Archive for the ‘HCSE’ Category

The summer holidays are over and schools are open again – sort of.

Restaurants, pubs and nightclubs are open again – sort of.

Gyms and leisure facilities are open again – sort of.

And after two months of gradual easing of social restrictions and massive expansion of test-and-trace we now have the spectre of a Second Wave looming.  It has happened in Australia, Italy, Spain and France so it can happen here.

As usual, the UK media are hyping up the general hysteria and we now also have rioting disbelievers claiming it is all a conspiracy and that re-applying local restrictions is an infringement of their liberty.

So, what is all the fuss about?

We need to side-step the gossip and get some hard data from a reliable source (i.e. not a newspaper). Here is what worldometer is sharing …

OMG!  It looks like The Second Wave is here already!  There are already as many cases now as in March and we still have the mantra “Stay At Home – Protect the NHS – Save Lives” ringing in our ears.  But something is not quite right.  No one is shouting that hospitals are bursting at the seams.  No one is reporting that the mortuaries are filling up.  Something is different. We need more data.That is odd! We can clearly see that cases and deaths went hand-in-hand in the First Wave with about 1:5 cases not making it.  But this time the deaths are not rising with the cases.

Ah ha!  Maybe that is because the virus has mutated into something much more benign and because we have got much better at diagnosing and treating this illness – the ventilators and steroids saved the day.  Hurrah!  It’s all a big fuss about nothing … we should still be able to have friends round for a party and go on pub crawls!

But … what if there was a different explanation for the patterns on the charts above?

It is said that “data without context is meaningless” … and I’d go further than that … data without context is dangerous because if it leads to invalid conclusions and inappropriate decisions we can get well-intended actions that cause unintended harm.  People might die.

So, we need to check the context of the data.

In the First Wave the availability of the antigen (swab) test was limited so it was only available to hospitals and the “daily new cases” were in patients admitted to hospital – the ones with severe enough symptoms to get through the NHS 111 telephone triage.  Most people with symptoms, even really bad ones, stayed at home to protect the NHS.  They didn’t appear in the statistics.

But did the collective sacrifice of our social lives actually save lives?

The original estimates of the plausible death toll in the UK ranged up to 500,000 from coronavirus alone (and no one knows how many more from the collateral effects of an overwhelmed NHS).  The COVID-19 body count to date is just under 50,000 so, putting a positive spin on that tragic statistic, 90% of the potential deaths were prevented.  The lock down worked.  The NHS did not collapse.  The Nightingale Hospitals stood ready and idle – an expensive insurance policy.  Lives were saved.

Why isn’t that being talked about?

And the context changed in another important way.  The antigen testing capacity was scaled up despite being mired in confusing jargon.  Who thought up the idea of calling them “pillars”?

Anyway, if we dig about on the GOV.UK website enough there is a definition:

So, Pillar 1 = NHS testing capacity Pillar 2 = commercial testing capacity and we don’t actually know how much was in-hospital testing and how much was in-community testing because the definitions seem to reflect budgets rather than patients.  Ever has it been thus in the NHS!

However, we can see from the chart below that testing activity (blue bars) has increased many-fold but the two testing streams (in hospital and outside hospital) are combined in one chart.  Well, it is one big pot of tax-payers cash after all and it is the same test.

To unravel this a bit we have to dig about on the website, download the raw data, and plot it ourselves.  Looking at Pillar 2 (commercial) we can see they had a late start, caught the tail of the First Wave, and then ramped up activity as the population testing caught up with the available capacity (because hospital activity has been falling since late April).

Now we can see that the increased number of positive tests could be explained by the fact that we are now testing anyone with possible COVID-19 symptoms who steps up – mainly in the community.  And we were unable to do this before because the testing capacity did not exist.

The important message is that in the First Wave we were not measuring what was happening in the community – it was happening though – it must have been.  We measured the effects. Hospital admissions with positive tests and deaths after positive tests.

So, to present the daily positive tests as one time-series chart that conflates both ‘pillars’ is both meaningless and dangerous and it is no surprise that the pubic are confused.


This raises a question: “Can we estimate how many people there would have been in the community in the First Wave so that we can get a sense of what the rising positive test rate means now?”

The way that epidemiologists do this is to build a generic simulation model of the system dynamics of an epidemic (a SEIR compartment model) and then use the measured data to calibrate the this model so that it can then be used for specific prediction and planning.

Here is an example of the output a calibrated multi-compartment system dynamics model of the UK COVID-19 epidemic for a nominal 1.3 million population.  The compartments that are included are Susceptible, Exposed, Infectious, and Recovered (i.e. not infectious) and this model also simulates the severity of the illness i.e. Severe (in hospital), Critical (in ITU) and Died.

The difference in size of the various compartments is so great that the graph below requires two scales – the solid line (Infectious) is plotted on the left hand scale and the others are plotted on the right hand scale which is 10 times smaller.  The green line is today and the reported data up to that point can be used to calibrate the model and to estimate the historical metrics that we did not measure – such as how many people in the community were infectious (and would have tested positive).

At the peak of the First Wave, for this population of 1.3 million, the model estimates there were about 800 patients in hospital (which there were) and 24,000 patients in the community who would have tested positive if we had been able to test them.  24,000/800 = 30 which means the peak of the grey line is 30 x higher than the peak of the orange line – hence the need for the two Y-axes with a 10-fold difference in scale.

Note the very rapid rise in the number of infectious people from the beginning of March when the first UK death was announced, before the global pandemic was declared and before the UK lock down was enacted in law and implemented.  Coronavirus was already spreading very rapidly.

Note how this rapid rise in the number of infectious people came to an abrupt halt when the UK lock down was put into place in the third week of March.  Social distancing breaks the chain of transmission from one infectious person to many other susceptible ones.

