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White Paper Jan 2015 Freddie McMahon - Director, Strategy and Innovation Putting Health into Context (and Context into Health) How Context Brokers and the Quantified Self will Transform Global Healthcare

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Page 1: Putting health into context (and context into health) final

White Paper Jan 2015

Freddie McMahon - Director, Strategy and Innovation

Putting Health into Context (and Context into Health)How Context Brokers and the Quantified Self will Transform Global Healthcare

Page 2: Putting health into context (and context into health) final

Anomaly42.com2

Overview

The size of the opportunity page 4

A new approach page 5

Quantified Self page 6

Introduction page 3

Fighting Disease with Data page 3

References page 13

Hidden in plain sight page 7

3 Vs of Big Data page 7

Data Security page 8

Towards a healthcare data ecosystem with the context broker page 9

Paradigm Shift page 10

Context In Practice page 11

Conclusion page 12

Rethink Global Healthcare page 10

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Introduction

The global healthcare system looks increasingly broken. If it’s not already in a state of crisis, most observers agree it will be soon.

It’s a crisis that affects us all. In many developing countries, we have yet to achieve basic levels of care, with social and economic problems hampering the evolution of reliable and sophisticated health services.

In developed nations, meanwhile, the cost of healthcare is spiralling out of control and the returns on that investment are diminishing rapidly.

Even worse, many of the health issues now confronting humankind are self-inflicted — the obesity crisis in the US, for example, is adding $190bn a year to the country’s healthcare budget, according to Cornell University’s John Cawley in a research paper i.

We should know better. And today we can know better.

Fighting Disease with Data

In the digital age, there is no shortage of data available to develop a healthcare ecosystem capable of transforming outcomes for people in need, both today and tomorrow. This data is key to both tackling preventable disease and dealing with disease that has not been prevented.

But there is a problem. None of the existing stakeholders in the healthcare ecosystem have yet confronted the task of managing data on a holistic, system-wide basis for the common good — for creating what we might coin a ‘health wealth’.Unfortunately, the ability to attain system value within healthcare is inversely related to the level of system fragmentation.The challenge, then, is to build a healthcare data ecosystem that aligns the different needs of those stakeholders, eliminates data fragmentation and siloism, and above all delivers better outcomes for the people of the world.

Enter the context broker.

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Global healthcare spending is currently on a stunning scale – around $6.5 trillionii a year and rising. The US alone spends 44% of the world’s health budget on just 4.4% of the world’s population – in 2012 its outlay was the equivalent of 17.9% of its GDP while the equivalent figure in the UK was 9.4%iii.

But the richer nations are getting neither value for money nor value at scale at the level of the individual.

For one thing, wastage is enormous: in the UK alone, $500m is spent annually on unnecessary prescriptions; in the US, meanwhile, the Institute of Medicine estimates that unnecessary tests are costing a mind-boggling $750bn each yeariv.

Moreover, even though a significant proportion of global healthcare spend is accounted for by a relatively small number of non-communicable diseases (NCDs), including cardio diseases, cancers, diabetes and mental health, we are failing to effectively tackle these conditions. Cardio diseases, diabetes and cancer account for 44% of total US healthcare spend, while 60% of deaths worldwide are due to NCDsv.

What’s very clear is that throwing money at the problem does not work. The US, which spends more on healthcare on a per-capita basis than almost any other country in the world, had an infant mortality rate of 6.14 infant deaths per 1,000 births in 2010vi.

The size of the opportunity

This is well above the average of four deaths per 1,000 births among the member countries in the Organisation for Economic Co-operation and Development (OECD). NCDs, to put it bluntly, do not care whether you are rich or poor.

Faced with the wholesale indifference of disease, we need to think differently and at a scale that matters.

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A new approach

How, then, do we fight these diseases more effectively and efficiently? The answer is twofold.

Firstly, we need smarter ways to evolve diagnoses and treatments for those who have already developed an NCD. At the same time, we need to become more skilled at preventing people falling prey to such diseases — 80% of the risk factors identified for common NCDs can be mitigated by lifestyle changes.

These are not unrealistic goals, for the information required both to develop better treatments and to promote healthier lifestyles is widely available. It exists in pockets all around the global health ecosystem – in hospitals and pharmacies, in research labs and universities, and in both the public and private sectors.

The second way to fight disease more efficiently is for us all to tap into, and learn from, the knowledge that is now available — and which, moreover, is being created at an exponential rate.

In his book, The Decision Tree: Taking Control of Your Health in the New Era of Personalized Medicine, former Wired executive editor, Thomas Goetz, demonstrated that individuals actively engaged in their healthcare decision-making have significantly better outcomes.

Increasingly, information is held by individuals themselves, within devices and apps generating a stream of data that is growing at an exponential rate. We are now witnessing the phenomenal growth of healthcare apps linked to wearable devices.

These wearables range from wristbands that monitor the number of steps taken each day by the wearer to more sophisticated kit that replicates the equipment that was once the preserve of healthcare professionals — monitoring blood pressure and the activity of the heart, for example.

