From Crowdsourcing to BigData - how ePatients, and their machines, are transforming health

From
Crowdsourcing
to BigData.
How ePatients, and their machines,
are evolving Health.

About
the authors
Ferdinando Scala
Leandro Agrò
Ferdinando Scala is an International Digital Strategist at Razorfish Healthware, a Publicis
Healthcare Communications Group (PHCG) company. His main fields of expertise are:
Strategic Consulting, Digital Strategy, Digital Transformation, Digital Engagement, Digital
Metrics Modelling, Collaborative Media, Marketing, Communications & Change Management.
An Alumnus of the prestigious Nunziatella Military School of Naples, Italy, Ferdinando holds
an MSc in Biology (summa cum laude) at University of Naples “Federico II”, and is currently
pursuing a BSc in Communications and Media at University of Salerno.
He started his career as a researcher in the field of satellite- and airborne-based environmental
monitoring, working in collaboration with Consiglio Nazionale delle Ricerche (C.N.R.), Centre
National de la Recherche Scientifique (C.N.R.S.), Deutsches Zentrum für Luft- und Raumfahrt
(D.L.R.) and European Space Agency (E.S.A.). He successively spent 12 years in Big Pharma
companies, holding positions in Sales, Marketing and Commercial Operations at both national
and international levels.
A passionate Wikipedia author (16.000+ contributions), on June 2011 he was shortlisted
for becoming a member of the Board of Trustees of the Wikimedia Foundation (WMF) and
on February 2013 he became a member of the global Elections Board. He was finally the
Candidacy Leader for the City of Naples, Italy, to be the hosting town for Wikimania 2013, the
global conference of Wikimedia Foundation.
Leandro Agrò is the Principal Experience Architect at Razorfish Healthware, a Publicis
Healthcare Communications Group (PHCG) company. His main fields of expertise are:
Service Design, User Experience, Interaction Design and Digital Strategy. As visiting Professor
at Siena University and Producer of Frontiers of Interaction Conference, Leandro has also been
awarded by Venice Biennale of Architecture, ADI Index, TechGarage, New York Times, Wired,
WebAward, and other International Institutions.
Leandro’s education originates from the Italian design culture. He completed a post graduate
degree in Interaction Design at Domus Academy (Milan, Italy), winning the Interaction Design
competition at Apple Computer, Cupertino, CA in 1997. As blogger and writer, Leandro
published more than 300 articles mostly focused on the consequences of technology and
innovation; he contributed to four books has spoken at TEDx, World Usability Day, UXCON,
eTech, World Business Forum and BayCHI (ACM).
In the last 15 years, Leandro designed the first UMTS/3G user interface ever developed; He
contributed to patents in the photo-video field; and designed the first multimodal computer UI
based on eye-gaze (patented) used in the healthcare field.
@fscalapro
@leeander
ferdinando.scala.phi
leeander
Linkedin.com/in/ferdinandoscala
Linkedin.com/in/leeander

Introduction
This whitepaper exposes today’s most relevant patient and healthcare data
trends for the benefit of health marketers, and how they will impact the
healthcare value chain.
Today oceans of data are being produced and collected both by people and
machines, at the same time changing the way we think about healthcare as
a field of study; as a result Patients - actually ePatients - are becoming ever
more informed and independent with their healthcare decisions.
This “perfect storm” in the making, revolving around new paradigms of
“Crowdsourcing” and “Big Data”, will radically change the current healthcare
Industry and reality of marketers. The mode in which drugs and healthcare
delivery are to be presented to healthcare professionals, patients and other
stakeholders is increasingly important in this new data driven paradigm. As a
marketer, are you ready to embrace this change?

4Razorfish | Healthware From Crowdsourcing to BigData June 2013
As the seminal book
Blue Ocean Strategy
by W. Chan Kim and René Mauborgne...
...demonstrated in 2005, real progress for a company does not lie in fighting for space in already crowded markets.
Instead, the creation of new operative space, where to operate alone, otherwise known as “blue oceans”, is the sole
viable option for building a consistent and durable strategic advantage.
While being highly rewarding when a company manages to find them, “blue oceans” are not easy to spot or build.
Basically, building a durable strategic advantage requires one to identify and put in relation concepts and resources
that are apparently unrelated. Normally, companies are not good at spotting new opportunities, since their operational
model is built to robustly guarantee excellence in delivering effectiveness around the available products and
services. The convergence of apparently unrelated concepts is in fact determining a quantum leap in the healthcare
environment, and only the companies that are prepared to ride the wave will succeed in the next years.
In the following paragraphs, we will show you how a monkey, a typewriter, the largest global encyclopaedia, your
smartphone and your health records are all related; and will shape the future of the healthcare industry.

01

KNOWLEDGE IN THE AGE OF INTERNET
Author: Leandro Agrò
Nearly every possible question has
an answer to be found somewhere
on the Net. This is valid if you are
searching for a theory, a point
of view, or relevant data and
information. This statement, as
extreme as it might seem, is true
irrespective to whether you are
looking for the manual for your
washing machine, or want to build a
space rocket – or Satellite - in your
own back yard!
Maybe building a satellite in the
garage is not the most practical
thing to do, but the fact that it is
possible shows that the knowledge
available to everyone on the
Internet even makes an apparently
impossible task, such as space
exploration, available to the masses.
The same depth of information is
not limited to space exploration, but
could empower individuals in their
knowledge of other uncommon
subjects such as Physics. For
example, Prof. Walter Lewin, from
Boston’s MIT Open Courseware,
is one of the best professors of
physics on the planet – and his
knowledge and highly entertaining
lectures are available to everyone for
free on the Net.
In summary, the Net today is the
repository of the best information
ever expressed by humanity in
virtually every area of knowledge
and industry; and this knowledge
is growing in organized hubs. For
example, TED conference (TED.com)
is a major destination of high-level
knowledge available to the public.
Importantly, TED is delivered in a
lecture/audience format accessible
via video. This leading conference
also has a version called TED
MED, specifically focused around
healthcare (http://www.tedmed.
com/videos).
Prestigious universities, conferences
that generate knowledge useful
to the future, new generation
institutions like the Singularity
University (SU), as well as individual
investigators who have an open-
source mind set and raise revenue
by means of crowd funding, all
have one thing in common: they
are collaboratively building and
disseminating their knowledge for
free on the Net. In this respect,
SU is one of the most important
examples of how this can happen.
As an institution whose mission
is “to assemble, educate and
Knowledge
repositories: TED,
amongst others
We can hope that “soon” (in a few decades), we will reach the tipping point
that will allow for accurate automated translations, for now we must make
use of the only intelligence adequate for this task: multilingual human
beings.
Crowdsourcing is becoming the way to handle accurate and contextual
multiple language translation.
Places like TED.com or VIDEUM.com (a video portal dedicated to
healthcare) are leveraging crowdsourcing to -potentially- translate and
“language enable” all content for the benefit of users around the world.
The Language Issue