Note how the peaks of hospital admissions, critical care admissions and deaths lag after the rise in infectious people (because it takes time for the coronavirus to do its damage) and how each peak is smaller (because only about 1:30 get sick enough to need admission, and only 1:5 of hospital admissions do not survive.

Note how the fall in the infectious group was more gradual than the rise (because the lock down was partial and because not everyone could stay at home – essential services like the NHS had to continue).


So, by early July it was possible to start a gradual relaxation of the lock down and from then we can see a gradual rise in infectious people again.  But now we were measuring them because of the growing capacity to perform antigen tests in the community.  The relatively low level and the relatively slow rise are much less dramatic than what was happening in March (because of the higher awareness and the continued social distancing and use of face coverings).  It is easy to become impatient and complacent.

But by early September it was clear that the number on infectious people was growing faster in the community – and then we saw the fall in hospital admissions reach a minimum and start to rise again. And the number if deaths reach a minimum and start to rise again.  And this evidence proves that the current level of social distancing is not enough to keep a lid on this disease.  We are in the foothills of a Second Wave.


So what do we do next?

First, we must estimate the effect that the current social distancing policies are having and one way to do that would be to stop doing them and see what happens.  Clearly that is not an ethical experiment to perform given what we already know.  But, we can simulate that experiment using our calibrated model.  Here is what is predicted to happen if we went back to the pre-lockdown behaviours: There would be a very rapid spread of the virus followed by a Second Wave that would be many times bigger than the first!!  Then it would burn itself out and those who had survived could go back to some semblance of normality.  The human sacrifice would be considerable.

So, despite the problems that the current social distancing is causing, they pale into insignificance compared to what could happen if they were dropped.

The previous model shows what is predicted would happen if we continue as we are with no further easing of restrictions and assuming people stick to them.  In short, we will have COVID-for-Christmas and it could be a very nasty business indeed as it would come at the same time as other winter-associated infectious diseases such as influenza and norovirus.

The next chart shows what could happen if we squeeze the social distancing brake a bit by focusing only on the behaviours that the track-and-trace-and-test system is highlighting as the key drivers of the growth infections, admissions and deaths.

What we see is an arrest of the rise of the number of infectious people (as we saw before), a small and not sustained increase in hospital admissions, then a slow decline back to the levels that were achieved in early July – and at which point it would be reasonable to have a more normal Christmas.

And another potential benefit of a bit more social distancing might be a much less problematic annual flu epidemic because that virus would also find it harder to spread – plus we have a flu vaccination which we can use to reduce that risk further.


It is not going to be easy.  We will have to sacrifice a bit of face-to-face social life for a bit longer.  We will have to measure, monitor, model and tweak the plan as we go.

And one thing we can do immediately is to share the available information in a more informative and less histrionic way than we are seeing at the moment.


The start of a new year, decade, century or millennium is always associated with a sense of renewal and hope.  Little did we know that in January 2020 a global threat had hatched and was growing in the city of Wuhan, Hubei Province, China.  A virus of the family coronaviridae had mutated and jumped from animal to man where it found a new host and a vehicle to spread itself.   Several weeks later the World became aware of the new threat and in the West … we ignored it.  Maybe we still remember the SARS epidemic which was heralded as a potential global catastrophe but was contained in the Far East and fizzled out.  So, maybe we assumed this SARS-like virus would do the same.

It didn’t.  This mutant was different.  It caused a milder illness and unwitting victims were infectious before they were symptomatic; and most got better on their own, so they spread the mutant to many other people.  Combine that mutant behaviour with the winter (when infectious diseases spread more easily because we spend more time together indoors), Chinese New Year and global air travel … and we have the perfect recipe for cooking up a global pandemic of a new infectious disease.  But we didn’t know that at the time and we carried on as normal, blissfully unaware of the catastrophe that was unfolding.

By February it became apparent that the mutant had escaped containment in China and was wreaking havoc in other countries – with Italy high on the casualty list.  We watched in horror at the scenes on television of Italian hospitals overwhelmed with severely ill people fighting for breath as the virus attacked their lungs.  The death toll rose sharply but we still went on our ski holidays and assumed that the English Channel and our quarantine policy would protect us.

It didn’t.  This mutant was different.  We now know that it had already silently gained access into the UK and was growing and spreading.  The first COVID-19 death reported in the UK was in early March and only then did we sit up and start to take notice.  This was too close to home.

But it was too late.  The mathematics of how epidemics spread was worked out 100 years ago, not long after the 1918 pandemic of Spanish Flu that killed tens of millions of people before it burned itself out.  An epidemic is like cancer.  By the time it is obvious it is already far advanced because the growth is not linear – it is exponential.

 

As a systems engineer I am used to building simulation models to reveal the complex and counter-intuitive behaviour of nonlinear systems using the methods first developed by Jay W. Forrester in the 1950’s.  And when I looked up the equations that describe epidemics (on Wikipedia) I saw that I could build a system dynamics model of a COVID-19 epidemic using no more than an Excel spreadsheet.

So I did.  And I got a nasty surprise.  Using the data emerging from China on the nature of the spread of the mutant virus, the incidence of severe illness and the mortality rate … my simple Excel model predicted that, if COVID-19 was left to run its natural course in the UK, then it would burn itself out over several months but the human cost would be 500,000 deaths and the NHS would be completely overwhelmed with a “tsunami of sick”.  And I could be one of them!  The fact that there is no treatment and no vaccine for this novel threat excluded those options.  My basic Excel model confirmed that the only effective option to mitigate this imminent catastrophe was to limit the spread of the virus through social engineering i.e. an immediate and drastic lock down.  Everyone who was not essential to maintaining core services should “Stay at home, Protect the NHS and Save lives“.  That would become the mantra.  And others were already saying this – epidemiologists whose careers are spent planning for this sort of eventuality.  But despite all this there still seemed to be little sense of urgency, perhaps because their super-sophisticated models predicted that the peak of the UK epidemic would be in mid-June so there was time to prepare.  My basic model predicted that the peak would be in mid-April, in about 4 weeks, and that it was already too late to prevent about 50,000 deaths.

