Creep-Crack-Crunch

The current crisis of confidence in the NHS has all the hallmarks of a classic system behaviour called creep-crack-crunch.

The first obvious crunch may feel like a sudden shock but it is usually not a complete surprise and it is actually one of a series of cracks that are leading up to a BIG CRUNCH. These cracks are an early warning sign of pressure building up in parts of the system and causing localised failures. These cracks weaken the whole system. The underlying cause is called creep.

SanFrancisco_PostEarthquake

Earthquakes are a perfect example of this phenomemon. Geological time scales are measured in thousands of years and we now know that the surface of the earth is a dynamic structure with vast contient-sized plates of solid rock floating on a liquid core of molten magma. Over millions of years the continents have moved huge distances and the world we see today on our satellite images is just a single frame in a multi-billion year geological video.  That is the geological creep bit. The cracks first appear at the edges of these tectonic plates where they smash into each other, grind past each other or are pulled apart from each other.  The geological hot-spots are marked out on our global map by lofty mountain ranges, fissured earthquake zones, and deep mid-ocean trenches. And we know that when a geological crunch arrives it happens in a blink of the geological eye.

The panorama above shows the devastation of San Francisco caused by the 1906 earthquake. San Francisco is built on the San Andreas Fault – the junction between the Pacific plate and the North American plate. The dramatic volcanic eruption in Iceland in 2010 came and went in a matter of weeks but the irreversible disruption it caused for global air traffic will be felt for years. The undersea earthquakes that caused the devastating tsunamis in 2006 and 2011 lasted only a few minutes; the deadly shock waves crossed an ocean in a matter of hours; and when they arrived the silent killer wiped out whole shoreside communities in seconds. Tens of thousands of lives were lost and the social after-shocks of that geological-crunch will be felt for decades.

These are natural disasters. We have little or no influence over them. Human-engineered disasters are a different matter – and they are just as deadly.

The NHS is an example. We are all painfully aware of the recent crisis of confidence triggered by the Francis Report. Many could see the cracks appearing and tried to blow their warning whistles but with little effect – they were silenced with legal gagging clauses and the opening cracks were papered over. It was only after the crunch that we finally acknowledged what we already knew and we started to search for the creep. Remorse and revenge does not bring back those who have been lost.  We need to focus on the future and not just point at the past.

UK_PopulationPyramid_2013Socio-economic systems evolve at a pace that is measured in years. So when a social crunch happens it is necessary to look back several decades for the tell-tale symptoms of creep and the early signs of cracks appearing.

Two objective measures of a socio-economic system are population and expenditure.

Population is people-in-progress; and national expenditure is the flow of the cash required to keep the people-in-progress watered, fed, clothed, housed, healthy and occupied.

The diagram above is called a population pyramid and it shows the distribution by gender and age of the UK population in 2013. The wobbles tell a story. It does rather look like the profile of a bushy-eyebrowed, big-nosed, pointy-chinned old couple standing back-to-back and maybe there is a hidden message for us there?

The “eyebrow” between ages 67 and 62 is the increase in births that happened 62 to 67 years ago: betwee 1946 and 1951. The post WWII baby boom.  The “nose” of 42-52 year olds are the “children of the 60’s” which was a period of rapid economic growth and new optimism. The “upper lip” at 32-42 correlates with the 1970’s that was a period of stagnant growth,  high inflation, strikes, civil unrest and the dark threat of global thermonuclear war. This “stagflation” is now believed to have been triggered by political meddling in the Middle-East that led to the 1974 OPEC oil crisis and culminated in the “winter of discontent” in 1979.  The “chin” signals there was another population expansion in the 1980s when optimism returned (SALT-II was signed in 1979) and the economy was growing again. Then the “neck” contraction in the 1990’s after the 1987 Black Monday global stock market crash.  Perhaps the new optimism of the Third Millenium led to the “chest” expansion but the financial crisis that followed the sub-prime bubble to burst in 2008 has yet to show its impact on the population chart. This static chart only tells part of the story – the animated chart reveals a significant secondary expansion of the 20-30 year old age group over the last decade. This cannot have been caused by births and is evidence of immigration of a large number of young couples – probably from the expanding Europe Union.

If this “yo-yo” population pattern is repeated then the current economic downturn will be followed by a contraction at the birth end of the spectrum and possibly also net emigration. And that is a big worry because each population wave takes a 100 years to propagate through the system. The most economically productive population – the  20-60 year olds  – are the ones who pay the care bills for the rest. So having a population curve with lots of wobbles in it causes long term socio-economic instability.

Using this big-picture long-timescale perspective; evidence of an NHS safety and quality crunch; silenced voices of cracks being papered-over; let us look for the historical evidence of the creep.

Nowadays the data we need is literally at our fingertips – and there is a vast ocean of it to swim around in – and to drown in if we are not careful.  The Office of National Statistics (ONS) is a rich mine of UK socioeconomic data – it is the source of the histogram above.  The trick is to find the nuggets of knowledge in the haystack of facts and then to convert the tables of numbers into something that is a bit more digestible and meaningful. This is what Russ Ackoff descibes as the difference between Data and Information. The data-to-information conversion needs context.

Rule #1: Data without context is meaningless – and is at best worthless and at worse is dangerous.

boxes_connected_PA_150_wht_2762With respect to the NHS there is a Minotaur’s Labyrinth of data warehouses – it is fragmented but it is out there – in cyberspace. The Department of Health publishes some on public sites but it is a bit thin on context so it can be difficult to extract the meaning.

Relying on our memories to provide the necessary context is fraught with problems. Memories are subject to a whole range of distortions, deletions, denials and delusions.  The NHS has been in existence since 1948 and there are not many people who can personally remember the whole story with objective clarity.  Fortunately cyberspace again provides some of what we need and with a few minutes of surfing we can discover something like a website that chronicles the history of the NHS in decades from its creation in 1948 – http://www.nhshistory.net/ – created and maintained by one person and a goldmine of valuable context. The decade that is of particular interest is 1998-2007 – Chapter 6

With just some data and some context it is possible to pull together the outline of the bigger picture of the decade that led up to the Mid Staffordshire healthcare quality crunch.

We will look at this as a NHS system evolving over time within its broader UK context. Here is the time-series chart of the population of England – the source of the demand on the NHS.

Population_of_England_1984-2010This shows a significant and steady increase in population – 12% overall between 1984 an 2012.

This aggregate hides a 9% increase in the under 65 population and 29% growth in the over 65 age group.

This is hard evidence of demographic creep – a ticking health and social care time bomb. And the curve is getting steeper. The pressure is building.

The next bit of the map we need is a measure of the flow through hospitals – the activity – and this data is available as the annual HES (Hospital Episodes Statistics) reports.  The full reports are hundreds of pages of fine detail but the headline summaries contain enough for our present purpose.

NHS_HES_Admissions_1997-2011

The time- series chart shows a steady increase in hospital admissions. Drilling into the summaries revealed that just over a third are emergency admissions and the rest are planned or maternity.

In the decade from 1998 to 2008 there was a 25% increase in hospital activity. This means more work for someone – but how much more and who for?

But does it imply more NHS beds?

Beds require wards, buildings and infrastructure – but it is the staff that deliver the health care. The bed is just a means of storage.  One measure of capacity and cost is the number of staffed beds available to be filled.  But this like measuring the number of spaces in a car park – it does not say much about flow – it is a just measure of maximum possible work in progress – the available space to hold the queue of patients who are somewhere between admission and discharge.

Here is the time series chart of the number of NHS beds from 1984 to 2006. The was a big fall in the number of beds in the decade after 1984 [Why was that?]

NHS_Beds_1984-2006

Between 1997 and 2007 there was about a 10% fall in the number of beds. The NHS patient warehouse was getting smaller.

But the activity – the flow – grew by 25% over the same time period: so the Laws Of Physics say that the flow must have been faster.

The average length of stay must have been falling.

This insight has another implication – fewer beds must mean smaller hospitals and lower costs – yes?  After all everyone seems to equate beds-to-cost; more-beds-cost-more less-beds-cost-less. It sounds reasonable. But higher flow means more demand and more workload so that would require more staff – and that means higher costs. So which is it? Less, the same or more cost?

NHS_Employees_1996_2007The published data says that staff headcount  went up by 25% – which correlates with the increase in activity. That makes sense.

And it looks like it “jumped” up in 2003 so something must have triggered that. More cash pumped into the system perhaps? Was that the effect of the Wanless Report?

But what type of staff? Doctors? Nurses? Admin and Clerical? Managers?  The European Working Time Directive (EWTD) forced junior doctors hours down and prompted an expansion of consultants to take on the displaced service work. There was also a gradual move towards specialisation and multi-disciplinary teams. What impact would that have on cost? Higher most likely. The system is getting more complex.

Of course not all costs have the same impact on the system. About 4% of staff are classified as “management” and it is this group that are responsible for strategic and tactical planning. Managers plan the work – workers work the plan.  The cost and efficiency of the management component of the system is not as useful a metric as the effectiveness of its collective decision making. Unfortuately there does not appear to be any published data on management decision making qualty and effectiveness. So we cannot estimate cost-effectiveness. Perhaps that is because it is not as easy to measure effectiveness as it is to count admissions, discharges, head counts, costs and deaths. Some things that count cannot easily be counted. The 4% number is also meaningless. The human head represents about 4% of the bodyweight of an adult person – and we all know that it is not the size of our heads that is important it is the effectiveness of the decisions that it makes which really counts!  Effectiveness, efficiency and costs are not the same thing.

Back to the story. The number of beds went down by 10% and number of staff went up by 25% which means that the staff-per-bed ratio went up by nearly 40%.  Does this mean that each bed has become 25% more productive or 40% more productive or less productive? [What exactly do we mean by “productivity”?]

To answer that we need to know what the beds produced – the discharges from hospital and not just the total number, we need the “last discharges” that signal the end of an episode of hospital care.

NHS_LastDischarges_1998-2011The time-series chart of last-discharges shows the same pattern as the admissions: as we would expect.

This output has two components – patients who leave alive and those who do not.

So what happened to the number of deaths per year over this period of time?

That data is also published annually in the Hospital Episode Statistics (HES) summaries.

This is what it shows ….

NHS_Absolute_Deaths_1998-2011The absolute hospital mortality is reducing over time – but not steadily. It went up and down between 2000 and 2005 – and has continued on a downward trend since then.

And to put this into context – the UK annual mortality is about 600,000 per year. That means that only about 40% of deaths happen in hospitals. UK annual mortality is falling and births are rising so the population is growing bigger and older.  [My head is now starting to ache trying to juggle all these numbers and pictures in it].

This is not the whole story though – if the absolute hospital activity is going up and the absolute hospital mortality is going down then this raw mortality number may not be telling the whole picture. To correct for those effects we need the ratio – the Hospital Mortality Ratio (HMR).

NHS_HospitalMortalityRatio_1998-2011This is the result of combining these two metrics – a 40% reduction in the hospital mortality ratio.

Does this mean that NHS hospitals are getting safer over time?

This observed behaviour can be caused by hospitals getting safer – it can also be caused by hospitals doing more low-risk work that creates a dilution effect. We would need to dig deeper to find out which. But that will distract us from telling the story.

Back to productivity.

The other part of the productivity equation is cost.

So what about NHS costs?  A bigger, older population, more activity, more staff, and better outcomes will all cost more taxpayer cash, surely! But how much more?  The activity and head count has gone up by 25% so has cost gone up by the same amount?

