Posts Tagged ‘acute’

Some of the differences between Scottish and English waiting times are pretty obvious. England has three 18-week referral-to-treatment targets and a 6-week diagnostic wait (pp.38 & 58), whereas Scotland has one 18-week referral-to-treatment target, a 6-week diagnostic wait, a 12 week inpatient/daycase Treatment Time Guarantee, and a non-legally-binding 12 week outpatient wait (p.5). Already we can see that it’s quite complicated in England, but even more complicated in Scotland.

If you dig into these targets you find the rules are different too. The differences are pretty big, and many patients who would have a right to short waiting times in England, enjoy no such guarantees in Scotland.

For instance, if you are referred to an English hospital then they have to accept the referral and treat you (unless they don’t provide that kind of care, or you agree to be treated elsewhere) (pp.7-8). But in Scotland the hospital can routinely send its patients just about anywhere it likes (p.16), even if the destination is way outside the boundaries of its Health Board; any patient who refuses can be taken off the waiting list or have their ‘clock’ reset to zero (p.17). In case you think that such long-distance transfers might be a rare event, Scottish Health Boards have regular arrangements to send increasingly large numbers of waiting list patients to the Golden Jubilee National Hospital west of Glasgow, even from as far away as Orkney (p.5).

You have to be ready at short notice in Scotland too, because the NHS considers seven days’ notice to be a “reasonable offer” (p.15), compared with three weeks in England (pp.34-35). (To protect urgent patients, hospitals can offer shorter-notice appointments in both nations, and patients are free to accept or reject them without penalty.)

And you should avoid changing your appointment in Scotland, even if you give them plenty of notice, because the hospital can use that as an opportunity to reset your clock to zero; if you change your appointment three times, they are normally expected to send you back to your GP (p.19). There are no such sanctions for changing appointments in England even if you give only short notice (p.28). In both nations, though, you can be taken off the list and sent back to your GP if you fail to attend your first outpatient appointment without giving notice (i.e. you ‘DNA’) (p.20, p.28).

If you are ever unavailable for treatment, either for medical or social reasons, then in Scotland your ‘clock’ is paused (p.22-25). This rule was very heavily applied (pp.10, 19) until a recent clampdown. In England the new main target (based on incomplete pathways: p.58) does not allow clock pausing at all, although clock pauses were certainly allowed and used against the previous main target.

Then there are patients who are completely excluded from the targets. For obvious reasons, both England and Scotland exclude obstetrics from their waiting time guarantees. If you are waiting for an organ transplant, then the wait for the organ itself is excluded in both nations. And if you want to become pregnant then assisted reproduction is covered in England, but not in Scotland. (p.13-4)

Both nations have short-wait guarantees for cancer outpatient appointments and initial treatment, but the English guarantee covers all cancers (pp.38-40) while in Scotland there are exclusions covering several cancer types (pp.15, 25-26). If you are having a course of cancer treatment then, in England, you are guaranteed your subsequent treatment within time limits, whether it’s surgery, chemotherapy or radiotherapy (pp.39-40); but there are no such guarantees in Scotland (p.5).

There are different exclusions in diagnostics as well. Scotland applies the 6-week guarantee only to eight key diagnostic tests (p.14), which means that English (but not Scottish) patients are guaranteed a 6-week wait for DEXA and various kinds of physiological measurement (p.8). However in both nations the diagnostic wait is part of the 18-week referral to treatment wait, so this may not make a massive difference in practice.

Why are the English rules apparently so much more patient-friendly and inclusive than the Scottish ones? I think the answer was right at the start: the nature of the waiting times targets.

In England, the overall targets have a tolerance, for instance that 92 per cent of patients on the waiting list must be within 18 weeks. That leaves an 8 per cent margin for the odd exceptions (and there will always be exceptions).

In Scotland, though, the legally-binding 12 week Treatment Time Guarantee is a 100 per cent target. There will still always be exceptions, so they must be allowed for in the rules; which means you need lots of rules.

Personally, I think the English approach is the better one. (And in case anyone north of the border is starting to suspect a national bias, I should say that I am Scottish and was born and brought up in Scotland.) Hard cases make bad law, and trying to define all the reasonable exceptions in the rules is inevitably going to be complex and imperfect. Better simply to allow a tolerance in the target and let the rules include everybody.

