RWE and Digital Health whitepaper (email)

Real world
evidence and
digital health:
PHARMA'S next
frontier

www.eyeforpharma.com 2
Real world evidence and digital healthcare:The next frontier
MichaelWeinberger, Senior Director, Digital Solutions, Product Development at Johnson &
Johnson discusses mHealth as an indispensible part of the healthcare landscape and the
need to provide utility to the end-user.
It is a foregone conclusion that mHealth will play a fundamental role in how we manage
healthcare in the future. In order for the pharmaceutical industry to deliver enhanced value
to payers, patients and HCPs they need to understand the consumer mindset. Our customers
reach a quick appreciation as to whether an app is a thinly veiled “digital trinket" or whether it
genuinely provides utility in terms of enhanced convenience, experience and outcomes. These
consumers are the true driving force in mHealth because unless an app delivers value to the
patient it will be quickly ignored or deleted. So, mHealth is not just another chapter in the story
of digital marketing—a new avenue to promote and to sell. Rather it is an opportunity to help
our customers reach their personal and family healthcare goals in new and exciting ways. And in
the process, mHealth will enable the industry to augment its talents as suppliers of product and
providers of services and solutions.
Rather than wait to be disintermediated, pharma needs to understand the transformative
potentialofthemHealthspace,unearthingthetechnologicalcapabilitiestoaddressfundamental
healthcare problems such as ageing society, an increasing rate of multiple morbidities and cost
concerns in a financially stretched healthcare system.The ability to collaborate and innovate will
separate the lumbering incumbents from the radical pioneers.
Michael Weinberger
Senior Director, Digital Solutions, Product Development
Johnson & Johnson
Foreword

Pharma’s biggest opportunity
Digital data generation is everywhere in healthcare,
from low cost fitness apps collecting real world
wellness data-to high-end medical sensors
monitoring disease right down to the cellular level.
As costs fall and mobile access improves, this huge
expansion in data generation and monitoring
could finally enable the industry to deliver on
some long-promised improvements, from patient-
centric personalized healthcare to a better drug
development process. The gain from recent
changes could be huge; an era of real world data
and mobile health would create swifter patient
access to cheaper and more effective healthcare.
As momentum continues, there is no doubt that
this shift will change the industry; the objective
of this whitepaper is to give the reader a glimpse
of this future. Interviews with thought leaders at
the cutting-edge of this field, underpinned with
extensive desk research, will tell the story of how
real world data and advances in wearables have
given pharma the tools to deliver patient-centric
services.
MOBILE

