Director of Gooroo Ltd (gooroo.co.uk), and a specialist in demand and capacity planning, and waiting time dynamics, both across the UK and internationally. HSJ columnist. Previously at an NHS Trust, the Department of Health, HM Treasury, and science research.
24 comments By Robert Findlay
Thanks Anonymous 2:51pm - I agree that involuntary waits should be a lot shorter than they are. But the 12-week Scottish target you quote is just for the inpatient/daycase stage of treatment; both Scotland and England set 18 weeks as the standard for referral-to-treatment waiting times.
A few more suggestions that have been put to me since I posted this:
Some missing waiters around the nine-week mark could be Choose & Book patients, who were told by C&B that no appointments were available and therefore raised an ASI (Appointment Slot Issue). Those patients might then be managed on paper by the hospital until their slot is arranged, which might take several weeks, during which they might not be reported as incomplete pathways. (Incidentally, this is a wasteful and risky administrative process, and the patient usually ends up in a similarly-dated slot to the one they would have had if C&B polling ranges had simply been extended.)
Some missing patients close to the 18-week mark at Trust level (though not at national level) are tertiary referrals. These arrive at the tertiary centre with time already on the clock (although there is now the option for the referring provider to take the 'hit' on any breaches caused by delays at their end: http://transparency.dh.gov.uk/files/2012/06/RTT-Reporting-patients-who-transfer-between-NHS-Trusts.pdf).
Ian and Harry - I agree with your general sentiments. This post was of course written in the specific context of the NAO report, which I see as an occasion and an opportunity for helpful change. My thoughts on waiting times targets more generally, and how waiting times should and could be achieved without a target-driven process, are outlined here: https://blog.nhsgooroo.co.uk/2013/09/what-next-for-18-weeks-policy/
Thank you for your thoughtful response, John, and I broadly agree with the points you make. I just wanted to pick up one point here so that it isn't left hanging.
As you mention, I am of course not suggesting a strict "first come, first served" approach. The principles I advocate for good waiting list management are "safe, fair, short, and efficient" (in pretty much that order).
It was beyond the scope of my article to discuss the safe management of urgent patients, or the reasons (other than patient choice) why "routine" patients should sometimes be admitted out of turn. if anyone is interested then I've discussed that elsewhere and here are a couple of links:
Adding back in the Trusts who are missing in recent months (but not adjusting for any missing Trusts a year ago - I don't have that data handy), the gap between this year and last year grew from 277,128 in September to 439,963 in February, and then shrank back to 390,813 in March. So yes, the gap does close a bit but from a much worse February position than the chart suggests.
You mean like this?
Or the last few paragraphs of these?
I am afraid I disagree about relaxing 18 weeks to 26 weeks RTT as well. The main reason the English NHS is struggling with 18 weeks at the moment is that the waiting list has been growing and is now too big. If the 18 week targets were all relaxed to 26 weeks, the list would carry on growing, and eventually there would be calls to relax 26 weeks too.
What I would suggest is the abolition of the admitted and non-admitted targets, because they perversely restrict Trusts from treating long-waiting patients and are unfair to patients. (The data should carry on being collected though.)
I would retain the incomplete pathways 18 week RTT target and the 'zero tolerance' one-year-waits target, although the incomplete pathways target could be relaxed from 92% to say 85% to allow more leeway for patient choice.
In the long run though, the main thing is to reduce the length of the queue, but I don't think a target based approach would work for that. However an expectation that CCGs will commission to ensure that local waiting lists will shrink rather than grow would help, although this would involve more money which leads on to another, more difficult discussion...
One of the great things about online publishing is that people can tell you very quickly when you make a mistake...
In the RJAH analysis I should have said that the first section (including the chart) is looking specifically at orthopaedics, and the next section about cohort tracking covers their all-specialties data.
My apologies for the muddle.
Hi Ginette - it's difficult to compare because other nations measure things differently, though the Nuffield Trust had a good try... from p.19 here: http://www.nuffieldtrust.org.uk/sites/files/nuffield/publication/140411_four_countries_health_systems_summary_report.pdf
My analysis of the Scottish position is here: https://www.hsj.co.uk/comment/the-explosion-in-scottish-waiting-times-is-a-political-timebomb/5082922.article#.VSe7yxd97lM
Thanks Anon 11:54am... could you email me at email@example.com with details and I'll look into it? It may not be possible/easy with the data available, but I'll see what I can do.
But money does grow on trees - how else could the money supply keep growing year after year?
The Bank of England explains it very well here: goo.gl/yqGX7U
Unfortunately the only people allowed to have sizeable "money trees" are currently the privately-sector high street banks, who create the nation's money when they make loans. The Government cannot currently create money because of longstanding fears about runaway inflation, but as Adair Turner argues in his recent book (www.amazon.co.uk/dp/0691169640) it should be safe to shift some of the "money trees" out of the private sector and into the public sector under independent regulation (especially at times like this, when inflation - far from being too high - is worryingly low, and when privately-created money tends to pour into house price bubbles instead of the productive economy).
