Population Health, Thought Leadership, Uncategorized March 11, 2021

Heatwaves are killing thousands every year – it will get worse

By Francesco Tamilia

The damage of heatwaves to human health, productivity and lifestyles is growing. This is primarily because of the increasing likelihood of heatwaves caused by climate change. What are the impacts of this silent killer and what can be done about it?

Seventy thousand people died during the 2003 heatwave in Europe – a fact that should pose frightening questions if scientific projections that suggest climate change will increase the frequency of heatwaves turn out to be correct. Yet, because the death toll and drastic impacts of heatwaves are not always so immediate and obvious, they rarely received adequate attention from policymakers and the public.

“When hot days come, people think it’s just time to go to the beach. They don’t think about the fact that heat can make people sick, it can kill them. Maybe it’s just human nature, but why doesn’t it spur public attention?” asks Kathy Baughman McLeod, founding member of the Extreme Heat Resilience Alliance (EHRA) and SVP and Director of the Adrienne Arsht–Rockefeller Foundation Resilience Center at the Atlantic Council. The EHRA, formed by more than 30 global organisations, seeks “to tackle the growing threat of extreme urban heat for vulnerable people worldwide”.

Of the impacts of climate change, heatwaves are considered to have one of the deadliest health impacts. According to The Lancet Countdown on Health and Climate Change 2020 report, “from 2000 to 2018, heat-related mortality in people older than 65 years increased by 57 per cent and, in 2018, reached 296,000 deaths. The majority of these occurred in Japan, Eastern China, Northern India and Central Europe.”

What exactly defines a heatwave? Because they can vary significantly depending on a range of factors such as humidity, heatwaves do not have a universally accepted definition. One of the most common definitions that is attributed to them relates to an intensity that exceeds a certain threshold (there is no worldwide accepted threshold) and a duration that lasts a certain length of time.

How heatwaves impact human health, and who is most at risk?

Experts in the UK and US have concluded that extreme heat can cause a variety of negative health impacts depending on the intensity and duration of the heatwave. Some research shows direct correlations between increasing heat and an increasing number of excess deaths, which often double on particularly hot days. The main causes of illness or death during a heatwave are cardiovascular, respiratory disease and heatstroke.

Other heat-related illnesses:

Heat exhaustion – the most common. It occurs as a result of water or sodium depletion, with no-specific features of malaise, vomiting and circulatory collapse, and is present when the core temperature is between 37°C and 40°C. Left untreated, it may evolve into heatstroke
Heat cramps – caused by dehydration and loss of electrolytes, often following exercise
Heat rash – small, red itchy papules
Heat oedema – dizziness and fainting, due to vasodilation and retention of fluid
Heatstroke – can become a point of no return whereby the body’s thermoregulation mechanism fails. This leads to a medical emergency, with symptoms of confusion; disorientation; convulsions; unconsciousness; hot dry skin; and core body temperature exceeding 40°C for between 45 minutes and eight hours. It can result in cell death, organ failure, brain damage or death

(Source: Heatwave Advice, Department of Health)

People most at risk are those over the age of 65, people with disabilities or pre-existing medical conditions and those working outdoors for long hours in non-cooled environments. Other factors that can increase risk include; limited access to green spaces, living in cities with high population density, living on a top floor and being homeless. Nowhere is immune to extreme heat but populations in the Europe and Eastern Mediterranean regions have been the most vulnerable of all the WHO regions, the 2020 Lancet report found.

People with chronic or severe illness are likely to be at particular risk, including the following conditions:

Respiratory disease
Cardiovascular and cerebrovascular conditions
Diabetes and obesity
Severe mental illness
Parkinson’s disease and difficulties with mobility
Renal insufficiency
Peripheral vascular conditions
Alzheimer’s or related diseases

(Source: Heatwave Advice, Department of Health)

2003 heatwave in Europe. Image courtesy of Reto Stockli and Robert Simmon, based upon data provided by the MODIS Land Science Team.

Other impacts of heatwaves

The impacts of heatwaves extend beyond people’s health; experts estimate that by 2030, lost productivity from heat stress at work, particularly in developing countries, will cost $4.2 trillion USD per year.

“Across the globe, a potential 302 billion work hours were lost in 2019, which is 103 billion hours more than were lost in 2000. Thirteen countries represented 80.7 per cent of the 302,4 billion global work hours lost in 2019,” The Lancet 2020 report found.

The 2003 heatwave was estimated to have cost £41 million in health-related costs and productivity losses in the UK alone. In the US, a 2014 study by economists Tatyana Deryugina and Solomon Hsiang looked at annual income data and daily weather data from 1969 to 2011 and found that years with more days above 59 F (15 C) are associated with significantly lower income per person: average per-day income declines by 1.5 per cent for each 1.8 F (1 C) increase in daily average temperature beyond 15 C (59 F).

Several studies have also found links between extremely hot days and the worsening of people’s mental health conditions. A study in Toronto associated the increased rates of emergency visits for mental health conditions to temperatures rising above 28 C (82 F).

Yet another equality issue

Like many public health issues, heatwaves do not impact everyone equally – they affect people of colour and lower socioeconomic status more than anybody else.

“The people contributing to it least are suffering the most. There’s a link between hot communities and trees. Low-income communities don’t have trees whereas suburbs do. Trees help keep the temperature down and, more importantly, they absorb pollution,” says Ms Baughman McLeod.

“By contrast, people of lower economic status and of colour are more likely to be living next to industrial complexes that are emitting pollution. Most of the time in those areas there are no trees that can absorb pollution and heat is a key component of that.”

This was confirmed by a 2018 paper in the US that found people living in less vegetated areas had a five per cent higher risk of death compared to those living in more vegetated areas. Scientists at the University of California in 2017 mapped racial divides in the US by proximity to trees. Results were clear: black people were 52 per cent more likely than white people to live in areas of unnatural “heat risk-related land cover,” while Asian people were 32 per cent more likely and Hispanics 21 per cent.