A new frontier of innovation
A data-driven future for patient services
Monitoring device sales are going through a period of
sustained, rapid growth. A recent report estimates that
the global market for monitoring and diagnostic medical
devices (including specific devices such as cardiac
monitors, glucose monitors, blood pressure monitors,
pulse oximeters, multi-parameter monitors and sleep
apnea monitors) will increase from just $0.65 billion
in 2012 to as much as $8.03 billion by 2019, a CAGR of
43.3% [1, 2].
While the largest share of the market in 2012 was in
cardiac monitors, followed by glucose monitors and
blood pressure monitors, the report predicts that
glucose monitoring devices and multi-parameter
monitoring devices will grow the fastest in the period
to 2019, with a CAGR of more than 45% [1]. The report
points to increased pressure in healthcare costs, aging
populations, and increases in age and lifestyle diseases
as driving factors behind this expansion, suggesting
interesting implications [1]. Properly applied, digital
healthcare is being taken seriously as a solution to deliver
cost-effective patient services towards an expensive,
and expanding, population. As payers struggle with the
costs of treating ageing populations the attractiveness
of digital devices that can cheaply collect and respond
to patient data is clear. “The interest in real world data is
increasing as resources for funding healthcare become
more limited, but advances in technology offer great
promise to reduce inefficiencies and support innovation”,
says James Harnett, Senior Director of Real World Data
and Analytics at Pfizer.
Collecting real world data: Electronic
health records
Although the appetite of governments and private payers
has been an important driver, much of recent innovation
has been enabled by progression in the integration of
electronichealthrecords(EHRs).Asthehealthcareindustry
has leapt forward in the digitalization of health records
this has allowed researchers to both aggregate EHRs
and combine them with other data sources, improving
results in both clinical research and patient management.
“Integrating data from a variety of different sources, such
as claims data and EHRs, creates richer datasets that can
generate newinsightsand hopefully improve our abilityto
predict outcomes,”says Harnett.“These kinds of processes
will shape the systems for collecting data, improving data
quality and integration in the future.”
An example of a recent innovation is Janssen Diagnostics’
AVIGA™; a secure and scalable electronic health record
(EHR) system tailored specifically for the management
and monitoring of people with HIV/AIDS. The system
allows for data integration and exchange between clinics,
laboratories, radiology departments, pharmacies and
record archives. It also includes automated government
reporting and compliance procedures.
Both researchers and physicians benefit from this
progression, ultimately allowing for the delivery of
improved services to the patient. “This system has
enabled the aggregation and interrogation of around
20,000 records over a 20-year period, which wouldn’t be
practical with paper records, or data kept on individual
clinic databases,” says Nigel Hughes, global director,
Marketing & Health Information Technology, Janssen
Diagnostics. “There is a degree of quid pro quo in the
system too – researchers could access the physician’s
data in a secure environment, and return the value
to the physicians in the form of research, audit and
benchmarking. Also, using automatically updated real
world data from diagnostic tools out in the field could
provide surveillance and early warning for infectious
diseases such as flu or even Ebola.”
Applying RWD in the Real World: How
data innovation is creating support for
patients and physicians
Data harvested from wearables will allow for more
effective use of existing real world data sources, such as
“There has been a lot of hype, but we
are at last starting to see some real
applications of digital healthcare for
doctors and patients.”
Andy Jones, Vice President, Pharmaceutical Innovation,
AstraZeneca.

EHRs or social media footprints. So far these capabilities
have primarily been used to enhance assessments of
interventions, such as a lifestyle change or a new therapy,
improving disease management. However recently
strides have been taken to allow the patient to benefit
from advancements in this technology too; giving
engaged patients greater control over their care.
“Traditionally, patients were given a care plan
and medication. As people are becoming more
knowledgeable, they want to be more involved in
the decision-making process, creating an agreed self-
management plan in collaboration with healthcare
professionals, supported by smart devices and tools,"
states Jones.
He points to the recent incorporation of the Archimedes
model into healthcare apps as an interesting example.
Created by Archimedes Inc’s co-founders David Eddy
and Len Schlessinger, this applies a mathematical model
to data from clinical trials, observational studies, and
retrospective studies to generate algorithms that can
predict how interventions will perform within a highly
customizable patient population [3]. By combining the
technology with existing diagnoses methods, physicians
make unprecedented progress towards actually
delivering personalized care. Hughes states, ““When a
patient goes to see his or her physician, the doctor can
look at Archimedes and find data such as response rates
in patients with the same disease and risk profile, but
receiving a range of different treatments. The doctor
can use this to discuss the potential outcomes with the
patient, which is a step towards personalizing medicine.”
The technology has also been integrated into
‘Archimedes IndiGO’, a physician and patient decision
support tool that has been used to power a number
of smartphone apps, including Every Body Walk!, Mix
It Up by HealthWorks, Thrive Across America, and KP
Preventive Care for Northern California. An interesting
example of this in action came through collaboration
between Archimedes IndiGO and the Marshfield Clinic
Research Foundation, with a heart monitoring app that
enables patients to self-administer heart health risk
assessments. The app, a winner of the US Department
of Health and Human Services’ Million Hearts Risk
Check Challenge in 2013, directs at-risk patients
towards nearby health screening sites, and contains
tools to facilitate collaboration between patients and
physicians, allowing them to co-create tailored plans to
improve heart health [4].
Through powering applications that personalize care,
or create space for patients to become a partner in
treatment decisions, recent developments in RWD could
transform disease management. However, even though
there is a lot of potential, it does require a certain level
of patient engagement to be effective. A challenge for
pharma, or physicians will be to ensure that patients are
willing to get involved in their own healthcare. If they
can create digital platforms that can create and sustain
engagement, then tangible benefits are there to be
achieved.“Patients who are engaged in their disease and
lifestyle management process and are accountable and
compliant have better outcomes than patients who are
less engaged.The level of engagement does not seem to
depend on cultural or socio-economic groups or disease
type, but on needs and beliefs," according to Jones.
Applying real world data: The impact
on drug development
The costs of developing a drug through to marketing
approval has risen to $2.6 billion, according to a Tufts
Center for the Study of Drug Development report in
November 2014, and adding in post-approval R&D,
including monitoring of safety and long-term side effects
in patients required by regulatory authorities, adds an
additional estimated $312 million [5].
“Real world data has a role in
development. By assessing drugs
early on, and linking medical
record data with 'omics' data, new
pathways can be identified, as
well as new and sometimes more
targeted indications. Further,
real world data can improve the
efficiencies of clinical trial programs
by informing trial design and
recruitment and a lot of attention is
being directed towards pragmatic
trials.”
James Harnett, Senior Director of Real World Data and
Analytics at Pfizer

