Future of Healthcare Provision Jan 2017

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FUTURE OF HEALTHCARE PROVISION:
Opportunities for Patient Engagement

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The Future Agenda programme is the world’s largest open
foresight programme and is based on the idea that by engaging
with others from different cultures, disciplines and industries we
can collectively create a more informed understanding of the
world in which we live. This makes it easier to shape a strategy
that will help to address the major challenges we face. Our aim
is to identify ways in which systems could function, consumers
behave and governments regulate over the next decade and
give all organisations, large or small, access to insights that we
hope, will help them to develop their future strategy.
The first Future Agenda programme ran in 2010 and brought
together views on what will impact the next decade from
multiple organisations. Building on expert perspectives that
addressed everything from the future of health to the future of
money, over 1500 organizations debated the big issues and
emerging challenges. Sponsored globally by Vodafone Group,
the programme looked out ten years to the world in 2020 and
connected CEOs and mayors with academics and students
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over 50,000 people from more than 145 countries who added
their views to the mix.
The second programme, Future Agenda 2.0, ran throughout
2015 looking at key changes in the world by 2025. Building on
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Context
Many believe the healthcare sector is ripe for a digital transformation. The escalating
challenges it faces are putting increasing stress on the system just as better
understanding of the possibilities of effective data sharing and analysis is emerging. A
growing number of companies, academics, regulators and investors see that we are
on the cusp of transition to a more integrated system. In the main this will be enabled
by greater patient engagement around meaningful data and associated actions.
Based on discussions in 5 countries in 2016 this initial
paper seeks to outline some of the key drivers of change
taking place across healthcare that supports this transition.
It discusses the sector’s three primary challenges of improving
access, controlling costs and accelerating personalization. It
then goes on to explore the importance of patient proximity,
a focus that is increasingly enhanced by the role of data in
all aspects of service delivery. Next it outlines three core
constraints of interoperability, security and privacy that must
be tackled if wider use of data is to be embraced fully. Particular
opportunities are seen to lie in rethinking data ownership and
in an open data ecosystem.Then it poses key questions on
issues around compliance and engagement such as how to
bring the uninitiated into the fold. Finally, it concludes with
a possible way forward, where patient centricity and patient
owned data features as core focus areas.

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Macro Healthcare Trends
Globally, on average, we have never been so healthy,
wealthy and educated. Although there have been long-
term improvements in health delivery and care, it is over
the past few decades that progress has really started to
build momentum. Advances in technology, public health
and governance have aligned to create a forum to share
understanding of the big health issues and identify ways
to address them. There have been some huge successes;
the IMF highlights that child death rates have fallen by more
than 30% since 2000, with about three million children’s
lives saved each year compared to 2000. Deaths from
malaria have fallen by one quarter and a simple vaccination
has meant that the death rate from measles has dropped by
79% over the same period.
However, lives are still being lost unnecessarily. Raising
fatalities from heart disease and stroke, diabetes and,
what are sometimes called the diseases of despair, drug
over-doses, alcoholism and suicide has meant that in the USA
life expectancy has declined for the first time in two decades.
Other rich countries are also suffering. In emerging economies
preventable diseases such as pneumonia, diarrhoea, malaria,
measles, HIV/AIDS and malnutrition are the primary killers.
During the initial conversations on the future of health three
issues were identified as the primary challenges.
Improving Access
Globally healthcare is already well over a $7 trillion industry.
But, despite its size, it only addresses about 30 per cent of
the world population; nearly 70 per cent is nowhere near
receiving decent healthcare services and, according to the
WHO, 400 million do not have access to even essential
health services.1
Depressing though these figures are, the
good news is that greater understanding of the relationship
between technology and treatment is revealing new ways to
access those who previously have been beyond reach.
The key obstacles to better healthcare include lack of health
education, poor medicine supply and distribution, insufficient
health facilities and staff, low investment in health and the
high cost of many medicines. Emerging markets carry the
main burden, however, even the wealthy West has problems,
mainly around universal treatments and affordability. For
governments health and our attitude to its provision has
become a political minefield influencing election results and
causing public outcry. As a result, around the world initiatives
are underway to find effective and long-term solutions.
Rethinking health care provision so it can be available
to a wider audience is a common government objective
and to this end tele-health, and especially ‘m-health’ has
already shown great promise globally. The timely delivery of
information direct to a patient can have a significant impact
on compliance. In Kenya, research shows that something as
simple as sending text messages to remind patients when to
take their HIV drugs improved adherence to the therapy by
12%. It can also be useful for those patients whose treatment
may be socially sensitive. In Tanzania, where many believe
medical interventions in childbirth is against God’s will, the
Wazazi Nipendeni service offers informative text messages
in Swahili directly to pregnant women and mothers with
new-born babies thus sparing them the embarrassment of
being seen with a healthcare worker. The messages include
instructions such as how to treat early pregnancy nausea,
information on the importance of breast milk and how to
monitor milk intake. The service has proved effective and
has scaled significantly since its launch in November 2012
reaching over 1,350,000 registrants and sending over 86m
million text messages.
Applying different business models can also transform
routine care. For example, franchising has enabled social
entrepreneurs to build infrastructure quickly. VisionSpring
already provides entrepreneurs in 13 countries with a
‘business in a bag’ - all the equipment they need to
diagnose and correct long-sightedness. By teaching local
‘vision entrepreneurs’ how to diagnose common problems
and so determine what type of mass-produced glasses can
correct these, the organization has significantly increased
reach and kept distribution costs low because information,
Globally healthcare is already well over a
$7 trillion industry. But it only addresses
about 30 per cent of the world population.
Improving Access
Controlling Costs
Accelerating Personalization