Heatwaves and climate change: a sign of what is to come

There are fingerprints of climate change all over the recent heatwaves. An overwhelming amount of scientific evidence suggests that climate change is already making heatwaves and extremely hot days more frequent and severe. The evidence also suggests that if immediate actions to reduce emissions are not taken, extreme weather events will become the norm. A 2019 report by the World Weather Attribution (WWA) found that the 2019 heatwave in western Europe “would have been extremely unlikely without climate change”.

More recently in 2020, Siberia hit a record-breaking temperature of 38 degrees celsius. Again, WWA found “with high confidence” that the January to June 2020 prolonged heat “was made at least 600 times more likely as a result of human-induced climate change.”

We must raise awareness

When Ms Baughman McLeod, along with international partners, decided to establish the Extreme Heat Resilience Alliance in summer 2020, their first priority was clear: raising awareness among decision-makers. “We found that heat was the place where there was not enough attention. I think it’s ironic that in 60 or 70 years of climate discussions, and we call it global warming, we’re not talking about heat. It’s killing more people than any other impact of climate change,” she says.

A report published in 2021 by the WHO concluded that public awareness of the health risk is relatively high in places that are regularly affected by hot spells. However, it also found that “the risk perception of heat among healthcare providers may be significantly lower than it should be, given the objective risks faced by their patients.”

Worryingly, the report also revealed poor levels of awareness of heat warnings among health professionals, including nurses in care homes, as well as a lack of knowledge of existing heat–health plans among hospital front-line staff.

Heatwaves are a silent killer, how can you solve a problem people don’t know about? In a landscape of crises, if something is not burning, people are not going to address it.

– Kathy Baughman McLeod, SVP and Director of the Adrienne Arsht–Rockefeller Foundation Resilience Center at the Atlantic Council.

How should we go about raising awareness and saving lives? The Extreme Heat Resilience Alliance believes that naming heatwaves can make a difference. Although Ms Baughman McLeod admits that this may not be as straightforward as naming hurricanes, she believes this can help save lives.

“We’re trying to build a framework that can be adapted at a local met service and the existing heat health warning systems,” she told Integrated Care Journal. “We’re piloting heatwave naming and we’ve put a science team together to help inform it. We’re also building a ‘how to name heatwaves policy’ toolkit for countries that we will take to the COP26 in Glasgow,” she adds.

Courtesy of Arsht–Rockefeller Foundation Resilience Center

It is now crystal clear that heatwaves are an international issue that is bound to worsen in the years ahead, causing tens of thousands of deaths. While heatwaves impact certain countries more than others, nowhere is immune. Policymakers and health professionals must close the current knowledge gap and put into place policies that safely protect the most vulnerable in our societies. As the chances of altering the global CO2 emissions fall year after year, more resources should also be dedicated to adaptation rather than mitigation.

All news

Getting what you need in healthcare: An information systems perspective

By Professor Terry Young; Dr Jonathan H. Klein

Information is one of the World Health Organization’s (WHO) six essential “building blocks” of a healthcare system. Concurring with this, we have invoked the idea of a health information seeker (Young & Klein, 2021), a concept that cuts through complexity to support policy and decisions around commissioning, adoption or use of IT.

A health information seeker might be someone feeling unwell, a carer or professional such as a doctor or nurse or health manager, even someone with an idle interest. It might be a data scientist needing to update health information. It might even be a hacker!

From their perspective, a healthcare information system must promote access to relevant information, while preventing information overload. The key questions about a health information system are:

Is it easy for its intended health information seekers to get what they need?
Are they protected from irrelevant, confusing or conflicting data?
Are inappropriate requests denied?

Most existing health information systems fail against such criteria on many counts.

Health information seekers are trying to make decisions. Should I see a doctor about this? What’s the best treatment for my patient? Do I need to cancel all elective surgery this afternoon? They have two routes: through interactive activity with technology (not necessarily digital), and through interpersonal activity. Information seekers have a repertoire of heuristics for seeking information from other entities, based on experience, intuition, rationality and guesswork. Their heuristics vary in quality and they are not always best placed to judge this quality for themselves.

Modelling the health information seeker

What more can we say about our information seeker? We might borrow Checkland’s (Checkland & Poulter, 2006) activity modelling concept to construct a generic activity model of the information seeker’s activities. Starting from a perceived need for information (the input to the system), the information seeker must first formulate what information is required. Then they can use this to identify and prioritise possible sources of the information. This will be followed, presumably, by actively seeking to obtain the information, following which the information will be assimilated and assessed, leading either to the need for information being met (the output) or a doubling back to earlier activities in the sequence as necessary.

Consider the UK’s bowel cancer screening programme (BCSP) for people aged 60-74 who receive a test kit by post every two years. Recipients are invited to return samples (also by post) which are tested. If positive, the individual must consult their GP urgently for further investigation. The sample requirement was recently altered from three samples over a few days, to a single sample and take-up increased from 59.3 per cent to 66.4 per cent, perhaps due to the greater convenience of the procedure.

With the test kit recipient as the health information seeker (other candidates are possible, but they would lead to different models), we can argue that the change in the information-seeking activity (the third activity in the activity model sequence in Figure 2) constitutes an improvement for the information seeker over what has gone before. (There is also an improvement in the diagnostic effectiveness of the test, which we have not considered here.)

Note that this system is proactive: many may not have sought this information until they received their first test kit. But if they had, there would have been considerable scope for dysfunction: there is an amazing range of bowel cancer advice available online, for instance, and the quality of each site may not be obvious to the searcher.

Conclusion

In the publication from which this article is derived (Young & Klein, 2021) we have discussed more expansively the implications for information systems designers of viewing an individual as a health information seeker. Here, we hope we have illustrated how this perspective, coupled with systemic thinking, can provide insights for meeting healthcare information needs in efficacious, effective and efficient ways.

References

P.B. Checkland & J. Poulter (2006) Learning for Action: A Short Definitive Account of Soft Systems Methodology and Its Use for Practitioners, Teachers and Students. Wiley, Chichester, UK.