To speed up this process and reduce the risk of
promising drugs falling by the wayside late in
development, companies want to be able to get an
understanding of which drug works in which patient
group and how well as soon as possible. The current
drug development model uses placebo-controlled
clinical trials in restricted groups of patients,
within an idealized setting that doesn’t reflect the
complications of many real world treatment cases.
This divergence carries risks that approved products
won’t deliver expected outcomes, something that
can be controlled through the incorporation of RWD.
“Even though placebo-controlled clinical trials are
regarded as the gold standard, they aren’t foolproof.
While the statistical analysis of real world data can be
challenging, there is more value in this kind of mix of
data," argues Hughes.
An example of a drug where real world performance
did not reflect clinical studies can be seen in Merck’s
non-steroidal anti-inflammatory drug (NSAID), Vioxx
(rofecoxib). The drug, designed to provide an alternative
treatment for osteoarthritis, passed successfully through
clinical trials and was approved for marketing in 1999.
However real world use, involving a broader cross section
of patients than those tested in the controlled trial, was
found to increase the risk of cardiovascular disease. Five
years post approval, the product was withdrawn from
the US market [6].
In order to avoid the repeat of cases such as Vioxx,
regulatory authorities are looking at moving towards
an adaptive pathways approach, which would allow
the incorporation of real world data at an earlier stage
of drug development. The European Medicines Agency
is carrying out pilots of this new model. This would
allow conditional approval based on phase II safety and
efficacy data, with full approval after collection of real
world data from observational post-approval studies
[7]. Through incorporating RWD, this would certainly
be an improvement of current regulatory procedures.
Real world data has the advantage over clinical trial
data in that it often represents a broader population,
often over a longer timeframe, and provides information
on comparators and outcomes that are not part of the
clinical trial protocol.
Theneedforbetterrealworlddatacollectionisparticularly
acute in certain disease areas, such as Parkinson’s disease,
where accurately gauging the efficacy of a drug is
dependent on monitoring people’s movements. Current
methodology relies on lab based imaging and tracking,
but this doesn’t necessarily reflect what happens in
an individual’s daily life. Hughes observes, “Drugs for
Parkinson’s disease can seem effective when assessed
using telemetry in the lab, but real time 24/7 data over
a month can produce results that contrast completely
with those seen in the clinic.”
A solution could be improved technology, providing
sensors that monitor in real time in a patients home
would make real world data collection in a realistic
environment much more feasible. An innovator in
this space is ORCATECH, an organization based at the
University of Oregon. ORCATECH uses unobtrusive
sensors to harvest kinetic data in real time. When used
for in-home assessment, the results from this approach
are comparable with lab-based or wearable systems,
with better convenience, along with long-term and
continuous rather than intermittent data [8-10].
Improving clinical trial enrollment
Enrolling patients for clinical trials can be a time-
consuming process, especially where it requires
finding patients with rare diseases or specific disease
subtypes, or recruiting individuals across a large
number of different sites. A system of opt-in tags
on patient EHRs, particularly where records have
been linked together across clinics, could be used to
highlight patients who have the right characteristics,
or who have expressed an interest to be involved in a
clinical trial. When an individual matches the inclusion
and exclusion data for a clinical trial, their physician
receives an alert.
“Companies are realizing that there are now multiple
routes to access data, not just through clinical trials,”
says Hughes. “This could change how clinical research
organizations [CROs] and drug development companies
work, and companies will have to adapt to new business
models.”
Driving and inspiring research
Real world data findings can drive research down
unexpected paths. Julian Gold, a Sydney, Australia-based
physician, realized that he had never come across a case
of someone who was HIV-positive and had multiple
sclerosis. In an extensive literature search of around a

