Archive for February, 2011
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.
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.
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.
In elective services, the worst sin of all is under-utilising the valuable resources you have available. It costs you financially (both as lost income and incurred expenditure), and it pushes up the waiting list and waiting times. So hospitals generally try to avoid this sin, and fill capacity up as much as possible.
However, you find that unpleasant things start happening as you push utilisation up towards the magic 100 per cent mark. Suddenly you are faced with lots of questions, such as:
- When all your appointment slots are full, how do you book urgent patients at short notice? How many slots should you hold back for them?
- Should those urgent slots ever be used for non-urgent patients?
- What should you do if an urgent referral comes in, but still no slots are available?
- When patients are cancelled by the hospital, should they get preferential treatment when you rebook them?
- Are the answers to these questions different, depending on whether you run a fully- or partially-booked appointments system?
The good news is that there are answers to all these questions, which means that you can utilise your elective capacity at 100 per cent. In fact 100 per cent utilisation is so desirable, that we took it as a basic assumption when beginning our research into the best tactics for booking elective patients.
So what are the answers to the questions above?
- Yes, you should reserve some appointment slots for urgent patients. It’s worth getting this right, because the worst performance comes from having too many. You can calculate the right number using our Booking Rules Calculator, which is available free of charge just after you login to Gooroo.
- In a fully-booked service, it is better to rebook cancelled routine patients into urgent slots when necessary. But in a partially-booked service this is not necessary. (Newly-added routine patients, however, should just get the next empty routine slot.)
- If an urgent patient needs to be booked at short notice, but there are no slots available, then you should cancel the routine patient who will be least inconvenienced.
- These cancelled routine patients should get preference over new routine patients when you’re dishing out the next available slots. In a fully-booked service they can access urgent slots too.
- As we have seen, the best tactics are slightly different for partially booked services. The best number of reserved urgent slots is also different.
Our research (which studied over a million years of simulated bookings) threw up some other results too.
Firstly, it is good to be as precise as possible about how long each urgent patient can safely wait, and book them right up to their clinically safe limit. This finding was expected from the work we conducted on waiting lists in the 1990s, but it was good to have it confirmed in simulation.
Secondly, fully-booked services perform almost as well as partially-booked services, if (and it’s a big if) the level of disruption is the same. Of course the whole point of running a partially booked service is to reduce the number of cancellations caused by staff taking annual leave, so there should be less disruption under partial booking (and so even better performance compared with a fully-booked one). (Set against that, you have greater certainty to patients in a fully-booked service, so take your choice…)
Thirdly, it doesn’t make very much difference whether you can arrange for any potential long-wait patients to accept a rebooking, if slots remain empty at short notice. This counter-intuitive result holds both for waiting times on their own, and for a basket of measures that takes disruption into account. Why? Simply because in a well-managed service there should be very few opportunities to rebook patients into short-notice slots; the slots are generally full.
Fourthly, there is good news on offering a choice of bookings to patients. You can offer slots in up to three different weeks without significant impact on waiting times or other aspects of performance. It might even reduce your DNA and rebooking rates.
Finally, we looked at another booking technique that is used in some hospitals: rippling. What is rippling? Imagine you have an urgent patient to book, but no empty slots that are soon enough. So you cancel the least-inconvenienced routine patient. Now what do you do with this cancelled patient? You could rebook them into the next available slot, which might be a long time in the future. Or you could cancel another routine patient in a couple of weeks time to make space, then cancel another a couple of weeks after that, and so on until you reach the next empty slot. So lots of patients are delayed a little, instead of one patient being delayed a lot.
Now that you’ve got your head around all that, you can forget it. Rippling isn’t a good idea. The disruption caused to patients by all those rebookings will always outweigh the benefits of shorter individual delays. “But what about my waiting time targets?”, you ask? Well, that is what the allowance is for, that lets 5 or 10 per cent of patients wait longer than the time limit.