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Quantified Self This is the age of the ‘quantified self’, in which individuals have the power to constantly monitor their bodies and the data they produce. We can keep an eye on the exercise we’re taking, the sleep we’re getting, our dietary intake, our stress levels and a multitude of other lifestyle factors.

Even better, we can monitor in real time the impact of making changes to our lifestyle, in order to enhance our health and well-being.

The quantified self depends on apps and the Internet of Things. Essentially, wearable devices rely on connected sensors that feed information back to apps that process the data and provide it to the individual user.

But the loop does not have to be a closed one: an aggregation of the anonymised data generated by hundreds of millions of quantified selves offers an incredibly rich – and continuously updated – database that has the power to deliver answers to some of our most fundamental questions about health, including NCDs.

Don’t underestimate the scale of the data being generated by wearable devices. Over the year to March 2014, 3.3 million Americans bought fitness bands from Nike, Fitbit or Jawbone in a market that grew 500%vii in each of the three previous years.

With the likes of Apple, Google, Microsoft and Samsung now moving into wearable technology, it is not difficult to foresee a world in which several billion users are simultaneously monitoring their health and well-being using such devices. On some estimates, 30% of smartphone owners will be using healthcare apps by the end of this year.

These will be clinical trials the likes of which the world has never seen before.

The scale of the opportunity is immense. This is our chance to transform the way we diagnose, treat and prevent the NCDs that are killing so many people around the world – and costing such enormous sums. We will do this not by devoting more resources to the battle against these NCDs, but by harnessing the power of something far more effective than hard cash - data.

The smartphone will become the primary source for healthcare applications and thus is positioned as a disrupter technology to global health

Smartphone user base in 2015 (millions)

30% of total smartphone users will be

using healthcare apps by 2015

TOTAL SMARTPHONES TOTAL HEALTHCARE USERS

1400

500

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Hidden in plain sightIf the opportunity is clear, the path to realising it is less so — especially without the necessary leadership, data-brokering and management of vast data ecosystems.

The reason for this is that, while vast amounts of healthcare data are now becoming available, and are growing by the day as wearable devices become ubiquitous, this data, in itself, has no value.

Instead, it is the stories within the data – the insight it is possible to generate from all that information – that will reveal new advances in healthcare. Yet finding those stories is the digital equivalent of finding a needle in a haystack: the value of data is hidden in plain sight.

One issue obscuring that value is the way in which the healthcare sector has developed in distinct silos. This is an industry with a diverse cast list. It includes pharmaceutical and life science companies, hospitals and clinicians, charities, academic institutions, carers, specialists in individual NCDs and third party service providers – the list goes on and on. And to that cast we must now add the mobile healthcare sector: the developers of the devices and apps that enable us to monitor our own health and which promise so much.

All of these players operate in isolation, generating and managing their own data. Each holds a piece of the jigsaw, but no-one is able to imagine the full picture, let alone see it clearly.

3 Vs of Big Data

It does not help that most of these players would find it difficult to share data directly with one another even if they wanted to. The healthcare sector suffers from data illiquidity – an inability to easily exchange information. The volume, velocity and variety of data – the so-called 3 Vs of Big Data – is simply too much for most organisations active in healthcare, whether in the private or the public sector.

Established healthcare companies can’t cope with the challenges presented by unstructured data, for example. They struggle with storage and processing. And they can’t operate in real time, or even close to it. The result is that the stories hidden within their data remain obscured – and the breakthroughs in dealing with NCDs are not achieved.

In part, the issue is cultural. In the pharmaceutical industry, for example, where businesses stand or fall on the strength of their intellectual property, the very idea of sharing data feels extremely uncomfortable.

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Data Security

Then there is the issue of data security and privacy. Healthcare industry players are acutely aware of patient concerns — not to mention regulatory scrutiny — about the confidentiality of their data. Even where data generated by an individual is anonymised and untraceable, strict rules govern how the information may be used and with whom it may be shared.

We are, in other words, confronted by a series of difficulties with which established healthcare organisations do not have the skills or experience to cope. Even new entrants to health from the technology sector, though well versed in dealing with data, are, in isolation, ill-equipped to deal with the scale of the challenge.

Yet the prizes on offer are too valuable to give up on. In human terms, the data now being generated holds the key to helping billions of people avoid many NCDs altogether and to treat those who do fall ill with far greater efficacy.

In socio-economic terms, meanwhile, the promise of this data is that governments and others will be able to do more with less — even to call a halt to the inexorable increase in healthcare spending that threatens to overwhelm the fiscal capacity of many countries.

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Towards a healthcare data ecosystem with the context brokerThe good news is that there is a solution. The solution is to build a data ecosystem in health, by which we mean a community of partners who are able, and willing, to share their data for the greater good.

These participants will offer up their pieces of the jigsaw in the knowledge that by remaining alone, the full picture will remain permanently out of sight. Those that choose to remain outside of the ecosystem, meanwhile, will be left behind by their competitors who do have access rights.

It is essentially a healthcare model based on ‘give and take’.