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products and services are standardized and simple to
implement. In India the Aravind Eye Care system that provides
cataract operations has adopted the same approach from
initial diagnosis through surgery to recovery with impressive
efficiency and effectiveness. It’s a factory-like approach to care
- lacking empathy perhaps but delivering impressive results.
Another way to connect to patients in hard to reach areas
is to piggy-back on existing institutions and infrastructure.
In the US MinuteClinic, often affiliated with local doctors
but based in shopping malls, benefit from existing footfall
and lower overhead costs. Others have even extended their
business activities in other sectors. Thailand’s Population
and Community Development Association, which focuses
on family planning and the prevention of sexually transmitted
diseases, established a chain of restaurants and resorts to
raise revenue - and to get out the message.
For many the inability to access services is because there
is a shortage of trained professionals. The WHO estimates
that there is currently a shortfall of 18 million healthcare
workers around the world to achieve and sustain universal
health coverage particularly in low and lower-middle income
countries. A recent commitment to create 40 million new
health worker jobs by 2030 will go some way to address the
problem but in the meantime m-health and e-health again
are playing a role in extending the reach of existing services.
It’s not a new idea but it is effective. For over 15 years in
Mexico Medicall Home has re-used simple mobile systems
to provide high quality 24x7 medical advice for its customers
across over 200 cities. The fixed monthly fee of around US$5
is far cheaper than the cost of a visit from a doctor.
This connection between improving access while
simultaneously reducing costs is the ultimate target for
many initiatives. There are many expensive options available
for increasing the reach of healthcare systems, but in a
cash-strapped world doing so in an affordable manner is a
growing prerequisite.
Controlling Costs
Lack of healthcare availability is one problem; affordability is
another. There is, and perhaps always will be, a never-ending
struggle to balance cost, quality and access. As nations
develop, their economies grow and their populations live
longer, and spending on healthcare rises. Most developed
countries now use upwards of 9% of their GDP on health care
– in the US, it’s over 17%. In India, spending is now over
4%, in China it is approaching 6% and in Indonesia over 3%.2
In fact, the UK is currently the only western country seeking
to reduce net healthcare spend per capita3
– something that
many other nations are monitoring with interest.
While acknowledging that disease prevention through access
to the likes of clean air and clean water is more effective
than its treatment, the challenge for healthcare providers
is to maintain and ideally improve the quality of care for
those who have an illness without increasing spend. Often
this means finding ways to make processes more efficient.
In some respects, emerging economies, which are often
grappling with infectious disease, are better equipped to
adapt to changing healthcare needs primarily because they
are unencumbered by legacy infrastructures. Huge changes
can sometimes be made quickly. Rwanda, despite recent
war and incredible poverty (income per head is $690 a year)
has managed to create a reasonably effective health system
including 45,000 health workers trained to give primary care
and a national health insurance program, Mutuelles de Sante,
which covers 81% of the 11 million population. A further
10% are covered by government insurance for soldiers and
civil servants. This makes the proportion of Rwandans who
have health insurance by far the highest in Africa. True this
achievement is, in part, due to the support of foreign aid but
other countries have not achieved as much.
Lessons can also be learned from India given that it is a
clear centre of process innovation. Aravind’s achievements in
cataract surgery have already been mentioned but there are
many other examples. For instance, LifeSpring has reduced
the price of childbirth by up-skilling midwives so that they can
provide most of the care – thus enabling doctors to oversee
more patients while reducing the standard cost of baby
delivery by 80%.
Most developed countries now use upwards
of 9% of their GDP on health care.

