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From
Crowdsourcingto BigData.How ePatients, and their machines,
are evolving Health.
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Aboutthe authors
Ferdinando Scala
Leandro Agr
Ferdinando Scala is an International Digital Strategist at Razorsh Healthware, a Publicis
Healthcare Communications Group (PHCG) company. His main elds o expertise are:
Strategic Consulting, Digital Strategy, Digital Transormation, Digital Engagement, Digital
Metrics Modelling, Collaborative Media, Marketing, Communications & Change Management.
An Alumnus o the prestigious Nunziatella Mi litary School o Naples, Italy, Ferdinando holds
an MSc in Biology (summa cum laude) at University o Naples Federico II, and is currently
pursuing a BSc in Communications and Media at University o Salerno.
He started his career as a researcher in the eld o satellite- and airborne-based environmental
monitoring, working in collaboration with Consiglio Nazionale delle Ricerche (C.N.R.), Centre
National de la Recherche Scientique (C.N.R.S.), Deutsches Zentrum r Lut- und Raumahrt
(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 shortl isted
or becoming a member o the Board o Trustees o the Wikimedia Foundation (WMF) andon February 2013 he became a member o the global Elections Board. He was nally the
Candidacy Leader or the City o Naples, Italy, to be the hosting town or Wikimania 2013, the
global conerence o Wikimedia Foundation.
Leandro Agr is the Principal Experience Architect at Razorsh Healthware, a Publicis
Healthcare Communications Group (PHCG) company. His main elds o expertise are:
Service Design, User Experience, Interaction Design and Digital Strategy. As visiting Proessor
at Siena University and Producer o Frontiers o Interaction Conerence, Leandro has also been
awarded by Venice Biennale o Architecture, ADI Index, TechGarage, New York Times, Wired,
WebAward, and other International Institutions.
Leandros education originates rom 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 ocused on the consequences o technology and
innovation; he contributed to our books has spoken at TEDx, World Usability Day, UXCON,
eTech, World Business Forum and BayCHI (ACM).
In the last 15 years, Leandro designed the rst UMTS/3G user interace ever developed; He
contributed to patents in the photo-video eld; and designed the rst multimodal computer UI
based on eye-gaze (patented) used in the healthcare eld.
@fscalapro
@leeander
ferdinando.scala.phi
leeander
Linkedin.com/in/ferdinandoscala
Linkedin.com/in/leeander
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Introduction
This whitepaper exposes todays most relevant patient and healthcare data
trends or the benet o health marketers, and how they will impact thehealthcare value chain.
Today oceans o data are being produced and collected both by people and
machines, at the same time changing the way we think about healthcare as
a eld o study; as a result Patients - actually ePatients - are becoming ever
more inormed and independent with their healthcare decisions.
This perect storm in the making, revolving around new paradigms o
Crowdsourcing and Big Data, will radically change the current healthcare
Industry and reality o marketers. The mode in which drugs and healthcare
delivery are to be presented to healthcare proessionals, patients and other
stakeholders is increasingly important in this new data driven paradigm. As a
marketer, are you ready to embrace this change?
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As the seminal book
Blue Ocean Strategyby W. Chan Kim and Ren Mauborgne...
...demonstrated in 2005, real progress or a company does not lie in ghting or space in already crowded markets.
Instead, the creation o new operative space, where to operate alone, otherwise known as blue oceans, is the sole
viable option or building a consistent and durable strategic advantage.
While being highly rewarding when a company manages to nd them, blue oceans are not easy to spot or build.
Basically, building a durable strategic advantage requires one to identiy 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 eectiveness around the available products and
services. The convergence o apparently unrelated concepts is in act 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 ollowing 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 uture o the healthcare industry.
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KNOWLEDGE IN THE AGE OF INTERNET
Author: Leandro Agr
Nearly every possible question has
an answer to be ound somewhere
on the Net. This is valid i you are
searching or a theory, a point
o view, or relevant data and
inormation. This statement, as
extreme as it might seem, is true
irrespective to whether you are
looking or the manual or yourwashing 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 act that it is
possible shows that the knowledge
available to everyone on the
Internet even makes an apparentlyimpossible task, such as space
exploration, available to the masses.
The same depth o inormation is
not limited to space exploration, but
could empower individuals in their
knowledge o other uncommon
subjects such as Physics. For
example, Pro. Walter Lewin, rom
Bostons MIT Open Courseware,
is one o the best proessors o
physics on the planet and his
knowledge and highly entertaining
lectures are available to everyone or
ree on the Net.
In summary, the Net today is the
repository o the best inormation
ever expressed by humanity in
virtually every area o knowledge
and industry; and this knowledge
is growing in organized hubs. For
example, TED conerence (TED.com)
is a major destination o high-level
knowledge available to the public.
Importantly, TED is delivered in a
lecture/audience ormat accessiblevia video. This leading conerence
also has a version called TED
MED, specically ocused around
healthcare (http://www.tedmed.
com/videos).
Prestigious universities, conerences
that generate knowledge useul
to the uture, 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 o crowd unding, all
have one thing in common: they
are collaboratively building and
disseminating their knowledge or
ree on the Net. In this respect,
SU is one o the most importantexamples o how this can happen.
