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Posts Tagged ‘booking’

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.

Of all the referral-to-treatment (RTT) waiting times targets, the toughest is currently the “90 per cent” target. This requires 90 per cent of patients to have waited less than 18 weeks as they are admitted, on an adjusted basis. Adjusted, that is, for clock pauses.

I must confess, I had always assumed that clock pauses have only a minor effect. There might be one or two Trusts, I thought, where clock pauses were (shall we say) giving the adjusted admitted target a fair wind. So I was really quite taken aback when I looked at the evidence.

Clock pauses are only allowed in limited and defined circumstances. According to the RTT Rules Suite (p.22, my emphasis):

Clocks may only be paused for patient initiated delays at the admission for treatment stage of the waiting time pathway.

Once a decision to admit has been made, patients should, of course, be offered the earliest available dates to come in, as appropriate. However, where patients decline these offers, then, for a clock to be paused, they must be offered at least 2 reasonable dates for admission. Reasonable is defined as an offer of an appointment with at least 3 weeks notice.

Not much scope, you might think, for widespread pausing, or for provider-initiated pausing to help achieve the target. So how much are clock pauses actually used, and what effect do they have on adjusted admitted waiting times?

In the following chart, each point represents one specialty at one Trust, and it shows all Trust-specialties where at least 50 patients were admitted during June 2012. The position along the x-axis shows the 90th centile adjusted admitted RTT waiting time; i.e. the waiting time exceeded by only 10 per cent of patients, measured from referral to admission with clock pauses deducted. The position up the y-axis shows how much time was deducted for clock pauses, compared with the 90th centile unadjusted admitted RTT waiting time.

Do you think that an alien, looking at this chart, might be able to guess what the adjusted admitted target is?

You have to admire the accuracy with which so many services are achieving 18 weeks, with exactly the right amount of clock pausing.

It is also striking how much more common clock pauses are, in those services that are only just achieving the 18 week target. For services that lie between 17 and 18 weeks, some 42 per cent include at least one week of clock pauses; for the rest, the figure is just 24 per cent. Looking at it another way, the 17-18 weekers include an average 1.5 weeks of clock pauses, and the rest just 0.7 weeks.

Let’s drill down into one specialty in one Trust where the impact of clock pauses is especially clear. In the chart below, the unadjusted admissions are shown by the solid red columns, and the adjusted admissions by the solid red line (data from the Department of Health).

The gap between the line and the columns shows the net number of clock pauses: i.e. the number being paused minus the number coming off pause. There are no net pauses at all below 15 weeks, then 39 net pauses between 15 and 18 weeks, and then above 18 weeks they all start coming off pause again.

If this service had paused only 37 patients instead of 39, it would have failed the target. By a remarkable coincidence, it has achieved the target by a similarly narrow margin every single month for the last three years; the extent of clock pausing varies, but the adjusted result remains the same.

I am not making a blanket accusation that any service, that narrowly achieves the adjusted admitted target with just the right level of clock pauses, is misusing clock pauses in order to achieve the target. But I think it is fairly clear that some of them probably are, and some systematically.

Does it matter? Yes, but not as much as it used to, because the recently-introduced incomplete pathways target does not allow clock pauses to be deducted. If that target ever achieves the primacy it deserves over the adjusted admitted target, then pauses will become largely irrelevant. Normal levels of patient-initiated pauses (which, as we saw in the first chart, do not have a big impact on waiting times) will be absorbed within 18 weeks and the 8 per cent tolerance on incomplete pathways.

Even as the targets stand today, any service with a very high level of clock pauses will still breach the incomplete pathways target (as the example above does). Unless, of course, a service decides to adjust the incomplete pathways for pauses too. That isn’t allowed, but it does happen; how else could you explain the chart below, in which long-waiting patients are apparently being admitted even though there are no long-waiting patients on the list (and weren’t the month before, either)?

 

(The Department of Health has just published the checks they run across all the monthly RTT data submitted by Trusts, including checks on clock pauses. You can download the document “RTT Assurance Data Checks (PDF, 54K)” here.)

Imperial College Healthcare NHS Trust is in the news, with startling reports of a breakdown in record-keeping that resulted in patients waiting up to 2-3 years. Some of the patients who got lost in the system were suspected cancer referrals who the Trust is still trying to locate, months or even years later. It has been a horrible, stomach-churning failure.

