Hamish Dibley

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Delaying the inevitable: a better way to think about delayed transfers of care

DTOCDelayed transfers of care, or ‘DTOC’ as it is colloquially referred to in NHS circles, is an entrenched national problem. It is often claimed that a combination of ‘cultural and structural factors’, an over-reliance in bed-based care and increasing numbers of people with complex conditions moving between providers is causing undue strain on the system. It is one of the principal issues said to affect the performance of A&E units up and down the country.

DTOC has a big impact across the whole healthcare economy in terms of activity, costs and reputation. It is generally accepted to centre on acute services for older people. But the question I pose is: by focusing on the acute are we concentrating efforts on the symptom or the cause? Every problem presents an opportunity. Every challenge requires an intention to signal a desire to improve through thinking and acting differently. DTOC is a symptom of a dysfunctional health care economy.

Concerted effort and numerous attempts have been made, over several years, to successfully address DTOC. These initiatives include the usual list of initiatives including ‘Appropriate Care for Everyone Programmes’ (without ever defining what appropriate in this context means), QIPP projects, engagement and public education packages and Older People’s Joint Commissioning Strategies.

Yet, successive schemes fail to impact on DTOC as they compartmentalise the problem through focusing on urgent care or complex care rather than understanding the root cause of the problems. The impact of these actions on improving DTOC performance remains stubbornly low. Initiatives tend to adopt a reactive and reductionist approach to resolving the problem.

The principal reasons for failure requires detailed study but can be summarised by adopting a (silo) service-first not patient-perspective and focusing on activity reduction and discharge pathways. The causes of waste or ‘system limitations’ affecting DTOC include:

  • Outsourcing of adult social care provision
  • Multiple patient assessments
  • Eligibility criteria in community and social care
  • Different organisational budgets, performance metrics and ways of working
  • Counter-productive financial incentives across the system
  • Service fragmentation such as a ‘medically fit’ focus
  • Alleged risk-averse attitudes amongst some clinical staff
  • An efficiency rather than effectiveness focus on reducing length of stay
  • A target mentality which limits attempts to understand in order to improve
  • Understanding the problem from the organisational perspective

‘Pooled budgets’ for services used by older people offers hope to reduce rates but only if it is accompanied by a change in commissioning and operational thinking and ways of working that extends beyond joint ‘commissioning of care’.

‘Current DTOC performance’ is monitored on a regular basis through weekly returns taken on one day each week from local acute trusts. The whole thing resembles the game-show Play Your Cards Right. Snapshot analysis shows the weekly rates of DTOC can vary with some weeks being ‘higher’ and others ‘lower’.

All of which leaves me with more questions than answers, and those questions are – what does this tell us? How does this information help us understand to improve? Does this ‘activity counting’ help develop knowledge and understanding around the patients who experience delays and the type and nature of activity this creates which leads to costs? What has operationally changed as a result of monitoring? How do we know if this has been effective? Or like the game show – is it simply a game of chance? Such ‘activity monitoring’ is as counter-productive as it is distorting. Improvement work must take place in the work not in meeting rooms.

I have recently completed a piece of work looking at the problem. I hope the study will provide the platform to overcome successive false starts, identify root causes and design a healthcare system to reduce DTOC levels through better understanding patient demand. But that, of course, is dependent on the willingness of local NHS leaders to adopt a different mindset.

It begins with adopting a different patient-centred perspective and intelligently analysing the problem. This work seeks to take a holistic approach and understand it from the patient perspective. It asks how many patients cause what type, patterns, predictability and volume of activity which results in costs. This way of thinking and acting is the means to achieve intelligent change leading to sustainable performance improvement.

What you discover is that the DTOC problem is NOT a general acute service for older people problem; hospitals deal with the consequences of the issue. When you compare A&E waiting time against DTOC rates it reveals different sets of challenges. One lot are external system problems where the acute provider is trying to deal with the consequences of fragmented care. But there are also internal system issues such as the impact of the 4-hour waiting time target which distorts performance and paradoxically helps make the problem worse (see my previous blog on the deficiencies with the A&E waiting time target).

As ever with healthcare, DTOC is a ‘vital few’ challenge – small numbers of patients consuming disproportionately high levels of activity, capacity and resources. For example, 1,700 patients admitted suffered with a DTOC over a 12 month period. The length of stay from their emergency admissions contributed to a third of the overall bed capacity of the hospital. Moreover, the real costs of DTOC are much higher than simply a blinkered focus on ‘excess bed days’ would allow for (an abstract and unhelpful financial ‘tariff’ distinction). Less than 2,000 people cost this particular secondary care system over £11 million every year. How much of this money is well spent? We simply don’t know.

But the small numbers show that the problem is predictable and therefore manageable.  It also represents a big opportunity providing healthcare leaders have the courage to make profound changes in the way we commission and provide healthcare services. To improve (and thereby reduce) DTOC there is a need to better understand patients and what services they already consume to design more effective medical and non-medical services around their care needs.

The issues affecting DTOC are complex. The mistake often made with improvement efforts is to try and cut through or standardise complexity. Wrong. As W Ross Ashby’s Law of Requisite Variety teaches us the most intelligent way to deal with variety is design systems and services against that variety. In healthcare the way to undertake this is to understand and then design against patient-level demand. This will be effective and if you think about it, if you are effective at something; by definition you will be efficient.

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Lop-sided logic: A&E and the 4-hour waiting time target

A&E Performance and the 4 Hour Target

Broadcast and newspaper headlines in the past couple of months have all been about pressures on A&E services. As ever with whirlwind media storms they typically tend to blow out before reasoned conclusions can be drawn.