NHS_Annual_SpendThis is the time-series chart of the cost per year of the NHS and because buying power changes over time it has been adjusted using the Consumer Price Index using 2009 as the reference year – so the historical cost is roughly comparable with current prices.

The cost has gone up by 100% in one decade!  That is a lot more than 25%.

The published financial data for 2006-2010 shows that the proportion of NHS spending that goes to hospitals is about 50% and this has been relatively stable over that period – so it is reasonable to say that the increase in cash flowing to hospitals has been about 100% too.

So if the cost of hospitals is going up faster than the output then productivity is falling – and in this case it works out as a 37% drop in productivity (25% increase in activity for 100% increase in cost = 37% fall in productivity).

So the available data which anyone with a computer, an internet connection, and some curiosity can get; and with bit of spreadsheet noggin can turn into pictures shows that over the decade of growth that led up to the the Mid Staffs crunch we had:

1. A slightly bigger population; and a
2. significantly older population; and a
3. 25% increase in NHS hospital activity; and a
4. 10% fall in NHS beds; and a
5. 25% increase in NHS staff; which gives a
6. 40% increase in staff-per-bed ratio; an an
7. 8% reduction in absolute hospital mortality; which gives a
8. 40% reduction in relative hospital mortality; and a
9. 100% increase in NHS  hospital cost; which gives a
10. 37% fall drop in “hospital productivity”.

An experienced Improvement Scientist knows that a system that has been left to evolve by creep-crack-and-crunch can be re-designed to deliver higher quality and higher flow at lower total cost.

The safety creep at Mid-Staffs is now there for all to see. A crack has appeared in our confidence in the NHS – and raises a couple of crunch questions:

Where Has All The Extra Money Gone?

 How Will We Avoid The BIG CRUNCH?

The huge increase in NHS funding over the last decade was the recommendation of the Wanless Report but the impact of implementing the recommendations has never been fully explored. Healthcare is a service system that is designed to deliver two intangible products – health and care. So the major cost is staff-time – particularly the clinical staff.  A 25% increase in head count and a 100% increase in cost implies that the heads are getting more expensive.  Either a higher proportion of more expensive clinically trained and registered staff, or more pay for the existing staff or both.  The evidence shows that about 50% of NHS Staff are doctors and nurses and over the last decade there has been a bigger increase in the number of doctors than nurses. Added to that the Agenda for Change programme effectively increased the total wage bill and the new contracts for GPs and Consultants added more upward wage pressure.  This is cost creep and it adds up over time. The Kings Fund looked at the impact in 2006 and suggested that, in that year alone, 72% of the additional money was sucked up by bigger wage bills and other cost-pressures! The previous year they estimated 87% of the “new money” had disappeared hte same way. The extra cash is gushing though the cracks in the bottom of the fiscal bucket that had been clumsily papered-over. And these are recurring revenue costs so they add up over time into a future financial crunch.  The biggest one may be yet to come – the generous final-salary pensions that public-sector employees enjoy!

So it is even more important that the increasingly expensive clinical staff are not being forced to spend their time doing work that has no direct or indirect benefit to patients.

Trying to do a good job in a poorly designed system is both frustrating and demotivating – and the outcome can be a cynical attitude of “I only work here to pay the bills“. But as public sector wages go up and private sector pensions evaporate the cynics are stuck in a miserable job that they cannot afford to give up. And their negative behaviour poisons the whole pool. That is the long term cumulative cultural and financial cost of poor NHS process design. That is the outcome of not investing earlier in developing an Improvement Science capability.

The good news is that the time-series charts illustrate that the NHS is behaving like any other complex, adaptive, human-engineered value system. This means that the theory, techniques and tools of Improvement Science and value system design can be applied to answer these questions. It means that the root causes of the excessive costs can be diagnosed and selectively removed without compromising safety and quality. It means that the savings can be wisely re-invested to improve the resilience of some parts and to provide capacity in other parts to absorb the expected increases in demand that are coming down the population pipe.

This is Improvement Science. It is a learnable skill.

18/03/2013: Update

The question “Where Has The Money Gone?” has now been asked at the Public Accounts Committee

 

What Can I Do To Help?

stick_figures_moving_net_150_wht_8609The growing debate about the safety of our health care systems is gaining momentum.

This is not just a UK phenomenon.

The same question was being asked 10 years ago across the pond by many people – perhaps the most familiar name is Don Berwick.

The term Improvement Science has been buzzing around for a long time. This is a global – not just a local challenge.

Seeing the shameful reality in black-and-white [the Francis Report] is a nasty shock to everyone. There are no winners here. Our blissful ignorance is gone. Painful awareness has arrived.

The usual emotional reaction to being shoved from blissful ignorance into painful awareness is characteristic;  and it does not matter if it is discovering horse in your beef pie or hearing of 1200 avoidable deaths in a UK hospital.

Our emotional reaction is a predictable sequence that goes something like:

Shock => Denial => Anger =>Bargaining =>Depression =>Acceptance

=> Resolution.

It is the psychological healing process that is called the grief reaction and it is a normal part of the human psyche. We all do it. And we do it both individually and collectively. I remember well the global grief reactions that followed the sudden explosion of Challenger; the sudden death of Princess Diana; and the sudden collapse of the Twin Towers.

Fortunately such avoidable tragedies are uncommon.

The same chain-reaction happens to a lesser degree in any sudden change. We grieve the loss of our old way of thinking – we mourn the passing away our comfortable rhetoric that has been rudely and suddenly disproved by harsh reality. This is the Nerve Curve.  And learning to ride it safely is a critical-to-survival life skill.  Especially in turbulent times.

The UK population has suffered two psychological shocks in recent weeks – the discovery of horse in the beef pie and the fuller public disclosure of the story behind the 1000’s of avoidable deaths in one of our Trust hospitals. Both are now escalating and the finger of blame is pointing squarely at a common cause: the money-tail-wagging-the-safety-dog.

So what will happen next?  The Wall of Denial has been dynamited with hard evidence. We are now into the Collective Anger phase.

First there will be widespread righteous indignation and a strong desire to blame, to hunt down the evil ones, and to crucify the responsible and accountable. Partly as punishment, partly as a lesson to others, and partly to prevent them doing harm again.  Uncontrolled anger is dangerous especially when there is a lethal weapon to hand. The more controlled, action-oriented and future-focused will want to do something about it. Now! There will be rallies, and soap-boxes, and megaphones. The We-Told-You-So brigade will get shoved aside and trampled in the rush to do something – ANYTHING. Conferences will be hastily arranged and those most fearful for their reputations and jobs will cough up the cash and clear their diaries. They will be expected to be there. They will be. Desperately looking for answers. Anxiously seeking credible leaders. And the snake-oil salesmen will have a bonanza! The calmer, more reflective, phlegmatic, academic types will call for more money for more research so that we can fully analyse and fully understand the problem before we do anything.

And while the noisy bargaining for more cash keeps everyone busy the harm will continue to happen.

Eventually the message will sink in as the majority accept that there is no way to change the past; that we cannot cling to what is out-of-date thinking; and that all of our new-reality-avoiding tactics are fruitless. And we are forced to accept that there is no more cash. Now we are in danger of becoming helpless and hopeless, slipping into depression, and then into despair. We are at risk of giving up and letting ourselves wallow and drown in self-pity. This is a dangerous phase. Depression is understandable but it is avoidable because there is always something than can be done. We can always ask the elephant-in-the-room questions. Inside we usually know the answers.

We accept the new reality; we accept that we cannot change the past, we accept that we have some learning to do; we accept that we have to adjust; and we accept that all of us can do something.

Now we have reached the most important stage – resolution. This is the test of our resolve. Are we all-talk or can we convert talk-to-walk?

stick_figure_help_button_150_wht_9911We can all ask ourselves one question: “What can I do to help?”

I have asked myself that question and my first answer was “As a system designer I can help by looking at this challenge as a design assignment and describe what I see “.

Design starts with the intended outcome, the vision, the goal, the objective, the specification, the target.

The design goal is: Significant reduction in avoidable harm in the NHS, quickly, and at no extra cost.

[Please note that a design goal is a “what we get” not a “what we do”. It is a purpose and not just a process.]

Now we can invite, gather, dream-up, brain-storm any number of design options and then we can consider logically and rationally how well they might meet our design goal.

What are some of the design options on the table?

Design Option 1. Create a cadre of hospital inspectors.

Nope – that will take time and money and inspection alone does not guarantee better outcomes. We have enough evidence of that.

Design Option 2. Get lots more PhDs funded, do high quality academic research, write papers, publish them and hope the evidence is put into practice.

Nope – that will take time and money too and publication alone does not guarantee adoption of the lessons and delivery of better outcomes. We have enough evidence of that too. What is proven to be efficacious in a research trial is not necessarily effective, practical or affordable  in reality.  

Design Option 3. Put together conferences and courses to teach/train a new generation of competent healthcare improvement practitioners.

Maybe – it has the potential to deliver the outcome but it too will take time and money. We have been doing conferences and courses for decades – they are not very cost-effective. The Internet may have changed things though. 

Design Option 4. All of the above plus broadcast via the Internet the current pragmatic know-how of the basics of safe system design to everyone in the NHS so that they know what is possible and they know how to get started.

Promising – it has the greatest potential to deliver the required outcome, a broadcast will cost nothing and it can start working immediately.

OK – Option 4 it is – here we go …

The Basics of How To Design a Safe System

Definition 1: Safe means free of risk of harm.

Definition 2Harm is the result of hazards combining with risks.

There are two components to safe system design – the people stuff and the process stuff.

For example a busy main road is designed to facilitate the transport of stuff from A to B. It also represents a hazard – the potential for harm. If the vehicles bump into each other or other things then harm will result. So a lot of the design of the vehicles and the roads is about reducing the risk of bumps or mitigating the effects (e.g. seat-belts).

The risk is multi-factorial. If you drive at high speed, under the influence of recreational drugs, at night, on an icy road then the probability of having a bump is high.  If you step into a busy road without looking then the risk of getting bumped into is high too.

So the path to better safety is to eliminate as many hazards as possible and to reduce the risks as much as possible. And we have to do that without unintentionally creating more hazards, higher risks, excessive delays and higher costs.

So how is this done outside healthcare?

One tried-and-tested method for designing safer processes is called FMEA – Failure Modes and Effects Analysis.

Now that sounds really nerdy and it is.  It is an attention-to-detail exercise that will make your brain ache and your eyes bleed. But it works – so it is worthwhile learning the basic principles.

For the people part there is the whole body of Human Factors Research to access. This is also a bit nerdy for us hands-on oily-rag pragmatists so if you want something more practical immediately then have a go with The 4N Chart and the Niggle-o-Gram (which is a form of emotional FMEA). This short summary is also free to download, read, print, copy, share, discuss and use.

OK – I am off to design and build something else – an online course for teaching safety-by-design.

What are you going to do to help improve safety in the NHS?

The Writing on the Wall – Part II

Who_Is_To_BlameThe retrospectoscope is the favourite instrument of the forensic cynic – the expert in the after-the-event-and-I-told-you-so rhetoric. The rabble-rouser for the lynch-mob.

It feels better to retrospectively nail-to-a-cross the person who committed the Cardinal Error of Omission, and leave them there in emotional and financial pain as a visible lesson to everyone else.

This form of public feedback has been used for centuries.

It is called barbarism, and it has no place in a modern civilised society.