To their credit, Imperial seem to be sorting things out pretty quickly: fixing the data, validating the waiting list, following up patients they are concerned about, clarifying scheduling procedures, and strengthening planning, all with external assistance and oversight. I don’t have inside knowledge of the actions they are taking, but it does look from the outside as if they are doing what you would expect.

Looking more broadly, how could the NHS become more resilient against this kind of failure? How can we make sure it never happens again and, if it does, that it is caught much more quickly to limit the damage?

Ultimately the answer is for any kind of waiting list to be regarded culturally as a sign of failure by the NHS, and to make involuntary waiting a thing of the past. But well before we reach that happy state there are more immediate and practical things we should do:

The first step is to simplify dramatically the reporting and targeting of waiting times. In common with most Trusts, Imperial’s scorecard in November 2011 (the last before their reporting break) tracked no fewer than eleven measures relating to the 18 week targets. Only one of those measures related to long-waiters still on the waiting list, and it was the second from last item. What were the other ten? Eight related to other waiting times targets set by the Department of Health, and the remaining two were Trust measures that simply tracked the numbers of patients being treated.

This proliferation is completely unnecessary. Get the waiting list right, and all the other measures take care of themselves. The Department of Health accepts the logic of scrapping the admitted and non-admitted targets, so let’s just do it. Then Imperial and everyone else can boil their 18 week reporting down to a single measure: the 92nd centile waiting time for incomplete pathways, so that Boards can see right away when things are going pear-shaped.

The second is to put an end to one-year waits. Patients don’t know where they stand with a 90 per cent guarantee (they are left wondering: am I one of the 10 per cent?). But if they know that nobody waits longer than a year then something is definitely wrong if they have. A one year limit works for hospitals too: if no patient ever waits longer than a year then systems are unlikely to slip for more than a few months (at the outside) before someone notices.

Thirdly, we can improve the tracking and management of the most important patients on the waiting list: no, not the imminent 18-week breaches, I mean patients with a high clinical urgency. There is a data field in each PAS system for recording the urgency of every patient on the waiting list: two week wait, urgent, or routine;  but in many hospitals this field is poorly used. Using it consistently would strengthen waiting list management and reduce the risk of urgent patients being delayed.

Finally, and in the longer-term, we can increase resilience by strengthening patients’ expectations and involvement during their waits. To their credit, the Government have made a start on this with the Operating Framework requirement to publicise to patients the 18 week guarantee. But these generalities are not specific enough: even BT do better, with regular personalised text updates on the escalation and fixing of the fault on your line. If patients were kept closely in touch with progress on their appointments, then they would be better placed to catch the ball if it dropped. The usual system of fire-and-forget referrals, “you’ll get a letter” hand-offs, centralised complaints procedures, and all the rest is too distant and siloed and we can surely involve patients in a more predictable and personal service.

How pressing is all this? Around England, and particularly in London, there are plenty of hospitals reporting dozens (even hundreds) of patients still waiting more than a year after referral. How sure can we be that nothing similar is happening at any of them, or that none of those patients are waiting even longer than the 2-3 years found at Imperial?

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 rob.findlay@nhsgooroo.co.uk

Getting ready

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

Last month I highlighted the case of a Trust’s Orthopaedic patients, whose waiting time clocks seemed to be mysteriously stuck just below 18 weeks. It was not clear how this was happening, and now we are completely in the dark because they have stopped submitting data.

Then last week, while analysing the December release of 18-weeks data, I spotted a similar pattern at a different Trust. Here are the 2011 waiting list snapshots (i.e. the incomplete pathways data) for Orthopaedics at Salisbury NHS Foundation Trust.

Again, there is a peak in the number of patients waiting just below 18 weeks. Again, this peak does not move forward in time as each successive month goes by; you might expect the peak to move forward by one month, every month. And where do the patients in the peak come from? If these were patients just feeding through the list and then being treated in the usual way, you would see a plateau (where patients were not being treated) followed by a cliff (where they were), not a peak sticking up suddenly in the middle of the waiting list.

So it looks, on the face of it, as if patients in the peak are having their waiting times frozen somehow. According to the RTT waiting times rules, clock pauses are allowed under certain circumstances when measuring adjusted admitted pathways, but there is no provision for pauses in either the non-admitted or incomplete pathways data. So it is difficult to understand how a static peak, in the incomplete pathways data shown above, is possible under the rules.