Let’s take a look at how week-by-week profiling can help acute providers with winter pressures. We want to maximise capacity utilisation, and minimise the risk of bed crises, cancellations, and 18-week breaches.

We’ll take it in two stages:

1) Preparing for winter: We will look at how emergency and urgent elective demand are likely to vary, week by week, through the winter; then plan routine elective work around the peaks.

2) During winter: As each winter week goes by, we’ll update this profile with outturn demand and activity, so that our plans for the rest of winter can adapt rapidly and continuously to unfolding events.

Preparing for winter

Nobody knows exactly how winter is going to turn out, so we need to make some reasonable assumptions about how much demand is likely to come in, and how it will vary week by week. A good place to start is by looking at what happened last year or, even better, the last three years, and then adjust it for anything else we know is going to happen.

Armed with this information, we’re ready to start working on our plan. Because we’re focusing on the profiles during winter, let’s assume we have already run our strategic plan for the coming months (based on achieving 18 weeks, or filling the available capacity, or whatever scenario we chose). So we have already worked out the overall demand, activity, and capacity for this future period, as well as the waiting list and waiting times we want to end up with. If our dataset already includes demand and activity profiles then we don’t need any more data and can go straight into the week-by-week profiling.

In this worked example the screenshots are taken from Gooroo Planner, where the Profiling screen looks like this:

The large top chart is the interactive activity profile, and we are going to edit this to reprofile elective surgery around the peaks and troughs in emergency and urgent demand. The large bottom chart is interchangeable by clicking for any of the thumbnails at the bottom, so it can show either activity and urgent/emergency demand, beds, theatres, clinics, or waiting times.

Let’s start by zooming in on the bed profile. We start this analysis using data that is based on last year’s demand profile and last year’s outturn activity profile. We’ve picked a major surgical service, and we’re going to see if we can reprofile it to stay out of trouble over winter.

The blue line shows the the number of beds used by our surgical service, plotted against the left axis, and the straight blue line shows the number of beds notionally allocated to this service. The orange line shows the total beds on our whole hospital site, plotted against the right axis, and again the straight orange line shows the physical on-site bed limit. Clearly, we are heading for trouble in January and February, where the number of beds required is far larger than the number available. Looking at the blue line, we can see that we are making things worse by scheduling so much elective surgery during the winter peak; the “red alerts” we experienced last winter are starting to look disturbingly avoidable.

So let’s start by reducing our plans for elective inpatients during the height of the peak. This is a simple matter of clicking and editing the points on the interactive top chart, to reduce the balance of work profiled during January and February until the editable profile looks like this:

After doing that, we get a bed profile that looks like this:

Much better. But what happens to waiting times as a result of this surgical slow-down? A peek at the waiting times chart reveals this:

The blue line shows waiting times just for the elective inpatient stage of treatment, and the orange line shows the RTT wait for this surgical service: that’s the wait for new outpatients, plus the wait for elective inpatients or daycases (whichever is greater). All waits are on a “90 per cent treated within” basis, so the orange line is comparable with the 18 week target. The bad news is that our waiting list is going to spike over winter, rendering the 18 week target unsustainable for 3 or 4 months.

We don’t want that to happen if we can avoid it. So let’s see if we can front-load some surgery to head off the problem. In real life we would have more than one surgical service to reprofile, but for the sake of this example we’ll try to do it all just with this one. So we’ll crack on with as much elective inpatient surgery as possible over the autumn, then slow down for as short a time as possible to keep beds just nicely full over the winter peak (but not too full – we are working to a target occupancy to allow for in-week fluctuations), and then pick things up again in March to deliver the balance of our planned activity towards the end of the year.

When we’ve finished editing the activity profile, it looks like this:

Now our bed profile looks like this:

That’s fine. Waiting times?

That’s fine too: we’ve front-loaded enough surgery to get the list right down before winter, so that even when it spikes we shouldn’t see any breaches. Then the balance of our planned activity is just right to bring us in on target for year end. (In a real hospital you would have several surgical services to play with, rather than just one, so this example is on the extreme side to illustrate the principle.)

That’s our profile done, then, from the comfort of late summer / early autumn. What are we going to do once the snow starts to fall?

Reacting to events during winter

Fast-forward to late January, and it’s cold. Emergency admissions shot up when the GP surgeries reopened after New Year; nothing unusual in that. But last week it shot up again and we had to cancel surgery. How does this affect our plan?