T. Young & J. H. Klein (2021) Information systems in health: what do you need and how will you get it? In: L. Goldschmidt & R. M. Relova (editors) (2021) Patient-Centered Digital Healthcare Technology: Novel Applications for Next Generation Healthcare Systems. The Institute of Engineering & Technology, London, UK.

About the authors

Dr Jonathan H. Klein is an Associate Professor in Management Science at Southampton Business School (University of Southampton, UK). His research interests include the application of systems thinking to healthcare management and delivery, and the nature and use of evidence in decision-making. He has a particular interest in the use of systems approaches, such as Checkland’s Soft Systems Methodology, to messy problems exhibiting high degrees of complexity, uncertainty, and subjectivity.

Professor Terry Young is Director of Datchet Consulting and Emeritus Professor, Brunel University London. His research interests throughout careers in industry and in academia lies in healthcare information systems and care delivery systems.

Jonathan and Terry’s introductory chapter on information services in health is now out in Patient-Centered Digital Healthcare Technology: Novel Applications for Next Generation Healthcare Systems.

Integrated Care Systems: where everything depends on everything and everything affects everything

By Jacqueline Mallender; Alastair Mitchell-Baker; Clare Morris; Terry Young

Designed correctly, Integrated Care Systems (ICSs) should deliver care more responsively and effectively than anything to date. Jacqueline Mallender, Alastair Mitchell-Baker, Clare Morris, and Terry Young explore.

Designed correctly, Integrated Care Systems (ICSs) should deliver care more responsively and effectively than anything to date. By harnessing the latest digital, policy, and organisational advances, with reformed payment mechanisms, ICSs promise better population health across the health-social, primary-secondary and mental-physical care divides.

As always, people are at the heart of the vision: citizens and communities, patients and families, clinical staff and leaders. To work for all, ICSs must focus on the journey each person makes, within a framework of policy, finance and governance.

ICSs are a response to now widely recognised failures in UK health and care delivery but are new to the NHS and are themselves subject to unfamiliar mechanisms of failure as well as success. In this article, we explore four challenges to integrated care – dynamics, delivery, design, and alignment – and recommend a new approach to system transformation.

Dynamics

Effective performance as a dynamic, integrated, system is radically different from the workings of the pseudo ‘internal market’ – with ‘transactional’ characteristics that have defined the last three decades of health and care delivery. It requires a change in mindset, new approaches, guidelines and procedures.

Furthermore, striving for ‘total connectivity’ means that small glitches can generate avalanches of knock-on effects. As systems become more integrated, the firebreaks of traditional provision disappear, and problems can spread further and faster. This means that ICSs must exhibit extreme resilience as they develop.

Delivery

The second challenge is in how to adapt what we have already learned from radically re-aligning payment methods with outcomes, and incentivise effective collaboration. NICE (The National Institute for Health and Clinical Excellence) has pioneered value-based policy since 1999, making the UK a global leader. An example would be best practice tariffs informed by NICE guidance (for instance in care for heart failure). However, value-for-money does not guarantee affordability within a departmental, local, regional, or annual budget (see Young & Mallender, 2020, Aligning value and incentives to make digital health really work, ICJ), so fresh thinking and new ways of working are needed. But this ambitious goal is well worth pursuing.

Design

While we are born with billions of neurons – grown in months – a brain takes decades to mature because it relies on interconnections, not just functioning units. Similarly, the ICS building blocks – clinics, theatres, equipment – can be built quickly today, but planning the connections between them takes much longer than it used to, while end-users absolutely must be involved from the outset.

This means that the balance between the planning and implementation of care shifts radically. A new mind-set must feel safe with longer planning and design cycles, more concurrency (where very different challenges are addressed together), all underpinned by more agile, adaptive commissioning.

Alignment

Finally, all ICS partners must align policy and operations across the whole system, including: policies to address variations in the wider determinants of health; operating public health programmes at scale; and providing integrated personalised care and treatment. The science of personalised medicine is well understood but the logistics are new and population health management requires tools that we are still only learning how to use.

Looking forward

The key things to focus on when designing an ICS are:

Earlier engagement with all stakeholders, including patients and staff, drawing them into the design from the start to unlock value and reduce risk. The old phasing is dead. Long live concurrency!
Deeper planning that goes right to the final service in operation, this includes: finance, efficiency; the built environment; information systems; digital; organisational structures; and clinical services.
Scenario testing. ICSs offer extreme performance and vulnerability, so attention must focus on failure modes and unintended consequences, as well as ways to make the most of their versatility and responsiveness in fast-changing crises.
Agile responses underpinned by automated data and intelligence. Out with old-style monthly KPIs; in with actionable intelligence, always available to all who need it.
People and relationships: our fates have never been more intertwined than in an ICS. When things go awry – as they will – the quality of relationships will dictate how we respond and stay on track.

Leaders and policymakers will need expertise that is better networked to reach deep knowledge in consensual ways that combines wider skills.

There are no shortcuts for fostering systems as complex and big as ICSs, so look for flexible support that can switch from strategy to technology, to organisational development, to finance, to clinical flows, to resource management, and can be sustained for the duration of development. Experienced hands – but with the curiosity and appetite for the new era – will be hugely valuable.

Don’t forget, our collective intuition has been honed in very different systems, so grill your experts with care before taking them on: you are looking for experience, agility and a wide range of skills, tools and capability.

If comprehensive system transformation is achieved, then providers and policymakers alike can share a wonderful sense of fulfilment, safe in the knowledge that they have created a solid foundation for integration to thrive throughout their system of health and care.

Contributors

Jacque Mallender, Director of Economics by Design. jacx@economicsbydesign.com

Jacque is an Economist and co-founder at Economics by Design. She is a respected international health and public policy economist and health evaluation practitioner. Over the last 35 years, Jacque has worked across health and social care with a focus on evaluation and health economics in UK, Europe, North America and more recently the Middle East and North Africa. She was a founding convenor of the joint Campbell and Cochrane Economics Methods Group and for 15 years was a committee member. In addition to her work at Economics By Design, Jacque is a Member of the Executive Committee of the Economic Research Council and an Associate of the Oxford Centre for Triple Value Healthcare.