It turns out I was right.  That is exactly what happened.  By mid-March London was already seeing an exponential rise in hospital admissions, intensive care admissions and deaths and suddenly the UK woke up and panicked.  By that time I had enlisted the help of a trusted colleague who is a public health doctor and who has studied epidemiology, and together we wrote up and published the emerging story as we saw it:

An Acute Hospital Demand Surge Planning Model for the COVID-19 Epidemic using Stock-and-Flow Simulation in Excel: Part 1. Journal of Improvement Science 2020: 68; 1-20.  The link to download the full paper is here.

I also shared the draft paper with another trusted friend and colleague who works for my local clinical commissioning group (CCG) and I asked “Has the CCG a sense of the speed and magnitude of what is about to happen and has it prepared for the tsunami of sick that primary care will need to see?

What then ensued was an almost miraculous emergence of a coordinated and committed team of health care professionals and NHS managers with a single, crystal clear goal:  To design, build and deliver a high-flow, drive-through community-based facility to safely see-and-assess hundreds of patients per day with suspected COVID-19 who were too sick/worried to be managed on the phone, but not sick enough to go to A&E.  This was not a Nightingale Ward – that was a parallel, more public and much more expensive endeavour designed as a spillover for overwhelmed acute hospitals.  Our purpose was to help to prevent that and the time scale was short.  We had three weeks to do it because Easter weekend was the predicted peak of the COVID-19 surge if the national lock down policy worked as hoped.  No one really had an accurate estimate how effective the lock down would be and how big the peak of the tsunami of sick would rise as it crashed into the NHS;  so we planned for the worst and hoped for the best.  The Covid Referral Centre (CRC) was an insurance policy and we deliberately over-engineered it use to every scrap of space we had been offered in a small car park on the south side of the NEC site.

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The CRC needed to open by Sunday 12th April and we were ready, but the actual opening was delayed by NHS bureaucracy and politics.  It did eventually open on 22nd April, just four weeks after we started, and it worked exactly as designed.  The demand was, fortunately, less than our worst case scenario; partly because we had missed the peak by 10 days and we opened the gates to a falling tide; and partly because the social distancing policy had been more effective than hoped; and partly because it takes time for risk-averse doctors to develop trust and to change their ingrained patterns of working.  A drive-through COVID-19 See-and-Treat facility? That was innovative and untested!!

The CRC expected to see a falling demand as the first wave of COVID-19 washed over, and that exactly is what happened.  So, as soon as that prediction was confirmed, the CRC was progressively repurposed to provide other much needed services such as drive-through blood tests, drive-through urgent care, and even outpatient clinics in the indoor part of the facility.

The CRC closed its gates to suspected COVID-19 patients on 31st July, as planned and as guided by the simple Excel computer model.

This is health care systems engineering in action.

And the simple Excel model has been re-calibrated as fresh evidence has emerged.  The latest version predicts that a second peak of COVID-19 (that is potentially worse than the first) will happen in late summer or autumn if social distancing is relaxed too far (see below).

But we don’t know what “too far” looks like in practical terms.  Oh, and a second wave could kick off just just when we expect the annual wave of seasonal influenza to arrive.  Or will it?  Maybe the effect of social distancing for COVID-19 in other countries will suppress the spread of seasonal flu as well?  We don’t know that either but the data of the incidence of flu from Australia certainly supports that hypothesis.

We may need a bit more health care systems engineering in the coming months. We shall see.

Oh, and if we are complacent enough to think a second wave could never happen in the UK … here is what is happening in Australia.

At the end of the decade it is the time to reflect on what has happened in the past before planning for the future.  As always, the hottest topic in health care is the status of the emergency care services, and we have the data – it is public.

This shows the last 9 years of aggregate, monthly data for Scotland (red), England (blue), Wales (teal) and N.Ireland (orange).  It does not take a data scientist and a supercomputer to interpret – there is a progressive system-wide progressive deterioration year-on-year.  The winter dips are obvious and the worst of these affect all four countries indicating a systemic cause … the severity of the winter weather/illness cycle -i.e. the Flu Season.

What this chart also says is that all the effort and money being expended in winter planning is not working well enough – and the nagging question is “Why not?”

Many claim that it is the predicted demographic “time bomb” … but if it is predicted then how come it has not been mitigated?

Many claim that it is a growing funding gap … but most NHS funding is spent on staff and  and training nurses, doctors and allied health professionals (AHPs) takes time.  Again, a predicted eventuality that has not been mitigated.

This looming crisis in a lack of heath care workers is a global health challenge … and is described by Mark Britnell in “Human – Solving the global workforce crisis in healthcare“.

Mark was the CEO of University Hospitals Birmingham from 2000 and has worked for KPMG since 2009 in a global health role so is well placed to present a strategic overview.


But, health care workers deliver care to patients – one at a time.  They are not responsible for designing the system of health care delivery; or ensuring all the pieces of that vast jigsaw link up and work in a synchronised way; or for the long term planning needed to mitigate the predictable effects of demographic drift and technology advances.

Who is responsible for that challenge and are they adequately trained to do it?

The evidence would appear to suggest that there is a gap that either no one has noticed or that no one is prepared to discuss.  An Undiscussable?


The global gap in the healthcare workforce is predicted to be about 20% by 2030.  That is a big gap to fill because with the NHS workforce of 1.3 million people – that implies training 260,000 new staff of all types in the next 10 years, in addition to replacing those that leave.

Assuming the processes and productivity stay as they are now.

So, perhaps there is a parallel approach, one that works more quickly and a lower cost.


When current health care processes are examined through a flow engineering lens they are found to be poorly designed. They are both ineffective (do not reliably deliver the intended outcome) and inefficient (waste a lot of resources in delivering any outcome).  Further examination reveals that the processes have never been designed … they have evolved.