The first thing to consider is this: does this spike mean that the total amount of demand has gone up, or might this peak be balanced by troughs later on? Frankly, who knows? Overall the external demand for healthcare rises stepwise every few years, and if demand happens to have gone up just in the last week then that may mean something, or nothing. If you want to add an extra chunk of demand to your forecast then that is easily done but, if the end result is forecasts that are more volatile but no more accurate, then what is the benefit? Ultimately it’s your call, but a compromise position might be to update the demand forecast every month, not every week, to smooth the volatility out a bit.

On the basis of a week’s worth of data, then, let’s assume it’s a wobble in the profile not an uptick in total demand. We also have outturn data on the activity we delivered for electives, as well as emergencies. So let’s update both our demand profile and our activity profile with the latest week’s data and see where we stand now.

The loss of surgery means that we are now heading for a 21 week RTT wait at the peak in mid-March, whereas before we were expecting to peak at 18 weeks. Perhaps we should have allowed a bit more margin for error in our original plan. However if our assumption about demand (that this spike is likely to be offset by less demand at other times) is correct, then we should have capacity to bring in the displaced patients over the coming weeks to restore the position, as the revised bed profile shows.

And so it goes, week by week, month by month, until the days start to lengthen again. Forecasting demand is not an exact science, especially at a week-by-week level of detail, so our plans for winter are always going to have a large amount of guesswork mixed in with the logic.

In this worked example, January’s spike in demand caused problems with cancellations and the risk of waiting times breaches. That kind of thing is a risk unless we can provide a more substantial buffer in capacity (e.g. in the form of lower bed occupancy) to absorb the variation. Nevertheless, in this example we were in a much better position than we had been the year before, when we had been galloping merrily towards a severe, prolonged, and utterly predictable bed crisis before the winter had even begun.

This worked example was illustrated using Gooroo Planner with integrated week-by-week profiling; you can see a slideshow version of it here. If you are already using Gooroo Planner then profiling is available to you now: look for the profiling button at the top of the Reports view page. If you aren’t using Gooroo Planner already, and would like to take a look, then email info@nhsgooroo.co.uk for a free on-site demo.

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.

Here are some resources to help you analyse the RTT waiting times pressures in your local area.

You can look up any Trust or PCT, any specialty, and get a detailed analysis with peer comparisons and time trends here: nhsgooroo.co.uk/reports (free registration required).

If you are managing towards the new target (that 92 per cent of the waiting list must be within 18 weeks), then these maps show the scale of the pressures. You can click any organisation to get more detail in a balloon.

If you want raw data on the number of patients waiting, both in total and for long-waiters, with year-on-year comparisons, then the next two maps have all that. You can access them by Trust and by Commissioner. On these interactive maps, the pin colours show the number of one-year waiters.

Ever feel you can’t cope with your waiting list problems? Do you have complex and significant ‘system issues’ to address?

Then why not take a holiday?

That’s right, for a limited time only, you can take a ‘reporting break’ absolutely free! So don’t publicise those long-waiters, keep them to yourself for a while. Relax, you’re on holiday!

(Contact your local commissioner and the Department of Health for further details. Offer subject to status.)

Imperial are taking a holiday. We don’t know exactly why, but if an anonymous comment in the HSJ is to be believed then it is not an IT problem.

What we do know is that it is extraordinary. Yes, other Trusts have had difficulties counting their waiting lists. Yes, other Trusts have taken short, unplanned reporting breaks when their systems failed. But a planned reporting break, with permission in advance? Unprecedented.

Who stands to benefit? Imperial, certainly. But what about the other parties involved?

Imperial says the ‘reporting break’ has already been discussed with NHS North West London and NHS London. The HSJ quotes a relaxed-sounding Department of Health. Do they stand to benefit? If Imperial takes a break, do the long-waiters drop out of the commissioner-side figures too? Would the potential for a waiting times breach at NHS London, noted by the HSJ, be avoided?

To find out, let’s look at an unplanned reporting break that happened last year. The blue columns show Kingston Hospitals’ reported over-18-week waiters; you can see the unplanned reporting break where data is missing for April and May. The orange columns show the same figures for their local PCT, and the reporting break is clearly visible there too. So on this occasion, a provider reporting break did show up in the commissioner-side figures.

This evidence suggests that Imperial’s reporting break could flatter the commissioner-side figures as well as their own, to the benefit of their PCT Cluster, NHS London, and the Department of Health.