As an institution whose mission
is to assemble, educate and
Knowledgerepositories: 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 tohealthcare) are leveraging crowdsourcing to -potentially- translate and
language enable all content for the benet of users around the world.
The Language Issue
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Traditional knowledge building
models are linked to the linear model
o thought. The organization o
concepts into a coherent signicant
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 ollow the train
o thought o the author(s). More
importantly, this kind o process
was considered as the only one to
eciently deliver coherent results.
Linear knowledge building models
have been put in discussion when
rst conronted with the theoretic
possibility to have innite time
and resources to build a logical
sequence o concepts. A well-
known exemplication o this
theory is the so-called innite
monkey theorem. According to
WHAT IS CROWDSOURCING
inspire a new generation o leaders
who strive to understand and
utilize exponentially advancing
technologies to address humanitys
grand challenges, SU uses the
collaborative strength o its students,
some o the most brilliant mindsin the world, to tackle and solve
problems which are out and beyond
their normal eld o competence.
The reasons behind the success
o collaborative phenomenon are
complex, and they are eloquently
explained in Dan Pinks TED lecture:
The puzzle o motivation: (http://
www.ted.com/talks/dan_pink_on_motivation.html)
In order to understand how the
collaborative building o knowledge
is realized, and what implications
it has or the inormation diusion
in general, and or the healthcare
eld in particular, we need to
delve deeper in the world o
crowdsourcing and collaborative
communities and projects.
Career analyst Dan Pink examines the puzzle
o motivation, starting with a act that socialscientists know but most managers dont:
Traditional rewards arent always as eecti veas we think
The infinite monkeytheorem
Author: Ferdinando Scala
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this theorem, i a monkey (thereore
a being not provided with human
logic or sense o purpose) had a
typewriter and innite time at its
disposition, it would be able to build
up the complete works o WilliamShakespeare by sheer brute orce,
by randomly tapping on the keys.
Even i this theorem has some
strong limitations, it is very important
rom the conceptual standpoint. It
conveys the idea according to which
even in apparently unavourable
conditions (non-human being,
random actions, lack o sense opurpose), by having innite 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 sel-aware human
beings, who perorm voluntary
actions, which are driven by asense o purpose, the time to build
a knowledge arteact consistently
reduces, in exponential relation
to the number o individuals or
resources available, even in the
absence o a ormal scope or
organization.
The conditions mentioned above are
at the base o the crowdsourcingconcept, which rst appeared
in 2006 in a seminal article by
Je Howe in Wired magazine.
Technology
Trigger
Plateau of
ProductivitySlope of Enlightenment
Trough of
Disillusionment
Peak of Inated
Expectations
EXPECTATIONS
TIME
Automatic Content
3D Scanners
Internet of Things
Natural Language Q&A
Speech-to-Speech Translation
Crowdsourcing
BigData
GamicationHTML5
Wireless Power
3D Printing
BYOD
Social AnalyticsPrivate 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
Virtual Worlds
Mobile OTA Payment
Media Tablets
Consumerization
Speech Recognition
Predictive Analytics
Biometric Authentication Methods
Audio Mining Speech Analysis
Autonomous Vehicles
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 2012http://en.wikipedia.org/wiki/Hype_cycle
beore the Peak o Expectations
Crowdsourcing is still the new thing. Theopportunities to leverage this technology and
approach are in ront o us, and the knowledge
we have inused in the Net is too much to behandled.
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The author presented or the rst
time the possibilities oered by
the unstructured, collaborative
approach or business purposes.
Since then, the meaning expanded
to a signicance that here we dene
as:
Since this publication, the concept
has exploded in a series o
applications outside the business
world, o which Wikipedia is the
most well-known example.
Wikipedia is probably the best-
known example o crowdsourcing
applied to knowledge building at a
worldwide and cross-cultural level.
Built rom the collaborative eort
o anonymous contributors, each
adding up a piece o inormation,
revising grammar and ormatting
pages, Wikipedia is as o now
the most complete repository o
human knowledge. One o the
Top-5 ranked websites in the world,
and consistently in rst 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 rom the United
States alone.
Also when examined in terms
o quality o content, Wikipedia
shows good consistency and
credibility, despite it being the
result o unstructured work. In a
renowned 2005 article in Nature,
Jim Giles argued that, or some
scientic areas, individual Wikipedia
articles had the same rate o errors
that a review o 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 unstructuredway, can collaboratively achieve
results which normally implied
the construction o a structured
expert panel, and the investment o
physical and economic resources.
More importantly, it demonstrated
the easibility o an apparently
daunting scope: gathering all human
knowledge in a single place, in
any possible language, and reely
available to everyone.
While still probably surpassing
The totalencyclopaedia:
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.
Author: Ferdinando Scala
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Wikipedia articles in terms o
overall content quality, EB ails in a
undamental aspect o knowledge
diusion, i.e. the availability o its
contents in any possible language
worldwide. Furthermore, even iEB
would set itsel to this scope, the
amount o personnel, skills, and
monetary resources especially,
would be prohibitive - and would
doom the project to ailure.
