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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 across 25 countries. Additional online interaction connected 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

the success of the first programme, this time 25 topics were explored in 120 workshops hosted by 50 different organisations across 45 locations. There was also specific focus on the next generation, including collaborating with schools, universities and other educational organisations. Rather than having a single sponsor, this time multiple hosts supported workshops on specific topics either globally or in their regions of interest. We would like to thank all of the 5000 experts around the world who have shared their views and made this project possible.

The results from the both programmes, published both online and in print, have been widely shared and used around by individuals and organisations looking to be more informed. TV programmes, talks, workshops and additional discussions have followed as people have explored the potential implications and opportunities in their sector or market.

The insights in this pdf are published under the Creative Commons Attribution-Non Commercial license

To get in touch with Future Agenda please contact us by email, twitter or post:

info@futureagenda.org@futureagenda84 Brook Street, London W1K 5EH

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ContextMany 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 AccessGlobally 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 CostsLack 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 PatientImplicit 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 effi ciency and enable the much sought-after more eff ective, personalized, healthcare, today several recognize that there are three important more constraints in the mix. These are interoperability, security and privacy. They evidently need to be considered in allfuture thinking.

InteroperabilityAlthough 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 effi cient 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 signifi cant 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 diffi culty 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 fi nancial support for the investment required. At some point the nettle will have to be grasped and signifi cant investments made. Some potentially pivotal changes are already afoot. The Aff ordable 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!

SecurityNot 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 identifi ed the probability of a ‘privacy Chernobyl’ – an event that changes our attitudes to data security - and suggested the most likely target for a signifi cant 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.

PrivacyAs 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 diff erentiating between personal vs. organizational information about any individual is one signifi cant area of debate, but equally so is the nuance of data access vs. data ownership. If the ownership of personal healthcare information can be clarifi ed 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 LandscapeFundamental 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 off ers 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 fi nance 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 artifi cial intelligence company has been granted access to healthcare data of 1.6m patients of three London hospitals. The fi rst 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.

DataOwnership

OpenData

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Open DataGiven 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 EngagementMuch 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.

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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

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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.

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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 http://healthaffairs.org/blog/2016/09/20/the-culture-of-data-sharing-has-to-change/

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 http://healthaffairs.org/blog/2016/09/20/the-culture-of-data-sharing-has-to-change/

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/

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