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The greatest success story of all however is probably
Narayana Healthcare which has brought the cost of high
quality cardiac surgery in India down to around $2000 per
patient, 1/50th of the comparable cost in many US facilities.
The focus is on offering as many operations as possible
without compromising on quality. Surgeons perform the most
complex procedures and other medical staff do everything
else. In addition, by, for example, using tablets instead of
patient charts, it is easier to create simulations to train a new
generation of critical care nurses across the country.
Dr. Devi Shetty, founder of Narayana sees that the principles
that have been developed and refined in India can certainly be
applied elsewhere. “We have developed what some see as a
‘frugal’ innovation approach to several healthcare challenges
and hence have proven design solutions for low-income
populations. These solutions can also be applied to higher
income economies with even greater efficiency benefits.”4
In the West lots of cost-containment options are being
discussed including limiting universal healthcare access,
increasing private healthcare insurance, expanding co-pay
arrangements, introducing personal healthcare budgets and
withdrawing treatment for behaviourally related conditions like
lung cancer and high BMI obesity. Some of these approaches
are to an extent compromises however. True, they may help
to reduce costs but at the same time they may well exclude
care for those with real need. With medical tourism growing
fast and some companies, such as Narayana, opening up
new facilities closer to Western markets, many are coming
around to Dr. Shetty’s view that frugal innovation approaches,
already proven in Asia and Africa, may well be the way ahead.
Personalized Medicine
Technology has a huge role to play in improving healthcare
delivery while controlling costs. Personalized medicine
and the prospect of customized therapies based on
more sophisticated diagnostics is a major focus for many
researchers and the opportunities for genetically orientated
pharmacogentics are substantial. With most current
medicines only working for 1 in 10 patients and many $1bn
blockbuster cancer drugs effective with only 25% of patients,
the potential for bespoke treatments is significant. But
aside from a few success stories like Herceptin and Xalkori,
personalized therapeutics have had only a limited impact
thus far. The trick is to develop a business case that works
for everyone. At the moment personalized drugs targeting
small groups with specific conditions are more expensive
than the alternatives that focus on larger populations so it’s
difficult for the pharmas to capture value. Looking ahead it
may well be that identifying the number of non-responders
for the treatment of say, rheumatoid arthritis, and therefore
reduce drug wastage may be a more popular approach.
Technology firms such as Apple and Google are already
spotting the opportunity to add their skills into personalized
medicine by gathering lifestyle data via remote monitoring
technologies. Accruing such information around lifestyle
choices adds preventative action into the treatment. Indeed
several now see that ‘we are going to be leaving population
medicine – where one size fits all – in favour of individualized
medicine’5
and implicit in this is that the patients will
increasingly drive their own care. Central to this is the wider
use and reduced cost of genetic profiling. With the growth of
organizations such as 23andme providing hereditary genetic
information commercially, a growing number of people can
see future conditions early and so take preventative action.6
Despite concerns about privacy and ownership, increased
access to personal health data will challenge existing
healthcare models focused on stereotypical conditions. In
the future several governments now expect personalized
diagnosis to be commonplace.
Taking this further, equipped with greater understanding
of the individual’s genetic disposition and new intervention
technologies, we may soon be able to proactively edit
genes and undertake minimally invasive surgery to reduce
the need for major surgery in later years. Gene editing
technologies such as CRISPR may mean that surgery is
prevented or minimised via early intervention. Coupled with
more predictive analysis across the system and the currently
spiralling costs of healthcare, more preventative healthcare
in the long term will eventually gain wider support and
traction in key areas and the combination of new technology
development with the need to improve system efficiency
accelerates introduction in many countries.
We may soon be able to proactively edit
genes and undertake minimally invasive.