And just because something is described as current practice does not prove that it is good design.

An expected symptom of a poorly designed process is a combination of chronic queues, delays, chaos, reactive fire-fighting and burnout.  And the assumed cause is often lack of resources because when extra resource is added the queues and chaos subsides, for a while.

But, if the unintentional poor design of the process is addressed then a sequence of surprising things can happen. The chaos evaporates immediately without any extra resources. A feeling of calm is restored and the disruptive fire-fighting stops. The health care workers are able to focus on what they do best and pride-in-work is restored. Patient experience improves and staff feel that feedback and become more motivated. The complaining abates, sickness and absence falls, funded-but-hard-to-recruit-to posts are refilled and there are more hands on the handle of a more efficient/effective/productive pump.  The chronic queues and delays start to melt away – as if by magic.

And if that all sounds totally impossible then here are a couple of recent, real-world case studies written by different teams in different cities in different parts of the UK.  One from cancer care and one from complex diabetic care.

They confirm that this chaos-to-calm transformation is possible.

So, is there a common thread that links these two examples?

Yes, there is, and once again the spotlight is shone on the Undiscussable Gap … the fact that the NHS does not appear to have the embedded capability to redesign itself.

There is a hidden workforce gap that none of the existing programmes will address – because it is not a lack of health care workers – it is a lack of appropriately trained health care manager-designers.


The Undiscussable Elephant Is In The Room … the Undiscussable Emperor Has No Clothes.

And if history teaches us anything, Necessity is the Mother of Innovation and the chart at the top of the page shows starkly that there is an Growing Urgent Necessity.

And if two embedded teams can learn this magic trick of flipping chaos into calm at no cost, then perhaps others can too?

Welcome to the New Decade of Hope and Health Care Systems Engineering.

The thing that gives me the biggest buzz when it comes to improvement is to see a team share their story of what they have learned-by-doing; and what they have delivered that improves their quality of life and the quality of their patients’ experience.

And while the principles that underpin these transformations are generic, each story is unique because no two improvement challenges are exactly the same and no two teams are exactly the same.

The improvement process is not a standardised production line.  It is much more organic and adaptive experience and that requires calm, competent, consistent, compassionate and courageous facilitation.

So when I see a team share their story of what they have done and learned then I know that behind the scenes there will have been someone providing that essential ingredient.

This week a perfect example of a story like this was shared.

It is about the whole team who run the Diabetic Complex Cases Clinic at Guy’s and St. Thomas’ NHS Trust in London.  Everyone involved in the patient care was involved.  It tells the story of how they saw what might be possible and how they stepped up to the challenge of learning to apply the same principles in their world.  And it tells their story of what they diagnosed, what they designed and what they delivered.

The facilitation and support was provided Ellen Pirie who works for the Health Innovation Network (HIN) in South London and who is a Level 2 Health Care Systems Engineer.

And the link to the GSTT Diabetic Complex Clinic Team story is here.

In 1986, Dr Don Berwick from Boston attended a 4-day seminar run by Dr W. Edwards Deming in Washington.  Dr Berwick was a 40 year old paediatrician who was also interested in health care management and improving quality and productivity.  Dr Deming was an 86 year old engineer and statistician who, when he was in his 40’s, helped the US to improve the quality and productivity of the industrial processes supporting the US and Allies in WWII.

Don Berwick describes attending the seminar as an emotionally challenging life-changing experience when he realised that his well-intended attempts to improve quality by inspection-and-correction was a counterproductive, abusive approach that led to fear, demotivation and erosion of pride-in-work.  His blinding new clarity of insight led directly to the Institute of Healthcare Improvement in the USA in the early 1990’s.

One of the tenets of Dr Deming’s theories is that the ingrained beliefs and behaviours that erode pride-in-work also lead to the very outcomes that management do not want – namely conflict between managers and workers and economic failure.

So, an explicit focus on improving pride-in-work as an early objective in any improvement exercise makes very good economic sense, and is a sign of wise leadership and competent management.


Last week a case study was published that illustrates exactly that principle in action.  The important message in the title is “restore the calm”.

One of the most demotivating aspects of health care that many complain about is the stress caused a chaotic environment, chronic crisis and perpetual firefighting.  So, anything that can restore calm will, in principle, improve motivation – and that is good for staff, patients and organisations.

The case study describes, in detail, how calm was restored in a chronically chaotic chemotherapy day unit … on Weds, June 19th 2019 … in one day and at no cost!

To say that the chemotherapy nurses were surprised and delighted is an understatement.  They were amazed to see that they could treat the same number of patients, with the same number of staff, in the same space and without the stress and chaos.  And they had time to keep up with the paperwork; and they had time for lunch; and they finished work 2 hours earlier than previously!

Such a thing was not possible surely? But here they were experiencing it.  And their patients noticed the flip from chaos-to-strangely-calm too.

The impact of the one-day-test was so profound that the nurses voted to adopt the design change the following week.  And they did.  And the restored calm has been sustained.


What happened next?

The chemotherapy nurses were able to catch up with their time-owing that had accumulated from the historical late finishes.  And the problem of high staff turnover and difficultly in recruitment evaporated.  Highly-trained chemotherapy nurses who had left because of the stressful chaos now want to come back.  Pride-in-work has been re-established.  There are no losers.  It is a win-win-win result for staff, patients and organisations.


So, how was this “miracle” achieved?

Well, first of all it was not a miracle.  The flip from chaos-to-calm was predicted to happen.  In fact, that was the primary objective of the design change.

So, how what this design change achieved?

By establishing the diagnosis first – the primary cause of the chaos – and it was not what the team believed it was.  And that is the reason they did not believe the design change would work; and that is the reason they were so surprised when it did.

So, how was the diagnosis achieved?