Which leaves the question, what really does bedevil A&E? Is the problem facing the front-end of acute hospitals down to underfunding of emergency medicine; the ‘downgrading’ or closure of A&E units; fragmented and unresponsive primary care services; NHS 111 (more on this in a future blog); the payment or ‘tariff’ system; unprecedented patient demand; blockages including static or declining bed capacity and delays in transferring patients out of hospital or all of the above? 

The direction of NHS England is to ‘centralise’ or ‘standardise’ emergency provision around fewer locations and downgrading others into Minor Injury Units (MIU) or Urgent Care Centres (UCC). To critics this move is one which creates a ‘two-tier’ system. The logic is an economy of scale one and follows where earlier efforts in stroke and heart care have lead; namely centralise medical expertise and services in order to improve outcomes.

Two things are for sure – we shouldn’t expect ‘healthcare professionals’, code in this case for paramedics, doctors and nurses to work ‘harder’, they already are. Nor should we condemn people for using A&E services inappropriately in whatever numbers. Clifford Mann, the President of the Royal College of Emergency Medicine was absolutely right when he said last month: “I don’t think we should blame people for going to the emergency department when we (the system) told them to go there. It’s absurd.”

It is true that over time, we have both incrementally and intentionally designed a reactive, fire-fighting, hospital focused, medical health system, with care very much an after-thought. Hospitals declaring they can’t cope through issuing ‘major incident’ alerts is the predictable consequence of some pretty foolhardy thinking. One such example is the 4-hour waiting time target in A&E. Ludicrously this activity measure is regarded by many as both a good indicator of A&E performance and quality. It is nothing of the sort.

The 4-hour waiting time target is a nationally-derived arbitrary indicator. The NHS in England (or more appropriately individual NHS Trusts) has missed its four-hour A&E waiting time target with performance dropping to its lowest level for a decade. Figures show that from October to December 2014, 92.6% of patients were seen in four hours – below the 95% target. The performance is the worst quarterly result since the target was introduced in 2004. Viewed a different way, 9 out of 10 people who go to A&E get ‘seen and treated’, discharged or admitted within the 4-hour window. Interestingly, whether we actually solved their problem is not measured and consequently never recorded.

The waiting time target’s reductionist logic is simple. It is an arbitrary indicator which is set from outside the immediate organisation (hospital) or business unit (A&E). The hospital and A&E is then expected to achieve the target come hell or high-water, through greater effort by its employees. 

The reason this happens is because there is a mistaken belief that it is people themselves who are the limiting constraint on performance within organisations – they need to work harder or refrain from using services for reasons that are deemed ‘inappropriate’. The reality is that people’s performance or usage of a particular service is a consequence of the influence of other parts of the system, of which they form a part – policies, processes, procedures, systems, management. 

To use an analogy, if a person enters a 10 mile race, in the knowledge that they can only run 5, the only way they can finish the race is to ‘game’ or ‘cheat’ and catch a bus after the 5 mile mark. This is what happens in organisations. If the A&E arbitrary target for transferring patients to a ward is 4 hours, but the existing capability (if measured) is only 5, then in effect, the bus is a trolley parked in the hospital corridor. Only now it is alleged, the wheels are coming off. 

The other problem with arbitrary targets is that they are self-limiting. With no knowledge of patient demand and existing capability to meet that demand, the artificial target actually could be well within the range of what is improvement is possible. Paradoxically, setting a target can actually lead to under-achievement, in both people and organisations. 

To compound the problem, along with the deficiencies inherent in setting an arbitrary target, measuring and judging performance at a single static point or over a single period of time is also counter-productive. This ignores the nature of variation that exists in almost everything we do, individually and collectively within an organisation. Here averages distort unless viewed within the context of the overall distribution of performance and the underlying trend, viewed against the demand placed on the system at any given point in time. 

Whilst we can’t remove the 4-hour waiting time (the real limiting constraint), we should treat it as unavoidable system limitation but not drive performance solely on achievement of the arbitrary number. The alternative ‘solution’ is very straightforward – establish more insightful information streams and/or make better use of data in a more operationally meaningful way. Asking useful questions will help understand and in-turn resolve problems: 

  • Before measuring anything, ensure you are measuring the right thing. Is the 4-hour target measuring the right thing? Measure what matters to patients – do we actually know what this is? Is it quick diagnosis, speedy treatment, medical or psychological reassurance or getting help?
  • When it comes to measurement we first have to understand patient demand. Do we empirically know why people choose to use A&E (patient demands) in order to understand how A&E can be better designed to deal with these demands (capability)? Simply ranking demands by their perceived inappropriateness without understanding the patient context doesn’t solve any problem.
  • Measure your existing capability over time and understand the statistical variation that exists, against an understanding of demand.
  • Express what you measure statistically, based on the nature of the distribution of the thing being measured.
  • Unless you intend to change something and if you must set a target, understand what is within your current organisational or business unit capability.
  • If you want to set a target outside your current capability, then identify what you are going to change to achieve this objective.
  • Do not let the setting of a target act as a system constraint in itself.
  • Do not make a business out of it – the aim should be continuous improvement not ranking.

This alternative approach would require us to regularly understand and measure local demand placed on the system (find out from their perspective why people actually come to A&E, don’t assume to know the answers) and the local capability to respond to this demand. Is demand predictable over time? What is the current system capability (staff mix, capability to meet the nature of patient needs and resourcing) to successfully address this demand?

A sophisticated understanding of patient demand and the capability to meet it will provide providers and commissioners with the ‘business intelligence’ they need to have a more effective A&E service. It informs us as to the level and nature of professional expertise required in A&E and when; availability of appropriate test facilities and beds; person-centred processes to effectively meet needs and even how best to approach the design and layout of A&E.

One thing we can forget though: the growing trend to rebrand A&E Emergency Department (ED) – that has zero impact.