Alastair Mitchell-Baker, Director of Tricordant. alastair@tricordant.com

Alastair enjoys working with a diverse range of clients as a consultant – from NHS and councils to international NGOs, government departments and global companies, in the areas of organisation design and development, strategy and systems and leadership development. He has also worked in NHS senior management including as a Chief Executive and a Non-Executive Director. He was co-founder of the European Organisation Design Forum.

Clare Morris, Director of RETHINK Partners. clare@rethinkpartners.co.uk

Clare Morris founded Rethink Partners after a career in senior health management in the NHS. She has significant experience of delivering integration across health and social care systems with a strong interest in community health, mental health, learning disabilities, children’s services and neurodiversity. Having delivered big changes as an NHS leader, Clare now works with others – at all levels – to make change happen and create the conditions in which integration can thrive.

Professor Terry Young, Director of Datchet Consulting. terry@datchet.consulting

Terry worked in industrial R&D before becoming an academic and is now Director of Datchet Consulting. With over 30 years’ experience in technology development and strategy, health systems, and methods to ensure value for money, his current focus lies in designing services using computer models and he set up the Cumberland Initiative to support healthcare organisations wishing to develop their services more systematically.

A recent paper on the cost-effectiveness of modelling was shortlisted for the Operational Society’s Goodeve Medal: Assessing the value of modelling and simulation in health care: An example based on increasing access to stroke treatment.

Algorithms of destruction?

By Professor Terry Young, BSc, PhD, FBCS

The models used to drive so many elements of life are sophisticated and complex, taking account of an extensive range of variables, yet they often end up missing the mark. Professor Terry Young explores the role of algorithms and how they can be maximised for healthcare.

While our exam boards dish out perplexing results and our health policy drives lockdown, they don’t always get the right result. The models they use are sophisticated and complex, taking account of an extensive range of variables but often end up missing the mark. So, what is wrong with our algorithms?

Algorithms and models are everywhere, and we approach them sensibly most of the time. For instance, a car driven by a speed demon during the week and by a fuel-obsessive at the weekend may suddenly display a peculiarity: the further it travels the more miles it predicts are left in the tank! We understand this and use other gauges when deciding whether to fill up. Some policymakers, however, trust algorithms implicitly (or implicitly trust those who do).

Throughout the Covid crisis, home shopping has had a bonanza on the back of sophisticated track-and-trace algorithms. Remember the mess at the start when getting a supermarket delivery was like finding gold dust? The companies soon fixed that, opened more slots, recruited staff, and the sector has boomed. Meanwhile, the wider economy, education and health, have withered.

Why has retail been so lucky and policymaking so unfortunate? Is it the algorithms?

I’ve spent my life with computer models from photonics to healthcare. At first, I was involved in specification and coding but later lost sight of the details, relying on other people’s eyes and keyboards when leading research teams.

Making good decisions with algorithms is clearly possible, even if it is hard at times. Success relies on good test cases and measuring key trends, as well as sound judgement. A good test case runs the model against what really happens, but tests fail without good data. Our problems with data at the start were understandable but the lack of quality now almost suggests a willful commitment to the joys of flying blind.

However, even if a model’s predictions cannot be checked directly – because the model or the data are not good enough – we can still work with the trends it predicts.

The 50,000 cases a day scenario was a great example of testing against reality and also of testing for trends: it was a brave move to make it public. We can now see that the algorithm significantly overpredicted cases of people testing positive while raising questions about the shape of the trend. Evidence is also emerging that many more people may have immunity than the model assumes.

It is hard to be clear because the data is so poor, but data specialists (@RP131, for instance) as well as public health commentators (such as the Centre for Evidence-Based Medicine at Oxford, www.cebm.net), note the differences between the predicted trends and the measured rises.

There were always good scientific reasons to doubt a tsunami. Wavelets? Probably. A second wave to dwarf the first? Unlikely. Manageable waves from here? Absolutely!

It’s more complicated than that, of course, but the key message is that algorithms are neither magic nor a menace. At their best, they have kept us going through the madness. At worst, faith in them may be contributing to it.

Professor Terry Young worked in industrial R&D before becoming an academic and is now Director of Datchet Consulting. With over 30 years’ experience in technology development and strategy, health systems, and methods to ensure value for money, his current focus lies in designing services using computer models and he set up the Cumberland Initiative to support healthcare organisations wishing to develop their services more systematically.

Three of his downloadable papers are:

Using industrial processes to improve patient care (2004, with Brailsford et al., British Medical Journal)

Performing or not performing: what’s in a target? (2017, with Eatock & Cooke, Future Hospital Journal)

Systems, design and value-for-money in the NHS: mission impossible? (2018, with Morton and Soorapanth, Future Hospital Journal)

Coronavirus: what’s up with our experts?

By Professor Terry Young, BSc, PhD, FBCS

Can we trust our experts? After months of lockdown, there is rising scepticism about them and their models. Professor Terry Young analyses of the role of experts in the pandemic so far and assesses what needs to change.

Can we trust our experts? After months of lockdown, there is rising scepticism about them and their models.

The guidance about lockdown has been relentless and we have followed it, closing schools and furloughing workers. Our headline figures, however, are among the worst in the world.

We have uncritically accepted advice based on flawed and incomplete science: flawed because it focused on a single aspect of the problem and incomplete because the data was so poor. Nor was the model ever the absolute guide we took it to be. A smart colleague of mine noted that he could predict anything from a huge second wave to nothing at all, just by fine-tuning his input parameters.

Of course, there may yet be surprises – perhaps our big cities were against us all along – but we can certainly do better from here.

What is the evidence? The general ONS picture (June 26, 2020) on coronavirus deaths is clear: 0.01 per cent are children, 11 per cent are working-age individuals, and 89 per cent are retired. Professor Sir David Spiegelhalter has shown how spectacularly the risk of death rises with age.