A more constructive question to ask is:

Could the evolving Mid-Staffordshire crisis have been detected earlier … and avoided?”

And this question exposes a tricky problem: it is much more difficult to predict the future than to explain the past.  And if it could have been detected and avoided earlier, then how is that done?  And if the how-is-known then is everyone else in the NHS using this know-how to detect and avoid their own evolving Mid-Staffs crisis?

To illustrate how it is currently done let us use the actual Mid-Staffs data. It is conveniently available in Figure 1 embedded in Figure 5 on Page 360 in Appendix G of Volume 1 of the first Francis Report.  If you do not have it at your fingertips I have put a copy of it below.

MS_RawData

The message does not exactly leap off the page and smack us between the eyes does it? Even with the benefit of hindsight.  So what is the problem here?

The problem is one of ergonomics. Tables of numbers like this are very difficult for most people to interpret, so they create a risk that we ignore the data or that we just jump to the bottom line and miss the real message. And It is very easy to miss the message when we compare the results for the current period with the previous one – a very bad habit that is spread by accountants.

This was a slowly emerging crisis so we need a way of seeing it evolving and the better way to present this data is as a time-series chart.

As we are most interested in safety and outcomes, then we would reasonably look at the outcome we do not want – i.e. mortality.  I think we will all agree that it is an easy enough one to measure.

MS_RawDeathsThis is the raw mortality data from the table above, plotted as a time-series chart.  The green line is the average and the red-lines are a measure of variation-over-time. We can all see that the raw mortality is increasing and the red flags say that this is a statistically significant increase. Oh dear!

But hang on just a minute – using raw mortality data like this is invalid because we all know that the people are getting older, demand on our hospitals is rising, A&Es are busier, older people have more illnesses, and more of them will not survive their visit to our hospital. This rise in mortality may actually just be because we are doing more work.

Good point! Let us plot the activity data and see if there has been an increase.

MS_Activity

Yes – indeed the activity has increased significantly too.

Told you so! And it looks like the activity has gone up more than the mortality. Does that mean we are actually doing a better job at keeping people alive? That sounds like a more positive message for the Board and the Annual Report. But how do we present that message? What about as a ratio of mortality to activity? That will make it easier to compare ourselves with other hospitals.

Good idea! Here is the Raw Mortality Ratio chart.

MS_RawMortality_RatioAh ha. See! The % mortality is falling significantly over time. Told you so.

Careful. There is an unstated assumption here. The assumption that the case mix is staying the same over time. This pattern could also be the impact of us doing a greater proportion of lower complexity and lower risk work.  So we need to correct this raw mortality data for case mix complexity – and we can do that by using data from all NHS hospitals to give us a frame of reference. Dr Foster can help us with that because it is quite a complicated statistical modelling process. What comes out of Dr Fosters black magic box is the Global Hospital Raw Mortality (GHRM) which is the expected number of deaths for our case mix if we were an ‘average’ NHS hospital.

MS_ExpectedMortality_Ratio

What this says is that the NHS-wide raw mortality risk appears to be falling over time (which may be for a wide variety of reasons but that is outside the scope of this conversation). So what we now need to do is compare this global raw mortality risk with our local raw mortality risk  … to give the Hospital Standardised Mortality Ratio.

MS_HSMRThis gives us the Mid Staffordshire Hospital HSMR chart.  The blue line at 100 is the reference average – and what this chart says is that Mid Staffordshire hospital had a consistently higher risk than the average case-mix adjusted mortality risk for the whole NHS. And it says that it got even worse after 2001 and that it stayed consistently 20% higher after 2003.

Ah! Oh dear! That is not such a positive message for the Board and the Annual Report. But how did we miss this evolving safety catastrophe?  We had the Dr Foster data from 2001

This is not a new problem – a similar thing happened in Vienna between 1820 and 1850 with maternal deaths caused by Childbed Fever. The problem was detected by Dr Ignaz Semmelweis who also discovered a simple, pragmatic solution to the problem: hand washing.  He blew the whistle but unfortunately those in power did not like the implication that they had been the cause of thousands of avoidable mother and baby deaths.  Semmelweis was vilified and ignored, and he did not publish his data until 1861. And even then the story was buried in tables of numbers.  Semmelweis went mad trying to convince the World that there was a problem.  Here is the full story.

Also, time-series charts were not invented until 1924 – and it was not in healthcare – it was in manufacturing. These tried-and-tested safety and quality improvement tools are only slowly diffusing into healthcare because the barriers to innovation appear somewhat impervious.

And the pores have been clogged even more by the social poison called “cynicide” – the emotional and political toxin exuded by cynics.

So how could we detect a developing crisis earlier – in time to avoid a catastrophe?

The first step is to estimate the excess-death-equivalent. Dr Foster does this for you.MS_ExcessDeathsHere is the data from the table plotted as a time-series chart that shows that the estimated-excess-death-equivalent per year. It has an average of 100 (that is two per week) and the average should be close to zero. More worryingly the number was increasing steadily over time up to 200 per year in 2006 – that is about four excess deaths per week – on average.  It is important to remember that HSMR is a risk ratio and mortality is a multi-factorial outcome. So the excess-death-equivalent estimate does not imply that a clear causal chain will be evident in specific deaths. That is a complete misunderstanding of the method.

I am sorry – you are losing me with the statistical jargon here. Can you explain in plain English what you mean?

OK. Let us use an example.

Suppose we set up a tombola at the village fete and we sell 50 tickets with the expectation that the winner bags all the money. Each ticket holder has the same 1 in 50 risk of winning the wad-of-wonga and a 49 in 50 risk of losing their small stake. At the appointed time we spin the barrel to mix up the ticket stubs then we blindly draw one ticket out. At that instant the 50 people with an equal risk changes to one winner and 49 losers. It is as if the grey fog of risk instantly condenses into a precise, black-and-white, yes-or-no, winner-or-loser, reality.

Translating this concept back into HSMR and Mid Staffs – the estimated 1200 deaths are the just the “condensed risk of harm equivalent”.  So, to then conduct a retrospective case note analysis of specific deaths looking for the specific cause would be equivalent to trying to retrospectively work out the reason the particular winning ticket in the tombola was picked out. It is a search that is doomed to fail. To then conclude from this fruitless search that HSMR is invalid, is only to compound the delusion further.  The actual problem here is ignorance and misunderstanding of the basic Laws of Physics and Probability, because our brains are not good at solving these sort of problems.

But Mid Staffs is a particularly severe example and  it only shows up after years of data has accumulated. How would a hospital that was not as bad as this know they had a risk problem and know sooner? Waiting for years to accumulate enough data to prove there was a avoidable problem in the past is not much help. 

That is an excellent question. This type of time-series chart is not very sensitive to small changes when the data is noisy and sparse – such as when you plot the data on a month-by-month timescale and avoidable deaths are actually an uncommon outcome. Plotting the annual sum smooths out this variation and makes the trend easier to see, but it delays the diagnosis further. One way to increase the sensitivity is to plot the data as a cusum (cumulative sum) chart – which is conspicuous by its absence from the data table. It is the running total of the estimated excess deaths. Rather like the running total of swings in a game of golf.

MS_ExcessDeaths_CUSUMThis is the cusum chart of excess deaths and you will notice that it is not plotted with control limits. That is because it is invalid to use standard control limits for cumulative data.  The important feature of the cusum chart is the slope and the deviation from zero. What is usually done is an alert threshold is plotted on the cusum chart and if the measured cusum crosses this alert-line then the alarm bell should go off – and the search then focuses on the precursor events: the Near Misses, the Not Agains and the Niggles.

I see. You make it look easy when the data is presented as pictures. But aren’t we still missing the point? Isn’t this still after-the-avoidable-event analysis?

Yes! An avoidable death should be a Never-Event in a designed-to-be-safe healthcare system. It should never happen. There should be no coffins to count. To get to that stage we need to apply exactly the same approach to the Near-Misses, and then the Not-Agains, and eventually the Niggles.

You mean we have to use the SUI data and the IR1 data and the complaint data to do this – and also ask our staff and patients about their Niggles?

Yes. And it is not the number of complaints that is the most useful metric – it is the appearance of the cumulative sum of the complaint severity score. And we need a method for diagnosing and treating the cause of the Niggles too. We need to convert the feedback information into effective action.

Ah ha! Now I understand what the role of the Governance Department is: to apply the tools and techniques of Improvement Science proactively.  But our Governance Department have not been trained to do this!

Then that is one place to start – and their role needs to evolve from Inspectors and Supervisors to Demonstrators and Educators – ultimately everyone in the organisation needs to be a competent Healthcare Improvementologist.

OK – I now now what to do next. But wait a minute. This is going to cost a fortune!

This is just one small first step.  The next step is to redesign the processes so the errors do not happen in the first place. The cumulative cost saving from eliminating the repeated checking, correcting, box-ticking, documenting, investigating, compensating and insuring is much much more than the one-off investment in learning safe system design.

So the Finance Director should be a champion for safety and quality too.

Yup!

Brill. Thanks. And can I ask one more question? I do not want to appear to skeptical but how do we know we can trust that this risk-estimation system has been designed and implemented correctly? How do we know we are not being bamboozled by statisticians? It has happened before!

That is the best question yet.  It is important to remember that HSMR is counting deaths in hospital which means that it is not actually the risk of harm to the patient that is measured – it is the risk to the reputation of hospital! So the answer to your question is that you demonstrate your deep understanding of the rationle and method of risk-of-harm estimation by listing all the ways that such a system could be deliberately “gamed” to make the figures look better for the hospital. And then go out and look for hard evidence of all the “games” that you can invent. It is a sort of creative poacher-becomes-gamekeeper detective exercise.

OK – I sort of get what you mean. Can you give me some examples?

Yes. The HSMR method is based on deaths-in-hospital so discharging a patient from hospital before they die will make the figures look better. Suppose one hospital has more access to end-of-life care in the community than another: their HSMR figures would look better even though exactly the same number of people died. Another is that the HSMR method is weighted towards admissions classified as “emergencies” – so if a hospital admits more patients as “emergencies” who are not actually very sick and discharges them quickly then this will inflated their estimated deaths and make their actual mortality ratio look better – even though the risk-of-harm to patients has not changed.

OMG – so if we have pressure to meet 4 hour A&E targets and we get paid more for an emergency admission than an A&E attendance then admitting to an Assessmen Area and discharging within one day will actually reward the hospital financially, operationally and by apparently reducing their HSMR even though there has been no difference at all to the care that patients actually recieve?

Yes. It is an inevitable outcome of the current system design.

But that means that if I am gaming the system and my HSMR is not getting better then the risk-of-harm to patients is actually increasing and my HSMR system is giving me false reassurance that everything is OK.   Wow! I can see why some people might not want that realisation to be public knowledge. So what do we do?

Design the system so that the rewards are aligned with lower risk of harm to patients and improved outcomes.

Is that possible?

Yes. It is called a Win-Win-Win design.

How do we learn how to do that?

Improvement Science.

Footnote I:

The graphs tell a story but they may not create a useful sense of perspective. It has been said that there is a 1 in 300 chance that if you go to hospital you will not leave alive for avoidable causes. What! It cannot be as high as 1 in 300 surely?

OK – let us use the published Mid-Staffs data to test this hypothesis. Over 12 years there were about 150,000 admissions and an estimated 1,200 excess deaths (if all the risk were concentrated into the excess deaths which is not what actually happens). That means a 1 in 130 odds of an avoidable death for every admission! That is twice as bad as the estimated average.