Traditional knowledge building
models are linked to the linear model
of thought. The organization of
concepts into a coherent significant
unit, like a speech, an article or a
book, always requires the author(s)
to plan in advance a logical structure
composed by “buckets”, like issues
to be addressed or chapters. These
“buckets” had to be organized in
a linear concatenation, so that the
reader could easily follow the train
of thought of the author(s). More
importantly, this kind of process
was considered as the only one to
efficiently deliver coherent results.
Linear knowledge building models
have been put in discussion when
first confronted with the theoretic
possibility to have infinite time
and resources to build a logical
sequence of concepts. A well-
known exemplification of this
theory is the so-called “infinite
monkey theorem”. According to
WHAT IS CROWDSOURCING
inspire a new generation of leaders
who strive to understand and
utilize exponentially advancing
technologies to address humanity’s
grand challenges”, SU uses the
collaborative strength of its students,
some of the most brilliant minds
in the world, to tackle and solve
problems which are out and beyond
their normal field of competence.
The reasons behind the success
of collaborative phenomenon are
complex, and they are eloquently
explained in Dan Pink’s TED lecture:
The puzzle of motivation: (http://
www.ted.com/talks/dan_pink_on_
motivation.html)
In order to understand how the
collaborative building of knowledge
is realized, and what implications
it has for the information diffusion
in general, and for the healthcare
field in particular, we need to
delve deeper in the world of
crowdsourcing and collaborative
communities and projects.
Career analyst Dan Pink examines the puzzle
of motivation, starting with a fact that social
scientists know but most managers don’t:
Traditional rewards aren’t always as effective
as we think
The infinite monkey
theorem
Author: Ferdinando Scala

this theorem, if a monkey (therefore
a being not provided with human
logic or sense of purpose) had a
typewriter and infinite time at its
disposition, it would be able to build
up the complete works of William
Shakespeare by sheer brute force,
by randomly tapping on the keys.
Even if this theorem has some
strong limitations, it is very important
from the conceptual standpoint. It
conveys the idea according to which
even in apparently unfavourable
conditions (non-human being,
random actions, lack of sense of
purpose), by having infinite time and
resources available, any knowledge-
building task is possible.
Things consistently change when
experimental conditions change.
When we have at our disposal
sentient and self-aware human
beings, who perform voluntary
actions, which are driven by a
sense of purpose, the time to build
a knowledge artefact consistently
reduces, in exponential relation
to the number of individuals or
resources available, even in the
absence of a formal scope or
organization.
The conditions mentioned above are
at the base of the crowdsourcing
concept, which first appeared
in 2006 in a seminal article by
Jeff Howe in “Wired” magazine.
Technology
Trigger
Plateau of
Productivity
Slope of Enlightenment
Trough of
Disillusionment
Peak of Inflated
Expectations
EXPECTATIONS
TIME
Automatic Content
3D Scanners
Internet ofThings
Natural Language Q&A
Speech-to-SpeechTranslation
Crowdsourcing
BigData
Gamification
HTML5
Wireless Power
3D Printing
BYOD
Social Analytics
Private Cloud Computing
Application Stores
Augmented Reality
In-Memory DB Management
NFC Payment
Cloud Computing
Mesh Networks
Gesture Control
In-Memory Analytics
Text Analytics
Home Health Monitoring
VirtualWorlds
Mobile OTA Payment
MediaTablets
Consumerization
Speech Recognition
Predictive Analytics
Biometric Authentication Methods
Audio Mining Speech Analysis
AutonomousVehicles
Holographic Display
Recognition
3D Bioprinting
Quantum Computing
Human Augmentation
Adapted from Gartner HypeCycle
Plateau will be reached in: Less than 10 years More than 10 years
CROWDSOURCING HYPE
Positioned in the Gartner Hype Cycle 2012
http://en.wikipedia.org/wiki/Hype_cycle
before the “Peak of Expectations”
Crowdsourcing is still the “new thing”. The
opportunities to leverage this technology and
approach are in front of us, and the knowledge
we have infused in the Net is too much to be
handled.

The author presented for the first
time the possibilities offered by
the unstructured, collaborative
approach for business purposes.
Since then, the meaning expanded
to a significance that here we define
as:
Since this publication, the concept
has exploded in a series of
applications outside the business
world, of which Wikipedia is the
most well-known example.
Wikipedia is probably the best-
known example of crowdsourcing
applied to knowledge building at a
worldwide and cross-cultural level.
Built from the collaborative effort
of anonymous contributors, each
adding up a piece of information,
revising grammar and formatting
pages, Wikipedia is as of now
the most complete repository of
human knowledge. One of the
Top-5 ranked websites in the world,
and consistently in first position in
Google search pages, Wikipedia
contains 23 million articles, has
about 100 000 active contributors
and it is edited in 285 languages.
In 2012, it received 2.7 billion page
views per month from the United
States alone.
Also when examined in terms
of quality of content, Wikipedia
shows good consistency and
credibility, despite it being the
result of unstructured work. In a
renowned 2005 article in Nature,
Jim Giles argued that, for some
scientific areas, individual Wikipedia
articles had the same rate of errors
that a review of the homologous
article on Encyclopaedia Britannica
(EB) could put in evidence. Even
though the article was disputed
by EB, eliciting a successive
rebuttal by Nature, it remains
evident that individuals, simply
driven by their will to contribute,
and working in an unstructured
way, can collaboratively achieve
results which normally implied
the construction of a structured
expert panel, and the investment of
physical and economic resources.
More importantly, it demonstrated
the feasibility of an apparently
daunting scope: gathering all human
knowledge in a single place, in
any possible language, and freely
available to everyone.
While still probably surpassing
The total
encyclopaedia:
Wikipedia
“The use of crowd, without
any formal or hierarchical
coordination structure
among its members, for
performing a certain
scope, in order to pursue
which, an exceptional
amount of resources would
be necessary; where
“exceptional amount
of resources” means a
quantity of time, money,
personnel or skill, and their
combinations, which would
exceed the capabilities of
any formal organization.”