million papers, there was only one case, in an individual
whose multiple sclerosis symptoms reduced when he
took drugs to treat HIV.
In the next step, Gold worked with a team of Danish
researchers who carried out a case-control analysis of
5,000 people with HIV and 5000 controls. This revealed
no cases either. They looked at the NHS’English Hospital
Episode Statistics, which included 21,207 HIV-positive
people and 5,298,496 controls between 1999 and 2011.
The team found that HIV positive people undergoing
treatment were 60% less likely to develop multiple
sclerosis, and 80% less likely if they had been treated for
more than five years [11, 12].
Looking at the observational data that is already
available in EHRs could provide yet more different paths
for treatment and study, particularly as integration and
connections between systems improve. As an example,
results from off label use of drugs in orphan indications
could drive development of new applications for existing
drugs. This would improve access for patients, and create
new markets, extending drug lifecycles.
There are many untapped registries of patients with rare
diseases; the real world information contained has the
potential to reveal considerable learnings on disease
etiology, the efficacy of drugs in different subgroups, as
well as long-term safety and outcomes. By connecting
electronic health records and registries, researchers
would be able to interrogate much larger pools of
patients and data, improving the likelihood of statistical
significance.
Social networking: Collecting data and
providing support
Although social media has historically mainly been used
by the healthcare industry to deliver patient support, and
education, it also has a role to play in collecting real world
data. Beyond making online messaging more interactive,
this data can be used to generate real medical insight,
particularly in disease detection.
Collecting social media data
Data collected from social media platforms such as
Facebook and Twitter, and also from search engines,
has been recently used to power tools to track and
predict disease outbreaks. During a 2012-2013 outbreak
of norovirus (winter vomiting virus), the UK’s Food
Standards Agency (FSA) were able to monitor the use of
certain key words and phrases on Twitter and link spikes
in these with lab reports of confirmed norovirus cases.
Increases in the use of certain symptom keywords
correlated well with later increases in lab reports [13].
Similar projects have also used Twitter to track flu
outbreaks in New York City [14]. Search activity can
yield useful real world data too – Google and Wikipedia
search activity has been used to track flu outbreaks
in the US and around the world, and Google search
activity to monitor dengue fever cases [15, 16]. The
potential value to global health cannot be understated,
monitoring these data sources could enable researchers
to predict outbreaks, which will enable health actors
to develop pre-emptive interventions or ensure that
sufficient resources are in place should outbreaks
spread. The progress of this technology is still limited
by the capabilities of natural language processing,
and may require manual involvement into to qualify
data. However as Stéphane Suisse, social intelligence
officer, Sanofi Pasteur notes, “Digital disease detection,