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On the plus side although the business model for
preventative healthcare is yet to be fully defined, those such
as McKinsey and the GSMA see this as a potential means
of saving $200bn a year just in the treatment of chronic
diseases across the OECD and BRIC countries. However,
the downside is that in the short term, governments will
have to manage and pay for the current approach to health,
treating illness and so on, at the same time as developing
the new system that maintains health. Good regulation will
be key. It is too complex and expensive for the pharma
industry to conduct trials without knowing the parameters
of regulatory compliance. Given this, for many nations the
full impact of preventative healthcare approaches may not
delivered until 20 to 50 years down the line. In the meantime
we will probably have to ‘double-pay’ for healthcare for
a generation.
Getting Closer to the Patient
Implicit within many of the shifts now being advocated to
further improve healthcare systems around the world is the
principle of getting closer to the patient. If, for example, the
delivery of care is literally in the home then significant benefits
are gained in terms of lower distribution costs and improved
adherence to clinical protocols. New digital technologies,
such as portable sensors providing tailored advice, mean that
healthcare systems have the potential to be designed more
for the patient’s convenience and less around expensive,
over stretched facilities such as hospitals. There are, for
example, growing ranges of apps through which users can
talk directly to doctors and therapists and soon it will become
common for patients to chat with artificial intelligence health
advisers through messaging apps. The ambition is huge.
Developers such as Babylon are not aiming for apps to simply
be symptom checkers; rather they are building knowledge
repositories that will monitor symptoms, diagnose and treat
patients.7
Advancements in artificial intelligence mean that
as more people use the service the more data is collected
and therefore the more accurate a diagnosis can be. In the
UK a doctor carries out about 7,000 consultations a year, an
app can base its response on billions of data points. Some
are already predictive - IBM/Medtronic will soon offer an app
to predict, three hours in advance, when a diabetes patient
may suffer from high or low blood sugar for example. As the
fitbit generation matures, mobile devices will monitor physical
change, diagnose problems and suggest behavior change.
If necessary, it will also refer you to a specialist. Aside from
significant cost savings, this is hugely positive for time-starved
carers and healthcare providers creating the opportunity to
offer patients more emotional and holistic support.
Using mobile devices in place of pathology labs is another
transformative technology that is having great early success,
particularly for the management time sensitive conditions
such as sexually transmitted diseases, and may well alter
the way medical laboratories are used. If successful, mobile
labs will be able to function anywhere where there is internet
connection having a huge impact on the hard to reach areas
such in India, Africa and Asia for example. DNA profiling via
mobile is also just around the corner. Designed by Oxford
Nanopore Technologies, the MinION, which uses a USB stick
powered device to sequence DNA in real time, is currently
being used in 3,500 labs to diagnose outbreaks of diseases
such as Ebola and pneumonia.8
A plug in module designed
for a smartphone will soon be available for home use. These
tests will identify infectious diseases but also have the potential
to diagnose cancers, organ decay and genetic diseases.
However despite its potential, mobile health is currently a
fragmented and nascent market that needs consolidation
to drive real change. Again regulation will be key, particularly
as there is a move beyond wellness towards managing
chronic conditions. The FDA supports a calibrated approach,
focusing more on areas where misinformation could be
dangerous rather than low risk apps that promote a healthy
lifestyle. Other regulators are likely to follow a similar path.
New digital technologies mean that
healthcare systems have the potential
to be designed more for the patient’s
convenience and less around expensive,
over stretched facilities such as hospitals.

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Clearly in the past few years, data and data exchange have
emerged as the ‘new currency’ in health care, and have
become a major force in redefining relationships, transforming
the industry into an information-driven business.9
As well as
providing increased efficiencies for healthcare providers it
is clear that better understanding through data analysis is
beneficial to patients, unlocking cures and transforming the
quality of care.
These days most attention is being showered on the
promise of “big data” in which giant databases on genomics,
population health and treatment are crunched in the hope of
discovering medical insights. But there is also a great deal
going on to improve treatments and outcomes through “small
data” and the collection and processing of modest amounts
of information from an individual patient. Here, data can be
shared at minimal risk to patient privacy. As yet however just
a small percentage of healthcare systems are doing even
this.10
Patients routinely transition from one organization to
another, receiving care and services from different providers,
health systems, and health plans. In too many instances,
health data does not follow the patient, creating gaps in
coverage and leading to fragmented, uncoordinated care
that diminishes quality and drives up costs.11
While the US
system is still a long way from implementing widespread data
sharing, there have been some notable recent moves. For
example, new entities such as the Health Transformational
Alliance, which represents almost seven million employees
of self-insured companies, are now aggregating health care
data about their employees in an effort to implement value-
based care.
As more information is available to the individual, many
people are able to make more informed decisions about
their health because they can become custodians of their
own health records. Wearable devices will increasingly
provide more detailed analysis and monitoring of our bodies
and shared data platforms allow us to compare our health
with that of our peers. As such, more of us now have the
capability to access detailed and specific information,
becoming as informed as health professionals about our
overall condition. Some fear that this information can easily
be misinterpreted by untrained amateurs; treating a patient,
after all, is often complex, emotional and wholly dependent
on circumstance. But the up side is that it allows individuals
to be more informed about their own conditions than ever
before and therefore less reliant on over-stretched primary
care providers.
Most people believe that medical expertise, delivered by a
one person to another will always be needed, not least to
ensure the humane delivery of treatments but the evidence
would suggest that the sharing of personal health data with
patients in established systems could give them greater
control over their own wellness. The US-based OpenNotes
initiative illustrates this. A trial began in 2010 as a one-year
demonstration project: it involved 105 primary care physicians
who invited 20,000 patients to read their patient visit notes
online. The results showed that, of those who did, around
75% reported better recall of care plans, better self-care,
a clearer understanding of their conditions, and a sense of
being better able to manage their condition.12
Of the patients
surveyed, 99% wished to continue using the service.13
Today,
OpenNotes states that over 11 million patients have access
to their clinician’s notes.14
More broadly aggregated, anonymized data is already
being leveraged for a wide range of social purposes from
healthcare to disaster response and the potential for
specific insight creation from larger population data sets is
attracting mounting attention. One of the most well known
examples is the free data sharing portal patientslikeme.
com. Since making its website available to all patients and
all conditions in 2011, its aim has been to put patients first
by helping individuals to track their symptoms and progress
against others with similar conditions. As of December 2016,
patientslikeme.com had a community of more than 400,000
people with more than 2500 conditions. While platforms
such as this operate successfully on the basis of enabling
people with common interests in specific conditions to see
and interact with each other’s anonymized information,
challenging questions are being raised about the extent
to which patients should share their individual data, and
with whom.
The Role of Data
More of us now have the capability to
access detailed and specific information,
becoming as informed as health
professionals about our overall condition.