In summary, rom the Wikipedia
vs. EB example, we can derive a
general theorem, which proves
itsel as correct when the ollowing
conditions are respected:
We have examined how
crowdsourcing generates huge
quantities o organized data by
means o the non-coordinated eort
o unrelated contributors. Even i
there is no hierarchical relationship
among contributors, the creation
o these huge knowledge buckets
is still strictly related to individual
human skill and willingness.
Once we understand the basic
concepts o crowdsourcing, we are
ready to revert the innite monkey
theorem, and bring our analysis on
a urther level. The next questions to
be considered are:
a. What happens when data
generators are potentially innite
in terms o the number and
quantity o parameters they take
into account?
b. What completely new
possibilities are available when
data generators are networked
into a system running under a set
o cybernetic rules, which ensure
constancy, reproducibility and
analytical accuracy o measured
phenomena?
The answers to these questions are
ound when examining the world o
Big Data, the concept o Quantied
Sel and their consequences or the
healthcare domain.
Today: All places that are
mono-cultural or with a single
sender that operates in logical
broadcast, make it increasingly
difcult to gain trust. Also, on the
other hand, it is difcult today
that a pyramid not sufciently
open - as is typical of crowd-
mechanisms - can nd the
necessary trust.
Pyramids as well as YouTube
- were built by many. Stories,
information or generally speaking,
content dene 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.
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WHAT ARE BIG DATA?
As the renowned physicist Lord
Kelvin (1824 - 1907) proclaimed, I
you cannot measure it, you cannot
improve it. This law was designed
by humans to meet the needs o
science, which were becoming
more complex. Over a century later,
we continue to nd this complexity
in every moment o our workinglives. Measuring everything has
become a human centric issue
about knowledge and control
in the Internet Age - exactly when
technology was able to ll 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 WASjust the beginning o an incredible
emergent trend: In the Internet
Age, or better yet, in the upcoming
Internet o Things Age, we do not
have enough humans to take care
o all sensors, devices, satellites,
and in general- inrastructures that
we create. Measuring everything is
an intrinsic need o the technology
we are leveraging to build our world.
And actually it is also a need o the
world itsel, as a planet, to ace the
impetuous evolution o the human
ootprint. Measuring everything has
already changed other industries
and healthcare is not immune.
Patients are the biggest communityin healthcare and - today - thanks to
all their portable smart technologies,
they are becoming an active actor
in health, nutrition and wellness
data collection. The diusion o
these technologies is becoming so
widespread, sensible in terms o
measured parameters, and easy to
carry or people, that it is opening a
brand-new opportunity, called the
Quantied Sel (QS) movement.
The QS approach is to incorporate
technology into data acquisition on
most aspects o a persons daily
lie in terms o inputs (e.g. ood
consumed, quality o surrounding
air), states (e.g. mood, arousal
and blood oxygen levels), and
perormance (mental and physical).
The primary methodology o sel-
quantication is data collection,
ollowed by visualization, cross-
reerencing and the discovery o
correlations.
This powerul trend has inspired
numerous hardware devices
(mostly in the wellness area) that
leverage components or cost
reductions in sensor technology,
mobile connectivity, and battery
lie, and that have already become
part o the everyday lie o millions
o users. This trend resulted in the
appearing and explosive expansion
o products like Withings, Nike+,
tbit, as well as sotware apps or
smartphones used to track almost
every aspect o lie.
Behind the QS, there is an emerging
desire or an individual to improve
onesel, and a natural human
Measure Everything: Ifyou cannot measure it,
you cannot improve it
Data sources:the Quantified Self
Author: Leandro Agr
Author: Leandro Agr
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Data sources:
crowdsourcing for menand machines
tendency towards competition within
ones own microcosm (riends &
ollowers).
The QS is also related to the
philosophy o interdependence,
donating inormation about onesel
to be used as a contribution towards
new knowledge about peoples
behaviour and habits as well as the
discovery o new medical cures.
From the Pharma perspective,
QS is creating an emerging andimmediately relevant group o
stakeholders. Right now, most o
the work o 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 o useul data. Using shared
tools such as Wikipedia or any
other collaborative tools on the
Web- people are able to conceive
and evolve spaces o 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 o todays
reality.
The Net is both or humans and
machines, and today we should
bear in mind that machines are
more numerous than their human
counterparts. The evolution
o human crowdsourcing and
participation is a mixed human/
machine crowdsourcing and
interaction.
In the eld o health, we can benet
rom 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 sel-tracking, and
more. (Cit. When Data Disrupts
healthcare http://www.youtube.com/
watch?v=IAt0jw306k).
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
o analysing inormation on a
worldwide scale or almost every
possible topic or matter.
The availability o di erent datasets
presents an opportunity or High
Tech Companies because data
scientists and technologists
already have the skills to manage
the data. We have already done
Author: Leandro Agr
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.
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something similar in the nancial
eld. Today, almost completely
driven by machines based on Big
Data analysis, relevant results can
be ound correlating the many
healthcare data sources.