The Mid Staffordshire statistics are bad enough; but the NHS-as-a-whole statistics are cumulatively worse because there are 100’s of other hospitals that are each generating not-as-obvious avoidable mortality. The data is very ‘noisy’ so it is difficult even for a statistical expert to separate the message from the morass.

And remember – that  the “expected” mortality is estimated from the average for the whole NHS – which means that if this average is higher than it could be then there is a statistical bias and we are being falsely reassured by being ‘not statistically significantly different’ from the pack.

And remember too – for every patient and family that suffers and avoidable death there are many more that have to live with the consequences of avoidable but non-fatal harm.  That is called avoidable morbidity.  This is what the risk really means – everyone has a higher risk of some degree of avoidable harm. Psychological and physical harm.

This challenge is not just about preventing another Mid Staffs – it is about preventing 1000’s of avoidable deaths and 100,000s of patients avoidably harmed every year in ‘average’ NHS trusts.

It is not a mass conspiracy of bad nurses, bad doctors, bad managers or bad policians that is the root cause.

It is poorly designed processes – and they are poorly designed because the nurses, doctors and managers have not learned how to design better ones.  And we do not know how because we were not trained to.  And that education gap was an accident – an unintended error of omission.  

Our urgently-improve-NHS-safety-challenge requires a system-wide safety-by-design educational and cultural transformation.

And that is possible because the knowledge of how to design, test and implement inherently safe processes exists. But it exists outside healthcare.

And that safety-by-design training is a worthwhile investment because safer-by-design processes cost less to run because they require less checking, less documenting, less correcting – and all the valuable nurse, doctor and manager time freed up by that can be reinvested in more care, better care and designing even better processes and systems.

Everyone Wins – except the cynics who have a choice: to eat humble pie or leave.

Footnote II:

In the debate that has followed the publication of the Francis Report a lot of scrutiny has been applied to the method by which an estimated excess mortality number is created and it is necessary to explore this in a bit more detail.

The HSMR is an estimate of relative risk – it does not say that a set of specific patients were the ones who came to harm and the rest were OK. So looking at individual deaths and looking for the specific causes is to completely misunderstand the method. So looking at the actual deaths individually and looking for identifiable cause-and-effect paths is an misuse of the message.  When very few if any are found to conclude that HSMR is flawed is an error of logic and exposes the ignorance of the analyst further.

HSMR is not perfect though – it has weaknesses.  It is a benchmarking process the”standard” of 100 is always moving because the collective goal posts are moving – the reference is always changing . HSMR is estimated using data submitted by hospitals themselves – the clinical coding data.  So the main weakness is that it is dependent on the quality of the clinicial coding – the errors of comission (wrong codes) and the errors of omission (missing codes). Garbage In Garbage Out.

Hospitals use clinically coded data for other reasons – payment. The way hospitals are now paid is based on the volume and complexity of that activity – Payment By Results (PbR) – using what are called Health Resource Groups (HRGs). This is a better and fairer design because hospitals with more complex (i.e. costly to manage) case loads get paid more per patient on average.  The HRG for each patient is determined by their clinical codes – including what are called the comorbidities – the other things that the patient has wrong with them. More comorbidites means more complex and more risky so more money and more risk of death – roughly speaking.  So when PbR came in it becamevery important to code fully in order to get paid “properly”.  The problem was that before PbR the coding errors went largely unnoticed – especially the comorbidity coding. And the errors were biassed – it is more likely to omit a code than to have an incorrect code. Errors of omission are harder to detect. This meant that by more complete coding (to attract more money) the estimated casemix complexity would have gone up compared with the historical reference. So as actual (not estimated) NHS mortality has gone down slightly then the HSMR yardstick becomes even more distorted.  Hospitals that did not keep up with the Coding Game would look worse even though  their actual risk and mortality may be unchanged.  This is the fundamental design flaw in all types of  benchmarking based on self-reported data.

The actual problem here is even more serious. PbR is actually a payment for activity – not a payment for outcomes. It is calculated from what it cost to run the average NHS hospital using a technique called Reference Costing which is the same method that manufacturing companies used to decide what price to charge for their products. It has another name – Absorption Costing.  The highest performers in the manufacturing world no longer use this out-of-date method. The implication of using Reference Costing and PbR in the NHS are profound and dangerous:

If NHS hospitals in general have poorly designed processes that create internal queues and require more bed days than actually necessary then the cost of that “waste” becomes built into the future PbR tariff. This means average length of stay (LOS) is financially rewarded. Above average LOS is financially penalised and below average LOS makes a profit.  There is no financial pressure to improve beyound average. This is called the Regression to the Mean effect.  Also LOS is not a measure of quality – so there is a to shorten length of stay for purely financial reasons – to generate a surplus to use to fund growth and capital investment.  That pressure is non-specific and indiscrimiate.  PbR is necessary but it is not sufficient – it requires an quality of outcome metric to complete it.    

So the PbR system is based on an out-of-date cost-allocation model and therefore leads to the very problems that are contributing to the MidStaffs crisis – financial pressure causing quality failures and increased risk of mortality.  MidStaffs may be a chance victim of a combination of factors coming together like a perfect storm – but those same factors are present throughout the NHS because they are built into the current design.

One solution is to move towards a more up-to-date financial model called stream costing. This uses the similar data to reference costing but it estimates the “ideal” cost of the “necessary” work to achieve the intended outcome. This stream cost becomes the focus for improvement – the streams where there is the biggest gap between the stream cost and the reference cost are the focus of the redesign activity. Very often the root cause is just poor operational policy design; sometimes it is quality and safety design problems. Both are solvable without investment in extra capacity. The result is a higher quality, quicker, lower-cost stream. Win-win-win. And in the short term that  is rewarded by a tariff income that exceeds cost and a lower HSMR.

Radically redesigning the financial model for healthcare is not a quick fix – and it requires a lot of other changes to happen first. So the sooner we start the sooner we will arrive. 

Robert Francis QC

press_on_screen_anim_150_wht_7028Today is an important day.

The Robert Francis QC Report and recommendations from the Mid-Staffordshire Hospital Crisis has been published – and it is a sobering read.  The emotions that just the executive summary evoked in me were sadness, shame and anger.  Sadness for the patients, relatives, and staff who have been irreversibly damaged; shame that the clinical professionals turned a blind-eye; and anger that the root cause has still not been exposed to public scrutiny.

Click here to get a copy of the RFQC Report Executive Summary.

Click here to see the video of RFQC describing his findings. 

The root cause is ignorance at all levels of the NHS.  Not stupidity. Not malevolence. Just ignorance.

Ignorance of what is possible and ignorance of how to achieve it.

RFQC rightly focusses his recommendations on putting patients at the centre of healthcare and on making those paid to deliver care accountable for the outcomes.  Disappointingly, the report is notably thin on the financial dimension other than saying that financial targets took priority over safety and quality.  He is correct. They did. But the report does not say that this is unnecessary – it just says “in future put safety before finance” and in so doing he does not challenge the belief that we are playing a zero-sum-game. The  assumotion that higher-quality-always-costs-more.

This assumption is wrong and can easily be disproved.

A system that has been designed to deliver safety-and-quality-on-time-first-time-and-every-time costs less. And it costs less because the cost of errors, checking, rework, queues, investigation, compensation, inspectors, correctors, fixers, chasers, and all the other expensive-high-level-hot-air-generation-machinery that overburdens the NHS and that RFQC has pointed squarely at is unnecessary.  He says “simplify” which is a step in the right direction. The goal is to render it irrelevent.

The ignorance is ignorance of how to design a healthcare system that works right-first-time. The fact that the Francis Report even exists and is pointing its uncomfortable fingers-of-evidence at every level of the NHS from ward to government is tangible proof of this collective ignorance of system design.

And the good news is that this collective ignorance is also unnecessary … because the knowledge of how to design safe-and-affordable systems already exists. We just have to learn how. I call it 6M Design® – but  the label is irrelevent – the knowledge exists and the evidence that it works exists.

So here are some of the RFQC recommendations viewed though a 6M Design® lens:       

1.131 Compliance with the fundamental standards should be policed by reference to developing the CQC’s outcomes into a specification of indicators and metrics by which it intends to monitor compliance. These indicators should, where possible, be produced by the National Institute for Health and Clinical Excellence (NICE) in the form of evidence-based procedures and practice which provide a practical means of compliance and of measuring compliance with fundamental standards.

This is the safety-and-quality outcome specification for a healthcare system design – the required outcome presented as a relevent metric in time-series format and qualified by context.  Only a stable outcome can be compared with a reference standard to assess the system capability. An unstable outcome metric requires inquiry to understand the root cause and an appropriate action to restore stability. A stable but incapable outcome performance requires redesign to achieve both stability and capability. And if  the terms used above are unfamiliar then that is further evidence of system-design-ignorance.   
 
1.132 The procedures and metrics produced by NICE should include evidence-based tools for establishing the staffing needs of each service. These measures need to be readily understood and accepted by the public and healthcare professionals.

This is the capacity-and-cost specification of any healthcare system design – the financial envelope within which the system must operate. The system capacity design works backwards from this constraint in the manner of “We have this much resource – what design of our system is capable of delivering the required safety and quality outcome with this capacity?”  The essence of this challenge is to identify the components of poor (i.e. wasteful) design in the existing systems and remove or replace them with less wasteful designs that achieve the same or better quality outcomes. This is not impossible but it does require system diagnostic and design capability. If the NHS had enough of those skills then the Francis Report would not exist.

1.133 Adoption of these practices, or at least their equivalent, is likely to help ensure patients’ safety. Where NICE is unable to produce relevant procedures, metrics or guidance, assistance could be sought and commissioned from the Royal Colleges or other third-party organisations, as felt appropriate by the CQC, in establishing these procedures and practices to assist compliance with the fundamental standards.

How to implement evidence-based research in the messy real world is the Elephant in the Room. It is possible but it requires techniques and tools that fall outside the traditional research and audit framework – or rather that sit between research and audit. This is where Improvement Science sits. The fact that the Report only mentions evidence-based practice and audit implies that the NHS is still ignorant of this gap and what fills it – and so it appears is RFQC.   

1.136 Information needs to be used effectively by regulators and other stakeholders in the system wherever possible by use of shared databases. Regulators should ensure that they use the valuable information contained in complaints and many other sources. The CQC’s quality risk profile is a valuable tool, but it is not a substitute for active regulatory oversight by inspectors, and is not intended to be.

Databases store data. Sharing databases will share data. Data is not information. Information requires data and the context for that data.  Furthermore having been informed does not imply either knowledge or understanding. So in addition to sharing information, the capability to convert information-into-decision is also required. And the decisions we want are called “wise decisions” which are those that result in actions and inactions that lead inevitably to the intended outcome.  The knowledge of how to do this exists but the NHS seems ignorant of it. So the challenge is one of education not of yet more investigation.

1.137 Inspection should remain the central method for monitoring compliance with fundamental standards. A specialist cadre of hospital inspectors should be established, and consideration needs to be given to collaborative inspections with other agencies and a greater exploitation of peer review techniques.

