From Crowdsourcing to BigData

7/28/2019 From Crowdsourcing to BigData

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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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4Razorfsh | Healthware From Crowdsourcing to BigData June 2013

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.



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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



18/32


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



19/32


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


20/32


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.


21/32


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


22/32


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.


23/32


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


24/32


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


25/32


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


26/32


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



27/32


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.


28/32


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


29/32


30/32


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.


31/32


32/32

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

[email protected].

EU | t +39 089.3061.411 | +39 089.3061.415

US | t +1 888.463.3793 | +1 646.935.4791

AboutRazorfsh Healthware

Razorfish Healthware

@RazorfishHW

Visit us on:

Razorfish Healthware

paginemediche.it

personasque.com

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