Wikipedia articles in terms of
overall content quality, EB fails in a
fundamental aspect of knowledge
diffusion, i.e. the availability of its
contents in any possible language
worldwide. Furthermore, even if EB
would set itself to this scope, the
amount of personnel, skills, and
monetary resources especially,
would be prohibitive - and would
doom the project to failure.
In summary, from the Wikipedia
vs. EB example, we can derive a
general theorem, which proves
itself as correct when the following
conditions are respected:
We have examined how
crowdsourcing generates huge
quantities of organized data by
means of the non-coordinated effort
of unrelated contributors. Even if
there is no hierarchical relationship
among contributors, the creation
of these huge knowledge buckets
is still strictly related to individual
human skill and willingness.
Once we understand the basic
concepts of crowdsourcing, we are
ready to revert the infinite monkey
theorem, and bring our analysis on
a further level. The next questions to
be considered are:
a. What happens when data
generators are potentially infinite
in terms of the number and
quantity of parameters they take
into account?
b. What completely new
possibilities are available when
data generators are networked
into a system running under a set
of cybernetic rules, which ensure
constancy, reproducibility and
analytical accuracy of measured
phenomena?
The answers to these questions are
found when examining the world of
Big Data, the concept of Quantified
Self and their consequences for the
healthcare domain.
Today: All places that are
mono-cultural or with a single
sender that operates in logical
broadcast, make it increasingly
difficult to gain trust. Also, on the
other hand, it is difficult today
that a “pyramid” not sufficiently
open - as is typical of crowd-
mechanisms - can find the
necessary trust.
Pyramids – as well as YouTube
- were built by many. Stories,
information or generally speaking,
“content” define who we are and
what we are able to do. While the
old giants –like Encyclopaedia
Britannica that are not available
in a print version anymore- are
silently passing in time, all the
new mega-content-structure
emerges on the Web, shaped in
ourselves in near real time.
The Credibility
Issue
“Given a collaborative
knowledge-building task of
any dimension, the quantity
of time and monetary
resources necessary for
completion is inversely
proportional to the number
of contributors and their
individual specific skills
level; while the quality of
final outcome is directly
proportional to this number
and skills set.”

WHAT ARE BIG DATA?
As the renowned physicist Lord
Kelvin (1824 - 1907) proclaimed, “If
you cannot measure it, you cannot
improve it”. This law was designed
by humans to meet the needs of
science, which were becoming
more complex. Over a century later,
we continue to find this complexity
in every moment of our working
lives. Measuring everything has
become a “human centric” issue
– about knowledge and control
in the Internet Age - exactly when
technology was able to fill it. But
more importantly, measurement has
emerged as a social need today
because we are living in real time in
the digital sphere. …and this WAS
just the beginning of an incredible
emergent trend: In the Internet
Age, or better yet, in the upcoming
Internet of Things Age, we do not
have enough humans to take care
of all sensors, devices, satellites,
and –in general- infrastructures that
we create. Measuring everything is
an intrinsic need of the technology
we are leveraging to build our world.
And actually it is also a need of the
world itself, as a planet, to face the
impetuous evolution of the human
footprint. Measuring everything has
already changed other industries –
and healthcare is not immune.
Patients are the biggest community
in healthcare and - today - thanks to
all their portable smart technologies,
they are becoming an active actor
in health, nutrition and wellness
data collection. The diffusion of
these technologies is becoming so
widespread, sensible in terms of
measured parameters, and easy to
carry for people, that it is opening a
brand-new opportunity, called the
Quantified Self (QS) movement.
The QS approach is to incorporate
technology into data acquisition on
most aspects of a person’s daily
life in terms of inputs (e.g. food
consumed, quality of surrounding
air), states (e.g. mood, arousal
and blood oxygen levels), and
performance (mental and physical).
The primary methodology of self-
quantification is data collection,
followed by visualization, cross-
referencing and the discovery of
correlations.
This powerful trend has inspired
numerous hardware devices
(mostly in the wellness area) that
leverage components for cost
reductions in sensor technology,
mobile connectivity, and battery
life, and that have already become
part of the everyday life of millions
of users. This trend resulted in the
appearing and explosive expansion
of products like Withings, Nike+,
fitbit, as well as software apps for
smartphones used to track almost
every aspect of life.
Behind the QS, there is an emerging
desire for an individual to improve
oneself, and a natural human
Measure Everything: If
you cannot measure it,
you cannot improve it
Data sources:
the Quantified Self

Data sources:
crowdsourcing for men
and machines
tendency towards competition within
one’s own microcosm (friends &
followers).
The QS is also related to the
philosophy of interdependence,
donating information about oneself
to be used as a contribution towards
new knowledge about people’s
behaviour and habits as well as the
discovery of new medical cures.
From the Pharma perspective,
QS is creating an emerging and
immediately relevant group of
stakeholders. Right now, most of
the work of data collection and
publication is made manually, while
every day more and more devices
become autonomous.
Using pen and paper, people are
already able to collect and share
tons of useful data. Using shared
tools such as Wikipedia –or any
other collaborative tools on the
Web- people are able to conceive
and evolve spaces of sense and
culture.
Powered by sensors – ever more
present in many devices – and
thanks to cloud computing – a
remote service that collects and
crunches the data – people are
re-writing their own knowledge
and, with it, a perception of today’s
reality.
The Net is both for humans and
machines, and today we should
bear in mind that machines are
more numerous than their human
counterparts. The evolution
of human crowdsourcing and
participation is a mixed human/
machine crowdsourcing and
interaction.
In the field of health, “we can benefit
from the multiple data types coming
on-stream at the same time. These
include electronic medical records,
inexpensive gene sequencing,
personal sensor data, qualitative
contributions by self-tracking, and
more”. (Cit. When Data Disrupts
healthcare http://www.youtube.com/
watch?v=IAt0jw306fk).
We need to talk with people, as well
as integrate in the “discussions” they
have with their machines.
This approach takes us to Big
Data, and unleashes the potential
of analysing information on a
worldwide scale for almost every
possible topic or matter.
The availability of different datasets
presents an opportunity for “High
Tech Companies” because data
scientists and technologists
already have the skills to manage
the data. We have already done
The day in which we will
produce more content in a
single day, than the rest of
human history, is near at
hand.
However, currently the
amount of data produced by
humans is very much less
than the data produced by
machines.