This is audit. This is the sixth stage of a 6M Design® – the Maintain step.  Inspectors need to know what they are looking for, the errors of commission and the errors of omission;  and to know what those errors imply and what to do to identify and correct the root cause of these errors when discovered. The first cadre of inspectors will need to be fully trained in healthcare systems design and healthcare systems improvement – in short – they need to be Healthcare Improvementologists. And they too will need to be subject to the same framework of accreditation, and accountability as those who work in the system they are inspecting.  This will be one of the greatest of the challenges. The fact that the Francis report exists implies that we do not have such a cadre. Who will train, accredit and inspect the inspectors? Who has proven themselves competent in reality (not rhetorically)?

1.163 Responsibility for driving improvement in the quality of service should therefore rest with the commissioners through their commissioning arrangements. Commissioners should promote improvement by requiring compliance with enhanced standards that demand more of the provider than the fundamental standards.

This means that commissioners will need to understand what improvement requires and to include that expectation in their commissioning contracts. This challenge is even geater that the creation of a “cadre of inspectors”. What is required is a “generation of competent commissioners” who are also experienced and who have demonstrated competence in healthcare system design. The Commissioners-of-the-Future will need to be experienced healthcare improvementologists.

The NHS is sick – very sick. The medicine it needs to restore its health and vitality does exist – and it will not taste very nice – but to withold an effective treatment for an serious illness on that basis is clinical negligence.

It is time for the NHS to look in the mirror and take the strong medicine. The effect is quick – it will start to feel better almost immediately. 

To deliver safety and quality and quickly and affordably is possible – and if you do not believe that then you will need to muster the humility to ask to have the how demonstrated.

6MDesign

 

Kicking the Habit

no_smoking_400_wht_6805It is not easy to kick a habit. We all know that. And for some reason the ‘bad’ habits are harder to kick than the ‘good’ ones. So what is bad about a ‘bad habit’ and why is it harder to give up? Surely if it was really bad it would be easier to give up?

Improvement is all about giving up old ‘bad’ habits and replacing them with new ‘good’ habits – ones that will sustain the improvement. But there is an invisible barrier that resists us changing any habit – good or bad. And it is that barrier to habit-breaking that we need to understand to succeed. Luck is not a reliable ally.

What does that habit-breaking barrier look like?

The problem is that it is invisible – or rather it is emotional – or to be precise it is chemical.

Our emotions are the output of a fantastically complex chemical system – our brains. And influencing the chemical balance of our brains can have a profound effect on our emotions.  That is how anti-depressants work – they very slightly adjust the chemical balance of every part of our brains. The cumulative effect is that we feel happier.  Nicotine has a similar effect.

And we can achieve the same effect without resorting to drugs or fags – and we can do that by consciously practising some new mental habits until they become ingrained and unconscious. We literally overwrite the old mental habit.

So how do we do this?

First we need to make the mental barrier visible – and then we can focus our attention on eroding it. To do that we need to remove the psychological filter that we all use to exclude our emotions. It is rather like taking off our psychological sunglasses.

When we do that the invisible barrier jumps into view: illuminated by the glare of three negative emotions.  Sadness, fear, and anxiety.  So whenever we feel any of these we know there is a barrier to improvement hiding  the emotional smoke. This is the first stage: tune in to our emotions.

The next step is counter-intuitive. Instead of running away from the negative feeling we consciously flip into a different way of thinking.  We actively engage with our negative feelings – and in a very specific way. We engage in a detached, unemotional, logical, rational, analytical  ‘What caused that negative feeling?’ way.

We then focus on the causes of the negative emotions. And when we have the root causes of our Niggles we design around them, under them, and over them.  We literally design them out of our heads.

The effect is like magic.

And this week I witnessed a real example of this principle in action.

figure_pressing_power_button_150_wht_10080One team I am working with experienced the Power of Improvementology. They saw the effect with their own eyes.  There were no computers in the way, no delays, no distortion and no deletion of data to cloud the issue. They saw the performance of their process jump dramatically – from a success rate of 60% to 96%!  And not just the first day, the second day too.  “Surprised and delighted” sums up their reaction.

So how did we achieve this miracle?

We just looked at the process through a different lens – one not clouded and misshapen by old assumptions and blackened by ignorance of what is possible.  We used the 6M Design® lens – and with the clarity of insight it brings the barriers to improvement became obvious. And they were dissolved. In seconds.

Success then flowed as the Dam of Disbelief crumbled and was washed away.

figure_check_mark_celebrate_anim_150_wht_3617The chaos has gone. The interruptions have gone. The expediting has gone. The firefighting has gone. The complaining has gone.  These chronic Niggles have have been replaced by the Nuggets of calm efficiency, new hope and visible excitement.

And we know that others have noticed the knock-on effect because we got an email from our senior executive that said simply “No one has moaned about TTOs for two days … something has changed.”    

That is Improvementology-in-Action.

 

Defusing Trust Eroders – Part III

<Bing Bong>

laptop_mail_PA_150_wht_2109Leslie’s computer heralded the arrival of yet another email!  They were coming in faster and faster – now that the word had got out on the grapevine about Improvementology

Leslie glanced at the sender. It was from Bob. That was a surprise. Bob had never emailed out-of-the-blue before.  Leslie was too impatient to wait until later to read the email.

<Dear Leslie, could I trouble you to ask your advice on something. It is not urgent.  A ten minute chat on the phone would be all I need. If that is OK please let me know a good time is and I will ring you. Bob>

Leslie was consumed with curiosity. What could Bob possibly want advice on? It was Leslie who sought advice from Bob – not the other way around.

Leslie could not wait and emailed back immediately that it was OK to talk now.

<Ring Ring>

Hello Bob, what a pleasant surprise! I am very curious to know what you need my advice about.

? Thank you Leslie.  What I would like your counsel on is how to engage in learning the science of improvement.

Wow!  That is a surprising question. I am really confused now. You helped me to learn this new thinking and now you are asking me to teach you?

? Yes. On the surface it seems counter-intuitive. It is a genuine request though. I need to learn and understand what works for you and what does not.

OK. I think I am getting an idea of what you are asking.  But I am only just getting grips with the basics. I do not know how to engage others yet and I certainly would not be able to teach anyone!

? I must apologise. I was not clear in my request. I need to understand how you engaged yourself in learning. I only provided the germ of the idea – it was you who added what was needed for it to develop into something tangible and valuable for you.  I need to understand how that happened.

Ahhhh! I see what you mean. Yes. Let me think. Would it help if I describe my current mental metaphor?

? That sounds like an excellent plan.

OK. Well your phrase ‘germ of an idea’ was a trigger. I see the science of improvement as a seed of information that grows into a sturdy tree of understanding.  Just like the ‘tiny acorn into the mighty oak’ concept.  Using that seed-to-tree metaphor helped me to appreciate that the seed is necessary but it is not sufficient. There are other things that are needed too. Soil, water, air, sunlight, and protection from hazards and predators.

I then realised that the seed-to-tree metaphor goes deeper.  One insight that I had was when I realised that the first few leaves are critical to success – because they provide the ongoing energy and food to support the growth of more leaves, and the twigs, branches, trunk, and roots that support the leaves and supply them with water and nutrients.  I see the tree as synergistic system that has a common purpose: to become big enough and stable enough to be able to survive the inevitable ups-and-downs of reality. To weather the winter storms and survive the summer droughts.

plant_metaphor_240x135It seemed to me that the first leaf needed to be labelled ‘safety’ because in our industry if we damage our customers or our staff we do not get a second chance!  The next leaf to grow is labelled ‘quality’ and that means quality-by-design.  Doing the right thing and doing it right first time without needing inspection-and-correction. The safety and quality leaves provide the resources needed to grow the next leaf which I labelled ‘delivery’.  Getting the work done in time, on time, every time.  Together these three leaves support the growth of the fourth – ‘economy’ which means using only what is necessaryand also having just enough reserve to ride over the inevitable rocks and ruts in the road of reality.

I then reflected on what the water and the sunshine would represent when applying improvement science in the real world.

It occurred to me that the water in the tree is like money in a real system.  It is required for both growth and health; it must flow to where it is needed, when it is needed and as much as needed. Too little will prevent growth, and too much water at the wrong time and wrong place is just as unhealthy.  I did some reading about the biology of trees and I learned that the water is pulled up the tree! The ‘suck’ is created by the water evaporating from the leaves. The plant does not have a committee that decides where the available water should go! It is a simple self-adjusting system.  

The sunshine for the tree is like feedback for people. In a plant the suns energy provides the motive force for the whole system.  In our organisations we call it motivation and the feedback loop is critical to success. Keeping people in the dark about what is required and how they are doing is demotivating.  Healthy organisations are feedback-fuelled!

? Yes. I see the picture in my mind clearly. That is a powerful metaphor. How did it help overcome the natural resistance to change?

Well using the 6M Design method and taking the ‘sturdy tree of understanding’ as the objective of the seed-to-tree process I then considered what the possible ways it could fail – the failure modes and effects analysis method that you taught me.

? OK. Yes I see how that approach would help – approaching the problem from the far side of the invisible barrier. What insights did that lead to?

poison_faucet_150_wht_9860Well it highlighted that just having enough water and enough sunshine was not sufficient – it had to be clean water and the right sort of sunshine.  The quality is as critical as the quantity. A toxic environment will kill tender new shoots of improvement long before they can get established.  Cynicism is like cyanide! Non-specific cost cutting is like blindly wielding a pair of sharp secateurs. Ignoring the competition from wasteful weeds and political predators is a guaranteed recipe-for-failure too.       

This metaphor really helped because it allowed me to draw up a checklist of necessary conditions for successful growth of knowledge and understanding.  Rather like the shopping list that a gardener might have. Viable seeds, fertile soil, clean water, enough sunlight, and protection from threats and hazards, especially in the early stages. And patience. Growing from seed takes time. Not all seeds will germinate. Not all seeds can thrive in the context our gardener is able to create.  And the harsher the elements the fewer the types of seed that have any chance of survival. The conditions select the successful seeds. Deserts select plants that hoard water so the desert remains a desert. If money is too tight the miserly will thrive at the expense of the charitable – and money remains hoarded and fought over as the organisation withers. And the timing is crucial – the seeds need to be planted at the right time in the cycle of change.  Too early and they cannot germinateg, too late and they do not have time to become strong enough to survive in the real world.    

? Yes. I see. The deeper you dig into your seeds-to-trees metaphor the more insightful it becomes.

Bob, you just said something really profound then that has unlocked something for me.

? Did I? What was it?

RainForestYou said ‘seeds-to-trees’.  Up until you said that I was unconsciously limiting myself to one-seed-to-one-tree. Of course! If it works for the individual it can work for the collective.  Woods and forests are collectives. The best example I can think of is a tropical rainforest.  With ample water and sunshine the plant-collective creates a synergistic system that has endured millions of years of global climate change. And one of the striking features of the tropical rain forest is the diversity of species. It is as if that diversity is an important part of the design. Competition is ever present though – all the trees compete for sunlight – but it is healthy competition. Trees do not succeed individually by hunting each other down. And the diversity seems to be an important component of healthy competition too. It is as if they are in a shared race to the sun and their differences are an asset rather than a liability. If all the trees were the same the forest would be at greater risk of all making the same biological blunder and suddenly becoming extinct if their environment changes unpredictably.  Uniformity only seems to work in harsh conditions.

? That is a profound observation Leslie. I had not consciously made that distinction.

So have I answered your question? Have I helped you? It has certainly helped me by being asked to putting my thoughts into words. I see it clearer too now.

? Yes. You are a good teacher. I believe others will resonate with your seeds-to-trees metaphor just as I have.