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Collaborations like this are showing the way for the potential
of prevention approaches. However, in order to make
them truly effective, the challenge of centralising essentially
decentralized systems at a national scale remains. Many
would say that combining datasets has really only ever
worked in fairly simple cases and with few interconnections.
With systems as widely varying and disparate as those
found across the healthcare sector, it could well be that
immense, centralized systems will never completely offer
efficient platforms as there are just too many moving parts.
Picking the data worth sharing and matching it with the most
appropriate platforms around specific issues, conditions,
demographics or public vs. private healthcare systems is
seen by many as the most pragmatic approach.
If, as some suggest, we all move towards universal healthcare
data access then we will create a world where information
silos are connected via third parties able to unify, mine and
discover new insights. Integrated public and private datasets
can then provide holistic views of the individual and value
shifts to decision-making analytics. Moreover, as we move
from disparate, under-utilized data sources to real-time
synthesis of multiple data platforms we will gain improved
accuracy and speed. Predictive analytics and genetic
profiling together can create more connected prediction and
so help to drive hyper-personalization and early action.
Looking ahead if, alongside improved access and lower
costs, the impact of personalized medicine is to become
truly significant, then patients will increasingly need to trust
in the sharing of their own data with others. After all, data
is only powerful in the presence of other data so the more
that is known, the more can be achieved. This may present
cultural challenges in some markets, particularly perhaps in
the West, where the sharing of personal information is often
not easily accepted. Public concerns around the unregulated
of use of data are already growing and unless controlled
successfully, as health apps become more popular, fears
around how personal data are stored used and shared will
become more pointed.
As we move from disparate, under-utilized
data sources to real-time synthesis of
multiple data platforms we will gain
improved accuracy and speed.

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Although the mainstream of expert opinion now supports
wider use of data across healthcare, there are several areas
where the potential opportunity is currently being mitigated.
While many organizations hope that improved data access
will eventually drive greater system efficiency and enable the
much sought-after more effective, personalized, healthcare,
today several recognize that there are three important
moreconstraintsinthemix.Theseareinteroperability,security
and privacy. They evidently need to be considered in all
future thinking.
Interoperability
Although there has been a proliferation of health data and
its collection, many see that we are not yet at a point of
unleashing its power because the vast majority of information
remains proprietary and fragmented among insurers,
providers, health record companies, government agencies,
and researchers. Despite the technological integration seen
in banking and other industries, health care data has largely
remained scattered and inaccessible.15
Indeed attempts to
make hospitals and clinics more efficient by building huge,
centralized IT systems have a sorry history - just look at a
failed patient-record system for Britain’s National Health
Service, scrapped at a cost of around £10 billion ($15 billion).
To date the global healthcare industry has so far struggled to
successfully manage the myriad stakeholders, regulations,
and privacy concerns required to build a fully integrated
healthcare IT system.16
The problem is clear; the Institute
of Medicine, for one, sees that: “A significant challenge to
progress resides in the barriers and restrictions that derive
from the treatment of medical care data as a proprietary
commodity by the organizations involved... Broader access
and use of healthcare data for new insights require not only
fostering data system reliability and interoperability but also
addressing the matter of individual data ownership and the
extent to which data central to progress in health and health
care should constitute a public good.”17
Part of the difficulty is that many of today’s healthcare
systems are rife with multiple and legacy systems. In the US,
for example, EHRs currently remain fragmented among 860
ambulatory care vendors and 270 in-patient vendors. The
UK is similarly disjointed. IT issues such as compatibility and
version control are obvious hurdles, as is the fact that many
healthcare systems are increasingly strapped for cash, which
inhibits their ability to secure sustained financial support for
the investment required. At some point the nettle will have
to be grasped and significant investments made. Some
potentially pivotal changes are already afoot. The Affordable
Care Act, for example, mandated that all medical suppliers
switch to electronic health records. It’s a small step and the
federal government had to spend $30 billion to subsidize this
push. Pity is is now being unwound!
Security
Not everyone is wholly supportive of interoperability however.
With the rising tide of data hacks and wider cyber security
now a mainstream concern in healthcare, the idea of
centralized ownership of medical records is increasingly
being viewed by some as a security risk. Leaders such as
Eric Topol, Founder of the Scripps Translational Science
Institute, are now advocating that “we need to decentralize
this data because the more it’s amassed, the more likely it’s
going to be hacked.”18
Certainly companies, governments and networks understand
that healthcare data is valuable to cybercriminals and indeed
is vulnerable to abuse. Once vast amounts of personal
health information are digitized they becomes a valuable
resource that drug developers, insurance companies and
governments themselves all want to access. Back in 2010,
a Future Agenda discussion in Washington DC identified the
probability of a ‘privacy Chernobyl’ – an event that changes
our attitudes to data security - and suggested the most likely
target for a significant attach to be US medical records.
Since then we have seen a growing incidence of cyber-
attacks across multiple industries and, within healthcare,
rising awareness of the potential risks and implications.
Three Core Constraints
Governments and networks understand that
healthcare data is valuable to cybercriminals
and indeed is vulnerable to abuse.
Security Privacy
Interoperability