To see how that ecosystem might work, consider diabetes, where 14 healthcare apps aimed at this potentially debilitating condition have captured 65% of the available market between them. This relatively small number of app publishers are reaching two-thirds of smartphone users who use technology to help them manage their condition. In aggregate, the group is hugely powerful – all the more so if it can be linked to those with diabetes expertise, knowledge and data throughout the wider healthcare sector.

Building such ecosystems will be the job of context brokers.

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Paradigm Shift Yefim V. Natis, Vice President & Fellow from the Gartner Group, believes the context broker is the future of Big Data. Context brokers, a new breed of specialist provider, are capable both of building the technology platforms required to manage the data flowing out of disparate sector players and of analysing that data to unlock the value hidden within it.

The context broker, Gartner believes, is set to trigger a paradigm shift in global healthcare — one that benefits both rich and poor at a scale never witnessed in this sector before.

Context brokers search for ‘digital moments’ — instances when the contextualisation of raw data produces previously unseen insight on which it is possible to act. In the healthcare sector, those insights will be breakthroughs and advances – not just in terms of new treatments, disease prevention and diagnostics, but also the identification of care that is currently inefficient or ineffective.

We are entering a new era of Radical Preventability.

The demands on context brokers are daunting. They will need to build secured cloud services capable of ingesting, storing and processing different types of data from myriad sources, both public and private. They will need to work with stakeholders looking to interrogate this data for specific types of insight on which to base their decisions, as well as with those that have identified opportunities to realise insight by adding their own data to the aggregate.

Often, speed will be of the essence. While super-fast processing is already in demand in sectors such as financial services, other industries will demand the same accelerated services. In healthcare, for example, imagine what a context broker with exhaustive information on Ebola might be able to achieve – and imagine the pressure on it to do so quickly.

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Context In Practice

These ambitions and aspirations may sound optimistic — futuristic, even — to many healthcare professionals, but context brokers are already enjoying excellent results in other business sectors – notably in finance, where they operate on the frontline of the battle against money laundering, financial crime and combating the financing of terrorism, for example. The technology to achieve similarly meaningful results in healthcare is already available. The future has arrived.

Ultimately, context brokers enable participants in the healthcare ecosystem to achieve more than they ever could in isolation. The whole, if you like, is far greater than the sum of the parts. As data curators, context brokers administer platforms and processes that deliver far greater value to each member of the community than those members would ever be able to achieve by themselves, overcoming the hostility towards data sharing many currently feel.

They do so, moreover, within a robust and controlled governance structure, compliant with data privacy and security laws.

And since context brokers are cloud-based, the cost of achieving these goals has been radically collapsed for all participants in any given ecosystem.

In short, information-driven healthcare represents the sector’s greatest opportunity to confront and control the NCDs that ravage mankind — and context brokers will be on the frontline of that battle.

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Conclusion

Healthcare is the biggest single drain on global resources, but however much money governments and authorities throw at the problems they face, it is never enough — the bill just keeps on rising.

To give you an idea of the extent of the problem, the World Health Organisation believes that, by 2030, the cost to the global economy of non-communicable diseases (NCDs) will reach $47 trillionviii, three times the size of the entire US economy last year.

The only practical solution is to be smarter about how we make healthcare decisions – to harness more and better information as we work out how to diagnose, treat and prevent conditions that are physically debilitating for individuals and economically destructive for society as a whole.

Vast amounts of such information are already available but, in the era of the Internet of Things, wearable devices and other healthcare technologies linked to smartphones and tablets will generate more data than we can possibly imagine. By the end of 2015, 500m people around the world will be using healthcare apps on smartphones.

Rethink Global Healthcare

Within this data lie the answers to many of our most crucial healthcare challenges. But such insights will remain obscured unless we build a data ecosystem in which as many actors in healthcare as possible share their data and work with technology platforms capable of unlocking the hidden value.

The evolution of context broker services operating on behalf of multiple stakeholders is now essential for the future of healthcare. They offer the ability to achieve a far more meaningful relationship between cost and quality, and to accelerate the health innovation cycle by continually extending the boundaries of knowledge.

The context broker has already rethought data. Now it is set to rethink global healthcare — and to revolutionise the health of entire societies in a way never seen before.

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References

ihttp://www.human.cornell.edu/bio.cfm?netid=jhc38

iihttp://www.accenture.com/SiteCollectionDocuments/PDF/

Accenture-Fueled-Healthcare-IT-Start-Up-Funding-Digital-

Disruption-Knocking.pdf

iiihttp://data.worldbank.org/indicator/SH.XPD.TOTL.ZS

ivhttp://kaiserhealthnews.org/morning-breakout/iom-report

vhttp://www.ncdalliance.org/globalepidemic

vihttp://journals.lww.com/journalpatientsafety/

Fulltext/2013/09000/A_New,_Evidence_based_Estimate_of_

Patient_Harms.2.aspx

viihttp://journals.lww.com/journalpatientsafety/

Fulltext/2013/09000/A_New,_Evidence_based_Estimate_of_

Patient_Harms.2.aspx

viiihttp://www.weforum.org/news/non-communicable-diseases-

cost-47-trillion-2030-new-study-released-today

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