Could it make the difference between success and breach at SHA level? It certainly could. If we look at the adjusted admitted pathways statistics for November 2011, we can see that NHS London achieved 90.3 per cent of admissions within 18 weeks, which turns out to be only 151 admitted patients clear of the 90 per cent target. So if Imperial clears its backlog, then it could easily cause NHS London to breach.

This is yet another illustration of the damage caused by the current admitted-patients target, which has recently been extended for another year by the Department of Health. Under a saner target regime the Trust and its commissioners would be keen to clear genuine long-waiters by treating them. But under the current perverse regime of treatment-based penalties and performance management, they are afraid to do so openly. This, then, is a possible motive for the reporting break.

What should be done differently? Firstly, Imperial should change its mind about taking a reporting break; let’s have all the figures out in the open, even if they aren’t perfect. Secondly, let’s ditch the treatment-based target regime, which Ministers accept is perverse, and move over to the new “92 per cent of the waiting list within 18 weeks” target right away. Thirdly, let’s see the Department of Health standing up for transparency in public services, instead of giving the nod to this extraordinary suspension of reporting.

Update on 16 Feb 2012: Imperial has started its holiday early, with permission from NHS London. They did not submit any data for the December 2011 RTT waiting times statistics published today.

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.

Where are the longest waits? What are waiting times like in your local NHS? How difficult is the new waiting time target? Here are some maps to help you find the answers.

All the maps are interactive: you can zoom and scroll, click on the pins for details in a balloon, and click the title in the balloon for a full analysis.

The first pair of maps is intended for journalists and the public. It highlights the longest-waiters, and you can click on the pins for year-on-year comparisons of the total number waiting, 18 week waiters and 52 week waiters. All data is for all specialties combined (see below for specialty-level data).

Long-waiters:  by Trust (Provider basis) and by PCT (Commissioner basis)

The second pair of maps is designed more for NHS managers and clinicians. It looks at the challenge of achieving the new RTT waiting times target, and the pins show the waiting time achieved by 92 per cent of the waiting list (the new target for this measure is 18 weeks). Click on the pins to see estimates of how hard it will be to achieve the new target, both with and without improving patient scheduling. For more details about the methodology see our earlier blog post on the new target. All data is for all specialties combined, and the analysis therefore assumes that resources can be deployed flexibly between specialties.

Achieving the new target: by Trust (Provider basis) and by PCT (Commissioner basis)

To drill down to specialty level, or to jump straight to a particular Trust or PCT, you will find a full set of detailed reports at the Gooroo website.

Full analysis by Trust/PCT and by specialty: All 18 week reports at specialty level

Merry Christmas!

Wow. Just wow. The number of English patients waiting more than a year has halved in October, to 10,911 (down from 20,052 in September). Just one Trust (Sheffield) has more than 1,000 one-year waiters, down from five Trusts in September. All specialties reflect the change, and it’s huge.

Alright, probably most of this was due to validation and data cleaning. But that is still a worthwhile thing to do, because unless very-long-waiting patients are validated there is no way of telling who really needs treatment and who is a data error. This is comfortably the best performance ever recorded by the NHS on one-year RTT waits, and I look forward to further gains as the new waiting-list target beds in.

A full set of stats with time trends can be downloaded in our waiting times fact checker here: Gooroo NHS waiting times fact checker.xls

So what about the new target that 92 per cent of the waiting list (incomplete pathways) should be within 18 weeks? Here’s the trend, and it shows how long 92 per cent of waiting list patients were waiting each month, England-wide.

At the time of the General Election, May 2010, the NHS in England came within a whisker of achieving the new target. Then things deteriorated towards winter and, apart from a summer blip, have been pretty much improving ever since then. We are in a much better position now than we were a year ago.

This overall picture is replicated at specialty level too. The specialty chart is pretty congested (there are 20 specialties on it), but you can see that all specialties are broadly moving as a pack. Even neurosurgery, which was breaking away as a problem area, is coming back down again now.

The Operating Framework insists that the new target is met in every Trust and every specialty, and the next chart shows what proportion of Trust-specialties are achieving it already. (This analysis includes all 2,251 Trust-specialties where at least 100 patients were on the waiting list.)

The above chart replicates the overall picture on over-18-week waiters: record-breaking performance at the time of the General Election, a decline over winter, and then an improvement which is being sustained. But it still shows that one-third of provider specialties are not achieving the target, so much of the NHS has work to do to get through winter and achieve the target next year.

