We are delighted to announce another major Future Agenda project – exploring the potential for more and better patient data to transform healthcare. During the second half of 2017 a series of events are taking place around the world to bring together different views on how evolutions in data creation, availability and sharing are providing greater autonomy, control and access to patient information while simultaneously ensuring safety and security. Following the well-regarded Future Agenda format, these will be discussions between experts in health, data and adjacent areas exploring how the emerging shifts may evolve, play out and with what implications. This is the emerging view of some of the key issues that different organisations believe will have impact how we access, share and make better use of patient data. This is the starting point for a wider global discussion that will highlight the most important shifts taking place, their likely effect and implications – as well as the associated security and safety concerns. Investigating the topic from the perspectives of hospitals, insurance companies, pharmaceuticals, health-care providers, technology firms, advisors, researchers, medical device manufacturers, data managers and regulators, this initiative will not only highlight the global issues but also focus on regional differences and implications. As with other recent Future Agenda projects on the Future of Trade, Cities and Philanthropy, the Future of Patient Data will produce a comprehensive view of what many different organisations and experts around the world see as the likely direction over the next decade. The resulting report will identify the key benefits, enablers and constraints and where are the major areas for further research, innovation and collaboration. For this project we have assembled a superb combination of events with hosts including leading companies, universities and governments. The current schedule of events is: Dubai (27th September) hosted by Herman Miller Johannesburg (10th October) hosted by Discovery Health Oslo (30th October) hosted by Accenture Brussels (9th November) hosted by UCB Sydney (15th November) co-hosted by TAL, Telstra and Pfizer Singapore (13th or 20th November) hosted by Accenture Mumbai (23rd November) co-hosted by Tata Consulting Services Toronto (early December) co-hosted by Cisco and York University San Francisco (early December) host TBC Boston (early December) host TBC London (14th December) hosted by Accenture We are also looking at adding extra events as diaries allow in Copenhagen, Munich, Sao Paulo and Tel-Aviv. As usual, throughout out the project we will share new insights gained from these discussions on Linked-In, SlideShare, Flickr and twitter so that others can comment, add to and challenge the views as they develop. Once the workshops are complete, we will compile a final report similar in format to the recent Future of Cities.

1. The Future of Pa-ent Data
An Emerging View to be Challenged
July 2017
The world’s leading open foresight program

2. Context
This is an ini@al point of view on the topic of pa@ent centric data. It is a
perspec@ve to be shared, challenged, built upon and enhanced via a series
global discussions that are taking place throughout the second half of 2017.

3. Challenging Models
Increased access to personal health data will challenge exis@ng
healthcare models focused on stereotypical condi@ons. In the future
several governments expect personalized diagnosis to be commonplace.

4. Preven-on and Compliance
The @mely delivery of informa@on direct to a pa@ent can have a significant
impact on compliance. Gathering lifestyle data via remote monitoring
technologies and wearables adds preventa@ve ac@on into the treatment.

5. Individualized Medicine
We are going to be leaving popula@on medicine – where one size fits all
– in favour of individualized medicine. Implicit in this is that
the pa@ents will increasingly drive their own care.

6. India Se?ng Global Standards
India is demonstra@ng an innova@ve approach to healthcare challenges and
has proven design solu@ons for low-income popula@ons. These solu@ons will
be applied to higher income economies with even greater efficiency benefits.

7. Gene-c Profiling
Key is the wider use and reduced cost of gene@c profiling. With the growth of
organiza@ons providing hereditary gene@c informa@on commercially, more
people can see future condi@ons early and so take preventa@ve ac@on.

8. Gene Edi-ng
Equipped with greater understanding of the individual’s gene@c disposi@on and
new interven@on technologies, we can proac@vely edit genes and undertake
minimally invasive surgery to reduce the need for major surgery in later years.

9. Ge?ng Closer to the Pa-ent
New digital technologies providing tailored advice mean that healthcare
systems are designed more for the pa@ent’s convenience, at home, and less
around expensive, over-stretched facili@es such as hospitals.

10. AI Driving Accuracy
It will become common for pa@ents to chat with ar@ficial intelligence health
advisers through messaging apps - As more people use these services, the
more data is collected and therefore the more accurate diagnosis can be.