something similar in the financial
field. Today, almost completely
driven by machines based on Big
Data analysis, relevant results can
be found correlating the many
healthcare data sources.
Up to this moment, we established
the basic concepts of crowdsourcing,
Big Data and Quantified Self, and
we could be tempted to consider
them as distinct and far away from
daily reality. Quite the opposite,
these technologies and trends are
already impacting the pharmaceutical
industry. In the following
paragraph, we will understand how
crowdsourcing is impacting R&D.
The traditional model for R&D
development in any company has
always been based on the selection,
hiring, and consolidation of the
best talent, to produce innovation
transfered into sellable products for
the market. This kind of process
has the advantage of ensuring
consistency and continuity of effort
toward a certain objective, which
functions well when the amplitude
of challenges is consistent with the
dimension of the R&D structure.
As a downside, having a
consolidated R&D structure implies:
a) Consistent organizational effort
in order to select, maintain, and
manage the right people in the right
place: with huge expenses in terms
of HR resources;
b) Limited ability and capability
to address prevalent scientific
problems; delimited by the individual
and collective skills of the R&D team
members; and the sheer number of
people, time and resources on hand.
As a consequence, when an R&D
challenge exceeding the talent
pool or organizational resources
capabilities arises, the development
process can come to a halt, with
huge consequences in terms of
overall financial and operational
capability of the company.
Crowdsourcing is a way of expanding
the available pool of talent, and
even gaining insights that would not
have been generated, due to the
structured development processes
inherent to a corporate structure.
Based on this concept, in 1998,
some Eli Lilly executives generated
the idea at the base of InnoCentive,
a crowdsourcing platform whose
initial field of application was
pharmaceutical R&D, but today
extends its business model in other
areas like engineering, computer
science, mathematics, chemistry,
life sciences, physical sciences and
business. The InnoCentive business
model is based on the online sharing
of pharmacological or clinical
development problems, for which
it is unpractical to find a solution
internally, and the call for proposals
to platform members. InnoCentive’s
members have thus the possibility
to contribute to the resolution
of proposed problems, earning
consultancy fees for their contribution
ranging from 500 to 1.000.000 USD.
The model has encountered
considerable success, to the point
that today prominent organizations
InnoCentive: a case
study in crowdsourcing
for pharma

in a wide array of business sectors
like BAE Systems (avionics),
Booz|Allen|Hamilton (consultancy),
The Economist and Nature (editors),
Hershey’s (food), Hewlett-Packard
(computers), Eli Lilly and Roche
(pharmaceuticals), NASA (space
exploration), PepsiCo (beverage)
and Procter&Gamble (Fast Moving
Consumer Goods) are currently
partnering with InnoCentive in
order to solve their problems. The
InnoCentive community includes
about 200.000 individuals from more
than 170 countries. As of now, it has
distributed fees for an overall amount
of 28.000.000 million USD.
All healthcare market players have
one very relevant thing in common:
they produce data. The whole of
healthcare is becoming an industry
based on Big Data.
Could this high-end technology be
an entry barrier in the healthcare
space?
No. Dozens of companies are
already competing in the massive
data collection arena, fighting to
offer qualified – low cost – analytic
tools.
Kaggle – based in California - is
a good example. Financed with
11.000.000 USD, Kaggle launched a
platform for predictive modelling and
analytics competitions. Companies
and researchers post their data, and
statisticians and data miners from all
over the world compete to produce
the best models.
As an example of an advanced
healthcare company, Boehringer
Ingelheim (BI) is actively engaged in
this platform to further its business.
Predictive “in silico” modeling of
biological endpoints is an important
and useful component of the drug
discovery process. To investigate
potential genotoxicity liabilities
in small molecule candidates,
the BI research team launched
a competition using Kaggle. The
BI team expected to realize the
following benefits:
• Competitive advantage in time
and cost efficiency
• Engagement with an external
community of data scientists
to create an awareness around
BI as a cutting edge, innovative
organization
• Reactivity: to almost immediately
deploy the winning model(s)
internally for use by medicinal
chemists through Bipredict, or
other local distribution platforms
The competition was launched
on 16 March 2012. As early as
22 March there were 74 teams
(comprised of 90 players) who had
submitted 277 entries. 24 of these
entries represented models that
were ‘better’ (i.e. more predictive)
than the best initial benchmark.
The success of this project has
been covered in a BI press release,
and received subsequent coverage
in several blogs. Moreover, tweets
from both @boehringer and
@boehringerUS have garnered
>200K impressions to date.
Kaggle Data Science
Competition: a BI case
study in crowdsourcing

02
“
”
Crowdsourcing, Big Data, and Quantified Self are important trends
revolutionizing the development of new drugs and connecting inherently
limited frameworks, like clinical studies.
The impact of these trends, however, is not limited solely to the domain of
clinical research; they are also readjusting the way corporations communicate
to their external audiences.
In the following section, it will become apparent how traditional, linear
communication models are being substituted by completely new ones. The
result of this process is a brand-new marketing and sales paradigm, which
requires pharma executives to readjust their cultural and operational models.

COMMUNICATION MODELS
The communication process is
traditionally defined as the passage
of informational units (content),
coded into some sensorial artefact
(language) from an entity which
produces them (emitter) to another
entity with receives them (receiver).
Context and channel employed in
passing the informational units from
one entity or the other are pivotal in
determining the quantity of delivered
information and its interpretation.
When described as such, it is
evident that communication
has historically been interpreted
as a linear process, in which
informational flow travels in one
direction, and no feedback is
considered. This philosophical
attitude was the cultural substrate
to the construction of the mass
communication system, whose
media (newspapers, radio and
television) acted as unidirectional
channels for message delivery from
emitters to target users. The result
of this model was that the owner(s)
of media channels were also the
owners of information. Media
owners were indeed in a position
to determine the agenda, i.e. the
type, combination and frequency of
information which, when delivered
from emitters to receivers, massively
contributed to build the audience’s
knowledge, attitude and opinions
about whatever issue the agenda
setters felt functional to their own
needs. In addition, agenda setters
also had the possibility to determine
not only which information had to
flow from emitters to receivers, but
also which information should not be
delivered.
Traditional advertising models also
conformed to this hierarchical logic,
in which there is a linear and non-
equal relationship between the
emitter and the receiver, where the
latter is passive in terms of acquiring
information. Traditional advertising
is based mainly on the attraction
of target users in predetermined
channels; the offering of valuable
content to them; and the application
of the so-called contextual (printed
paper) or interruption marketing
(radio and television). In this
respect, the main strategy used by
advertisers to ensure their content
was received was the saturation of
physical (tabular advertising) and/
or media (press/radio/television)
space. This is so the end user had
a higher possibility of encountering
the message throughout the day.
In parallel, within a specific medium
(like television), the most successful
brands were the ones having the
possibility to win the competition
for the most fruitful time slots (prime
time), i.e. the moment of the day when
most users were connected to that
medium/channel. Finally, persistence
of the message, and therefore the
realization of sales, depended on the
single campaign extended over time,
and frequency of message repetition
Hierarchical models
and broadcasting