Who has the longest waiters? Here’s the top twenty, ranked by the 92nd centile waiting time (and showing the number of one-year waiters too).

The total number of patients waiting continues to follow the seasonal trend of recent years:

This is interesting in itself. How can the NHS be maintaining its waiting list so precisely? Somehow the system must be responding in minute ways to preserve the status quo. Surely, if we can keep the waiting list static, we could steadily reduce it too? One day, perhaps, we will cease to be satisfied with maintaining a waiting list and just get rid of it. It’s always nice to have a dream.

How hard are we all working? Here’s the activity trend for admitted patients:

Again, an exact mirror of recent years. No sign of an austerity crunch, and no increase in productivity either.

The overall verdict? Steady as she goes, really. The trends suggest that we are heading for a repeat of last year. That means winter waiting list pressures when everybody downs elective tools for Christmas and New Year, followed by a recovery in the Spring.

Today [17th November 2011] in the HSJ, Anthony McKeever and I make the case for an upper limit on waiting times in England: a guaranteed one-year maximum waiting time from referral to treatment, that no patient should ever be made to breach.

But is it possible? At first glance it looks easy. The NHS in England treats and discharges over a million patients from the waiting list every month. There are fewer than 20,000 patients waiting more than a year. So that’s equivalent to less than 3 hours’ work. Even if we assume that all 20,000 need to be admitted (and could not be treated in or discharged from outpatients), it’s still less than 12 hours’ worth of admissions.

So all we have to do is take some of the routine patients who we currently treat much sooner, make them wait a couple of days longer, and spend those two days clearing the over-one-year waiters. Easy. Let’s start tomorrow.

If only life were so simple. There are clinical priorities to take into account – and the over-one-year waiters are not spread evenly across the NHS. Around 40 per cent of Trusts have none at all, so they would be twiddling their thumbs during the two “clearance days”. Six Trusts (we are using the August 2011 figures for England throughout this post) have over 1,000 over-one-year waiters, which would keep them busy for longer than two days. This interactive map shows where all the over-one-year waiters are:

Long-waiters are clustered by specialty, as well as by Trust. This is an even bigger barrier than geography, because gynaecologists cannot just scrub up and do a couple of orthopaedic lists. Although patients can easily be offered the choice of quicker treatment at another hospital, they cannot be offered treatment by another specialty.

This clustering by specialty and Trust means that, if we want to understand how we could achieve a one-year maximum wait, we need to go right down to Trust and specialty level. (A local analysis would go further, to consultant level, but for now we are restricted by the published RTT data which only goes down to specialty.)

Treating the one-year-waiters

At Trust and specialty level, if we divide the number of over-one-year waiters by the rate that patients are admitted, we can calculate the number of working days it would take to clear the one-year waiters: the so-called “clearance time”. (We are erring on the side of caution by assuming that all these patients need to be admitted; in practice many will prove on validation to be miscoded, or can be treated and discharged from outpatients.)

There are 169 Trusts in the data we are looking at, with an average of nearly 8 waiting list specialties in each Trust: 1,331 Trust-specialty combinations in all. So here is the distribution of clearance times for all 1,331 Trust-specialties in England:

The over-one-year waiters are highly concentrated: only 87 Trust-specialties have clearance times over a week (5 working days), 49 over 2 weeks, and just 21 over 4 weeks.

Those Trusts will have neighbours who could take on some of the work. Most patients who have already exercised Choice (and met their consultant, waited for ages, and are now expecting to be treated soon), might not choose to switch provider. But capacity can equally be freed-up by extending opportunities for newly-referred patients, so they can choose an alternative provider where patients are not kept waiting for a year. This could be done through the existing Choice mechanism, and this could be facilitated using national-level expertise to ensure that Choice is extended in a targeted manner around each highly-pressured service.

On the basis of these numbers, then, there are just a few dozen Trust-specialty hotspots that need really close attention; not an insuperable task on a national scale. This is looking promising.

Improving patient scheduling

But there are problems with trying to clear one-year-waiters simply by treating them. Back in the 1990s, “waiting list initiatives” were commonly used all over the country in an effort to “chop the tail off” the waiting list. Unfortunately, the tail tended to grow back again, usually within a few months. Behind the 12-month waiters stands a cohort of 11-month waiters, and behind them stands an even larger cohort of 10-month waiters, and every month they all shuffle forward. So what can we do?