By using an advanced systems engineering technique called Complex Physical System (CPS) modelling.  That was the game changer!  All the basic quality improvement techniques had been tried and had not worked – process mapping, direct observation, control charts, respectful conversations, brainstorming, and so on.  The system structure was too complicated. The system behaviour was too complex (i.e. chaotic).

What CPS revealed was that the primary cause of the chaotic behaviour was the work scheduling policy.  And with that clarity of focus, the team were able to re-design the policy themselves using a simple paper-and-pen technique.  That is why it cost nothing to change.

So, why hadn’t they been able to do this before?

Because systems engineering is not a taught component of the traditional quality improvement offerings.  Healthcare is rather different to manufacturing! As the complexity of the health care system increases we need to learn the more advanced tools that are designed for this purpose.

What is the same is the principle of restoring pride-in-work and that is what Dr Berwick learned from Dr Deming in 1986, and what we saw happen on June 19th, 2019.

To read the story of how it was done click here.

This is the name given to an endemic, chronic, systemic, design disease that afflicts the whole NHS that very few have heard of, and even fewer understand.

This week marked two milestones in the public exposure of this elusive but eminently treatable health care system design illness that causes queues, delays, overwork, chaos, stress and risk for staff and patients alike.

The first was breaking news from the team in Swansea led by Chris Jones.

They had been grappling with the wicked problem of chronic queues, delays, chaos, stress, high staff turnover, and escalating costs in their Chemotherapy Day Unit (CDU) at the Singleton Hospital.

The breakthrough came earlier in the year when we used the innovative eleGANTT® system to measure and visualise the CDU chaos in real-time.

This rich set of data enabled us, for the first time, to apply a powerful systems engineering  technique called counterfactual analysis which revealed the primary cause of the chaos – the elusive and counter-intuitive design disease carvoutosis multiforme fulminans.

And this diagnosis implied that the chaos could be calmed quickly and at no cost.

But that news fell on slightly deaf ears because, not surprisingly, the CDU team were highly sceptical that such a thing was possible.

So, to convince them we needed to demonstrate the adverse effect of carveoutosis in a way that was easy to see.  And to do that we used some advanced technology: dice and tiddly winks.

The reaction of the CDU nurses was amazing.  As soon as they ‘saw’ it they clicked and immediately grasped how to apply it in their world.  They designed the change they needed to make in a matter of minutes.


But the proof-of-the-pudding-is-in-the eating and we arranged a one-day-test-of-change of their anti-carveout design.

The appointed day arrived, Wednesday 19th June.  The CDU nurses implemented their new design (which cost nothing to do).  Within an hour of the day starting they reported that the CDU was strangely calm.   And at the end of the day they reported that it had remained strangely calm all day; and that they had time for lunch; and that they had time to do all their admin as they went; and that they finished on time; and that the patients did not wait for their chemotherapy; and that the patients noticed the chaos-to-calm transformation too.

They treated just the same number of patients as usual with the same staff, in the same space and with the same equipment.  It cost nothing to make the change.

To say they they were surprised is an understatement!  They were so surprised and so delighted that they did not want to go back to the old design – but they had to because it was only a one-day-test-of-change.

So, on Thursday and Friday they reverted back to the carveoutosis design.  And the chaos returned.  That nailed it!  There was a riot!!  The CDU nurses refused to wait until later in the year to implement their new design and they voted unanimously to implement it from the following Monday.  And they did.  And calm was restored.


The second milestone happened on Thursday 11th July when we ran a Health Care Systems Engineering (HCSE) Masterclass on the very same topic … chronic systemic carveoutosis multiforme fulminans.

This time we used the dice and tiddly winks to demonstrate the symptoms, signs and the impact of treatment.  Then we explored the known pathophysiology of this elusive and endemic design disease in much more depth.

This is health care systems engineering in action.

It seems to work.

One of the most surprising aspects of systems is how some big changes have no observable effect and how some small changes are game-changers. Why is that?

The technical name for this phenomenon is leverage points.

When a nudge is made at a leverage point in a real system the impact is amplified – so a small cause can have a big effect.

And when a big kick is made where there is no leverage point the effort is dissipated. Like flogging a dead horse.

Other names for leverage points are triggers, buttons, catalysts, fuses etc.


The fact that there is a big effect does not imply it is a good effect.

Poking a leverage point can trigger a catastrophe just as it can trigger a celebration. It depends on how it is poked.

Perhaps that is one reason people stay away from them.

But when our heath care system performance is in decline, if we do nothing or if we act but stay away from leverage points (i.e. flog the dead horse) then we will deny ourselves the opportunity of improvement.

So, we need a way to (a) identify the leverage points and (b) know how to poke them positively and know how to not poke them into delivering a catastrophe.


Here is a couple of real examples.


The time-series chart above shows the A&E performance of a real acute trust.  Notice the pattern as we read left-to-right; baseline performance is OKish and dips in the winters, and the winter dips get deeper but the baseline performance recovers.  In April 2015 (yellow flag) the system behaviour changes, and it goes into a steady decline with added winter dips.  This is the characteristic pattern of poking a leverage point in the wrong way … and the fact it happened at the start of the financial year suggests that Finance was involved.  Possibly triggered by a cost-improvement programme (CIP) action somewhere else in the system.  Save a bit of money here and create a bigger problem over there. That is how systems work. Not my budget so not my problem.

Here is a different example, again from a real hospital and around the same time.  It starts with a similar pattern of deteriorating performance and there is a clear change in system behaviour in Jan 2015.  But in this case the performance improves and stays improved.  Again, the visible sign of a leverage point being poked but this time in a good way.

In this case I do know what happened.  A contributory cause of the deteriorating performance was correctly diagnosed, the leverage point was identified, a change was designed and piloted, and then implemented and validated.  And it worked as predicted.  It was not a fluke.  It was engineered.


So what is the reason that the first example much more commonly seen than the second?