You can find full details of this research in our Research White Paper 4, available after login here. And you can get practical experience using our simulator training program: SimTrainer (the first four levels are free of charge).
No wonder GPs up and down the country are looking at commissioning with unease, if not dread. The current system wouldn’t suit them at all. But commissioning doesn’t need to be this way, and the door is standing open for a much more human and collaborative approach that plays to GPs’ skills as doctors.
So what’s wrong with the current system? In short, the adversarial contract-driven approach doesn’t work.
Every year the PCT and the local hospital sit down with a copy of the standard (and compulsory) NHS contract, and negotiate the activity and the Key Performance Indicators (KPIs). The contract is only signed after they have reached agreement on all the terms (or after the SHA arbitrator has imposed agreement on the warring parties). After the financial year begins, the PCT holds the hospital to account for any failures against the KPIs by applying the contractual sanctions. If the hospital is doing more activity than specified in the contract (called “overperforming”), complex terms are applied to work out how the excess should be paid for.
What effect does all this have on the delivery of healthcare?
When it comes to quality, all eyes are focused on the KPIs (and only the KPIs). Remember that these have to be agreed in advance by both parties, and the hospital has no interest in creating a rod for its own back. So, even though the KPIs make a very long list, they are only a tiny subset of everything that means “quality” in healthcare. Even when something is specified, the standard is pitched at acceptable rather than aspirational. The usual response to these shortcomings is to define more KPIs, to make them tougher, and to raise the sanctions. But that doesn’t fix the essential problem.
Activity is a problem too. Neither the PCT nor the hospital can predict the demand for healthcare accurately, so the activity specified in the contract always misses the mark. The complex clauses that deal with “overperformance” serve to weaken the link between activity and money. PCTs can berate hospitals for overperforming or having excessive waiting times, and hospitals can berate PCTs for failing to manage demand, but what can either party actually do about it? And even when they can do something, do they want to? Hospitals make good money from uncontrolled demand, and can even generate income by referring work to themselves and other hospitals without prior approval.
And that’s just the incumbent providers. Tendering for new providers is long and complicated, with lots of pitfalls that can scupper the entire process. When a commissioner eventually makes it to the end of the process, the moment has probably passed anyway, and even if it hasn’t you are still in the unhelpful world of adversarial contract-management.
How could things be better?
GPs are small-business owners, and the world of the small business is quite different from this. Firstly, you pay for everything you order, and you don’t pay for anything you don’t order; so everybody knows where they stand when it comes to money.
Secondly, if a supplier does anything to displease you with regard to quality, anything at all, you have a grown-up discussion after which the supplier either puts things right or risks losing future business; the relationship works best when it is co-operative not adversarial, and quality is driven up relentlessly by customer expectations.
Thirdly, you can switch suppliers any time you like, although it takes effort to do this; so suppliers are keen to retain your business, and you are reasonably keen to avoid having to switch.
Healthcare can be like this too, and the Any Willing Provider (AWP) model provides most of the framework. The biggest thing missing from the official process is some way for GPs unilaterally to stop paying for anything they don’t refer, and it would be helpful if the Department of Health could put this right.
Even if this isn’t fixed officially, once GPs are established with co-operative relationships in a competitive (or potentially competitive) environment, then local providers should quickly learn that their interests lie in going along with GPs’ aspirations; because if they don’t, then it won’t be long before their local GPs are looking for alternatives right across their service range. They won’t be slow to do so either; not just because they know their patients and want the best for them, but also because they are scientifically trained and more than capable of generating and analysing relevant information about the service they are receiving.
Ah, defenders of the status quo say, but this is just a race to the bottom: AWP providers will only have to pass the minimum CQC standards, drive down their prices, and all the GPs will start herding patients their way.
This view is mistaken.
From the provider side, we have already seen how it is the existing contractual process that drives down standards. And from the GP side, the argument is frankly insulting: it accuses GPs of being completely uninterested in quality.