Looking back, we protected those least at risk instead of those at greatest risk. To get things so completely wrong is serious. How could the advice and the reality have been so completely contradictory?

We know experts have been right in the past – with MMR vaccines 20 years ago, for instance – when sections of the public and the media were wrong. However, back then, they had good data, the situation was well understood and it was purely a medical problem. This time, it was a catastrophe on all fronts that we chose to treat as a medical emergency.

Throughout the pandemic, data has been scarce, as has experience of this type of crisis. It looks like our experts over-reacted to lesser risks and missed the big ones. That said, we knew about hospital-acquired infections and should have stemmed the tide in hospitals. We need to review the hospital discharges into care homes and should probably have foreseen the care home tragedy that followed.

This time we needed better data on the spread of the disease and the numbers who have recovered, but we chose not to make than an absolute priority.

Why does this matter now? Well, if the same expertise continues to dominate, it will hopelessly enmesh us in impossible rules targeted, once again, at those least at risk. One has only to watch a football match, with masked officials ghosting around empty stands while players spit and blow their noses all over the pitch, to sense that the choreography of contagion is still misunderstood and that guidance is still based on extreme and very partial advice.

The good news is that with fewer deaths, almost any track and trace system might now work. In a democracy, good things and bad things take a bit longer, but this might be a belated breakthrough.

The bad news is that that our firebreak, chopping up our supply chains and closing our schools, has unleashed chaos, unbelievably costly chaos, that will take years to play out.

We need a more grown-up and challenging debate with the experts. What is more, we need to broaden the pool of expertise to include manufacturing, business, the economy, and transport.

We need better guidelines than those currently being imposed on school children, students and working people: rules that reflect the risks they really face, as we get our schools, universities and industry back up and running.

We all have a stake in our future, and whatever future we choose, it’s not just about lockdown.

Healthy information: Science and logistics

By Professor Terry Young; Professor Stephen Smith

Healthcare depends upon two data types; the clinical, which determines the best we can do and the logistics, that limit what most people will get. Right now, our best is diverging alarmingly from our average, say Professor Terry Young and Professor Stephen Smith. It’s time to invest in logistics.

Healthcare is about knowledge: Patients who know more tend to live healthier lives, and professionals who know more, care better for patients.

With a knowledge-differentiating condition such as diabetes, those who learn about weight and blood sugar can live rewarding lives. Those who don’t, fill a disproportionate number of hospital beds, risking peripheral neuropathies and sight loss, while their families face untimely losses of loved ones.

Diabetes research is knowledge-based for drug and technology combinations that capture better data and deliver real-time medication. As a result, type one diabetes no longer hampers one’s career and even Mrs May, for example, was able to pursue a full, if somewhat brutal, lifestyle as Prime Minister.

In the Twentieth Century, health information exploded beyond belief. Grainy pictures of bones became images of minute tumours or videos of thoughts flickering across someone’s brain. Biochemistry caught the first stirrings of disease and we decoded the genetics of who would suffer from what, and which treatments would work.

Our therapeutic knowledge tracked these diagnostic developments and the great killers of earlier centuries (except malnutrition and war) retreated before antibiotics, massively and minimally invasive surgery, and a cocktail of smart drugs and devices.

Now, think about stroke. At first, this looks like the diabetes story since there are many healthy lifestyle choices that cut the risk of stroke. Moreover, highly specialised care is needed to diagnose and treat the initial insult and there is often a period of ongoing care afterward.

However, two critical differences between diabetes and stroke open our eyes to another type of information. First, the stroke patient is at greater mercy of the system: Someone else must spot the symptoms and someone else must reach the patient. Second, unless there is a rapid-response system, the outlook is poor. Delay is lethal, leading to disability or death.

A stroke care system must process patients in intricately coordinated ways and under extreme time pressure, 24/7 and at scale. Coordination and timing at scale is the new Twenty-First Century challenge – medical logistics. While what we know in medical science determines the best we can deliver, our medical logistics knowledge determines what we deliver to most people.

Information systems for medical science are all about records and machinery that deliver numbers: Electronic patient records, path labs, biochemical labs, sequencing labs, radiology services, pharmaceutical dosages and side effects. Information systems for medical logistics are about people, places, resources and time: Where a 999 call comes from, where the ambulance is now, how many beds are available, where each member of staff is, and what machines are ready, now. More broadly, we need health population statistics to distribute our resources accordingly.

We make both types of information work in combination when a stroke victim in Kent is airlifted to Kings College Hospital within the golden hour. However, the information needed above the helipad is very different to that used in the neuro-OR just below it.

Our Twentieth Century success gives us ever better medical science information systems, increasingly augmented with advanced artificial intelligence (AI). The best we can do keeps getting better.

Importance of data

However, our inattention to the logistics of care means that the average service we deliver across the country is a long way behind. Worse still, logistics data is confused with audit data. Armies of people in the UK collect data about services, much of it of dubious quality and a vast majority of which is never used to alter patient care.

We argue that such data collection has become dangerous. Firstly, because the data driving government statistics rarely help to make a single decision to speed a patient through the system. Audit therefore skews data selection away from its use in care delivery. Secondly, audit enjoys priority over operations and people are fired when the audit numbers are wrong. This is inevitable in a state run, top down, unitary healthcare system.

The alternative, point of care access to logistics data for health professionals to better manage patient care and the flow of individuals, has fewer and weaker champions. Thus, audit data displaces logistics data as well as skewing it.

Healthcare depends upon two data types; the clinical determining the best we can do and the logistics that limit what most people will get. Right now, our best is diverging alarmingly from our average and, until we invest in the logistics of health, this trend is bound to continue.