That is a very good question … and to answer it we need to explore the decision making process that leads up to these actions because I refuse to believe that anyone intentionally makes decisions that lead to actions that lead to deterioration in health care performance.

And perhaps we can all learn how to poke leverage points in a positive way?

This recent tweet represents a significant milestone.  It formally recognises and celebrates in public the impact that developing health care systems engineering (HCSE) capability has had on the culture of the organisation.

What is also important is that the HCSE training was not sought and funded by the Trust, it was discovered by chance and funded by their commissioners, the local clinical commissioning group (CCG).


The story starts back in the autumn of 2017 and, by chance, I was chatting with Rob, a friend-of-a-friend, about work. As you do. It turned out that Rob was the CCG Lead for Unscheduled Care and I was describing how HCSE can be applied in any part of any health care system; primary care, secondary care, scheduled, unscheduled, clinical, operational or whatever.  They are all parts of the same system and the techniques and tools of improvement-by-design are generic.  And I described lots of real examples of doing just that and the sustained improvements that had followed.

So he asked “If you were to apply this approach to unscheduled care in a large acute trust how would you do it?“.  My immediate reply was “I would start by training the front line teams in the HCSE Level 1 stuff, and the first step is to raise awareness of what is possible.  We do that by demonstrating it in practice because you have to see it and experience it to believe it.

And so that is what we did.

The CCG commissioned a one-year HCSE Level 1 programme for four teams at University Hospitals of North Midlands (UHNM) and we started in January 2018 with some One Day Flow Workshops.

The intended emotional effect of a Flow Workshop is surprise and delight.  The challenge for the day is to start with a simulated, but very realistic, one-stop outpatient clinic which is chaotic and stressful for everyone.  And with no prior training the delegates transform it into a calm and enjoyable experience using the HCSE approach.  It is called emergent learning.  We have run dozens of these workshops and it has never failed.

After directly experiencing HCSE working in practice the teams that stepped up to the challenge were from ED, Transformation, Ambulatory Emergency Care and Outpatients.


The key to growing HCSE capability is to assemble small teams, called micro-system design teams (MSDTs) and to focus on causes that fall inside their circle of control.

The MSDT sessions need to be regular, short, and facilitated by an experienced HCSE who has seen it, done it and can teach it.

In UHNM, the Transformation team divided themselves between the front-line teams and they learned HCSE together.  Here’s a picture of the ED team … left to right we have Alex, Mark and Julie (ED consultants) then Steve and Janina (Transformation).  The essential tools are a big table, paper, pens, notebooks, coffee and a laptop/projector.

The purpose of each session is empirical learning-by-doing i.e. using a real improvement challenge to learn and practice the method so that before the end of the programme the team can confidently “fly” solo.

That is the key to continued growth and sustained improvement.  The HCSE capability needs to become embedded.

It is good fun and immensely rewarding to see the “ah ha” moments and improvements happen as the needle on the emotometer moves from “Can’t Do” to “Can Do”.

Metamorphosis is re-arranging what you already have in a way that works better.


The tweet is objective evidence that demonstrates the HCSE programme delivers as designed.  It is fit-for-purpose.  It is called validation.

The other objective evidence of effectiveness comes from the learning-by-doing projects themselves.  And for an individual to gain a coveted HCSE Level 1 Certificate of Competency requires writing up to a publishable quality and sharing the story. Warts-and-all.

To read the full story of just click here

And what started this was the CCG who had the strategic vision, looked outside themselves for innovative approaches, and demonstrated the courage to take a risk.

Commissioned Improvement.

One of the big hurdles in health care improvement is that most of the low hanging fruit have been harvested.

These are the small improvement projects that can be done quickly because as soon as the issue is made visible to the stakeholders the cause is obvious and the solution is too.

This is where kaizen works well.

The problem is that many health care issues are rather more difficult because the process that needs improving is complicated (i.e. it has lots of interacting parts) and usually exhibits rather complex behaviour (e.g. chaotic).

One good example of this is a one stop multidisciplinary clinic.

These are widely used in healthcare and for good reason.  It is better for a patient with a complex illness, such as diabetes, to be able to access whatever specialist assessment and advice they need when they need it … i.e. in an outpatient clinic.

The multi-disciplinary team (MDT) is more effective and efficient when it can problem-solve collaboratively.

The problem is that the scheduling design of a one stop clinic is rather trickier than a traditional simple-but-slow-and-sequential new-review-refer design.

A one stop clinic that has not been well-designed feels chaotic and stressful for both staff and patients and usually exhibits the paradoxical behaviour of waiting patients and waiting staff.


So what do we need to do?

We need to map and measure the process and diagnose the root cause of the chaos, and then treat it.  A quick kaizen exercise should do the trick. Yes?

But how do we map and measure the chaotic behaviour of lots of specialists buzzing around like blue-***** flies trying to fix the emergent clinical and operational problems on the hoof?  This is not the linear, deterministic, predictable, standardised machine-dominated production line environment where kaizen evolved.

One approach might be to get the staff to audit what they are doing as they do it. But that adds extra work, usually makes the chaos worse, fuels frustration and results in a very patchy set of data.

Another approach is to employ a small army of observers who record what happens, as it happens.  This is possible and it works, but to be able to do this well requires a lot of experience of the process being observed.  And even if that is achieved the next barrier is the onerous task of transcribing and analysing the ocean of harvested data.  And then the challenge of feeding back the results much later … i.e. when the sands have shifted.


So we need a different approach … one that is able to capture the fine detail of a complex process in real-time, with minimal impact on the process itself, and that can process and present the wealth of data in a visual easy-to-assess format, and in real-time too.

This is a really tough design challenge …
… and it has just been solved.

Here are two recent case studies that describe how it was done using a robust systems engineering method.

Abstract

Abstract

On Thursday we had a very enjoyable and educational day.  I say “we” because there were eleven of us learning together.