What GPs are actually interested in, just like customers in any market, is value: quality and cost considered together. So GPs will happily pay for a significantly better service, even if it costs a little more, just as consumers in the high street are willing to pay extra for better food and more advanced personal stereos. (In fact the history of machines for playing music shows how the result can be vastly higher quality and vastly lower cost.)
GPs needn’t fear commissioning; they just need to find a way of doing it in a way that suits them. It will come naturally, once they realise it’s possible. The people who may struggle are the ex-PCT staff who are hoping to support the commissioning consortia; will they be able to switch mindset to the GPs’ way of thinking, or will the contract-driven habits prove too deep to unlearn?
Why is forward planning such a slog in the NHS? Fundamentally, all we are doing is this:
- Take what happened last year
- Add a bit
- Adjust for any specific pathway and demand management changes
- Apply some agreed performance assumptions using well-known equations
- Output the results as activity, capacity and money.
- Profile it all into a monthly plan.
The first thing that makes it difficult is the sheer volume of numbers involved. Your plans need to break everything down at least by specialty (treatment function code), or by HRG chapter, or even by HRG. Then you need to separate out emergency spells, elective spells, A&E, first outpatients, etc. And you need to split it by commissioner or provider, and possibly by provider site as well. All in all, you are looking at dozens of service lines at least, and quite possibly hundreds.
The second problem is that different kinds of data come from different places in different formats (including notes of meetings and scraps of paper). Some of the performance assumptions are broad-brush, some are detailed, and some are exceptions to a general rule. They somehow need knitting together into a single planning model. And they keep changing: time goes by and more recent activity data becomes available; performance assumptions and pathways are negotiated and amended; new guidance comes down from the Department of Health (and in future the Commissioning Board).
The third problem is that some of the historical data is prone to errors: activity is not completely or correctly coded, there are delays in recording events on the system, there are duplicates and omissions, and changing customs and practices cause coding drift and other systematic error. To some extent, these errors can be detected and corrected automatically; in many cases they can’t.
The fourth problem is that well-known equations do not exist for some of the workings. Waiting time standards of the form “90% of patients must be treated within 8 weeks” have historically been a high-profile example; the standard is easy to state, but to model it properly you need to take in the effect of clinical urgency, cancellations, whether you are running a fully-booked or partially-booked system, and other factors. If you try to simplify the problem by assuming that current practice reflects how things ought to be, then you are ignoring (often substantial) opportunities to improve.
There are similar problems with monthly profiling: you can profile non-elective work based on historical patterns; but what agreed methods are there for profiling inpatient elective work around peaks in non-elective demand, when the 18-week waiting time limit means that you can’t slow down surgery very much over the winter?
The fifth problem is that you probably have the wrong tools for the job. The suggested tool for presenting your plans is usually a spreadsheet, and (despite the well-known problems with spreadsheet errors, and their limitations when it comes to iterative calculations) they are the cultural default.
How much does this matter? Aren’t these plans just shelfware? Feeding the beast, and all that?
Actually, no. Although your painstakingly-crafted plans may end up on the shelf afterwards, there are two good reasons why the effort is important:
- The planning process causes lots of conversations to happen that do change the way healthcare is delivered, and the numbers make sure those conversations are tough enough.
- The financial squeeze is now adding urgency: PCTs will not be allowed to create a legacy of debt for future GP consortia, continually-rising demand is no longer affordable, and hospitals have a capacity overhang from the boom years… and so back to point 1 above.
It is natural when planning to focus on the correctness of the calculations. The complexity of the process can make this all-consuming.
But it is equally important to make sure that everyone else involved can keep track of the performance and pathway assumptions being used. Why? Because when clinicians and managers make changes to healthcare in real life, they are implementing changes to these assumptions.
Of course the calculations must be right, and the “bottom line” results are crucial in showing how much further negotiation will be needed. But it is also worth paying attention to the presentation of those key assumptions. If other people can easily see what they are, what they mean, and how they change during negotiations, then better decisions will be made about them, and the planning process will be a more powerful force for improvement in the real world.