Up to this moment, we established
the basic concepts o crowdsourcing,
Big Data and Quantied Sel, and
we could be tempted to consider
them as distinct and ar away rom
daily reality. Quite the opposite,
these technologies and trends are
already impacting the pharmaceutical
industry. In the ollowing
paragraph, we will understand how
crowdsourcing is impacting R&D.
The traditional model or R&D
development in any company has
always been based on the selection,hiring, and consolidation o the
best talent, to produce innovation
transered into sellable products or
the market. This kind o process
has the advantage o ensuring
consistency and continuity o eort
toward a certain objective, which
unctions well when the amplitude
o challenges is consistent with the
dimension o the R&D structure.
As a downside, having a
consolidated R&D structure implies:
a) Consistent organizational eort
in order to select, maintain, and
manage the right people in the right
place: with huge expenses in terms
o HR resources;
b) Limited ability and capability
to address prevalent scientic
problems; delimited by the individual
and collective skills o the R&D team
members; and the sheer number o
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 o
overall nancial and operational
capability o the company.
Crowdsourcing is a way o expandingthe available pool o 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 o InnoCentive,
a crowdsourcing platorm whoseinitial eld o application was
pharmaceutical R&D, but today
extends its business model in other
areas like engineering, computer
science, mathematics, chemistry,
lie sciences, physical sciences and
business. The InnoCentive business
model is based on the online sharing
o pharmacological or clinical
development problems, or which
it is unpractical to nd a solution
internally, and the call or proposals
to platorm members. InnoCentives
members have thus the possibility
to contribute to the resolution
o proposed problems, earning
consultancy ees or their contribution
ranging rom 500 to 1.000.000 USD.
The model has encountered
considerable success, to the point
that today prominent organizations
InnoCentive: a casestudy in crowdsourcing
for pharmaAuthor: Ferdinando Scala
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in a wide array o business sectors
like BAE Systems (avionics),
Booz|Allen|Hamilton (consultancy),
The Economistand Nature (editors),
Hersheys (ood), 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 includesabout 200.000 individuals rom more
than 170 countries. As o now, it has
distributed ees or an overall amount
o 28.000.000 million USD.
All healthcare market players have
one very relevant thing in common:
they produce data. The whole o
healthcare is becoming an industry
based on Big Data.
Could this high-end technology be
an entry barrier in the healthcare
space?
No. Dozens o companies are
already competing in the massive
data collection arena, ghting to
oer qualied low cost analytictools.
Kaggle based in Caliornia - is
a good example. Financed with
11.000.000 USD, Kaggle launched a
platorm or predictive modelling and
analytics competitions. Companies
and researchers post their data, and
statisticians and data miners rom all
over the world compete to producethe best models.
As an example o an advanced
healthcare company, Boehringer
Ingelheim (BI) is actively engaged in
this platorm to urther its business.
Predictive in silico modeling o
biological endpoints is an important
and useul component o 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
ollowing benets:
Competitive advantage in time
and cost eciency
Engagement with an external
community o data scientists
to create an awareness around
BI as a cutting edge, innovative
organization
Reactivity: to almost immediately
deploy the winning model(s)internally or use by medicinal
chemists through Bipredict, or
other local distribution platorms
The competition was launched
on 16 March 2012. As early as
22 March there were 74 teams
(comprised o 90 players) who had
submitted 277 entries. 24 o these
entries represented models that
were better (i.e. more predictive)
than the best initial benchmark.
The success o this project has
been covered in a BI press release,
and received subsequent coverage
in several blogs. Moreover, tweets
rom both @boehringer and
@boehringerUS have garnered
>200K impressions to date.
Kaggle Data ScienceCompetition: a BI case
study in crowdsourcing
Author: Leandro Agr
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Crowdsourcing, Big Data, and Quantied Sel are important trends
revolutionizing the development o new drugs and connecting inherently
limited rameworks, like clinical studies.
The impact o these trends, however, is not limited solely to the domain o
clinical research; they are also readjusting the way corporations communicate
to their external audiences.
In the ollowing section, it will become apparent how traditional, linearcommunication models are being substituted by completely new ones. The
result o this process is a brand-new marketing and sales paradigm, which
requires pharma executives to readjust their cultural and operational models.
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COMMUNICATION MODELS
The communication process is
traditionally dened as the passage
o inormational units (content),
coded into some sensorial arteact
(language) rom an entity which
produces them (emitter) to another
entity with receives them (receiver).
Context and channel employed in
passing the inormational units romone entity or the other are pivotal in
determining the quantity o delivered
inormation and its interpretation.
When described as such, it is
evident that communication
has historically been interpreted
as a linear process, in which
inormational fow travels in one
direction, and no eedback isconsidered. This philosophical
attitude was the cultural substrate
to the construction o the mass
communication system, whose
media (newspapers, radio and
television) acted as unidirectional
channels or message delivery rom
emitters to target users. The result
o this model was that the owner(s)o media channels were also the
owners o inormation. Media
owners were indeed in a position
to determine the agenda, i.e. the
type, combination and requency o
inormation which, when delivered
rom emitters to receivers, massively
contributed to build the audiences
knowledge, attitude and opinions
about whatever issue the agenda
setters elt unctional to their own
needs. In addition, agenda setters
also had the possibility to determine
not only which inormation had to
fow rom emitters to receivers, but
also which inormation should not be
delivered.