Thank you Bob. I believe I am beginning to understand something you said in a previous conversation – “the teacher is the person who learns the most”.  I am going to test our seeds-to-trees metaphor on the real world! And I will feedback what I learn – because in doing that I will amplify and clarify my own learning.

? Thank you Leslie. I look forward to learning with you.


Defusing Trust Eroders – Part I

Defusing Trust Eroders – Part II


The F Word

There is an F-word that organisations do not like to use – except maybe in conspiratorial corridor conversations.

What word might that be? What are good candidates for it?

Finance perhaps?

Certainly a word that many people do not want to utter – especially when the financial picture is not looking very rosy. And when the word finance is mentioned in meetings there is usually a groan of anguish. So yes, finance is a good candidate – but it is not the F-word.

Failure maybe?

Yes – definitely a word that is rarely uttered openly. The concept of failure is just not acceptable. Organisations must succeed, sustain and grow. Talk of failure is for losers not for winners. To talk about failure is tempting fate. So yes, another excellent candidate – but it is not the F-word.

OK – what about Fear?

That is definitely something no one likes to admit to.  Especially leaders. They are expected to be fearless. Fear is a sign of weakness! Once you start letting the fear take over then panic starts to set in – then rash decisions follow then you are really on the slippery slope. Your organisation fragments into warring factions and your fate is sealed. That must be the F-word!

Nope.  It is another very worthy candidate but it is not the F-word.


[reveal heading=”Click here to reveal the F-word“]


The dreaded F-word is Feedback.

We do not like feedback.  We do not like asking for it. We do not like giving it. We do not like talking about it. Our systems seem to be specifically designed to exclude it. Potentially useful feedback information is kept secret, confidential, for-our-eyes only.  And if it is shared it is emasculated and anonymized.

And the brave souls who are prepared to grasp the nettle – the 360 Feedback Zealots – are forced to cloak feedback with secrecy and confidentiality. We are expected to ask  for feedback, to take it on the chin, but not to know who or where it came from. So to ease the pain of anonymous feedback we are allowed to choose our accusers. So we choose those who we think will not point out our blindspot. Which renders the whole exercise worthless.

And when we actually want feedback we extract it mercilessly – like extracting blood from a reluctant stone. And if you do not believe me then consider this question: Have you ever been to a training course where your ‘certificate of attendance’ was with-held until you had completed the feedback form? The trainers do this for good reason. We just hate giving feedback. Any feedback. Positive or negative. So if they do not extract it from us before we leave they do not get any.

Unfortunately by extracting feedback from us under coercion is like acquiring a confession under torture – it distorts the message and renders it worthless.

What is the problem here?  What are we scared of?


We all know the answer to the question.  We just do not want to point at the elephant in the room.

We are all terrified of discovering that we have the organisational equivalent of body-odour. Something deeply unpleasant about our behaviour that we are blissfully unaware of but that everyone else can see as plain as day. Our behaviour blindspot. The thing we would cringe with embarrassment about if we knew. We are social animals – not solitary ones. We need on feedback yet we fear it too.

We lack the courage and humility to face our fear so we resort to denial. We avoid feedback like the plague. Feedback becomes the F-word.

But where did we learn this feedback phobia?

Maybe we remember the playground taunts from the Bullies and their Sychophants? From the poisonous Queen-Bees and their Wannabees?  Maybe we tried to protect ourselves with incantations that our well-meaning parents taught us. Spells like “Sticks and stones may break my bones but names will never hurt me“.  But being called names does hurt. Deeply. And it hurts because we are terrified that there might be some truth in the taunt.

Maybe we learned to turn a blind-eye and a deaf-ear; to cross the street at the first sign of trouble; to turn the other cheek? Maybe we just learned to adopt the Victim role? Maybe we were taught to fight back? To win at any cost? Maybe we were not taught how to defuse the school yard psycho-games right at the start?  Maybe our parents and teachers did not know how to teach us? Maybe they did not know themselves?  Maybe the ‘innocent’ schoolyard games are actually much more sinister?  Maybe we carry them with us as habitual behaviours into adult life and into our organisations? And maybe the bullies and Queen-Bees learned something too? Maybe they learned that they could get away with it? Maybe they got to like the Persecutor role and its seductive musk of power? If so then then maybe the very last thing the Bullies and Queen-Bees will want to do is to encourage open, honest feedback – especially about their behaviour. Maybe that is the root cause of the conspiracy of silence? Maybe?

But what is the big deal here?

The ‘big deal’ is that this cultural conspiracy of silence is toxic.  It is toxic to trust. It is toxic to teams. It is toxic to morale.  It is toxic to motivation. It is toxic to innovation. It is toxic to improvement. It is so toxic that it kills organisations – from the inside. Slowly.

Ouch! That feels uncomfortably realistic. So what is the problem again – exactly?

The problem is a deliberate error of omission – the active avoidance of feedback.

So ….. if it were that – how would we prove that is the root cause? Eh?

By correcting the error of omission and then observing what happens.


And this is where it gets dangerous for leaders. They are skating on politically thin ice and they know it.

Subjective feedback is very emotive.  If we ask ten people for their feedback on us we will get ten different replies – because no two people perceive the world (and therefore us) the same way.  So which is ‘right’? Which opinions do we take heed of and which ones do we discount? It is a psycho-socio-political minefield. So no wonder we avoid stepping onto the cultural barbed-wire!

There is an alternative.  Stick to reality and avoid rhetoric. Stick to facts and avoid feelings. Feed back the facts of how the organisational system is behaving to everyone in the organisation.

And the easiest way to do that is with three time-series charts that are updated and shared at regular and frequent intervals.

First – the count of safety and quality failure near-misses for each interval – for at least 50 intervals.

Second – the delivery time of our product or service for each customer over the same time period.

Third – the revenue generated and the cost incurred for each interval for the same 50 intervals.

No ratios, no targets, no balanced scorecard.

Just the three charts that paint the big picture of reality. And it might not be a very pretty picture.

But why at least 50 intervals?

So we can see the long term and short term variation over time. We need both … because …

Our Safety Chart shows that near misses keep happening despite all the burden of inspection and correction.

Our Delivery Chart shows that our performance is distorted by targets and the Horned Gaussian stalks us.

Our Viability Chart shows that our costs are increasing as we pay dearly for past mistakes and our revenue is decreasing as our customers protect their purses and their persons by staying away.

That is the not-so-good news.

The good news is that as soon as we have a multi-dimensional-frequent-feedback loop installed we will start to see improvement. It happens like magic. And the feedback accelerates the improvement.

And the news gets better.

To make best use of this frequent feedback we just need to include in our Constant Purpose – to improve safety, delivery and viability. And then the final step is to link the role of every person in the organisation to that single win-win-win goal. So that everyone can see how they contribute and how their job is worthwhile.

Shared Goals, Clear Roles and Frequent Feedback.

And if you resonate with this message then you will resonate with “The Three Signs of  Miserable Job” by Patrick Lencioni.

And if you want to improve your feedback-ability then a really simple and effective feedback tool is The 4N Chart

And please share your feedback.

[/reveal]

A Recipe for Improvement PIE.

Most of us are realists. We have to solve problems in the real world so we prefer real examples and step-by-step how-to-do recipes.

A minority of us are theorists and are more comfortable with abstract models and solving rhetorical problems.

Many of these Improvement Science blog articles debate abstract concepts – because I am a strong iNtuitor by nature. Most realists are Sensors – so by popular request here is a “how-to-do” recipe for a Productivity Improvement Exercise (PIE)

Step 1 – Define Productivity.

There are many definitions we could choose because productivity means the results delivered divided by the resources used.  We could use any of the three currencies – quality, time or money – but the easiest is money. And that is because it is easier to measure and we have well established department for doing it – Finance – the guardians of the money.  There are two other departments who may need to be involved – Governance (the guardians of the safety) and Operations (the guardians of the delivery).

So the definition we will use is productivity = revenue generated divided cost incurred.

Step 2 – Draw a map of the process we want to make more productive.

This means creating a picture of the parts and their relationships to each other – in particular what the steps in the process are; who does what, where and when; what is done in parallel and what is done in sequence; what feeds into what and what depends on what. The output of this step is a diagram with boxes and arrows and annotations – called a process map. It tells us at a glance how complex our process is – the number of boxes and the number of arrows.  The simpler the process the easier it is to demonstrate a productivity improvement quickly and unambiguously.

Step 3 – Decide the objective metrics that will tell us our productivity.

We have chosen a finanical measure of productivity so we need to measure revenue and cost over time – and our Finance department do that already so we do not need to do anything new. We just ask them for the data. It will probably come as a monthly report because that is how Finance processes are designed – the calendar month accounting cycle is not negotiable.

We will also need some internal process metrics (IPMs) that will link to the end of month productivity report values because we need to be observing our process more often than monthly. Weekly, daily or even task-by-task may be necessary – and our monthly finance reports will not meet that time-granularity requirement.

These internal process metrics will be time metrics.

Start with objective metrics and avoid the subjective ones at this stage. They are necessary but they come later.

Step 4 – Measure the process.

There are three essential measures we usually need for each step in the process: A measure of quality, a measure of time and a measure of cost.  For the purposes of this example we will simplify by making three assumptions. Quality is 100% (no mistakes) and Predictability is 100% (no variation) and Necessity is 100% (no worthless steps). This means that we are considering a simplified and theoretical situation but we are novices and we need to start with the wood and not get lost in the trees.

The 100% Quality means that we do not need to worry about Governance for the purposes of this basic recipe.

The 100% Predictability means that we can use averages – so long as we are careful.

The 100% Necessity means that we must have all the steps in there or the process will not work.

The best way to measure the process is to observe it and record the events as they happen. There is no place for rhetoric here. Only reality is acceptable. And avoid computers getting in the way of the measurement. The place for computers is to assist the analysis – and only later may they be used to assist the maintenance – after the improvement has been achieved.

Many attempts at productivity improvement fail at this point – because there is a strong belief that the more computers we add the better. Experience shows the opposite is usually the case – adding computers adds complexity, cost and the opportunity for errors – so beware.

Step 5 – Identify the Constraint Step.

The meaning of the term constraint in this context is very specific – it means the step that controls the flow in the whole process.  The critical word here is flow. We need to identify the current flow constraint.

A tap or valve on a pipe is a good example of a flow constraint – we adjust the tap to control the flow in the whole pipe. It makes no difference how long or fat the pipe is or where the tap is, begining, middle or end. (So long as the pipe is not too long or too narrow or the fluid too gloopy because if they are then the pipe will become the flow constraint and we do not want that).

The way to identify the constraint in the system is to look at the time measurements. The step that shows the same flow as the output is the constraint step. (And remember we are using the simplified example of no errors and no variation – in real life there is a bit more to identifying the constraint step).

Step 6 – Identify the ideal place for the Constraint Step.

This is the critical-to-success step in the PIE recipe. Get this wrong and it will not work.

This step requires two pieces of measurement data for each step – the time data and the cost data. So the Operational team and the Finance team will need to collaborate here. Tricky I know but if we want improved productivity then there is no alternative.

Lots of productivity improvement initiatives fall at the Sixth Fence – so beware.  If our Finance and Operations departments are at war then we should not consider even starting the race. It will only make the bad situation even worse!

If they are able to maintain an adult and respectful face-to-face conversation then we can proceed.

The time measure for each step we need is called the cycle time – which is the time interval from starting one task to being ready to start the next one. Please note this is a precise definition and it should be used exactly as defined.