in parallel with traditional epidemiology, will be an
important reporting tool in the future.”
Using social media for support
Patient social media groups, such as PatientsLikeMe, as
well as platforms like Facebook and Twitter, also allow
patients to share information and support each other. As
patients may tell other people in their peer group details
that they may not wish to say to their doctors, or simply
may not feel that it is relevant, this can provide a source
of real world data for healthcare professionals. These
discussions can also provide drug developers with ideas
of what patients (rather than healthcare professionals
or researchers) are looking for from a therapeutic. This
can be particularly useful when assessing markets that
are not familiar, as Suisse states,“Social media data helps
us to learn and understand how people feel about
vaccinations in different countries.”
Through collecting data, there is an opportunity for
companies to personalize interaction with patients,
for example creating more sophisticated messages for
engaged patients, such as specific goals for those who
exercise regularly, delivered via text messages or alerts.
This degree of tailoring requires detailed understanding
of the patient, which can be gathered using smartphone
apps with simple and short questionnaires. The same
apps could be used to create useful tools for patients,
such as calendars that track vaccinations or medications,
or methods to record and report adverse events. Creating
connections will help companies to better address
expectations and deal with issues.
However, this increasingly connected world can also
cause headaches for pharma, particularly in the case of
clinical trials that are still ongoing. “Patients will discuss
their treatments and how they feel, and consequently
may be able to work out who is taking the active drug
or the placebo. This could have an impact on outcomes,"
says Hughes.
The key takeaway is the importance of understanding
where social media can be a valuable tool, and where
it may be a hindrance. Pharmaceutical companies can
use social media as a route for education and support
for patients, create opportunities for two-way discussion,
and build brand awareness and loyalty. However, as
patients become more educated and knowledgeable,
it’s important that social media contact provides patient-
centric, useful and relevant content and remains focused
on support without straying into aggressive sales and
marketing. This will help to build and maintain trust.

Many of the advancements in capabilities for mobile
healthcare have been driven by falling costs and by
improvementsinmobileaccessinboththedevelopedand
thedevelopingworld.Coverageisat100%ormoreinmany
developed countries including Australia, Germany, Japan,
South Korea, Sweden, UK and USA, as well as developing
countries such as Algeria, Botswana, Brazil, Chile, Indonesia
and Malaysia [17]. Coupled with increased access to high-
speed mobile broadband (see Figure 1) across all regions,
there are now wide-spread networks capable of delivering
powerful remote healthcare services. The opportunity
is particularly huge in Sub-Saharan Africa - where rural
regions have been challenged by the lack of infrastructure
to deliver quality health services. There are immediate
gains to be had from linking patients with previously
disconnected healthcare resources. Imbalances whereby
talented and experienced doctors are concentrated
in urbanized areas, can now be more easily addressed
through the provision of treatment information, diagnosis
and follow-ups managed by remote experts.
Effectiveness with scale
The technology and rationale behind many of these
applications, or purpose built devices, isn’t necessary
innovative, the groundbreaking aspect is the scale at which
these are being adopted. It is this higher adoption rate that
unlocks the potential of the technology to change how
Smartphone penetration:
The power of numbers
we approach healthcare, something that has only recently
been made possible with smartphone penetration and
widespread high-speed networks.
Many monitoring devices involve predictive capabilities
that allow healthcare professionals, or software, to remotely
interpret data and intervene to improve outcomes; however,
in order to be effective across a diverse patient population
these devices depend on representative data collection that
only comes with scale. “The greater adoption of wearables
means the generation of greater volumes of more varied
data, providing more complete and real time information on
patients that can improve outcomes but also may represent
potential analytic challenges that require machine learning
methods and cloud computing.
Figure 1: High-speed mobile broadband subscribers (millions)
1300
1200
1100
100
900
800
700
600
500
400
300
200
100
0
USA & Canada Latin America AfricaWestern Europe Middle EastEastern Europe Asia pacific
17
177
295
2
52
261
46
203
383
2
67
213
1
34
206
2
46
124
75
1213
Source: GMSA & PricewaterhouseCoopers [17]
325
n 2008
n 2010
n 2014E
“Collectingandsharingdataisn’t
anythingnew,it’sjustbeengivennew
terminology.Technologieslikecloud
storageandmobilebroadbandare
becomingmorecommonlyusedand
widelyaccepted,bothinhealthcare
andinthegeneralpopulation.The
momentumisincreasing.”
Andreas Caduff, CEO, Biovotion AG.