11. mHealth Regula-on
Mobile health is currently a fragmented and nascent market that needs
consolida@on to drive real change. Regula@on will be key, par@cularly as
there is a move beyond wellness towards managing chronic condi@ons.

12. An Informa-on Business
Data and data exchange have emerged as the ‘new currency’ in
health care, and will become a major force in redefining rela@onships,
transforming the industry into an informa@on-driven business.

13. Small Data
We see more focus on improving treatments / outcomes through “small data”
and the collec@on and processing of modest amounts of informa@on from an
individual pa@ent. Data can be shared at minimal risk to pa@ent privacy.

14. Data Gaps
In many instances, health data does not yet follow the pa@ent, crea@ng gaps
in coverage and leading to fragmented, uncoordinated care that diminishes
quality and drives up costs. In the future, these gaps will disappear.

15. Individual Custodians
As more informa@on 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.

16. New Trust Rela-onship
The adop@on of many digital technologies within
integrated health and care systems will require the
development of a new trust rela@onship with the ci@zen.

17. System Change
For many, implemen@ng digital health technologies requires a
whole system change. Such a transforma@on is more difficult
to implement when an established healthcare system is in place.

18. Conserva-ve Regulators
As legislators and funders of healthcare tend to be risk averse, there is a
regulatory desire for certainty with a con@nuous concern about unintended
consequences of change. Regulators may therefore slow adop@on.

19. Resistance from Healthcare Professionals
Change from clinicians and professionals in health oen have the least
appe@te for change – it is oen viewed as a threat to roles and responsibili@es.
Dialogue around new innova@ons is key to overcoming resistance.

20. Crea-ng Pull
One of the most effec@ve leavers to encouraging adop@on of digital will be
the ‘fear of missing out’ on gaining a compe@@ve edge in cost and quality.
Crea@ng pull as well as push will be pivotal for wider pa@ent data sharing.

21. Personal Data Sharing
The sharing of personal health data with pa@ents in established systems
will give them greater control over their own wellness. Pa@ents will
increasingly need to trust in the sharing of their own data with others.

22. Combining Data Sets
Picking the data worth sharing and matching it with the most appropriate
pla`orms around specific issues, condi@ons, demographics or public vs.
private healthcare systems is seen as the most pragma@c approach.

23. Expanding Set of Personal Health Data
Data used to measure pa@ent health / wellness expands beyond clinical indicators to
consider social determinants, pa@ent experience, pa@ent-reported outcomes,
transac@onal data, and real-@me data from connected objects and environments.

24. Predic-ve Analysis
As we move to real-@me synthesis of mul@ple data pla`orms we will gain
improved accuracy and speed. Predic@ve analy@cs and gene@c profiling
together create more connected predic@on and drive hyper-personaliza@on

25. Public Concerns
Public concerns around the unregulated of use of data are growing and,
unless controlled successfully, as apps become more popular, fears around
how personal data are stored used and shared will become more pointed.

26. Proprietary Data
A significant challenge to progress in healthcare resides in the barriers
and restric@ons that derive from the treatment of medical care data
as a proprietary commodity by the organiza@ons involved.

27. Stewards and Security
Despite the increased enthusiasm for pa@ent data and the adop@on of EHR,
insufficient aben@on is being paid to security. With more prominent cyber-
abacks, we will trust our data only to those with the highest levels of security.

28. Reaching the 5%
While many health apps are used by the healthy and the worried well,
reaching the 5% of pa@ents that incur 50% of healthcare costs remains
a major challenge: Comorbidity con@nues to drive the greatest spend.
Diabetes
CVD
Depression
Anxiety

29. A Public Good
Broader use of healthcare data requires not only fostering data system
reliability and interoperability but also addressing individual data ownership
and the extent to which data should cons@tute a public good.

30. Public Benefit vs. Personal Risk
In linking and sharing more data we will increasingly weigh public benefits
against personal risk. The poten@al harm from unauthorised release of
confiden@al data will be a conundrum for many in the healthcare sector.

31. Decentralized Secure Data
We need to decentralize health data because the more it’s amassed,
the more likely it’s going to be hacked. Centralized ownership of
medical records is increasingly seen as a security risk.

32. Global Privacy Standards
Global standards will eventually be created for each country to sign up to
and use as a basis going ahead: However garnering agreement will be
difficult as each region has a different approach to pa@ent data.