Whatever Salisbury were doing in Orthopaedics in 2011, it was successful in narrowly achieving the headline target that 90 per cent of adjusted admitted patients should be within 18 weeks. When I say narrowly, I mean that in each of those 12 months their performance stayed in the range 17.962 weeks to 17.999 weeks (and was within two patients of failure on 7 of those months).

It is impossible to tell exactly what is going on, just by looking at these figures. If there is an innocent explanation then I would like to hear it. But if there isn’t, then I would hesitate to lay all the blame at the Trust’s door, because the target that is being so narrowly achieved is perverse. The system of harsh penalties and “performance management” surrounding it has the effect of coercing Trusts into doing bad things.

So if any changes in counting methods do turn out to be needed in Salisbury, it would be good to see commissioners and performance managers exercising restraint to allow the Trust to deal with any backlogs openly. Above all, it should not be forced into taking a ‘reporting break’. There are too many of those going on at the moment already.

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:

1. carry on treating routine patients in turn even if they all wait over 18 weeks;
2. 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
3. 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

A clued-up 18-weeks manager put me on the spot recently. We manage patient bookings according to their position on the whole 18 week pathway, she said. How do you model that?

My first answer was the usual one: it’s best to model each stage of the pathway separately. That way you get systematic management and planning at each step, and the outpatient booking department isn’t tempted to pass on its waiting time problems for the inpatient department to solve later.

Ah, she said, but we’re a small Trust, and we just have one booking office for all stages of the pathway. What you say is fair enough if all patients follow the same pathway; but what if some have a diagnostic stage and some don’t? Then modelling each stage separately won’t work because, at the inpatient stage, the post-diagnostic patients are much closer to 18 weeks than the others.

Well, that was a tougher question, and I didn’t have an answer to hand. Multi-stage, multi-strand pathways would be tough to model properly (taking into account clinical priorities, cancellations, booking rules, etc) and I’m not aware of anyone having done it. But it’s a good question and it deserves an answer, and after thinking about it I think the answer is this.

Booking

The scenario we are talking about is:

Let’s start with the practicalities of managing patient bookings on this pathway. The outpatient stage is a genuine single-stage booking process, and is directly suitable for good booking techniques that achieve 100 per cent slot utilisation, shorter waits, protected clinical priorities, and minimised disruption.

Then at the diagnostic stage, patients can be added to the waiting list with their original referral date, and flagged if they suffered cancellation in outpatients. This ensures that those who have already waited longest are booked first, and that previously-cancelled patients receive preferential treatment (and have capacity set aside for them). Apart from that, the diagnostic stage can also be managed as a straightforward single-stage booking process.

The inpatient stage is more complex, because the major pathway split at the diagnostic stage means there are two quite distinct classes of routine patient, with quite different waiting time histories. Nevertheless, if the inpatient stage is managed using a partial booking system and patients are added to the waiting list with their original referral dates, then I think it can also be managed as a straightforward single-stage process.

Under a partial booking system, appointments are only issued a certain number of weeks ahead, so those patients who bypassed the diagnostic stage will wait a few weeks before being given their appointments, whereas patients who had a diagnostic will be given appointments soon after being added to the inpatient list. This restores evenness to the two halves of the pathway, and allows the 18 week target to be achieved across both parts of the pathway, with the largest possible total waiting list.

Planning

What about planning? When it comes to planning future activity to achieve the 18 week operating standard, the outpatient stage can be modelled as a single stage, as above. After that point, if you do want to model the split pathway, I think it makes sense to split it (for planning purposes only) all the way to the end, so that it looks like this:

So, for example, your planning might involve working out the activity, capacity and cost required to achieve 90 per cent treated within:

• 6 weeks, for outpatients
• 6 weeks, for diagnostics
• 6 weeks, for post-diagnostic inpatients
• 12 weeks, for non-diagnostic inpatients

That way, you are planning to achieve the overall 18-week target, but still taking advantage of the longer waits available on the non-diagnostic inpatient path.

Incidentally, whilst it is fine to split the pathway like this for planning purposes, it is usually better to avoid splitting an operational booking system. The differences in waiting times between one consultant and another are bad enough, without adding any further splits.