Traditional advertising models also
conormed 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 o acquiring
inormation. Traditional advertising
is based mainly on the attraction
o target users in predetermined
channels; the oering o valuable
content to them; and the application
o 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 o
physical (tabular advertising) and/
or media (press/radio/television)
space. This is so the end user had
a higher possibility o encountering
the message throughout the day.In parallel, within a specic medium
(like television), the most successul
brands were the ones having the
possibility to win the competition
or the most ruitul time slots (prime
time), i.e. the moment o the day when
most users were connected to that
medium/channel. Finally, persistence
o the message, and thereore the
realization o sales, depended on the
single campaign extended over time,
and requency o message repetition
Hierarchical modelsand broadcasting
Author: Ferdinando Scala
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within a single day.
While unctioning well or many
decades, and allowing the surge
and ortune o a whole industry
based on traditional media, this
mechanism has proved to be
progressively less ecient over
the last ew years. In particular,
television has suered an extensive
loss o ecacy in terms o public
adherence, principally owing to
an increase in the requency o
interruption marketing practices.
The introduction o technologies like
remote control and TIVO strongly
empowered users against the
mounting wave o advertising slots,
and their excessive requency in the
body o programs. Furthermore,
while remaining o interest to the
generations who were involved in
this system o content broadcasting,
television has progressively lost
its power as a medium, especially
or the younger generations, those
who rst embraced the digital
media revolution and its mobile
development.
This resulted in the declining
ecacy o television as a means o
sales generation or Fast Moving
Consumer Goods (FMCG), and in
the pharmaceutical eld or Over
The Counter (OTC) drugs. While
commercial and pharmaceutical
industries began to realize this act,
an increasing amount o investment
was progressively diverted rom
traditional media to the new digital
channels.
The traditional sales orce could
be seen as the prescription drug
equivalent o broadcast media; with
a large number o representatives
using the same materials and
delivering the same message to
their customers. Pharmaceutical
companies have already been
steadily moving rom this traditional
model by using customer proling
to tailor messages and interactions.
This is becoming ever easier
to manage given the variety o
digital channels now available to
physicians.
These past ew years have been
a testimony to the strength o
the digital revolution, with the
progressive introduction o
technological assets and tools
having undamentally changed the
communication panorama. The
building o the World Wide Web and
its mobile development generated a
completely new system o relations
and communicational fuxes,
identied 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 inormation selector and an
emitter, whose infuence and impact
depend on the extent and depth
o their social network. The rate
o disruption is so deep that the
lexicon has changed, generating
the neologism prosumer, to
dene a new type o actor. The
term prosumer results rom the
merging o the words producer
and consumer. In the specic
inormational domain, it has the
signicance o a person who is
The network modeland P2P
Author: Ferdinando Scala
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simultaneously a producer and a
consumer o inormation. People
previously known as target or
audience have been enabled
through the construction o
networking inrastructures and tools
(social networks like Facebook or
LinkedIn; collaborative media like
Wikipedia) to exit the traditional
paradigm. Where they were
ormerly absorbing inormation
rom hierarchical, unidirectional
media, they are now inormationemitters with their closely related
peers. It should be recognized
that inormation exchange among
peers existed prior to the creation
o social networks. Indeed, a large
part o the traditional advertising
model was primarly based on
infuencing the so-called opinion
leaders, i.e., individuals who had,because o their standing and
measure o infuence, the capability
to spread, by axing in the minds
o others, messages coming
rom the interested emitters. The
pharmaceutical world has always
relied on this paradigm, e.g. passing
inormation about new drugs,
new indications and new clinical
studies, to prominent physicians
(Key Opinion Leaders - KOLs).
These KOLs assumed the role o
interpreters o the pharmaceutical
industrys data and messaging
towards the medical community.
What has changed orever with
this advent o Internet and social
networks is the sheer number o
people simultaneously reached by
a discussion about a topic, has
changed rom a ew (lets say the
direct colleagues o 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
o the virtual network a single
individual has, and irrespective o
the geographical dimension).
In this context, while still maintaining
a strong measure o infuence, the
opinion o Key Opinion Leaders is
somewhat blunted and diluted by
the possibility that other subjects
(prosumers) actively select and
spread inormation, according to
their own rules and belies. 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 requency and quality o
interactions) are based on trust and
credibility.
It is thereore important to
understand the new rules which
apply to the new channels, which
are much more volatile and
immaterial than beore.
We shouldnt consider this evolved
marketing scenario -where peers
need to be requently reached
with coherent messages- just as a
ragmented target to address with
a common message. Empowered
HCP and Patients are walking away
rom any kind o broadcast. Today
the most ecient way to reach themis joining (or leading) the so-called
Conversation.
As a quick background about the
Real time is formarketing (theCluetrain manifesto)
Author: Leandro Agr
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idea o conversation, we should
start rom the seminal book The
Clue Train Manifesto (also known as
CTM, 1999).
The Clue Train Manifesto contains
95 theses that re-dened Online
Markets and re-shaped marketers
culture.