33. Informed Consent
Given complex data flows, informed consent is increasingly challenging –
so an alterna@ve is needed: An accountability governance model incorpora@ng
ethics and respec`ul data use is a compelling subs@tute or complement.

34. Data Marketplaces
Data is a currency, it has a value and a price, and so requires a marketplace.
Ecosystems for trading data are emerging and soon both personal and
clinical data will be represented in new healthcare data marketplaces.

35. Linkability of Open Data
No data will be truly anonymous: Current open data prac@ce assumes that
technology will be not be able to relink it to its source. This is not the
case and so, by 2025, we will see different levels of re-iden@fica@on.

36. Personal Data Stores
Pa@ents will not only access their data, but also own it. The adop@on of
personal data stores lead to universally accepted creden@als and share data
with mul@ple partners so that pa@ents can receive personalized services.

37. Digital Skills Gaps
As healthcare becomes more digital, healthcare professionals struggle to keep
up. A skills gap emerges and the adop@on of new approaches is held back.
Re-skilling and up-skilling becomes a priority focus for many systems.

38. A Human Right
Having access to your own health data will be seen as a human right.
More states will grant ci@zens legal ownership of their health informa@on.
We will allow access to our health data, but our data will be ours to control.

39. Data Ownership
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.

40. The Privacy Illusion
There is a rising general belief in the right to data privacy and the right
to data security. Both are illusions: Security is impossible without
increased monitoring - and so true privacy is also impossible.

41. Global vs. Local
Technology is by its very nature global and data does not respect na@onal
boundaries. Na@on states try to set the rules but tensions in global
interoperability drive us to design for global standards, but with localised use.

42. Internet of Me
The combina@on of increasing compu@ng power and digital health leads to the
Internet of Me: Pa@ents get informa@on that is highly customized to who they
are and treatments become more effec@ve through greater personaliza@on.

43. Digital Infrastructure Gap
With many hospitals and prac@@oners working across a mul@tude of IT
pla`orms of very different degrees of sophis@ca@on, the infrastructure gap
between varied facili@es becomes a barrier to roll-out of new technologies.

44. Too Much Informa-on
As more data is available, some seek to restrict the total informa@on being
shared with pa@ents. Fear of data overload exceeding the individuals’ capacity
to see things in perspec@ve leads pla`orms to filter what is shared.

45. Humans in the Network
The next genera@on of implanted devices and addi@onal sensors within the
body increasingly make humans part of the network. Safety concerns around
hacking and privacy issues on tracking challenge some health systems.

46. Diagnosing Anxiety
Facial recogni@on soware has the capacity to iden@fy stress and anxiety
and, alongside other digital diagnos@c tools - such as voice pabern analysis,
will be increasingly used to iden@fy and monitor mental health problems.

47. Healthy Smart Ci-es
The poten@al to integrate personal health data with more ‘Smart City’
sensing technologies, such as air and water pollu@on monitoring, may
help achieve the growing healthier city ambi@ons in some loca@ons.

48. More Specialist Healthcare Professionals
Beber health care results can be generated by more focused study undertaken
in less @me. For instance, surgeons undergo more rapid specialist rather
than broader generalist training - some@mes around a single condi@on.

49. Augmented Reality
The applica@on of both AR and VR technologies to healthcare will
increase effec@veness. For example, 3D visualiza@ons of a pa@ent’s internal
organs within their body allow for detailed examina@on before first incision

50. In-body Sensors
Sensors resident inside the body increasingly enable molecular intelligence.
Biosensors, neural dust, implantable devices and smart drugs all provide a
plethora of new data that together improve detec@on and monitoring.

51. Ulterior Mo-ves
Some organisa@ons use personal pa@ent data to screen customers
and employees: Employers recruit only the healthiest and insurance
companies increasingly refuse cover to those with unacceptable risks.

52. Standardised Measures
The shi from payment for interven@on (e.g. pills) to payment-on-results is
underway. Many want agreed standardiza@on for target outcomes. Funders,
providers, insurers, regulators and data pla`orms all seek common targets.

53. Ques-ons
As we share and build on this view we would like to know what you agree
with, what you don’t, what is missing and, most importantly, what will
be some of the key impacts and implica@ons – both globally and regionally.

54. Future Agenda
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