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It is true that any data set, however well protected, is
highly susceptible to a cyber attack and health records are
attractive targets. The industry is vulnerable; in 2015 data
breaches affected over 112m records.19
In 2016, Anthem,
the second largest health insurer in the US had over 80m
records accessed by a hack.20
This is an ongoing threat
as cybercriminals become ever more imaginative in their
approach. Europol’s 2016 Internet Organized Crime Threat
Assessment (IOCTA) identified a new strain of server-side
ransom-ware predominately targeting the healthcare industry.
Privacy
As the technical capabilities of big data, in its myriad forms,
have reached a level of sophistication and pervasiveness
that can be capitalized upon to uncover better healthcare
solutions, there is a growing public understanding that,
although accessing data is possible technically, it may not
be culturally acceptable – particularly as health records
show the most sensitive details about us, from alcohol and
drug abuse to sexually transmitted diseases and abortions.
Attitudes around this vary between nations. In Singapore, for
example, the prospect of the government providing every
child with a ‘fit-bit’ device for 24/7 healthcare monitoring is
seen by many as a progressive and positive move. In other
countries this is an unnecessary infringement of privacy. Trust
in government changes significantly around the world and
few nations beyond Singapore would currently countenance
such an intrusion.
The global nature of technology has created new types of
interaction and as data whizzes across borders, creating
workable rules out of varying national standards is becoming
a priority. Global standards are needed for each country to
sign up to and use as a basis going ahead but much can
be learned from individual national approaches. Germany for
example is seen to be one of the most proactive in terms of
balancing the big data opportunity with privacy concerns. It
allows for emergency patient data to be stored digitally, but
the Bundestag has also mandated security to be “top priority”
defining more robust logging and encryption requirements.21
Necessity will mean that global standards will eventually be
created but even garnering local agreement in Europe has
been difficult; America has a different approach; China and
India, both of which have more people online than Europe
and America have citizens, have another.
There is a growing public understanding
that, although accessing data is possible
technically, it may not be culturally
acceptable.

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If wider data sharing is to be enabled, then clarity on data
ownership is critical. Successfully differentiating between
personal vs. organizational information about any individual is
one significant area of debate, but equally so is the nuance of
data access vs. data ownership. If the ownership of personal
healthcare information can be clarified either directly or via a
growing range of intermediary platforms, then we can see
an emerging world of more collaborative healthcare. Data-
centric patients will ideally shift from a dependency on expert
practitioners: They will take on more responsibility for their
own care and so collaborate with a wider range of health
professionals as they pursue improved health and prevention
The Opportunity Landscape
Fundamental to realizing some of the future opportunities is
not only how to better share data, but also to consider how
we manage its ownership and to what extent we make data
more open.
Data Ownership
As data sharing is gaining wider support, the implicit issue
of who owns that data is correspondingly also escalating in
attention. Fundamental here is the perception of the growing
value of data and the huge economic incentive to generate
and collect data from whatever sources are available. As
more data from more things becomes accessible, we can
increasingly see a public and private data “land grab” taking
place by organizations.
Currently, an individual’s general online data - personal
details, social media, etc. - is stored across many online
accounts and services. People then elect to opt in to (or out
of) third-party offers giving away personal data in exchange
for a more personalized service. The data in these exchanges
is often retained with the third-party and inherent within
these exchanges is the possibility of breach of privacy. Soon
though, it could be the case that customers not only access
their data, but also own it and don’t have to give it away and
yet still receive personalized services.
In the retail and finance sectors many now advocate
the adoption of so-called personal data stores: Led by
developments in authentication, an increasing array of
personal data platforms are now migrating across the
consumer arena and entering the healthcare sector. These
may well lead to universally accepted credentials stores that
share data with multiple partners. In doing so they will give
consumers, and hence patients, greater ownership.22
Beyond the individual’s personally-owned data, there is also
the important distinction of the information held by others that
can be made better use of - and in particular that which is
held by healthcare institutions. In the UK, Google’s DeepMind
and the NHS have formed a formal relationship whereby the
artificial intelligence company has been granted access to
healthcare data of 1.6m patients of three London hospitals.
The first two collaborations to emerge from this work are a
way to alert staff of patient kidney deterioration via a smart
phone app and a digital eye scan to identify sight-threatening
conditions.23
These and other collaborations are based on
the freedom of hospitals to share patient data with third
parties. It is clear that the intelligent bet taking place here
is that DeepMind can use the information and its agent led
machine-learning tools to form algorithms that better map
and predict issues in certain patient groups and individuals
– and perhaps is an indication of what technology can make
possible going forward. Inevitably however, there are privacy
and permissions concerns over the release of such a volume
of information being potentially handed over to, or made
accessible to, the commercial side of Google.
Tim Berners-Lee has been steadfast in making a relevant
point that “the data we create about ourselves should
be owned by each of us, not by the large companies that
harvest it. Users should own their own data and be free to
merge it with other sets as and when it could provide them
useful insight.”24
Fundamental here is the perception of the
growing value of data.
Data
Ownership
Open
Data