So there is an element of choice in austerity, and the pot of money is not fixed. It would be nice if there were some kind of national debate about it all.
There are also some very accessible explanations at the Positive Money website positivemoney.org
It's still a concern, Andrew. The reason is that, although the target is breached at national level, a majority of local clinical services remain near target. (See the last chart here: https://www.hsj.co.uk/topics/quality-and-performance/march-sees-worst-ever-breach-of-englands-18-weeks-target/7004746.article?blocktitle=Comment&contentID=20364)
So the pressure to admit approaching long-waiters remains. In fact both prioritising approaching long-waiters, and remaining close to target, are features of the PTL approach to waiting list management that is currently dominant in the NHS.
A major role for CCGs is to commission enough hospital activity to keep up with demand and (where necessary) to clear excessive backlogs. But CCGs cannot measure either demand or backlogs, for the simple reason that they don't have regular access to the necessary data on waiting lists and waiting list movements. If follows that they cannot effectively commission hospital activity, and instead have to rely on providers to tell them what to do.
Until CCGs have the basic information they need to do their jobs, it is somewhat difficult to see how the landscape could be anything other than provider dominated.
Anon 7:46 - yes that is a good point. Unfortunately the RTT statistics don't distinguish between inpatients and daycases, and the bed statistics are quarterly, so an August bed effect is hard to tease explicitly out of the data.
On the other hand, you may agree that the long-waiters who are often the most difficult to admit are inpatients, partly because they need a lot of theatre time, but also (especially from now until mid/late February) because of lack of beds.
Nevertheless your overall point that holidays can sensibly be planned-for is well made - sensible planning ahead is the main point I was trying to make too.
Andrew - you are right that if the list doesn't shrink significantly in autumn then that spells trouble (though I'd say August is too close to the seasonal peak to be a good marker). And yes, there are (small) signs of acceleration in the list growth which is worrying.
Anon 12:00 - this is a matter for interpretation, but personally I'd incline towards the cock-up/unintended consequences line. But I'm sure you are right that neglected conditions may cost more when they finally reach the front of the queue or are admitted as emergencies (though I haven't seen data on this, I'm afraid), and would add that waiting lists are costly to administer too. And of course longer waits are unquestionably a worse service for patients - I too remember the '80s and '90s and nobody wants to go back to those multi year waits.
Thanks Anon @ 2:10pm... yes you are right about the log chart. I chose a log chart because it shows how much things are increasingly proportionately, so anything that doubles goes up by the same distance on the chart. Also it allows all those lines to appear on a single chart, even though the magnitudes are very different - otherwise the 52wk+ line would be completely lost at the bottom.
You can download the raw numbers in the fact checker spreadsheet, which is downloadable near the top of the piece, just above the ad.
You make a fair point about RMCs etc, but unfortunately I don't think there is any real way of detecting them in these high-level published figures. Even with very detailed local data it would take a certain amount of picking through it all to isolate the effect of RMCs etc at different points along the pathway. Conversion rates along surgical pathways tend to be quite volatile at the best of times so I'm not sure they would be a good proxy - probably better to watch what is happening in the RMC directly, I would have thought?
I wonder where the 85% occupancy figure came from, or the idea that the other 15% of cots don't need staff?
A quick look on the internet produced this DH guidance
which says "Planned capacity should not exceed an average occupancy of 80%, as the increase in mortality becomes statistically significantly worse above this level (reference 60)."
However when you follow the reference you get this paper:
which says "Mortality rose linearly across the whole range of occupancy, suggesting that staffing became more inadequate as units became busier"
...which again points to two issues: a) are there enough cots? and b) are they adequately staffed?
On the number of cots, a statistical analysis could at least show the relationship between occupancy and the risk of running out of cots, based on the variation in non-elective demand at a particular unit. Perhaps such an analysis should be part of the commissioning process, so that commissioners could be clear about the level of risk they were accepting when commissioning a particular level of occupancy?
Anon 13:16: you are right as far as monitoring is concerned, but unfortunately it doesn't work as a target. The NHS tried it with the old admitted/non-admitted targets, but it ended up punishing trusts for treating their longest-waiting patients. So many trusts adopted a tactic called quota management - if the target is that 90% of patients should have waited less than 18 weeks at the time they are admitted, then achieving the target is easy: don't admit a long-waiter until you've admitted 9 short-waiters. The same problem would arise if the target became the average wait of those treated - you can achieve the target simply by not treating long-waiters.
Hi Anon 06:51 - I'm not sure where you think I'm making that argument, but if you could quote the relevant passage then I'll be happy to explain what I meant. In general I would comment that measuring every patient's waiting time is a good thing (and happens anyway), but there is no compulsion to turn it into an average.
Anon 15:59 - broadly yes. But what isn't quite so obvious is that the analogy still mostly works even when you have urgent patients and many queues of different lengths in the mix. The purpose of the 'index' is to show that those other factors are stable enough over time (at national level) that the size of the waiting list is the main driver. For an individual queue (e.g. one subspecialty in one hospital) different dynamics come to the fore and can overwhelm the list size effect.