within a single day.
While functioning well for many
decades, and allowing the surge
and fortune of a whole industry
based on traditional media, this
mechanism has proved to be
progressively less efficient over
the last few years. In particular,
television has suffered an extensive
loss of efficacy in terms of public
adherence, principally owing to
an increase in the frequency of
interruption marketing practices.
The introduction of technologies like
remote control and TIVO strongly
empowered users against the
mounting wave of advertising slots,
and their excessive frequency in the
body of programs. Furthermore,
while remaining of interest to the
generations who were involved in
this system of content broadcasting,
television has progressively lost
its power as a medium, especially
for the younger generations, those
who first embraced the digital
media revolution and its mobile
development.
This resulted in the declining
efficacy of television as a means of
sales generation for Fast Moving
Consumer Goods (FMCG), and in
the pharmaceutical field for Over
The Counter (OTC) drugs. While
commercial and pharmaceutical
industries began to realize this fact,
an increasing amount of investment
was progressively diverted from
traditional media to the new digital
channels.
The traditional sales force could
be seen as the prescription drug
equivalent of broadcast media; with
a large number of representatives
using the same materials and
delivering the same message to
their customers. Pharmaceutical
companies have already been
steadily moving from this traditional
model by using customer profiling
to tailor messages and interactions.
This is becoming ever easier
to manage given the variety of
digital channels now available to
physicians.
These past few years have been
a testimony to the strength of
the digital revolution, with the
progressive introduction of
technological assets and tools
having fundamentally changed the
communication panorama. The
building of the World Wide Web and
its mobile development generated a
completely new system of relations
and communicational fluxes,
identified as a “network model”
The network model disrupts the
traditional, hierarchical models, by
breaking the linear and non-equal
relationships between emitter and
receiver. The receiver becomes
an information selector and an
emitter, whose influence and impact
depend on the extent and depth
of their social network. The rate
of disruption is so deep that the
lexicon has changed, generating
the neologism “prosumer”, to
define a new type of actor. The
term “prosumer” results from the
merging of the words “producer”
and “consumer”. In the specific
informational domain, it has the
significance of a “person who is
The network model
and P2P

simultaneously a producer and a
consumer of information”. People
previously known as “target” or
“audience” have been enabled
through the construction of
networking infrastructures and tools
(social networks like Facebook or
LinkedIn; collaborative media like
Wikipedia) to exit the traditional
paradigm. Where they were
formerly absorbing information
from hierarchical, unidirectional
media, they are now information
emitters with their closely related
peers. It should be recognized
that information exchange among
peers existed prior to the creation
of social networks. Indeed, a large
part of the traditional advertising
model was primarly based on
influencing the so-called “opinion
leaders”, i.e., individuals who had,
because of their standing and
measure of influence, the capability
to spread, by affixing in the minds
of others, messages coming
from the interested emitters. The
pharmaceutical world has always
relied on this paradigm, e.g. passing
information about new drugs,
new indications and new clinical
studies, to prominent physicians
(Key Opinion Leaders - KOLs).
These KOLs assumed the role of
interpreters of the pharmaceutical
industry’s data and messaging
towards the medical community.
What has changed forever with
this advent of Internet and social
networks is the sheer number of
people simultaneously reached by
a discussion about a topic, has
changed from a few (let’s say the
direct colleagues of a GP or the
peer Specialists in a Hospital, and
generally limited to the immediate
geographical surrounding); to many
hundreds (in relation to the extent
of the virtual network a single
individual has, and irrespective of
the geographical dimension).
In this context, while still maintaining
a strong measure of influence, the
opinion of Key Opinion Leaders is
somewhat blunted and diluted by
the possibility that other subjects
(prosumers) actively select and
spread information, according to
their own rules and beliefs. Under
these circumstances, the personal
relationships among peers (where
“personal” does not necessarily
imply a direct connection in the
physical world; and is measured
on the frequency and quality of
interactions) are based on trust and
credibility.
It is therefore important to
understand the new rules which
apply to the new channels, which
are much more volatile and
immaterial than before.
We shouldn’t consider this evolved
marketing scenario -where peers
need to be frequently reached
with coherent messages- just as a
fragmented target to address with
a common message. Empowered
HCP and Patients are walking away
from any kind of broadcast. Today
the most efficient way to reach them
is joining (or leading) the so-called
“Conversation”.
As a quick background about the
Real time is for
marketing (the
Cluetrain manifesto)

idea of “conversation”, we should
start from the seminal book “The
Clue Train Manifesto” (also known as
CTM, 1999).
The Clue Train Manifesto contains
95 theses that re-defined Online
Markets and re-shaped marketers
culture.
During these years, powered by
the digital change, networked
markets self-organize faster than the
companies that have traditionally
served them. Thanks to the Web,
markets become better informed,
smarter, and more demanding of
qualities. In this new scenario –as
declared by the first thesis of the
Clue Train Manifesto: markets are
conversations.
What does it mean when one says,
“markets are conversations”?
Authors assert that people
leverage the “human-to-human”
conversations with companies,
which potentially transform
traditional business practices
radically in today’s reality.
Conversation is the CTM key
concept: According to the second
and third thesis reported in the
book, “Markets consist of human
beings, not demographic sectors”
and “Conversations among human
beings sound human. They are
conducted in a human voice”.
These few theses are enough to
radically shift what most companies
are doing in their communication
plane, both in the physical and
digital spheres. The consequence is
the communication of a totally new
value chain, because “Hyperlinks
subvert hierarchy” and people –
through the Internet - no longer
depend on traditional knowledge
and information sources.