13
Open Data
Given the changes taking place, there is a huge potential
upside in sharing data even more openly and being able to
interrogate very large population data sets. Indeed, many
now believe that as health care data is a public good, it
should be made publically available.25
Old questions about
who can and cannot access data within a given organization
are now being replaced by questions on how the data and
data sharing can provide best patient benefit.26
A core issue here is to what extent the open data protocols
now being used for improving transport, energy use,
agriculture and nutrition can also be applied to the more
personal arena of healthcare. When health data is openly
available, and the infrastructure and tools exist to take
advantage of it, it becomes a very valuable resource.
Back in 2013 the consulting firm McKinsey estimated that
harnessing open data in healthcare could help generate
$300 to $450 billion per year in value to the U.S. economy. 27
As such organizations like the UK’s NHS are keen to make
it clear that “open data should not be confused with ‘data-
sharing’ and holds limited risks in terms of confidentiality and
patient data so long as appropriate safeguards are put into
place as part of the publication process.”28
In the US, the
Health Data Initiative is eager to make high value health data
more accessible to entrepreneurs, researchers, and policy
makers in the hopes of better health outcomes for all.29
As the volume and complexity of health data grows, it is
increasingly important to every aspect of the biomedical
research enterprise.
Of course, as with any data set, the key is to identify what
is important. The health data of an entire population will
contain a huge amount of noise so choosing the right
information is vital. Those who prioritize best will be able to
unlock significant opportunities and so improve diagnosis.
Compliance and Engagement
Much of what has been written about the advent of the
digital health transformation assumes that patients will
be educated and engaged. While this is the target design
assumption for many of the new platforms, apps and
communities that have been developed, some question
how compliance and engagement can be ensured. If, as
research suggests, most of the lead users of health apps
on smartphones are the ‘worried well’ or educated patients
managing chronic conditions such as diabetes, then what
about the others? Questions are being asked about how to
bring the uneducated and those with little concern for their
own health until it’s too late into the fold. Similarly, while apps
are convenient and easy to use in a relaxed state, how will
patients react when facing acute healthcare challenges?
Where and how best to deliver emotional support to patients
managing their condition alone? Also, how can growing
interest and interaction with commercial apps translate into
data sharing with healthcare organizations?
Questions are being asked about how to
bring the uneducated and those with little
concern for their own health until it’s too
late into the fold.

14
The emerging environment of open protocols, mobile-
enabled services and patient ownership of information
is termed the Internet of Me (IoM), a more person-centric
expression of Internet of Things. IoM is a world where
individuals can still receive services more pertinent to them,
but without giving away data and with less risk of loss of
privacy through data breaches.
For some, the future of data is increasingly focused on how to
best to use the IoM to enable customers to not only access
their data, but also own it and don’t have to give it away and
yet still receive personalized services. Julian Ranger, founder
of the digital librarian start-up, Digi.me, sees that Iceland’s
Living Lab program will be one such large-scale test.30
The
concept is straightforward, calling for data to be opened up
from the four areas of social, banking, telecoms and health
and then to provide everyone in Iceland with an app for
their smartphone or device. The app serves as the pipe that
connects the user with information, in order to receive more
personalized service. Where this trial differs is that individuals
do not have to give way a slice of personal data in exchange
for personalized services offered by an organization. Rather, it
is the user that instigates the deal with third parties of choice
and importantly, third parties do not get access to data
as it remains with the user and app. Third-parties instead
interrogate the data, accessing a richer stream of data from
multiple sources rather than the ‘thin slice’ that they have
grown accustomed to in today’s world and processing itself
takes place in the app on the individual’s device. The end
result is that the user receives a more personalized service,
the user’s information stays in situ and selected third parties
receive much more complete response to queries, allowing
them to respond with a more intelligent, targeted service: a
healthy exchange for all parties.
Many are convinced that patient centricity
will revolutionize health service delivery.
A Way Forward