About the authors

Using industrial processes to improve patient care (2004, with Brailsford et al., British Medical Journal)

Performing or not performing: what’s in a target? (2017, with Eatock & Cooke, Future Hospital Journal)

Systems, design and value-for-money in the NHS: mission impossible? (2018, with Morton and Soorapanth, Future Hospital Journal)

Professor Stephen K Smith is a clinician/executive having held senior positions in Academic Medicine and the NHS at the University of Cambridge, Imperial College, London, NTU Singapore and most recently the University of Melbourne. He currently serves on various health and health technology Boards including Chair of East Kent Hospitals University NHS Foundation Trust, and Netscientific Plc. and previously the Boards of Imperial College, London, Imperial College Healthcare NHS Trust, the National Healthcare Group, Singapore, the Royal Melbourne Hospital, Melbourne, and the Victorian Comprehensive Cancer Centre, Australia.

Professor Smith led the formation of the UK’s first Academic Health Science Centre at Imperial College Healthcare NHS Trust and was its first CEO. A gynaecologist by training, he has published over 230 papers on reproductive medicine and cancer. He was awarded his Doctor of Science in 2001 for his work in Cambridge on the complex gene pathways that regulate the growth of blood vessels in reproductive tissue. He was founder/director of the Sino-Japanese pharmaceutical company, GNI Group Plc, that is quoted on Tokyo SE and currently chairs a group of start-up digital health companies. He is a Trustee of Pancreatic Cancer UK and the Epilepsy Society.

Over the moon: Astronauts, digital twins and healthier services

By Professor Terry Young, BSc, PhD, FBCS

This month marks 50 years since Neil Armstrong said: “One small step for man.” This momentous feat of ingenuity, innovation and effort resulted in one of the greatest achievements in the history of mankind. What could the same appetite do for healthcare today? – Professor Terry Young.

You may remember Apollo 13 in 1970 because of the astronauts who didn’t step down, due to an onboard explosion. For several days, Mission Control managed the stricken spacecraft and innovated violently to bring the three men home. I remember – or think I do – watching grainy clouds, breathlessly waiting until the parachutes on the screen heralded splashdown and safety.

In Ron Howard’s film of the mission, flight director Gene Kranz (in the white waistcoat), portrayed by Ed Harris, is a great project manager. I bought Kranz’s book, ‘Failure is not an option,’ and decide to watch the film annually with the final year project management students, using the mission as a case study (along with London Ambulance’s Computer Aided Dispatch) on managing out of failure.

So what was pioneered by NASA back then that is so relevant today? First, they built one of the first global information systems for real-time decision-making. With less information than F1 teams collect at the races, they made high-quality decisions at pace and, despite the danger, they did not lose a life in orbit until long after the moon was abandoned. However, it was not just the technology, but the intent that mattered. A clear focus on decision-making yielded spectacular results.

Second, they used simulation all the time. Everything about space was new – the technology, zero gravity, getting through hatches in bulky outfits, aligning and docking spacecraft, the list went on. However, astronauts on a mission had to get it right first time and so NASA pioneered ways to develop mission protocols and test them to destruction, giving everyone the best shot after lift-off. Most obviously, they built mock-ups to train in.

More sophisticated was their quest to discover what might go wrong. Today, computer models run scenarios to see how various interventions play out. Back then, they used competing teams: A simulation team to define a scenario; and a flight control team to run it as a real mission.

Whenever there was a new question, getting into a simulator or simulating a scenario was a natural way to find an answer. Information and communications technology has come a long way since then, as have medical simulators and computer modelling, but the pioneering connections made half a century ago remain valid.

So why doesn’t every healthcare facility or service have a digital twin – a model of how it works, driven by real patient arrival and discharge patterns? And why, every time there is a waiting problem, or extra staff have to be recruited at short notice, or the spend rises mysteriously, is the first port of call not a session with the digital twin? What is wrong with this proven method of understanding the dynamics of a problem and finding what works with the fewest side effects?

We already have the mock-ups, so why are our simulation labs in which we educate our students not closed for education once a month and used for learning about the wider system? A dummy will not die if a simulation exercise can’t process patients quickly enough. The technology is already there: Why don’t we use it?

The appetite for simulation and real-time data in operational decisions drove one of the great achievements of the modern era. What could the same appetite do for healthcare today? Today we have the technology – where is the focus and intent?

Professor Terry Young worked in industrial R&D before becoming an academic and is now Director of Datchet Consulting. With over 30 years’ experience in technology development and strategy, health systems, and methods to ensure value for money, his current focus lies in designing services using computer models and he set up the Cumberland Initiative to support healthcare organisations wishing to develop their services more systematically. Three of his downloadable papers are:

Using industrial processes to improve patient care (2004, with Brailsford et al., British Medical Journal)

Performing or not performing: what’s in a target? (2017, with Eatock & Cooke, Future Hospital Journal)

Systems, design and value-for-money in the NHS: mission impossible? (2018, with Morton and Soorapanth, Future Hospital Journal)

Patient flows: Where engineering meets medicine

By Professor Terry Young; Jim Wilkerson

Engineering in medicine is not just about linear accelerators or medical technology scattered across wards, operating rooms (ORs) and other health spaces – Jim Wilkerson, System Director at Memorial Health System in Illinois, USA, and Terry Young of Datchet Consulting, write for ACJ.

As with icebergs, these are just the visible tip of an enormous engineering presence in healthcare today, especially in designing how people flow through the system to make better use of its resources. Jim Wilkerson, System Director at Memorial Health System in Illinois, USA, and Terry Young of Datchet Consulting write for ACJ.

An example of visible engineering is the CT scanner, a sophisticated product that costs around $2,000,000 and must operate in a lead-lined room (an engineering exercise in itself). Nearby, staff capture, manipulate and store 3D, high-resolution images from patients with anything from brain injury to arthritis. As a powerful, versatile, diagnostic, it is widely in demand.

Because it is so useful, expensive and immovable, invisible engineering must plan for as many patients as possible to use it. The engineering team at Memorial Health System exists to design the flows between wards, clinics, ORs, and facilities such as catheterisation laboratories (cath labs) or radiology departments.

This industrialised approach involves concepts still at the periphery of medical experience. The terminology may be familiar, but routine application is not. Memorial Health System promotes a Lean Six Sigma approach, a combination of Japanese and US manufacturing innovation, using point of care technology to speed diagnosis and move people through the system. There are strong reasons to do so in any care system, but access to a CT scanner makes such a focus particularly easy to justify.