INTRODUCING THE ePATIENT
In a world where a global conversation
is evolving the whole healthcare
market, people use the Internet to find
tons of information about any disease,
and to potentially contact anyone to
collect different opinions.
The power of information-access
in the hands of any single person
today, is bigger than the one
available to US President 20 years
diseases to which we are vulnerable.
In just two hundred years we have
gone from a society suspicious of
science, to one centred around
science.
Today we live in a world where
private companies such as SPACEX
launch into the orbit rockets and
satellites and where ten percent
of the gross domestic product of
the world’s major economies is
spent on health. In the world of
pharmaceutical companies, we
find examples such as Johnson
& Johnson (the largest of all Big
Pharma), which is at 40th position
of the Fortune 500 ranking. The
size of this company is based on its
120.000 direct employees and over
$60 billion in sales. In comparison,
Apple, with its $65 billion and half of
the employees of J&J, is just above
at 35th position of Fortune 500
(2012 pre-iPhone5 rankings).
ago. Today we have the “big picture”
of healthcare at our fingertips. For
example, today we know that there
has never been a time in the past
when humanity was better off in
terms of wealth and health than
it is today. The video “The Joy of
Stats: 200 Countries, 200 Years,
4 Minutes” by Hans Rosling (BBC
Four) could suffice to inspire this
systemic optimism.
This depends on many factors,
including what we know today about
our health and how to treat
“The Joy of Stats”
This video illustrates how over the past two
centuries, life expectancy and per capita wealth,
have vastly improved for many nations. Of course
the current state of health does not mean that
there are no other potential alarms for the planet,
BUT if you look at our health, we cannot miss the
underlying declaration of this video that WE ARE
GOOD and have NEVER BEEN BETTER.
http://www.youtube.com/watch?v=jbkSRLYSojo

The comparison - even that of
wealth – between the consumer-
oriented Apple, and J&J or any other
pharmaceutical company, might
seem completely out of place, and
actually, for a long time, it was.
In recent years, however, the
mutation of both economic and
cultural dynamics has made
comparisons of companies like
these more justified. The need to
be more efficient and closer to
the end customer, even in health
organizations, is changing from
within.
The digital culture that permeates
society has changed the needs
and expectations of customers,
forcing entire industries to convert
mentalities, or come to terms with
the traumatic entry of outsiders, who
have already done so. Regardless of
your opinion of the Mayan prophesy
announcing the end of the World
by 21 December 2012, that was the
year in which some major players in
the healthcare world went through
their “perfect storm.”
2012 has indeed been labelled
‘annus horribilis’ due to the number
of healthcare patents that are
approaching expiry. By 2015,
following the expiry of very relevant
patents, the ranking of the 50 largest
pharmaceuticals may undergo
drastic changes or even some
surprising extinctions. This crisis has
forced many companies to return to
heavy investment in R&D. By nature,
this contemporary approach often
translates into research in the field
of biotech. As a result, the culture of
many companies is moving from a
“cure-all drug” to a “drug tailor-made
for you.”
A key point of this cultural shift is the
change in the almost total access to
the medical information base. At the
same instant in which a disease -
especially if not particularly severe -
affects us, we become transformed
not into “sick people” but into
ePatients: people who are able,
through the distributed knowledge in
the Internet network, to learn about
their conditions as well as treatment
options, comparing the different
therapeutic approaches and results.
However, one needs to be careful
and not consider the ePatient as a
consequence of technology or an
outcome of the Facebook era.
Dave deBronkart coined the
definition of ePatient, made
famous with his speech at the TED
Conference, when he narrated this
episode:
“That Fall of 1969, the Whole Earth
Catalog came out. [...] We think of
hippies of being just hedonists, but
there’s a very strong component
-- I was in that movement -- a
very strong component of being
responsible for yourself. This book’s
(the Whole Earth Catalog) subtitle
Healthcare is moving out
of its “Ford” era just as the
culture of the Internet is
growing evermore rampant,
and this mix is potentially
disruptive.

is: “Access to Tools.”[...] Tom
Ferguson was the medical editor of
the Whole Earth Catalog. And he
saw that the great majority of what
we do in medicine and healthcare
is taking care of ourselves. In fact,
he said it was 70-80% of how we
actually take care of our bodies. Well
he also saw that when healthcare
turns to medical care because of
a more serious disease, the key
thing that holds us back is access
to information. And when the
Web came along, that changed
everything, because not only could
we find information, we could find
other people like ourselves who
could gather, who could bring us
information. He coined this term
e-Patients - equipped, engaged,
empowered, enabled.”
This hippie counterculture note
helps emphasize how seeing the
ePatient as an insignificant role
would be a double faux pas. Firstly,
since it is an ingrained, long-
established phenomenon. And
secondly because phenomena that
benefit from digital advancement
are rapidly approaching their tipping
point: http://en.wikipedia.org/wiki/
The_Tipping_Point.
ePatients are motivated and
prepared to do everything it takes
to help save their own lives, and
looking at the opportunities that
this change has created, you
could say this democratization and
consumerisation of healthcare is not
necessarily a bad thing.
ePatients are not the only forces
that are influencing the world of
healthcare. The entire industry is
affected by new situations. Recently,
in The NewYorker, an article was
published with this provocative title:
“Restaurant chains have managed to
combine quality control, cost control,
and innovation. Can healthcare?”
The thesis of this article is
summarized as follows: The
Cheesecake Factory, used as an
example, is part of the casual dining
industry and, present everywhere in
the United States, can serve fresh
food, cooked on the spot, with a
growing price/quality ratio to eight
million people each year. In attaining
this result, they have democratized
access to certain foods for lower
income groups, and at the same
time, they had to influence the
processes of supply logistics and
their suppliers, optimizing logistics
and processes both internal and
external.
This action, which affects the source,
is of course only possible when you
reach a certain critical mass. The
process of improving the quality/cost
ratio of the entire sector of casual
dining, started when the chains
became protagonists. Now, this
very same change is happening in
healthcare.
“Medicine, though, had held out
against the trend. Physicians were
always predominantly self-employed,
working alone or in small private-
practice groups. American hospitals
tended to be community-based.
But that’s changing. Hospitals and
clinics have been forming into large
conglomerates.
According to the Bureau of Labor