During these years, powered by
the digital change, networked
markets sel-organize aster than the
companies that have traditionallyserved them. Thanks to the Web,
markets become better inormed,
smarter, and more demanding o
qualities. In this new scenario as
declared by the rst thesis o 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 transorm
traditional business practices
radically in todays reality.
Conversation is the CTMkey
concept: According to the second
and third thesis reported in the
book, Markets consist o human
beings, not demographic sectors
and Conversations among human
beings sound human. They are
conducted in a human voice.
These ew theses are enough to
radically shit what most companies
are doing in their communication
plane, both in the physical and
digital spheres. The consequence is
the communication o a totally new
value chain, because Hyperlinks
subvert hierarchy and people
through the Internet - no longer
depend on traditional knowledge
and inormation sources.
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INTRODUCING THE ePATIENT
In a world where a global conversation
is evolving the whole healthcare
market, people use the Internet to nd
tons o inormation about any disease,
and to potentially contact anyone to
collect dierent opinions.
The power o inormation-access
in the hands o 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 rom a society suspicious o
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
o the gross domestic product o
the worlds major economies is
spent on health. In the world o
pharmaceutical companies, we
nd examples such as Johnson
& Johnson (the largest o all Big
Pharma), which is at 40th position
o the Fortune 500 ranking. The
size o this company is based on its
120.000 direct employees and over
$60 billion in sales. In comparison,
Apple, with its $65 billion and hal o
the employees o J&J, is just above
at 35th position o Fortune 500
(2012 pre-iPhone5 rankings).
ago. Today we have the big picture
o healthcare at our ngertips. For
example, today we know that there
has never been a time in the past
when humanity was better o in
terms o wealth and health than
it is today. The video The Joy o
Stats: 200 Countries, 200 Years,
4 Minutes by Hans Rosling (BBC
Four) could suce to inspire this
systemic optimism.
This depends on many actors,
including what we know today about
our health and how to treat
Author: Leandro Agr
The Joy of Stats
This video il lustrates how over the past two
centuries, lie expectancy and per capita wealth,
have vastly improved or many nations. O coursethe current state o health does not mean that
there are no other potential alarms or the planet,BUT i you look at our health, we cannot miss the
underlying declaration o this video that WE ARE
GOOD and have NEVER BEEN BETTER.
http://www.youtube.com/watch?v=jbkSRLYSojo
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The comparison - even that o
wealth between the consumer-
oriented Apple, and J&J or any other
pharmaceutical company, might
seem completely out o place, and
actually, or a long time, it was.
In recent years, however, the
mutation o both economic and
cultural dynamics has made
comparisons o companies like
these more justied. The need to
be more ecient and closer to
the end customer, even in health
organizations, is changing rom
within.
The digital culture that permeates
society has changed the needs
and expectations o customers,
orcing entire industries to convert
mentalities, or come to terms with
the traumatic entry o outsiders, who
have already done so. Regardless o
your opinion o the Mayan prophesy
announcing the end o the World
by 21 December 2012, that was the
year in which some major players in
the healthcare world went through
their perect storm.
2012 has indeed been labelled
annus horribilis due to the number
o healthcare patents that are
approaching expiry. By 2015,
ollowing the expiry o very relevant
patents, the ranking o the 50 largest
pharmaceuticals may undergo
drastic changes or even some
surprising extinctions. This crisis has
orced many companies to return to
heavy investment in R&D. By nature,
this contemporary approach oten
translates into research in the eld
o biotech. As a result, the culture o
many companies is moving rom a
cure-all drug to a drug tailor-made
or you.
A key point o this cultural shit is thechange in the almost total access to
the medical inormation base. At the
same instant in which a disease -
especially i not particularly severe -
aects us, we become transormed
not into sick people but into
ePatients: people who are able,
through the distributed knowledge in
the Internet network, to learn abouttheir conditions as well as treatment
options, comparing the dierent
therapeutic approaches and results.
However, one needs to be careul
and not consider the ePatient as a
consequence o technology or an
outcome o the Facebook era.
Dave deBronkart coined the
denition o ePatient, made
amous with his speech at the TED
Conerence, when he narrated this
episode:
That Fall o 1969, the Whole Earth
Catalog came out. [...] We think o
hippies o being just hedonists, but
theres a very strong component
-- I was in that movement -- a
very strong component o being
responsible or yoursel. This books
(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.
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is: Access to Tools.[...] Tom
Ferguson was the medical editor o
the Whole Earth Catalog. And he
saw that the great majority o what
we do in medicine and healthcare
is taking care o ourselves. In act,
he said it was 70-80% o how we
actually take care o our bodies. Well
he also saw that when healthcare
turns to medical care because o
a more serious disease, the key
thing that holds us back is access
to inormation. And when theWeb came along, that changed
everything, because not only could
we nd inormation, we could nd
other people like ourselves who
could gather, who could bring us
inormation. He coined this term
e-Patients - equipped, engaged,
empowered, enabled.