The money measure for each step we need is the fully absorbed cost of time of providing the resource.  Your Finance department will understand that – they are Masters of FACTs!

The magic number we need to identify the Ideal Constraint is the product of the Cycle Time and the FACT – the step with the highest magic number should be the constraint step. It should control the flow in the whole process. (In reality there is a bit more to it than this but I am trying hard to stay out of the trees).

Step 7 – Design the capacity so that the Ideal Constraint is the Actual Constraint.

We are using a precise definition of the term capacity here – the amount of resource-time available – not just the number of resources available. Again this is a precise definition and should be used as defined.

The capacity design sequence  means adding and removing capacity to and from steps so that the constraint moves to where we want it.

The sequence  is:
7a) Set the capacity of the Ideal Constraint so it is capable of delivering the required activity and revenue.
7b) Increase the capacity of the all the other steps so that the Ideal Constraint actually controls the flow.
7c) Reduce the capacity of each step in turn, a click at a time until it becomes the constraint then back off one click.

Step 8 – Model your whole design to predict the expected productivity improvement.

This is critical because we are not interested in suck-it-and-see incremental improvement. We need to be able to decide if the expected benefit is worth the effort before we authorise and action any changes.  And we will be asked for a business case. That necessity is not negotiable either.

Lots of productivity improvement projects try to dodge this particularly thorny fence behind a smoke screen of a plausible looking business case that is more fiction than fact. This happens when any of Steps 2 to 7 are omitted or done incorrectly.  What we need here is a model and if we are not prepared to learn how to build one then we should not start. It may only need a simple model – but it will need one. Intuition is too unreliable.

A model is defined as a simplified representation of reality used for making predictions.

All models are approximations of reality. That is OK.

The art of modeling is to define the questions the model needs to be designed to answer (and the precision and accuracy needed) and then design, build and test the model so that it is just simple enough and no simpler. Adding unnecessary complexity is difficult, time consuming, error prone and expensive. Using a computer model when a simple pen-and-paper model would suffice is a good example of over-complicating the recipe!

Many productivity improvement projects that get this far still fall at this fence.  There is a belief that modeling can only be done by Marvins with brains the size of planets. This is incorrect.  There is also a belief that just using a spreadsheet or modelling software is all that is needed. This is incorrect too. Competent modelling requires tools and training – and experience because it is as much art as science.

Step 9 – Modify your system as per the tested design.

Once you have demonstrated how the proposed design will deliver a valuable increase in productivity then get on with it.

Not by imposing it as a fait accompli – but by sharing the story along with the rationale, real data, explanation and results. Ask for balanced, reasoned and respectful feedback. The question to ask is “Can you think of any reasons why this would not work?” Very often the reply is “It all looks OK in theory but I bet it won’t work in practice but I can’t explain why”. This is an emotional reaction which may have some basis in fact. It may also just be habitual skepticism/cynicism. Further debate is usually  worthless – the only way to know for sure is by doing the experiment. As an experiment – as a small-scale and time-limited pilot. Set the date and do it. Waiting and debating will add no value. The proof of the pie is in the eating.

Step 10 – Measure and maintain your system productivity.

Keep measuring the same metrics that you need to calculate productivity and in addition monitor the old constraint step and the new constraint steps like a hawk – capturing their time metrics for every task – and tracking what you see against what the model predicted you should see.

The correct tool to use here is a system behaviour chart for each constraint metric.  The before-the-change data is the baseline from which improvement is measured over time;  and with a dot plotted for each task in real time and made visible to all the stakeholders. This is the voice of the process (VoP).

A review after three months with a retrospective financial analysis will not be enough. The feedback needs to be immediate. The voice of the process will dictate if and when to celebrate. (There is a bit more to this step too and the trees are clamoring for attention but we must stay out of the wood a bit longer).

And after the charts-on-the-wall have revealed the expected improvement has actually happened; and after the skeptics have deleted their ‘we told you so’ emails; and after the cynics have slunk off to sulk; and after the celebration party is over; and after the fame and glory has been snatched by the non-participants – after all of that expected change management stuff has happened …. there is a bit more work to do.

And that is to establish the new higher productivity design as business-as-usual which means tearing up all the old policies and writing new ones: New Policies that capture the New Reality. Bin the out-of-date rubbish.

This is an essential step because culture changes slowly.  If this step is omitted then out-of-date beliefs, attitudes, habits and behaviours will start to diffuse back in, poison the pond, and undo all the good work.  The New Policies are the reference – but they alone will not ensure the improvement is maintained. What is also needed is a PFL – a performance feedback loop.

And we have already demonstrated what that needs to be – the tactical system behaviour charts for the Intended Constraint step.

The finanical productivity metric is the strategic output and is reported monthly – as a system behaviour chart! Just comparing this month with last month is meaningless.  The tactical SBCs for the constraint step must be maintained continuously by the people who own the constraint step – because they control the productivity of the whole process.  They are the guardians of the productivity improvement and their SBCs are the Early Warning System (EWS).

If the tactical SBCs set off an alarm then investigate the root cause immediately – and address it. If they do not then leave it alone and do not meddle.

This is the simplified version of the recipe. The essential framework.

Reality is messier. More complicated. More fun!

Reality throws in lots of rusty spanners so we do also need to understand how to manage the complexity; the unnecessary steps; the errors; the meddlers; and the inevitable variation.  It is possible (though not trivial) to design real systems to deliver much higher productivity by using the framework above and by mastering a number of other tools and techniques.  And for that to succeed the Governance, Operations and Finance functions need to collaborate closely with the People and the Process – initially with guidance from an experienced and competent Improvement Scientist. But only initially. This is a learnable skill. And it takes practice to master – so start with easy ones and work up.

If any of these bits are missing or are dysfunctional the recipe will not work. So that is the first nettle the Executive must grasp. Get everyone who is necessary on the same bus going in the same direction – and show the cynics the exit. Skeptics are OK – they will counter-balance the Optimists. Cynics add no value and are a liability.

What you may have noticed is that 8 of the 10 steps happen before any change is made. 80% of the effort is in the design – only 20% is in the doing.

If we get the design wrong the the doing will be an ineffective and inefficient waste of effort, time and money.


The best complement to real Improvement PIE is a FISH course.


Safety by Despair, Desire or Design?

Imagine the health and safety implications of landing a helicopter carrying a critically ill patient on the roof of a hospital.

Consider the possible number of ways that this scenario could go horribly wrong. But in reality it does not because this is a very visible hazard and the associated risks are actively mitigated.

It is much more dangerous for a slightly ill patient to enter the doors of the hospital on their own two legs.  Surely not!  How can that be?

First the reality – the evidence.

Repeated studies have shown that about 1 in 300  emergency admissions to hospitals do not leave alive and their death is avoidable. And it is not just weekends that are risky. That means about 1 person per week for each large acute hospital in England. That is about a jumbo-jet full of people every week in England. If you want to see the evidence click here to get a copy of a recent study.

How long would an airline stay in business if it crashed one plane full of passengers every week?

And how do we know that these are the risks? Well by looking at hospitals who have recognised the hazards and the risks and have actively done something about it. The ones that have used Improvement Science – and improved.


In one hospital the death rate from a common, high-risk emergency was significantly reduced overnight simply by designing and implementing a protocol that ensured these high-risk patients were admitted to the same ward. It cost nothing to do. No extra staff or extra beds. The effect was a consistently better level of care through proactive medical management. Preventing risk rather than correcting harm. The outcome was not just fewer deaths – the survivers did better too. More of them returned to independent living – which had a huge financial implication for the cost of long term care. It was cheaper for the healthcare system. But that benefit was felt in a different budget so there was no direct financial reward to the hospital for improving the outcome.  So the improvement was not celebrated and sustained. Finance trumped Governance. Desire to improve safety is not enough.


Eventually and inevitably the safety issue will resurface and bite back.  The Mid Staffordshire Hospital debacle is a timely reminder. Eventually despair will drive change – but it will come at a high price.  The emotional knee jerk reaction driven by public outrage will be to add yet more layers of bureaucracy and cost: more inspectors, inspections and delays.  The knee jerk is not designed to understand the root cause and correct it – that toxic combination of ignorance and confidence that goes by the name arrogance.


The reason that the helicopter-on-the-hospital is safer is because it is designed to be – and one of the tools used in safe process design is called Failure Modes and Effects Analysis or FMEA.

So if there is anyone reading this who is in a senior clinical or senior mangerial role in a hospital that has any safety issues – and who has not heard of FMEA then they have a golden opportunity to learn a skill that will lead to safer-by-design hospital.

Safer-by-design hospitals are less frightening to walk into, less demotivating to work in and cheaper to run.  Everyone wins.

If you want to learn more now then click here for a short summary of FMEA from the Institute of Healthcare Improvement.

It was written in 2004. That is eight years ago.

Intuitive Counter

If it takes five machines five minutes to make five widgets how long does it take ten machines to make ten widgets?

If the answer “ten minutes” just popped into your head then your intuition is playing tricks on you. The correct answer is “five minutes“.

Let us try another.

If the lily leaves on the surface of a lake double in area every day and if it takes 48 days to cover the whole lake then how long did it take to cover half the lake?  Twenty four days? Nope. The correct answer is 47 days and once again our intuition has tricked us. It is obvious in hindsight though – just not so obvious before.

We all make thousands of unconscious, intuitive decisions every day so if we make unintended errors like this then they must be happening all the time and we do not realise. 

OK one more and really concentrate this time.

If we have a three-step sequential process and the chance of a significant safety error at each step is 10%, 30% and 20% respectively then what is the overall error rate for the process?  A: (10%+30%+20%) /3 = 60%/3 = 20%? Nope. Um 30%? Nope. What about 60%?  Nope. The answer is 49.6%. And it is not intuitively obvious how that is the correct answer.


When it comes to numbers, counting, and anything to do with chance and probability then our intuition is not a safe and reliable tool. But we rely on it all the time and we are not aware of the errors we are making. And it is not just numbers that our intuition trips us up over!


A lot of us are intuitive thinkers … about 40% in fact. The majority of leaders and executives are categorised as iNtuitors when measured using a standard psychological assessment tool. And remember – they are the ones making the Big Decisions that effect us all.  So if their intuition is tripping them up then their decisions are likely to be a bit suspect.

Fortunately there is a group of people who do not fall into these hidden cognitive counting traps so easily. They have Books of Rules of how to do numbers correctly – and they are called Accountants. When they have the same standard assessment a lot of them pop up at the other end of the iNtuitor dimension. They are called Sensors.   Not because they are sensitive (which of course they are) but because they rank reality more trustworthy than rhetoric. They trust what they see – the facts – the numbers.  And money is a number. And numbers  add up exactly so that everything is neat, tidy, and auditable down to the last penny. Ahhhh – Blisse is Balanced Books and Budgets.  


This is why the World is run by Accountants.  They nail our soft and fuzzy intuitive rhetoric onto the hard and precise fiscal reality.  And in so doing a big and important piece of the picture is lost. The fuzzy bit,


Intuitors have a very important role. They are able to think outside the Rule Book Box. They are comfortable working with fuzzy concepts and in abstract terms and their favourite sport is intuitive leaping. It is a high risk sport though because sometimes Reality reminds them that the Laws of Physics are not optional or subject to negotiation and innovation. Ouch!  But the iNtuitors ability to leap about conceptuallycomes in very handy when the World is changing unpredictably – because it allows the Books of Rules to be challenged and re-written as new discoveries are made. The first Rule is usually “Do not question the Rules” so those who follow Rules are not good at creating new ones. And those who write the rules are not good at sticking to them.