Statistics, only a quarter of doctors
are self-employed—an extraordinary
turnabout from a decade ago,
when a majority were independent.
They’ve decided to become
employees, and health systems
have become chains. In medicine,
we are trying to deliver a range
of services to millions of people
at a reasonable cost and with a
consistent level of quality. Unlike the
Cheesecake Factory, we haven’t
(yet) figured out how.”
Similar examples can be drawn in
many areas across the world of
healthcare. Even the area of medical
devices is not without drastic
changes. Just going to the Apple
Store, one can find many medical
devices that cost less than a
hundred dollars. Just five years ago,
we could only find these devices in
a pharmacy and we would only have
purchased them on medical advice.
One example? Withings Blood
Pressure Monitor, for an easy and
accurate self-measurement of your
blood pressure directly on your
iPhone. http://www.withings.com/
en/bloodpressuremonitor.
From ePatients to the influences of
changing forces across the value
chain, the world of healthcare is
rapidly changing. A key player in
this change is that of technological
acceleration. When digitalization
affects one industry, it does not
leave it immune to its actors, or
better yet, pulverized and in many
ways expands the supply chain,
requiring all existing actors to
deal with change and possibly
predisposes it to new opportunities.
Healthcare is not free from this
explosive effect of digital and
ePatients represent the most visible
part of this rapid change.
ePatients are not special people. We
are ePatients when we:
• Seek information on the Internet
about symptoms or diseases
• Seek practical advice via social
networks and share experiences
related to health
• Use self-tracking or wellness
devices because we aspire to
feel better
• Think of a hospital as a service
company
• Look at the tools that doctors
use and compare them with
the technologies that we have
in-house
• Look at drugs no longer as
closed boxes accessible only
by doctors, but as products we
use and to which we subject to
careful scrutiny before purchase
• We influence those around us
by sharing our experiences on
health
An article published on January
16, 2012 by TechCrunch “PEW
Research was reporting that 17
percent of mobile phone users
were using their devices to look up
health and medical information, and
Juniper recently estimated 44 million
health apps were downloaded in
2011.”
In 2011, in terms of earnings, the
area of mobile health applications
reached $ 718 MM. The main
reason for the significant growth is
an increase of smartphone users on
the demand side, and the increase

of mobile health applications on the
supply side that has doubled since
2010.
Many major healthcare companies
have found mobile health
applications as being an effective
medium to promote and deliver
healthcare products and services.
More information on the mobile
health application market can be
found in the detailed report by
research2guidance entitled, “The
Mobile Health Market Report 2011-
2016”, which describes the impact
of smartphone applications on the
health industry.
As easily understandable, the
above mentioned trends are not
restricted to pioneer attempt toward
a new level for patients to acquire
and share medical information. On
the contrary, it already generated
PatientsLikeMe, a very notable
example about how collaborative
attitude can incredibly improve the
levels of treatment and quality of life
of patients.
We, in Pharma, can’t drive,
over-influence or hide
the global conversation
ePatients started about
healthcare. We should be
part, and culturally lead it.
A bright mind, an anthropologist, a TED fellow, recently discovered that he
has brain cancer.
As an artist and freethinker, he decided to publish on the Net all data
regarding his disease. Unfortunately most of the data were recorded in
private data format, hence were not visible and sharable over the Net.
What did he do?
He hacked the data, and published everything on a website. Thousands
of people read the data, hundreds of physicians participated by providing
alternative information and data to him and to the medical staff.
This Italian ePatient’s story was so largely followed by the media, that the
Ministry of health declared their willingness to pass a law engaging medical
institutions to provide health exams in an open format.
This is not the end to this story as this thinker – working closely with the
authors of this whitepaper – declared:
“the ‘e’ before the word ‘patient’ is not there to testify technology. This ‘e’
is there to destroy the word “patient”, usually considered as a subset of
people with inferior autonomy, power and will (as is often the case when
someone enters in a hospital).”
The Internet is a disruptive ingredient and ePatients will leverage this
superpower to stay in the same category as the other humans. The next
word will be just “persona”.
The World After the ePatients

PatientsLikeMe is a collaborative
platform where patients and
caregivers have the possibility to
share their own experiences and
problems, in order to gather help
from people in the same condition.
The platform was born in 2004 as
a specialized sharing environment
for patients affected by Amyotrophic
Lateral Sclerosis (ALS, or Lou
Gehrig’s disease), a chronic and
disabling neurologic illness, which
has an average fatality rate of
39 months from early onset. A
very famous ALS sufferer is the
prominent physicist Stephen
Hawking; also a most unusual one,
having survived the illness for more
than fifty years.
The PatientsLikeMe (PLM) virtual
environment was ideated by the
families of ALS patients, who were
searching for advice and support
about how to better cope with the
progressive decline of their loved
one capabilities, while also ensuring
the best possible treatment and
support strategies. What started
as a simple method for gaining
support in response to a need, soon
transformed into a powerful tool for
patients, caregivers, and, ultimately,
doctors.
Despite the fact that the person for
which PLM had been conceived
did not survive the disease and
passed on shortly after, his
parents managed to gather ideas,
information and even economic
support by simply relying on
the power of crowdsourcing.
The platform was built so that
members can share with their peers
synchronic and diachronic data
about their illness and treatment
history, and also more qualitative
data regarding their personal state,
like the insurgence of depression
or mood during recovering, the
quality of life associated with both
conditions and treatments, and so
on.
As a consequence to the approach
taken, founders were able to gather
funds worth about 50 million USD
in support of the ALS Therapy
Development Institute, a non-profit
biotechnology company whose
mission is developing treatments
for ALS. Furthermore, when the
platform was opened to other
illnesses, there was a surge in
membership, which in a short
time attained more than 100,000,
distributed over about 1,200
different diseases.
When it moved outside the ALS
domain and differentiated its data
gathering to include other diseases,
PLM opened itself to become one
of the most prominent Web-based
clinical data sources in the world.
This allowed it to include services
like those bringing awareness
to Clinical Trials awareness and
scientific work. Opposite to the
traditional model for patient
enrolment into clinical studies, which
is based on the referral of patients
to researchers by traditional referral
systems like hospitals and GPs;
PLM was in the position to make
its members aware of ongoing
clinical trials all over the United
States, segmented by condition
and demographics, thanks to a
PatientsLikeMe: a case
study on the power of
ePatients

partnership with ClinicalTria.gov.
This allowed patients to have a
direct source of information about
which studies of interest were
on-going, and taking steps for
participating in them. This led to a
greater speed in terms of enrolment
rate (which is always one of the most
difficult and frustrating tasks for
researchers) and greatly improved
the overall statistical significance
of the gained data, due to the
larger dimension of statistic sample
available.
PatientsLikeMe is therefore a
significant hot spot of the new
operational landscape, occupied
by both physicians and pharma
industry. On the other side,
patients empowerment is not to
be treated as a menace by the
above mentioned stakeholders.
Alternatively, the very same
revolution which is empowering the
patients, is empowering pharma
marketers with new powerful, highly
measurable, and flexible tools for the
diffusion of their messages.