Pharma and mHealth
Introduction
The pharmaceutical industry has yet to harness the
enormous potential of mHealth. There are just under 250
apps created by pharmaceutical companies available
on iOS and Android today, ranging from chronic disease
management to medical reference tools.3
In a highly
fragmented market, only Sanofi Aventis has managed
to clock serious download figures (more than 1 million),
which compared to leading developers outside of
pharma is still relatively small. mHealth is still in relative
infancy however, with recent research finding that half
of health app publishers have only released one or two
products.4
One way for pharma to catch up is to pay attention to
what market leaders are doing. This means observing
the app categories that are gaining most traction with
consumers and placing patient benefits rather than
brand awareness at the center of initiatives. Industry
experts have also called for pharma to integrate
apps with their products and services, to provide an
improved overall service to patients and healthcare
providers. These benefits should be included in
reimbursement mechanisms, reflective of the ultimate
objective to create real value. Finally, app best practices
such as interoperability, gamification elements and
seamless user experience, are all essential to success
in this increasingly competitive field.
Scale of the opportunity
Advocatesclaimthatmobiletechnologycanhelpengage
patients, improve compliance, support preventative
care models and lower healthcare costs by reducing
avoidable hospital admissions. Tackling such issues will
require ambitious thinking. For example, Qualcomm’s
XPRIZE is this year awarding US$10m of development
capital to the winning team of a competition to develop a
consumer-friendly, mobile device capable of diagnosing
and interpreting a set of 15 conditions and capturing
vital health metrics.
By 2017, according to Research and Markets, half of the
3.4 billion smartphone or tablet users worldwide will use
mobile health apps .Research2guidance found that the
mobile health app market will reach US$26bn by 2017,
six times greater than the 2014 value (US$4bn).
Source: research2guidance mHealth App Developer Economics survey 2010, 2011, 2012 and 2014, n=2032, CHD refers to coronary heart disease
mHealth app category business potential in next 5 years
3
mHealth App Developer Economics 2014, research2guidance
4

Fitness (30,9%), medical references (16,6%) and wellness
(15,5%) are the main mHealth categories in the sector,
according to research2guidance. On the other hand,
chronically ill (31%) and fitness seekers (28%) are the
main target groups for mHealth apps publishers. At
present, just 14% of the apps target physicians, 12%
other (not specified), 8% temporarily ill people and 7%
aim at hospitals. Diabetes and Obesity are the top ranked
therapeutic areas for mHealth publishers. Furthermore,
Hypertension, Depression, Coronary Heart Disease (CHD)
and Cancer have a significant potential in the next five
years. Physicians and hospitals are seen as the primary
distribution channel for mHealth apps in the future,
followed by app stores, pharmacies and healthcare
webpages.
Lux Research anticipates that the mobile health
devices market is expected to grow eight fold to
US$41.8bn in 2023.5
While consumer devices are
leading at present, it’s anticipated that from 2018
clinical devices will surpass them. The growth will be
driven by vital signs monitoring and in vitro diagnostic
(IVD) devices. Clinical vital signs monitoring devices
will grow from US$372m in 2013 to US$16bn in 2023.
This will be supported by value-added services and
larger revenue streams.

Overcoming the challenges
There are myriad barriers to development of the
mHealth sector. Chief among them are concerns about
data security. With users submitting sensitive medical
information, many are concerned that more needs to be
done to reassure stakeholders that data privacy will be
fully respected.
30,000
25,000
20,000
15,000
10,000
5,000
0
2013 2014 2015 2016 2017
Global mHealth market revenue in US$ (2013-2017)
Business potential of different therapeutic areas for mHealth apps by rank in 5 years
Source: research2guidance, mHealth App Market Report 2013-2017
Source: research2guidance mHealth App Developer Economics survey 2010, 2011, 2012 and 2014, n=2032, CHD refers to coronary heart disease
n Services n Device Sales n Paid downloads
nTransactions n Advertisement
69%
21%
5%
4%
1%
Rank 2010-2015 2011-2016 2012-2017 2014-2019
1 Diabetes 78% Diabetes 80% Diabetes 76% Diabetes 69%
2 Obesity 57% Obesity 45% Obesity 56% Obesity 39%
3 Hypertension 55% Hypertension 40% Depression 42% Hypertension 29%
4 CHD 50% CHD 39% Hypertension 41% Depression 22%
5 Asthma 40% Depression 25% CHD 40% Cancer 19%
5
mHealth Showdown: Consumer and Clinical Devices’ Battle for Market Dominance, Lux
Research 2014

