated in turn. Unfortunately, admitting so many long-waiters would also fail the 18-week target: that 90 per cent of admitted patients must have waited less than 18 weeks. For this, you could be fined up to 5 per cent of your elective care revenue by your commissioners.
What’s the alternative? You could choose to achieve the target regardless. That means you could only devote up to 10 per cent of your capacity to the longest-waiting patients. The number of long-waiting patients would grow inexorably, but because you would be achieving the admission-based target you would not be fined.
When faced with this choice, different Trusts go different ways. Here is a scattergram for Ophthalmology (it’s a similar picture in other specialties too). The chart shows the time within which 90 per cent of patients are admitted (vertical axis) plotted against the time within which 90 per cent of patients are still waiting (horizontal axis). (Data is for December 2010 from Department of Health.)
The rump of Trusts are nestled in the desirable quarter of the 18-week gridlines. But some aren’t, and two of them are picked out in different colours: Royal Berkshire NHS Foundation Trust (in red), and Western Sussex Hospitals NHS Trust (in green). I’ve chosen them because they illustrate the two options quite well.
The next link is a drilldown into Royal Berkshire’s data. They are comfortably achieving the admission-based 18 week target. But since mid-2009 the waiting list has been growing inexorably, with 68 per cent of incomplete pathways (i.e. patients still waiting) over 18 weeks. Nevertheless, the Trust has (almost) consistently met the 18-week target by not admitting long-waiters in significant numbers. This is not a criticism of the Royal Berkshire; they have been under massive pressure to do this. But it is an indictment of the admission-based 18-weeks target.
And here is a drilldown into Western Sussex’s data. Their waiting times have also grown since mid-2009, and an even higher proportion of their incomplete pathways (75 per cent) are already over 18 weeks. But this Trust has devoted a lot of capacity to treating those long-waiting patients, so that few are waiting longer than 30 weeks. Unfortunately their efforts to treat long-waiters mean they look very bad against the admission-based target, achieving only 53 per cent of admissions within 18 weeks. This puts them at risk of maximum fines from their commissioners, even though they are doing the right thing for their patients.
The admission-based 18-week target is clearly a problem when waiting lists grow. It deters hospitals from treating their long-waiting patients; it violates the principle that patients with similar clinical priority should be treated in turn; and it misleads the public with statistics that make everything look rosy.
The solution, I suggest, is to change the target from “90 per cent of admissions within 18 weeks” to “90 per cent of incomplete pathways within 18 weeks” (i.e. 90 per cent of those still waiting, at any point in time, should not have waited longer than 18 weeks). Now that central enforcement of the target has ceased, this could be negotiated locally between commissioners and providers.
It would mean tackling the underlying issue, of course, and that would be expensive at Trusts like the Royal Berkshire and Western Sussex. But isn’t tackling the underlying issues and improving outcomes for patients meant to be what the reformed, clinician-led NHS is all about?