Over the last five years, pharma
companies have all been moving
toward the integration of digital
strategy into their marketing mix; not
longer a “nice to have” addendum,
but as an important pillar of overall
brand strategy. The rate and extent
of this integration is such that in
some cases and markets digital is
becoming immaterial, i.e. it is not
anymore a part of the whole, but
permeates all the communication
activities.
The acceleration toward the creation
of an integrated digital approach
produced a surge in the number
of digital assets available online,
typically dedicated to brand or
therapeutic area communications.
As a consequence, companies now
face a fundamental rule of digital
communications: rapid content
obsolescence. Differently from
previous operational models, whose
rhythm of content production and
diffusion was following a time scale
of approximately three months,
digital communications erase the
communicating power of content
much faster. Quite typically, content
is now considered obsolete in a time
span that ranges from thirty and forty
days maximum.
These new conditions generated a
paradox, under which companies
are forced to have a constant flow of
content in order to fuel their online
assets (if they don’t do so, assets die
quite rapidly due to loss of interest);
while not having the economic and
organizational power to generate
enough content to fill the gap.
Again, acknowledging that ePatients
(as well as eDoctors) are generating
and spreading content, and
leveraging this phenomenon, can
be the answer to an apparently
insoluble dilemma. Therefore,
content sources like collaborative
media are pivotal in allowing a digital
asset to be constantly fresh and
updated. On the other side, there
is the problem of differentiating and
selecting interesting content from the
qualitatively unsuitable. This can be
attained by individualizing the users
who produce content of sufficient
quality in collaborative communities;
and providing them with privileged
information in order to make their
content production faster and of
better quality. This way, it is possible
to build a wide panel of affectionate
users, which entertain a strong
relationship with the company, and
develop a mutually advantageous
dynamic. By accessing privileged
materials and tools, to produce better
content they will have the possibility to
shine in front of their social network;
while delivering messages from the
company with maximized quality
and credibility. And so, these content
providers become the “KOLs” of the
digital communication era.
ActiveMint is an interesting example
which uses crowdsourcing in order to
monitor and reward healthy behavior.
CROWDSOURCING AND ePATIENTS
FOR MARKETING

This Web-based platform gathers
data from ePatients (defined not
necessarily patients, but as healthy
people) about their daily behavior. In
particular, enrolled users continously
post healthy behaviors on their profile.
These posts range from behaviors
like taking a walk, checking in at a
gym, eating a type of food, drinking
a certain quantity of water. This
virtuous behavior is rewarded by
earning points on the platform, which
can be redeemed under the form
of gift cards and other real world
rewards. The platform generated the
interest of a number of insurance
companies, which finance the
rewards in exchange for advertising
opportunities on the platform.
What is interesting and actionable
about this example is the possibility
of using the very same approach for
patient adherence initiatives. There
is a possibility here to get patients
to adhere to a treatment schedule,
by rewarding not only the timely
dosing of their prescribed treatment,
but also providing support for
patients maintaining a more complex
therapeutic regime, such as following
a diet, practicing certain exercises,
etc. From a marketing standpoint,
this approach could be valuable to
gather reliable data about the rate of
therapy adherence, and also spotting
collective behavior which could
determinate adherence or
non-adherence, not normally
evidenced by means of customary
market analysis techniques.

Conclusions
The Internet Age has brought with it an almost infinite amount of information,
allowing anyone and everyone the resources to build their knowledge –
to build anything in fact! Crowdsourcing is an innovative way of working
together to pool and analyse more data than we could ever achieve alone.
How can you use this vast resource in your day-to-day life as a marketer?
Just spending 10-15 minutes of your searching outside of our comfort zone
of FirstWord newsletters, PM Live, MM&M, etc could open up a new world
of resources to mine for insights into the disease areas in which we work. It
could give us the opportunity to become exposed to the thoughts, feelings
and motivations of people living their lives with these diseases; sharing the
thoughts, their data and shaping their own futures.
Have you considered ePatients as a stakeholder in your
marketing plan?
Whilst we cannot drive, over-influence or hide the opinions and broadcasts
of ePatients we might consider how to engage with them, or simply use their
knowledge and resources to better understand the needs and behaviours of
your most-empowered end customers.
With these new paradigms of Crowdsourcing and Big Data, the ePatient is
a force to be reckoned with, the perfect storm that will sweep through and
radically change the future of the healthcare industry.
Are you as a marketer ready to embrace this change?
Want more?
Follow us on our social media stream, or directly reach out to the authors for
learning how to align your brand / franchise / organization to the mounting
wave of digitally-enabled healthcare.

Razorfish Healthware is a global leader in digital and healthcare
communications, leveraging a unique mix of insight, technology, creativity
and industry savvy to deliver digital innovations, solutions and tools that drive
improved health outcomes.
Our deep understanding of the innovation process, human-technology
interactions, and the healthcare ecosystem enables us to generate
transformational experiences that empower people’s health and wellness
decisions.
Razorfish Healthware is a single organization able to deploy our full
suite of services in support of any market with more than 300 dedicated
professionals based in 9 countries around the world: US, France, Germany,
Italy, Spain, UK, Australia, China, India.
Razorfish Healthware is part of Publicis Healthcare Communications Group
(PHCG) , the largest and most innovative health oriented communication
group.
Razorfish Healthware’s service offering is made up of three specialized
business units, an Advisory practice offering technology strategy and
enterprise consulting; a digital communications and marketing practice and
a solutions and technology practice offering a range of enterprise business
tools and related services.
For more information please visit
razorfishhealthware.com
info@razorfishhealthware.com.
EU | t +39 089.3061.411 | f +39 089.3061.415
US | t +1 888.463.3793 | f +1 646.935.4791
About
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@RazorfishHW
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