There was Declan, Chris, Lesley, Imran, Phil, Pete, Mike, Kate, Samar and Ellen and me (behind the camera).  Some are holding their long-overdue HCSE Level-1 Certificates and Badges that were awarded just before the photo was taken.

The theme for the day was System Dynamics which is a tried-and-tested approach for developing a deep understanding of how a complex adaptive system (CAS) actually works.  A health care system is a complex adaptive system.

The originator of system dynamics is Jay Wright Forrester who developed it around the end of WW2 (i.e. about 80 years ago) and who later moved to MIT.  Peter Senge, author of The Fifth Discipline was part of the same group as was Donella Meadows who wrote Limits to Growth.  Their dream was much bigger – global health – i.e. the whole planet not just the human passengers!  It is still a hot topic [pun intended].


The purpose of the day was to introduce the team of apprentice health care system engineers (HCSEs) to the principles of system dynamics and to some of its amazing visualisation and prediction techniques and tools.

The tangible output we wanted was an Excel-based simulation model that we could use to solve a notoriously persistent health care service management problem …

How to plan the number of new and review appointment slots needed to deliver a safe, efficient, effective and affordable chronic disease service?

So, with our purpose in mind, the problem clearly stated, and a blank design canvas we got stuck in; and we used the HCSE improvement-by-design framework that everyone was already familiar with.

We made lots of progress, learned lots of cool stuff, and had lots of fun.

We didn’t quite get to the final product but that was OK because it was a very tough design assignment.  We got 80% of the way there though which is pretty good in one day from a standing start.  The last 20% can now be done by the HCSEs themselves.

We were all exhausted at the end.  We had worked hard.  It was a good day.


And I am already looking forward to the next HCSE Masterclass that will be in about six weeks time.  This one will address another chronic, endemic, systemic health care system “disease” called carveoutosis multiforme fulminans.

This week saw the publication of a landmark paper – one that will bring hope to many.  A paper that describes the first step of a path forward out of the mess that healthcare seems to be in.  A rational, sensible, practical, learnable and enjoyable path.


This week I also came across an idea that triggered an “ah ha” for me.  The idea is that the most rapid learning happens when we are making mistakes about half of the time.

And when I say ‘making a mistake’ I mean not achieving what we predicted we would achieve because that implies that our understanding of the world is incomplete.  In other words, when the world does not behave as we expect, we have an opportunity to learn and to improve our ability to make more reliable predictions.

And that ability is called wisdom.


When we get what we expect about half the time, and do not get what we expect about the other half of the time, then we have the maximum amount of information that we can use to compare and find the differences.

Was it what we did? Was it what we did not do? What are the acts and errors of commission and omission? What can we learn from those? What might we do differently next time? What would we expect to happen if we do?


And to explore this terrain we need to see the world as it is … warts and all … and that is the subject of the landmark paper that was published this week.


The context of the paper is improvement of cancer service delivery, and specifically of reducing waiting time from referral to first appointment.  This waiting is a time of extreme anxiety for patients who have suspected cancer.

It is important to remember that most people with suspected cancer do not have it, so most of the work of an urgent suspected cancer (USC) clinic is to reassure and to relieve the fear that the spectre of cancer creates.

So, the sooner that reassurance can happen the better, and for the unlucky minority who are diagnosed with cancer, the sooner they can move on to treatment the better.

The more important paragraph in the abstract is the second one … which states that seeing the system behaviour as it is, warts-and-all,  in near-real-time, allows us to learn to make better decisions of what to do to achieve our intended outcomes. Wiser decisions.

And the reason this is the more important paragraph is because if we can do that for an urgent suspected cancer pathway then we can do that for any pathway.


The paper re-tells the first chapter of an emerging story of hope.  A story of how an innovative and forward-thinking organisation is investing in building embedded capability in health care systems engineering (HCSE), and is now delivering a growing dividend.  Much bigger than the investment on every dimension … better safety, faster delivery, higher quality and more affordability. Win-win-win-win.

The only losers are the “warts” – the naysayers and the cynics who claim it is impossible, or too “wicked”, or too difficult, or too expensive.

Innovative reality trumps cynical rhetoric … and the full abstract and paper can be accessed here.

So, well done to Chris Jones and the whole team in ABMU.

And thank you for keeping the candle of hope alight in these dark, stormy and uncertain times for the NHS.

This week, it was my great pleasure to award the first Health Care Systems Engineering (HCSE) Level 2 Medal to Dr Kate Silvester, MBA, FRCOphth.

Kate is internationally recognised as an expert in health care improvement and over more than two decades has championed the adoption of improvement methods such as Lean and Quality Improvement in her national roles in the Modernisation Agency and then the NHS Institute for Innovation and Improvement.

Kate originally trained as a doctor and then left the NHS to learn manufacturing systems engineering with Lucas and Airbus.  Kate then brought these very valuable skills back with her into the NHS when she joined the Cancer Services Collaborative.

Kate is co-founder of the Journal of Improvement Science and over the last five years has been highly influential in the development of the Health Care Systems Engineering Programme – the first of its kind in the world that is designed by clinicians for clinicians.

The HCSE Programme is built on the pragmatic See One-Do Some-Teach Many principle of developing competence and confidence through being trained and coached by a more experienced practitioner while doing projects of increasing complexity and training and coaching others who are less experienced.

Competence is based on evidence-of-effectiveness, and Kate has achieved HCSE Level 2 by demonstrating that she can do HCSE and that she can teach and coach others how to do HCSE as well.

To illustrate, here is a recent FHJ paper that Kate has authored which illustrates the HCSE principles applied in practice in a real hospital.  This work was done as part of the Health Foundation’s Flow, Cost and Quality project that Kate led and recent evidence proves that the improvements have sustained and spread.  South Warwickshire NHS Foundation Trust is now one of the top-performing Trusts in the NHS.