This hippie counterculture note
helps emphasize how seeing the
ePatient as an insignicant role
would be a double aux pas. Firstly,
since it is an ingrained, long-
established phenomenon. And
secondly because phenomena that
benet rom 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 o healthcare is not
necessarily a bad thing.
ePatients are not the only orces
that are infuencing the world o
healthcare. The entire industry is
aected 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 o this article is
summarized as ollows: The
Cheesecake Factory, used as an
example, is part o the casual dining
industry and, present everywhere in
the United States, can serve resh
ood, 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 oods or lower
income groups, and at the same
time, they had to infuence the
processes o supply logistics and
their suppliers, optimizing logistics
and processes both internal and
external.
This action, which aects the source,
is o course only possible when you
reach a certain critical mass. The
process o improving the quality/cost
ratio o the entire sector o 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 sel-employed,
working alone or in small private-
practice groups. American hospitals
tended to be community-based.
But thats changing. Hospitals and
clinics have been orming into large
conglomerates.
According to the Bureau o Labor
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Statistics, only a quarter o doctors
are sel-employedan extraordinary
turnabout rom a decade ago,
when a majority were independent.
Theyve decided to become
employees, and health systems
have become chains. In medicine,
we are trying to deliver a range
o services to millions o people
at a reasonable cost and with a
consistent level o quality. Unlike the
Cheesecake Factory, we havent
(yet) gured out how.
Similar examples can be drawn in
many areas across the world o
healthcare. Even the area o medical
devices is not without drastic
changes. Just going to the Apple
Store, one can nd many medical
devices that cost less than a
hundred dollars. Just ve years ago,
we could only nd these devices in
a pharmacy and we would only have
purchased them on medical advice.
One example? Withings Blood
Pressure Monitor, or an easy and
accurate sel-measurement o your
blood pressure directly on your
iPhone. http://www.withings.com/
en/bloodpressuremonitor.
From ePatients to the infuences o
changing orces across the value
chain, the world o healthcare is
rapidly changing. A key player in
this change is that o technological
acceleration. When digitalization
aects 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 ree rom this
explosive eect o digital and
ePatients represent the most visible
part o this rapid change.
ePatients are not special people. We
are ePatients when we:
Seek inormation on the Internet
about symptoms or diseases
Seek practical advice via social
networks and share experiences
related to health
Use sel-tracking or wellnessdevices because we aspire to
eel better
Think o 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
careul scrutiny beore purchase
We infuence those around us
by sharing our experiences on
health
An article published on January
16, 2012 by TechCrunch PEW
Research was reporting that 17percent o mobile phone users
were using their devices to look up
health and medical inormation, and
Juniper recently estimated 44 million
health apps were downloaded in
2011.
In 2011, in terms o earnings, the
area o mobile health applications
reached $ 718 MM. The mainreason or the signicant growth is
an increase o smartphone users on
the demand side, and the increase
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o mobile health applications on the
supply side that has doubled since
2010.
Many major healthcare companies
have ound mobile health
applications as being an eective
medium to promote and deliver
healthcare products and services.
More inormation on the mobile
health application market can be
ound in the detailed report by
research2guidance entitled, The
Mobile Health Market Report 2011-
2016, which describes the impact
o smartphone applications on the
health industry.
As easily understandable, the
above mentioned trends are not
restricted to pioneer attempt toward
a new level or patients to acquire
and share medical inormation. On
the contrary, it already generated
PatientsLikeMe, a very notable
example about how collaborative
attitude can incredibly improve the
levels o treatment and quality o lie
o patients.
We, in Pharma, cant 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 ePatients 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
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PatientsLikeMe is a collaborative
platorm where patients and
caregivers have the possibility to
share their own experiences and
problems, in order to gather help
rom people in the same condition.
The platorm was born in 2004 as
a specialized sharing environment
or patients aected by Amyotrophic
Lateral Sclerosis (ALS, or Lou
Gehrigs disease), a chronic and
disabling neurologic illness, which
has an average atality rate o
39 months rom early onset. A
very amous ALS suerer is the
prominent physicist Stephen
Hawking; also a most unusual one,
having survived the illness or more
than ty years.
The PatientsLikeMe (PLM) virtual
environment was ideated by the
amilies o ALS patients, who were
searching or advice and support
about how to better cope with the
progressive decline o their loved
one capabilities, while also ensuring
the best possible treatment and
support strategies. What started
as a simple method or gaining
support in response to a need, soon
transormed into a powerul tool or
patients, caregivers, and, ultimately,
doctors.
Despite the act that the person or
which PLM had been conceived
did not survive the disease and
passed on shortly ater, his
parents managed to gather ideas,
inormation and even economic
support by simply relying on
the power o crowdsourcing.
The platorm 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 o depression
or mood during recovering, the
quality o lie associated with both
conditions and treatments, and so
on.
As a consequence to the approach
taken, ounders were able to gather
unds worth about 50 million USD
in support o the ALS Therapy
Development Institute, a non-prot
biotechnology company whose
mission is developing treatments
or ALS. Furthermore, when the
platorm 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
dierent diseases.