We know that waiting times can be reduced with better patient scheduling. Our daily experience of queues tells us that if some people queue-jump then other people wait longer. In our daily lives, fair queues are first-come-first-served. In healthcare things are more complicated because we have patients with cancer and other urgent conditions, and they quite rightly need to jump the queue on routine patients. So the four principles of good NHS waiting list management are:

1. Higher clinical urgency means shorter wait.

2. Similar clinical urgency means treat (broadly) in order of arrival.

3. Keep the longest waits down to a reasonable level.

4. Do all this without impairing the efficient use of capacity.

When Trusts have waiting time pressures on the scale we are discussing here, they may feel that the standard NHS contract inhibits their scope for treating long-wait patients. The contract allows commissioners to apply financial penalties to Trusts if they admit a high proportion of over-18-week waiters, which can limit Trusts’ ability to tackle long-wait backlogs. The corresponding waiting time measures that are monitored and promoted nationally could have a similar effect.

It would be helpful if it could be agreed that these penalties and measures should not be applied to those Trusts and specialties with the longest waiting times, in return for allowing them to tackle their backlogs wholeheartedly and achieve sustainable one year maximum waiting times. In the next bit of analysis we shall assume that an ‘amnesty’ is put in place for a while.

We are going to estimate the maximum waiting times that each Trust-specialty could achieve, if it managed its waiting lists according to the four principles above. There are, of course, quite a lot of assumptions behind these calculations, and you’ll find them in the footnote*. Here is the distribution:

According to these estimates, all but 34 Trust-specialties should be able to achieve maximum waits below one year by applying the disciplines that underpin best practice. This is a smarter solution than brute-force waiting list initiatives, because better patient scheduling improves maximum waiting times in a sustainable way. The “tail” doesn’t “grow back”.

Improving scheduling is not a trivial task, but there is scope for sharing experience and expertise to help Trusts work through the issues and processes involved., Many Trusts have found it challenging to implement Choose and Book in ways that are consistent with the principles of good waiting list management. But that’s not to say it can’t be done – there is just a need to reinforce success and to spread learning. Internal mechanisms like the IST and IMAS have a good track record in supporting places that struggle.

But no amount of good waiting list management can stop waiting times from going up if the backlog is growing relentlessly. So services with severe waiting time pressures need to agree future plans with their commissioners that ensure the waiting list will shrink rather than grow. Pressures vary from place to place, of course, but nationally the waiting list is not currently rising year-on-year so we are not in the position of fighting a relentlessly incoming tide.

If those ingredients can be put in place then one-year maximum waiting times are starting to look very achievable.

Better scheduling plus backlog clearance

Ideally we want to combine both approaches: better scheduling, and one-year backlog clearance. The next chart makes a start at putting these two approaches together.

Each “bubble” represents a single specialty at a single Trust. The size of the bubble shows the number of over-one-year waiters. Its position on the horizontal axis shows the sustainable maximum waiting time (without any backlog clearance). Its position on the vertical axis shows the clearance time for admitting all the over-one-year waiters (without improving scheduling). Different specialties are plotted in different colours, with surgical specialties as discs and medical specialties as circles.

The first thing to notice is that most Trust-specialties with over-one-year waits could at least halve their maximum waiting times, if they improved their patient scheduling practices in line with the principles of good NHS waiting list management; most of the bubbles on the chart are to the left of the 26-week line.

Looking at the services with the greatest pressures, we can see that many of our biggest challenges in terms of backlog clearance (towards the top of the chart) could probably achieve a one-year maximum wait with better scheduling alone (the centre of their bubbles lie to the left of the 52-week line). Conversely, many services with high achievable waiting times (to the right of the chart) have relatively short clearance times (they are close to the bottom). This is excellent news, as it suggests there are relatively few services that could not be brought within a year with a combination of methods.