So, after enough painful encounters with Reality the iNtuitors find their comfort zones in board rooms, academia and politics – where they can avoid hard Reality and concentrate on soft Rhetoric. Here they can all have a different conceptual abstract mental model and can happily discuss, debate and argue with each other for eternity. Of course the rest of the Universe is spectacularly indifferent to board room, academic and political rhetoric – but the risk to the disinterested is when the influential iNtuitors impose their self-generated semi-delusional group-think on the Real World without a doing a Reality Check first.  The outcome is entirely predictable ….

And as the hot rhetoric meets cold reality the fog of disillusionment forms. 


So if we wish to embark on a Quest for Improvement then it is really helpful to know where on the iNtuitor-Sensor dimension each of us prefers to sit. Intuitors need Sensors to provide a reality check and Sensors need Intuitors to challenge the status quo.  We are not nailed to our psychological perches – we can shuffle up and down if need be – we do have a favourite spot though; our comfort zone.

To help answer the “Where am I on the NS dimension?” question here is a  Temperament Self-Assessment Tool that you can use. It is based on the Jungian, Myers-Briggs and Keirsey models. Just run the programme, answer the 72 questions and you will get your full 4-dimensional profile and your “centre” on each. Then jot down the results on a scrap of paper. 

There is a whole industry that has sprung up out these (and other) psychological assessment tools. They feed our fascination with knowing what makes us tick and the role of the psychoexpert is to de-mystify the assessments for us and to explain the patterns in the tea leaves (for a fee of course because it takes years of training to become a Demystifier). Disappointingly, my experience is that almost every person I have asked if they know their Myers-Briggs profile say “Oh yes, I did that years ago, it is SPQR or something like that but I have no idea what it means“.  Maybe they should ask for their Demystification Fee to be returned?

Anyway – here is the foundation level demystification guide to help you derive meaning from what is jotted on the scrap of paper.

First look at the N-S (iNtuitor-Sensor) dimension.  If you come out as N then look at the T-F (Thinking-Feeling) dimension – and together they will give an xNTx preference or an xNFx preference. People with these preferences are called Rationals and Idealists respectively.  If you prefer the S end of the N-S dimension then look at the J-P (Judging-Perceiving) result and this will give an xSxJ or xSxP preference. These are the Guardians and the Artisans.  Those are the Four Temperaments described by David Keirsey in “Please Understand Me II“. If you are near the middle of any of the dimensions then you will show a blend of temperaments. And please note – it is not an either-or category – it is a continuous spectrum.

How we actually manifest our innate personality preferences depends on our education, experiences and the exact context. This makes it a tricky to interpret the specific results for an individual – hence the Tribe of Demystificationists. And remember – these are not intelligence tests, and there are no good/bad or right/wrong answers. They are gifts – or rather gifts differing. 


So how does all this psychobabble help us as Improvement Scientists?

Much of Improvement Science is just about improving awareness and insight – so insight into ourselves is of value.  

Rationals (xNTx) are attracted to occupations that involve strategic thinking and making rational, evidence based decisions: such as engineers and executives. The Idealists (xNFx) are rarer, more sensitive, and attracted to occupations such as teaching, counselling, healing and being champions of good causes.  The Guardians (xSxJ) are particularly numerous and are attracted to occupations that form the stable bedrock of society – administrators, inspectors, supervisors, providers and protectors. They value the call-of-duty and sticking-to-the-rules for the good-of-all. Artisans (SPs) are the risk-takers and fun-makers; the promotors, the entertainers, the explorers, the dealers, the artists, the marketeers and the salespeople.

These are the Four Temperaments that form the basic framework of the sixteen Myers-Briggs polarities.  And this is not a new idea – it has been around for millenia – just re-emerging with different names in different paradigms. In the Renaissance the Galenic Paradigm held sway and they were called the Phlegmatics (NT), the Cholerics (NF), the Melancholics (SJ) and the Sangines (SP) – depending on which of the four body fluids were believed to be out of balance (phlegm, yellow bile, black bile or blood). So while the paradigms have changed, the empirical reality appears to have endured the ages.

The message for the Improvement Scientist is two-fold:

1. Know your own temperament and recognise the strengths and limitations of it. They all have a light and dark side.
2. Understand that the temperaments of groups of people can be both synergistic and antagonistic.

It is said that birds of a feather flock together and the collective behaviour of departments in large organisations tend to form around the temperament that suits that organisational function.  The character of the Finance department is usually very different to that of Operations, or Human Resources – and sparks can (and do) fly when they engage each other. No wonder chief executives have a short half-life and an effective one is worth its weight in gold! 

The interdepartmental discord that is commonly observed in large organisations follows more from ignorance (unawareness of the reality of a spectrum of innate temperaments) and arrogance (expecting everyone to think the same way as we do). Antagonism is not an inevitable consequence though – it is just the default outcome in the absence of awareness and effective leadership.

This knowledge highlights two skills that an effective Improvement Scientist needs to master:

1. Respectful Educator (drawing back the black curtain of ignorance) and
2. Respectful Challenger (using reality to illuminate holes in the rhetoric).

Intuitive counter or counter intuitive?

The Frightening Cost Of Fear

The recurring theme this week has been safety and risk.

Specifically in a healthcare context. Most people are not aware just how risky our current healthcare systems are. Those who work in healthcare are much more aware of the dangers but they seem powerless to do much to make their systems safer for patients.


The shroud-waving  zealots who rant on about safety often use a very unhelpful quotation. They say “Every system is perfectly designed to deliver the performance it does“. The implication is that when the evidence shows that our healthcare systems are dangerous …. then …. we designed them to be dangerous.  The reaction from the audience is emotional and predictable “We did not intend this so do not try to pin the blame on us!”  The well-intentioned shroud-waving safety zealot loses whatever credibility they had and the collective swamp of cynicism and despair gets a bit deeper.


The warning-word here is design – because it has many meanings.  The design of a system can mean “what the system is” in the sense of a blueprint. The design of a system can also mean “how the blueprint was created”.  This process sense is the trap – because it implies intention.  Design needs a purpose – the intended outcome – so to say an unsafe system has been designed is to imply that it was intended to be unsafe. This is incorrect.

The message in the emotional backlash that our well-intended zealot provoked is “You said we intended bad things to happen which is not correct so if you are wrong on that fundamental belief then how can I trust anything else you say?“. This is the reason zealots lose credibility and actually make improvement less likely to happen.


The reality is not that the system was designed to be unsafe – it is that it was not designed not to be. The double negatives are intentional. The two statements are not the same.


The default way of the Universe is evolutionary (which is unintentional and reactive) and chaotic (which is unstable and unsafe). To design a system to be not-unsafe we need to understand Two Sciences – Design Science and Safety Science. Only then can we proactively and intentionally design safe, stable, and trustable systems.    If we do nothing and do not invest in mastering the Two Sciences then we will get the default outcome: unintended unsafety.  This is what the uncomfortable  evidence says we have.


So where does the Frightening Cost of Fear come in?

If our system is unintentionally and unpredictably unsafe then of course we will try to protect ourselves from the blame which inevitably will follow from disappointed customers.  We fear the blame partly because we know it is justified and partly because we feel powerless to avoid it. So we cover our backs. We invent and implement complex check-and-correct systems and we document everything we do so that we have the evidence in the inevitable event of a bad outcome and the backlash it unleashes. The evidence that proves we did our best; it shows we did what the safety zealots told us to do; it shows that we cannot be held responsible for the bad outcome.

Unfortunately this strategy does little to prevent bad outcomes. In fact it can have has exactly the opposite effect of what is intended. The added complexity and cost of our cover-my-back bureaucracy actually increases the stress and chaos and makes bad outcomes more likely to happen. It makes the system even less safe. It does not deflect the blame. It just demonstrates that we do not understand how to design a not-unsafe system.


And the financial cost of our fear is frighteningly high.

Studies have shown that over 60% of nursing time is spent on documentation – and about 70% of healthcare cost is on hospital nurse salaries. The maths is easy – at least 42% of total healthcare cost is spent on back-covering-blame-deflection-bureaucracy.

It gets worse though.

Those legal documents called clinical records need to be moved around and stored for a minimum of seven years. That is expensive. Converting them into an electronic format misses the point entirely. Finding the few shreds of valuable clinical information amidst the morass of back-covering-bureaucracy uses up valuable specialist time and has a high risk of failure. Inevitably the risk of decision errors increases – but this risk is unmeasured and is possibly unmeasurable. The frustration and fear it creates is very obvious though: to anyone willing to look.

The cost of correcting the Niggles that have been detected before they escalate to Not Agains, Near Misses and Never Events can itself account for half the workload. And the cost of clearing up the mess after the uncommon but inevitable disaster becomes built into the system too – as insurance premiums to pay for future litigation and compensation. It is no great surprise that we have unintentionally created a compensation culture! Patient expectation is rising.

Add all those costs up and it becomes plausible to suggest that the Cost of Fear could be a terrifying 80% of the total cost!


Of course we cannot just flick a switch and say “Right – let us train everyone in safe system design science“.  What would all the people who make a living from feeding on the present dung-heap do? What would the checkers and auditors and litigators and insurers do to earn a crust? Join the already swollen ranks of the unemployed?


If we step back and ask “Does the Cost of Fear principle apply to everything?” then we are faced with the uncomfortable conclusion that it most likely is.  So the cost of everything we buy will have a Cost of Fear component in it. We will not see it written down like that but it will be in there – it must be.

This leads us to a profound idea.  If we collectively invested in learning how to design not-unsafe systems then the cost of everything could fall. This means we would not need to work as many hours to earn enough to pay for what we need to live. We could all have less fear and stress. We could all have more time to do what we enjoy. We could all have both of these and be no worse off in terms of financial security.

This Win-Win-Win outcome feels counter-intuitive enough to deserve serious consideration.


So here are some other blog topics on the theme of Safety and Design:

Never Events, Near Misses, Not Agains and Nailing Niggles

The Safety Line in the Quality Sand

Safety By Design

The Safety Line in the Quality Sand

Improvement Science is about getting better – and it is also about not getting worse.

These are not the same thing. Getting better requires dismantling barriers that block improvement. Not getting worse requires building barriers to block deterioration.

When things get tough and people start to panic it is common to see corners being cut and short-term quick fixes taking priority over long-term common sense.  The best defense against this self-defeating behaviour is the courage and discipline to say “This is our safety line in the quality sand and we do not cross it“.  This is not dogma it is discipline. Dogma is blind acceptance; discipline is applied wisdom.

Leaders show their mettle when times are difficult not when times are easy.  A leader who abandons their espoused principles when under pressure is a liability to themselves and to their teams and organisations.

The barrier that prevents descent into chaos is not the leader – it is the principle that there is a minimum level of acceptable quality – the line that will not be crossed. So when a decision needs to be made between safety and money the choice is not open to debate. Safety comes first.  

Only those who believe that higher quality always costs more will argue for compromise. So when the going gets tough those who question the Safety Line in the Quality Sand are the ones to challenge by respectfully reminding them of their own principles.

This challenge will require courage because they may be the ones in the seats of power.  But when leaders compromise their own principles they have sacrificed their credibility and have abdicated their power.