Under this framework, computer models create prototype designs in search of greater service resilience or to eliminate waiting and other forms of waste. This highly numerate approach relies on a variety of data sources from internal information services to voice of the customer (VoC) systems in order to refine a model until it mirrors the existing system accurately. It is then used to trial new scenarios. In this case, one scenario was found to agree with the measured post-implementation situation to within 58 seconds in reducing delays by half an hour.

In 2014, a CT scanner at Memorial Health was becoming overloaded, but before purchasing a second machine, the design team explored the situation. It became clear that one source of delay concerned patients who arrived for a scan but had not been fully prepared – in some cases, they had to receive further medication first. To address this, a scenario was modelled in which an extra member of staff would check patients earlier and ensure that those arriving were ready to be scanned. It showed that creating this extra position for 8½ hours a day during peak demand would reduce the peak delay from requesting a scan to starting it by around a third. It was trialled for a limited time and then implemented permanently.

The in-house modeller used a package known as SIMUL8 to build and run the scenarios in less than a week, which at an internal charge-out rate of <$50/hour, came to <$1,500. Getting a decision through the board was estimated at <$20,000, while the extra staff member cost just over $50,000/year. Whatever the exact costs, the benefits were huge: $2,000,000 saved in not buying a new scanner and an estimated benefit of $700,000/year based on shortening patients’ lengths of stay through better flow and thus reducing costs.

This spectacular example is by no means unusual where models are routinely applied in designing services but it does not fully describe the value of the improvement, either. The full benefit of smoother, faster patient flows through CT will vary from patient to patient. If someone has just had a stroke, saving half an hour could have a big impact upon their survival and the quality of recovery. It will usually have less of an impact for patients needing a routine scan. To include the full health premium in a business case would involve collecting much more data (starting with the case mix of patients using the scanner).

At a time when health services are stressed and stretched, and there is a steady cry for more resources, this type of engineering is more important than ever. Evidence is starting to emerge that design plays a valuable role in services and we anticipate that it will not be long before this evidence is overwhelming. Until then, a failure to design systematically within an engineering framework is looking ever more negligent.

About the authors

Jim Wilkerson serves as the System Director for Operations Improvement for Memorial Health System of Springfield, Illinois. In this position, Jim oversees the training, development, and deployment of the system’s Lean Six Sigma resources and performance improvement work. Jim has been involved in designing Memorial’s quality and safety program that has been recognized as a state, national and international leader in healthcare. He holds two Bachelors of Science degrees in Finance and Business Economics and a Master’s in Rehabilitation Counselling. He is a Certified Lean Six Sigma Master Black Belt and a Licensed Clinical Professional Counsellor.

Terry Young is Professor Emeritus at Brunel University London. Following a PhD in laser spectroscopy, he worked for 16½ years in industrial R&D with GEC and technology strategy with Marconi. His research focus shifted during this time to healthcare services and his academic research, since 2001, when he moved to Brunel University London, has focused on the organisation and delivery of health services with emphasis on the value and role of technology. He is now an emeritus professor and Director of Datchet Consulting.

This case study was published in Health Systems under the title, The costs and value of modelling-based design in healthcare delivery: five case studies from the US (https://doi.org/10.1080/20476965.2018.1548255).

NHS: Using technology to wage war on waste

By Professor Terry Young, BSc, PhD, FBCS

Professor Terry Young analyses why the NHS has failed to reduce waste where other sectors have succeeded. Could technology enable an answer to be found at last?

While waiting for a flight in the departure lounge of an airport recently, I asked the pilot when we were expecting to leave. He dug out his tablet, swished about with his finger and said the inbound flight was the other side of Glasgow and would be on stand in 20 minutes. I asked about refuelling and the stacking over Heathrow and his trusty tablet told him everything.

As he left to do his pre-flight checks, I reflected that I could not have had such a conversation with any NHS manager, nurse or doctor. But then, pilots did not talk that way, either, when the NHS was born, 70 years ago.

It is tempting to look at the pilot’s world of timely figures and tracking information and to prescribe the same for the NHS. But what is it about flying or any of a dozen other sectors that has transformed them ahead of the NHS?

The answer involves two deceptively simple ideas – knowledge and process. Leaders in these other sectors were not specifically seeking knowledge or process but invested in them relentlessly because they were chasing something else – something that is critical to the NHS today.

Surprisingly, it was a deep-seated aversion to waste that drove this change. By the 1960s, for instance, supermarkets could see that delay in getting produce to the shop was a waste, not just because food goes off, but because the supermarket must spend money on a product right up to the moment a sale is made. Walmart’s investment in computer systems, barcode scanners, smart tags, and networks in the 1970s is testament to a frighteningly expensive war on waiting.

In the 1990s, a decade before the NHS attempted its national IT network, Walmart spent a similar amount on its own network, persuading its suppliers to invest considerably more, and made it work. The reason the NHS failed while Walmart succeeded was that the NHS had no clear idea of what waste the network was meant to eliminate, while Walmart knew exactly how the network would help make better decisions faster and how much decisions were worth.

Today, health researchers all over the world are working hard to identify waste in all its forms; from the obvious waste of prescriptions and treatments that are not needed to the less visible business of variation in practice. Lord Carter, for instance, has shown that similar NHS services can cost wildly different amounts to run, depending on where they are. So, what is holding the NHS back from a decisive victory over waste?

Firstly, many in healthcare find it at least as distasteful to express waste in financial terms as they find the waste itself. This is understandable to some extent since many NHS staff encounter several examples a month where money, or the paperwork that goes with it, comes before the patient. However, without a more reasonable relationship between the NHS’s mandate and the resources that make it run, there will always be significant, invisible waste.

Secondly, one cannot reduce waste without metrics, and the NHS struggles with measures of effectiveness. Too often these are associated with punishment, not often enough with polishing the process. Winning the war on waste will need better metrics applied in better ways.