In fact there are only 11 Trust-specialties with one-year clearance times over 10 days and sustainable maximum waiting times over 1 year. The table below shows these 11 services. For each one, we have calculated the effect of applying both better scheduling and backlog clearance together: we worked out the size of waiting list needed to sustain a one-year maximum wait, and then worked out the clearance time needed to achieve that list size, on the (cautious) assumption that all patients need to be admitted. (In some cases, the reduction in list size is larger than just clearing the over-one-year waiters.) Here are the results:

Specialty	Trust	Clearance time to one-year sustainable max wait (working days)
Gastroenterology	Wirral University Teaching Hospital NHS Foundation Trust	890
Gastroenterology	Croydon Health Services NHS Trust	220
Gastroenterology	Royal United Hospital Bath NHS Trust	162
Gastroenterology	East Sussex Healthcare NHS Trust	143
Other specialties	Wirral University Teaching Hospital NHS Foundation Trust	112
Neurosurgery	The Newcastle Upon Tyne Hospitals NHS Foundation Trust	71
Other specialties	St George’s Healthcare NHS Trust	55
Neurosurgery	St George’s Healthcare NHS Trust	44
Urology	United Lincolnshire Hospitals NHS Trust	27
Gastroenterology	St George’s Healthcare NHS Trust	21
Gastroenterology	Guy’s and St Thomas’ NHS Foundation Trust	12

Surprisingly, no orthopaedic services make it onto the list. Of the 11 Trust-specialties that do, a majority (6) are in gastroenterology (a high-urgency specialty with many planned patients, some of whom might be miscoded), 2 in neurosurgery (which is only provided in a few Trusts), 2 in “other specialties” (the nature of which will vary from Trust to Trust), and the remaining one is urology. All of these would need to be looked at closely and locally to validate the list, establish the true level of clinical urgency and other service issues, and develop plans to ensure that the waiting list will shrink rather than grow in the future.

Looking at the table above, you are probably curious about the extraordinary result at the top of the table for Gastroenterology at the Wirral. Here is the detailed analysis (and similar reports are available for all Trusts and specialties at www.nhsgooroo.co.uk/reports). This is a striking example of a service achieving the NHS Constitution target that 90 per cent should be admitted within 18 weeks, even though as many as one in ten waiting list patients are breaching 40 weeks.

Conclusion

The big question is: could the NHS achieve a one-year maximum RTT waiting time? Our analysis points to a resounding “yes”. Would it cost a lot? No, perhaps no more than the administrative costs of a national initiative.

The reason, in a nutshell, is that very few Trusts and specialties have severe one-year waiting time pressures, and there is scope for using Choice in targeted ways to divert patients to other Trusts that have the capacity to meet both their clinical needs and their reasonable expectations in terms of waiting times. There is also considerable scope, if certain existing contractual and managerial measures can be waived, to make waiting times fairer and shorter by improving patient scheduling.

The Infrastructure required to support a national drive on one-year waiting times is, we believe, already in place at national level and could be focused temporarily on the task for the six months or so it would take to complete. We expect that DH and the NHS Commissioning Board could support health economies in a number of ways:

> by asking Commissioners to pinpoint Trust-specialties that have the greatest pressures and to agree recovery plans for dealing with them.

> by rewarding GPs that take positive action to eliminate excessive patient waits as part of the authorisation process for their Clinical Commissioning Groups;

> by exploring ways of developing a “clearing house” to match backlogs with available capacity elsewhere;

> by providing operational expertise to help Trusts optimise their patient scheduling (including through Choose and Book);

> by ensuring that other aspects of contract and performance management do not inadvertently impede progress; and

> by insisting that high-pressure services are planned so that waiting times will continue to remain below one year.

In today’s HSJ article we explained why a maximum one-year wait is worth achieving. Here we have shown that, with a deliberate effort, it can be achieved. And we hope that, before very long, it will.

 

* Some of these assumptions are fairly broad-brush because the published data is limited; a better analysis would use locally-available data and separate the pathway into stages. The assumptions are:

> We estimated the rate that patients are added to the waiting list in two ways: firstly, by reconciling activity and changes in list size; and secondly from the number of patients in the short-waiting cohorts (allowing for common data errors with very-short waiters).

> The proportion of urgent patients was measured from admissions within 62 days, capped at the median for each specialty.

> Using the results of detailed patient-by-patient simulation research, we calculated the waiting time that 99 per cent of admissions would achieve with good waiting list management. We have used this as our estimate of the maximum waiting time, on the grounds that operational managers have more options to book patients flexibly than our simulator.

> We have necessarily assumed that each Trust-specialty is able to pool enough work between consultants to even out the subspecialty pressures between them.

This post first appeared at HSJ blogs

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:

1. treat patients with higher clinical priority first
2. treat patients with similar clinical priority in turn
3. treat the least-urgent patients within a reasonable time
4. 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.

Conclusion

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?