15
Taking this kind of thinking to the UK health sector, to install
‘the pipe’ users would need to agree to the installation of
an app on their device – one that protects their data. To
create ‘flow’ access to key information from EHR providers
is needed, most probably through GP surgeries. As only
a few EHR providers manage patient records on behalf of
the NHS, only a small number of open, standardized APIs
would be required. This primary data set, coupled to say,
an individual’s additive information from wearables could
provide a fairly clear picture of an individual’s health record.
While important to recall that GPs do not have access to all
of an individual’s healthcare information, it is fair to state that
they have access to much of it. At this stage individuals would
then always have most of their own healthcare data in one
place providing them with a richer picture and enabling them
to authorize its use when needed with healthcare providers.
Of course, more information should be included with time,
but at a basic functional level one app and approximately
four or five APIs is enough to get something the size of a
UK-wide program moving.
Much is to be planned and still more delivered, but it seems
that many are convinced that patient centricity will transform
health service delivery, help manage costs and enable
doctors and nurses to give better care. People will always
be needed to treat people but technology can provide
much wanted support. Kind reassurance and caring human
contact can transform both mental and physical health in
ways which mobile apps, however efficient, can never do.
It’s true, although health in emerging markets would be
most effectively improved by access to clean water, clean
air, more food and better housing, digital solutions have
a clear role to play in managing disease. In the West, as
ageing populations, lifestyle driven conditions and longer life
expectancy press down on the existing system, efficiency
gains from data and technology will also play a key part in
the changes to come.
People will always be needed to treat
people but technology can provide much
wanted support.

17
Refrences
1
http://www.who.int/mediacentre/news/releases/2015/uhc-report/en/
2
http://data.worldbank.org/indicator/SH.XPD.PCAP
3
http://www.health.org.uk/news/health-foundation-responds-government’s-spending-review
4
http://www.futureagenda.org/view/initial_perspective/the-future-of-health
5
http://medcitynews.com/2016/10/topol-patient-data-civil-right/
6
https://www.23andme.com
7
https://www.ft.com/content/1efb95ba-d852-11e6-944b-e7eb37a6aa8e
8
https://www.ft.com/content/1efb95ba-d852-11e6-944b-e7eb37a6aa8e
9
http://healthaffairs.org/blog/2016/09/20/the-culture-of-data-sharing-has-to-change/
10
http://www.healthaffairs.org/healthpolicybriefs/brief.php?brief_id=122
11
12
http://catalyst.nejm.org/opennotes-knowing-change-health-care/
13
http://catalyst.nejm.org/opennotes-knowing-change-health-care/
14
http://www.opennotes.org/who-is-sharing-notes/
15
https://www.brookings.edu/blog/techtank/2016/05/18/health-care-data-as-a-public-utility-how-do-we-get-there/
16
http://www.mckinsey.com/industries/healthcare-systems-and-services/our-insights/healthcares-digital-future
17
https://www.nap.edu/read/12212/chapter/6
18
http://medcitynews.com/2016/10/topol-patient-data-civil-right/
19
http://www.forbes.com/sites/danmunro/2015/12/31/data-breaches-in-healthcare-total-over-112-million-records-in-2015
20
http://www.informationisbeautiful.net/visualizations/worlds-biggest-data-breaches-hacks/
21
http://www.out-law.com/en/articles/2015/july/new-digital-health-laws-passed-by-german-law-makers/
22
https://medium.com/the-internet-of-me/why-cant-marketers-see-the-simple-answer-to-their-data-problems-
ec3c74cb984d#.im8osg1kc
23
https://www.theguardian.com/technology/2016/jul/05/google-deepmind-nhs-machine-learning-blindness
24
https://www.theguardian.com/technology/2014/oct/08/sir-tim-berners-lee-speaks-out-on-data-ownership
25
https://www.brookings.edu/blog/techtank/2016/05/18/health-care-data-as-a-public-utility-how-do-we-get-there/
26
27
http://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/open-data-unlocking-innovation-and
performance-with-liquid-information
28
https://www.england.nhs.uk/ourwork/tsd/data-info/open-data/
29
https://www.healthdata.gov/content/about
30
https://livinglabiceland.com/

Future of Healthcare Provision Jan 2017

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