When it moved outside the ALS
domain and dierentiated its data
gathering to include other diseases,
PLM opened itsel to become one
o 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
scientic work. Opposite to the
traditional model or patient
enrolment into clinical studies, which
is based on the reerral o patients
to researchers by traditional reerral
systems like hospitals and GPs;
PLM was in the position to make
its members aware o ongoingclinical trials all over the United
States, segmented by condition
and demographics, thanks to a
PatientsLikeMe: a casestudy on the power of
ePatients
Author: Ferdinando Scala
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partnership with ClinicalTria.gov.
This allowed patients to have a
direct source o inormation about
which studies o interest were
on-going, and taking steps or
participating in them. This led to a
greater speed in terms o enrolment
rate (which is always one o the most
dicult and rustrating tasks or
researchers) and greatly improved
the overall statistical signicance
o the gained data, due to the
larger dimension o statistic sampleavailable.
PatientsLikeMe is thereore a
signicant hot spot o 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 powerul, highly
measurable, and fexible tools or the
diusion o their messages.
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Over the last ve years, pharma
companies have all been moving
toward the integration o digital
strategy into their marketing mix; not
longer a nice to have addendum,
but as an important pillar o overall
brand strategy. The rate and extent
o this integration is such that in
some cases and markets digital isbecoming immaterial, i.e. it is not
anymore a part o the whole, but
permeates all the communication
activities.
The acceleration toward the creation
o an integrated digital approach
produced a surge in the number
o digital assets available online,
typically dedicated to brand ortherapeutic area communications.
As a consequence, companies now
ace a undamental rule o digital
communications: rapid content
obsolescence. Dierently rom
previous operational models, whose
rhythm o content production and
diusion was ollowing a time scale
o approximately three months,digital communications erase the
communicating power o content
much aster. Quite typically, content
is now considered obsolete in a time
span that ranges rom thirty and orty
days maximum.
These new conditions generated a
paradox, under which companies
are orced to have a constant fow ocontent in order to uel their online
assets (i they dont do so, assets die
quite rapidly due to loss o interest);
while not having the economic and
organizational power to generate
enough content to ll 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. Thereore,
content sources like collaborative
media are pivotal in allowing a digital
asset to be constantly resh and
updated. On the other side, there
is the problem o dierentiating and
selecting interesting content rom the
qualitatively unsuitable. This can be
attained by individualizing the users
who produce content o sucientquality in collaborative communities;
and providing them with privileged
inormation in order to make their
content production aster and o
better quality. This way, it is possible
to build a wide panel o aectionate
users, which entertain a strong
relationship with the company, and
develop a mutually advantageousdynamic. By accessing privileged
materials and tools, to produce better
content they will have the possibility to
shine in ront o their social network;
while delivering messages rom the
company with maximized quality
and credibility. And so, these content
providers become the KOLs o the
digital communication era.
ActiveMint is an interesting example
which uses crowdsourcing in order to
monitor and reward healthy behavior.
CROWDSOURCING AND ePATIENTSFOR MARKETINGAuthor: Ferdinando Scala
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Conclusions
The Internet Age has brought with it an almost innite amount o inormation,
allowing anyone and everyone the resources to build their knowledge to build anything in act! Crowdsourcing is an innovative way o 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 lie as a marketer?
Just spending 10-15 minutes o your searching outside o our comort zone
o FirstWord newsletters, PM Live, MM&M, etc could open up a new world
o resources to mine or insights into the disease areas in which we work. It
could give us the opportunity to become exposed to the thoughts, eelings
and motivations o people living their lives with these diseases; sharing the
thoughts, their data and shaping their own utures.
Have you considered ePatients as a stakeholder in your
marketing plan?
Whilst we cannot drive, over-infuence or hide the opinions and broadcasts
o ePatients we might consider how to engage with them, or simply use their
knowledge and resources to better understand the needs and behaviours o
your most-empowered end customers.
With these new paradigms o Crowdsourcing and Big Data, the ePatient is
a orce to be reckoned with, the perect storm that will sweep through andradically change the uture o 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 or
learning how to align your brand / ranchise / organization to the mounting
wave o digitally-enabled healthcare.
7/28/2019 From Crowdsourcing to BigData
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7/28/2019 From Crowdsourcing to BigData
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Razorfsh Healthware is a global leader in digital and healthcare
communications, leveraging a unique mix o insight, technology, creativity
and industry savvy to deliver digital innovations, solutions and tools that drive
improved health outcomes.
Our deep understanding o the innovation process, human-technology
interactions, and the healthcare ecosystem enables us to generate
transormational experiences that empower peoples health and wellnessdecisions.
Razorfsh Healthware is a single organization able to deploy our ull
suite o services in support o any market with more than 300 dedicated
proessionals based in 9 countries around the world: US, France, Germany,
Italy, Spain, UK, Australia, China, India.
Razorfsh Healthware is part o Publicis Healthcare Communications Group
(PHCG) , the largest and most innovative health oriented communication
group.
Razorfsh Healthwares service oering is made up o three specialized
business units, an Advisory practice oering technology strategy and
enterprise consulting; a digital communications and marketing practice and
a solutions and technology practice oering a range o enterprise business
tools and related services.
For more inormation please visit
razorfishhealthware.cominfo@razorfishhealthware.com.
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