More recently, Kate has trained and coached new practitioners in Exeter and North Devon who have delivered improvements and earned their HCSE 1 wings.

Congratulations Kate!

One of the most frequent niggles that I hear from patients is the difficultly they have getting an appointment with their general practitioner.  I too have personal experience of the distress caused by the ubiquitous “Phone at 8AM for an Appointment” policy, so in June 2018 when I was approached to help a group of local practices redesign their appointment booking system I said “Yes, please!


What has emerged is a fascinating, enjoyable and rewarding journey of co-evolution of learning and co-production of an improved design.  The multi-skilled design team (MDT) we pulled together included general practitioners, receptionists and practice managers and my job was to show them how to use the health care systems engineering (HCSE) framework to diagnose, design, decide and deliver what they wanted: A safe, calm, efficient, high quality, value-4-money appointment booking service for their combined list of 50,000 patients.


This week they reached the start of the ‘decide and deliver‘ phase.  We have established the diagnosis of why the current booking system is not delivering what we all want (i.e. patients and practices), and we have assembled and verified the essential elements of an improved design.

And the most important outcome for me is that the Primary Care MDT now feel confident and capable to decide what and how to deliver it themselves.   That is what I call embedded capability and achieving it is always an emotional roller coaster ride that we call The Nerve Curve.

What we are dealing with here is called a complex adaptive system (CAS) which has two main components: Processes and People.  Both are complicated and behave in complex ways.  Both will adapt and co-evolve over time.  The processes are the result of the policies that the people produce.  The policies are the result of the experiences that the people have and the explanations that they create to make intuitive sense of them.

But, complex systems often behave in counter-intuitive ways, so our intuition can actually lead us to make unwise decisions that unintentionally perpetuate the problem we are trying to solve.  The name given to this is a wicked problem.

A health care systems engineer needs to be able to demonstrate where these hidden intuitive traps lurk, and to explain what causes them and how to avoid them.  That is the reason the diagnosis and design phase is always a bit of a bumpy ride – emotionally – our Inner Chimp does not like to be challenged!  We all resist change.  Fear of the unknown is hard-wired into us by millions of years of evolution.

But we know when we are making progress because the “ah ha” moments signal a slight shift of perception and a sudden new clarity of insight.  The cognitive fog clears a bit and a some more of the unfamiliar terrain ahead comes into view.  We are learning.

The Primary Care MDT have experienced many of these penny-drop moments over the last six months and unfortunately there is not space here to describe them all, but I can share one pivotal example.


A common symptom of a poorly designed process is a chronically chaotic queue.

[NB. In medicine the term chronic means “long standing”.  The opposite term is acute which means “recent onset”].

Many assume, intuitively, that the cause of a chronically chaotic queue is lack of capacity; hence the incessant calls for ‘more capacity’.  And it appears that we have learned this reflex response by observing the effect of adding capacity – which is that the queue and chaos abate (for a while).  So that proves that lack of capacity was the cause. Yes?

Well actually it doesn’t.  Proving causality requires a bit more work.  And to illustrate this “temporal association does not prove causality trap” I invite you to consider this scenario.

I have a headache => I take a paracetamol => my headache goes away => so the cause of my headache was lack of paracetamol. Yes?

Errr .. No!

There are many contributory causes of chronically chaotic queues and lack of capacity is not one of them because the queue is chronic.  What actually happens is that something else triggers the onset of chaos which then consumes the very resource we require to avoid the chaos.  And once we slip into this trap we cannot escape!  The chaos-perpretuating behaviour we observe is called fire-fighting and the necessary resource it consumes is called resilience.


Six months ago, the Primary Care MDT believed that the cause of their chronic appointment booking chaos was a mismatch between demand and capacity – i.e. too much patient demand for the appointment capacity available.  So, there was a very reasonable resistance to the idea of making the appointment booking process easier for patients – they justifiably feared being overwhelmed by a tsunami of unmet need!

Six months on, the Primary Care MDT understand what actually causes chronic queues and that awareness has been achieved by a step-by-step process of explanation and experimentation in the relative safety of the weekly design sessions.

We played simulation games – lots of them.

One particularly memorable “Ah Ha!” moment happened when we played the Carveout Game which is done using dice, tiddly-winks, paper and coloured-pens.  No computers.  No statistics.  No queue theory gobbledygook.  No smoke-and-mirrors.  No magic.

What the Carveout Game demonstrates, practically and visually, is that an easy way to trigger the transition from calm-efficiency to chaotic-ineffectiveness is … to impose a carveout policy on a system that has been designed to achieve optimum efficiency by using averages.  Boom!  We slip on the twin banana skins of the Flaw-of-Averages and Sub-Optimisation, slide off the performance cliff, and career down the rocky slope of Chronic Chaos into the Depths of Despair – from which we cannot then escape.

This visual demonstration was a cognitive turning point for the MDT.  They now believed that there is a rational science to improvement and from there we were on the step-by-step climb to building the necessary embedded capability.


It now felt like the team were pulling what they needed to know.  I was no longer pushing.  We had flipped from push-to-pull.  That is called the tipping point.

And that is how health care systems engineering (HCSE) works.


Health care is a complex adaptive system, and what a health care systems engineer actually “designs” is a context-sensitive  incubator that nurtures the seeds of innovation that already exist in the system and encourages them to germinate, grow and become strong enough to establish themselves.

That is called “embedded improvement-by-design capability“.

And each incubator need to be different – because each system is different.  One-solution-fits-all-problems does not work here just as it does not in medicine.  Each patient is both similar and unique.


Just as in medicine, first we need to diagnose the actual cause;  second we need to design some effective solutions; third we need to decide which design to implement and fourth we need to deliver it.

But the how-to-do-it feels a bit counter-intuitive, and if it were not we would already be doing it. But the good news is that anyone can learn how to do HCSE.