Finally, if other sectors are anything to go by, waste often hides in the most unlikely places. The fact that a ward is full, or that the list at a surgery is overflowing, does not tell us whether either is efficiently run. It usually requires information from a long way back as well as knowledge of the wider service, to judge what is going on.

Given robust definitions of waste, however, the ingenuity of the NHS could be unleashed to track and eliminate it. The NHS employs some of the brightest people in the world – robust design and technology empowered delivery is not beyond them, nor is affordable, high quality, care at scale. What the NHS needs now is a clear target and the will to pursue it relentlessly.

Using industrial processes to improve patient care (2004, with Brailsford et al., British Medical Journal)

Performing or not performing: what’s in a target? (2017, with Eatock & Cooke, Future Hospital Journal)

Systems, design and value-for-money in the NHS: mission impossible? (2018, with Morton and Soorapanth, Future Hospital Journal)

Health systems: What should they deliver and why is this so difficult?

By Professor Terry Young, BSc, PhD, FBCS

What do we want from a health system? Professor Terry Young looks at the advantages of modelling to understand what solutions will be most effective and the difficulties of implementing change in the UK.

What do we want from a health system? Surprisingly, there is a consensus. Our STPs (Sustainability and Transformation Partnerships) are seeking:

Hospitals with unified points of entry and ways to track all patients’ needs all the time
Streamlined services elsewhere that are responsive, connect to one another and avoid duplication.
Smart information to make this new world of care affordable and manageable.

Many also want preventative measures, measures promoting healthier lifestyles, and mental health measures which, if anything, present an even trickier challenge. There are a number of tensions that contribute to our inability to make the health and care service we want.

The first reason health and care services in the UK struggle to deliver change is that we have been inordinately successful in delivering good care in the past.

This creates a sense that the skill-set needed to shape the future is already within our grasp.

The systems that we currently have in place have been shaped by those earlier successes. When there were fewer of us and we didn’t live so long or suffer from more than one condition at a time, systems could be simpler to meet more manageable needs. Even our ideas for measuring performance were shaped by, or are a reaction to, that context.

From the healthcare estate, we have inherited across the country to the way we think about care, the specialised clinical disciplines and the delegation of responsibility and accountability between services are all a result of heritage within the sector. However, things have changed somewhat. People are living longer, developing more long-term lifestyle diseases and multi-morbidity.

Moving care into the community

One cannot simply make like-for-like substitutions when transferring care from the hospital to the community since community services operate completely differently. In 2016, the Whole Systems Partnership built a model to explore a community-based cardio-respiratory service to accept 10 per cent of urgent cases and 50 per cent of GP referrals, replace 15 per cent of inpatient admissions, and manage 80 per cent of follow-up appointments. The model redefined the workforce into four skill levels to deliver a leaner skill-mix, a smaller overall workforce with a clear idea of the structures needed in both hospital and community.

Finding a new language

Our second challenge is to live with our legacy while finding a new language to articulate a wholly different future.

Even without a legacy, healthcare systems would still be almost impossible to design because they are so complicated and different pieces of the puzzle take wildly different amounts of time to develop. People take time to train – more than a decade in many cases – while drugs and technology develop at vastly different rates. At the other end of the spectrum, buildings go up quickly, but approvals and funding slow the process down. How then, do you introduce a new idea and ensure that it can be delivered?

The key to any design is knowing what to keep and what to change. Taking a cancer centre, for example: should it be designed for those heavy linear accelerators? Will the treatments in 25 years be mainly energy beams, chemistry, genomics or nanotechnology? And will oncologists, gerontologists, GPs or nurse practitioners run the service?

This is a fiendishly difficult problem because it involves great uncertainty about the future and requires great confidence that the final system will deliver what we want, without unpleasant, unintended consequences.

Simulation: try before you buy

In other sectors, people simulate or even game to explore such extremes. In the ‘60s, for instance, when nobody knew how to land people on the moon, huge effort went into simulation and simulators. Part of this was cultural; teams that created unfamiliar launch or recovery scenarios competing against teams that would run the missions, adding new pieces of doctrine every time a simulated mission crashed. On the other hand, there were mock-ups of each capsule and piece of equipment and the astronauts learned to work with, or within, it.

Today, one would not plan a new route for an airline or launch a new smartphone without extensive simulation of each operation and the impact of changing demand and other external forces. Even our cars have simple simulators that estimate whether we will reach our destination or run out of fuel.

It doesn’t matter where you start simulating: In a clinic, consulting room, ward, theatre, or at home. Simulations are part of our industrial heritage, so we understand well how to build, test and use models. Good models eventually enmesh the whole system to show where delays will build up, how much an extra nurse on the ward will cost or what benefit a new scanner will bring to all the people who will use it.

The Memorial Health System in Illinois models all patient journeys in detail from the emergency department to CT scanners and on to wards. Its engineering design methods routinely identify savings that can be applied. In one case, an extra elevator implemented to cut delays as patients moved from wards to the operating theatre paid for itself in a few days. In another study to streamline CT scanning, the addition of an extra individual to check the preparation of the patients saved half an hour per patient, which fell within a minute of modelled predictions.

We know an enormous amount about health and have leveraged that knowledge miraculously over the past half-century. What we must now learn is how to design systems to leverage that knowledge more cheaply and consistently than anything anyone has yet achieved. For the real challenge is more difficult still: To design the new while keeping the old system going until it is replaced.

Professor Terry Young worked in industrial R&D before becoming an academic. He has over 30 years’ experience in technology development and strategy, health systems, and value for money. His recent sabbatical was spent gathering evidence of where simulation has been used in healthcare and how much it is worth to design new processes. Three of his downloadable papers are:

Using industrial processes to improve patient care (2004, with Brailsford et al., British Medical Journal)

Performing or not performing: what’s in a target? (2017, with Eatock & Cooke, Future Hospital Journal)

Systems, design and value-for-money in the NHS: mission impossible? (2018, with Morton and Soorapanth, Future Hospital Journal)