Another key concern is the need for standardization
across all platforms and products, enabling integration
into healthcare provision. The leading app publishers
ensure that their platforms are seamlessly interoperable
with those from other industry players; this paves the
way to drive wider adoption of mHealth as a whole.
Collaboration is the watchword here, and pharma
should be seeking to work with healthcare providers,
app publishers and crucially each other, in order to win
in the long term.
Convincing healthcare professionals is another key
obstacle on the horizon. If clinical applications are to
overtake patient-targeted applications over the next
decade, then a lot of convincing is yet to be done.
The encouraging factor here is that clinicians are all
users of mobile devices, and will most likely eventually
accept ideas that either save them time or make
them better at their jobs. Innovators such as the team
behind drawMD, profiled in this paper, are among
the best placed to advise on cracking the physician
demographic.
These concerns, particularly over data privacy, will be
addressed with time. Looking back at smartphone
adoption, in 2009 only 13% of all handsets shipped
in the first quarter were smartphones. The app market
is developing fifteen times faster than the growth rate
of stationary internet users.6
This widespread and fast-
growinginterestinappsmeansthatit’snotunforeseeable
for apps to be prescribed or recommended by physicians
for treatment in the near future.
As this crest is reached, it’s important for pharma to look
beyond the idea of apps as marketing tools, and view
them as serious clinical opportunities. This will require a
mindset shift among healthcare providers too, who will
need to recognize that while apps do have real potential
to deliver much-needed savings, reducing hospital
admissions and boosting adherence, to provide genuine
support they will also need to be fully integrated into the
reimbursement or payment process.
6
Although some mHealth solutions cross several
categories of use, most solutions can be defined
as falling into one of four categories, wellness,
prevention, diagnosis, as well as treatment
management and monitoring. With the benefits
that improved adherence could bring to healthcare
systems, both in terms of reducing costs, as well
as improving outcomes, apps within treatment
management and monitoring are viewed as having
particular potential. And Gartner estimates that
wearables alone will drive 50% of all app interactions
by 2017.
With employee health insurance costs for individuals
with diabetes as much as $6000 more than those
for people without the disease, and as a condition
whereby maintaining consistent patient engagement
with treatment is particularly tricky, much mHealth
innovation has taken place around support. Many of
these solutions incorporate simple cellular-enabled
glucose meters, which can track glucose readings and
deliver automated support based on the readings,
however a common challenge has been maintaining
patient engagement beyond the short-term.
A company which has made interesting progress
here is US-based Telcare, which has supplemented a
glucose monitor with technology that allows carers,
or physicians to remotely monitor compliance and
intervene if necessary, tackling the issue of relying
just on patient engagement.This is also a particularly
supportive development for those who are caring
for children with diabetes, or elderly relatives.
Trials of this approach, whereby a monitoring device
is combined with a support system that allows
others to intervene, have been cost-effective.Telcare
studies have shown that individuals who were given
an mHealth glucose meter along with support from
a disease management centre that was responsive
to real-time biometric analysis, experienced positive
outcomes. Of the 50% of patients that participated
actively, claims were reduced year-over-year by
$3,384 [19, 20].
Case Study: improved diabetes care through mHealth support

Wellness
The Wellness area includes self-help apps and devices
that promote positive behaviours, such as exercise or
healthy eating, and help people to give up less healthy
behaviours, such as smoking. Examples include phone-
based apps such as MyFitnessPal, which tracks eating
and promotes weight loss, iQuit, which help people to
reduce or cease cigarette smoking, and MapMyRun,
which monitors activity levels [12].
Prevention
Mobile health solutions for prevention are designed
to increase awareness of disease, and help to control
disease outbreaks, as well as encourage healthy
living. These typically target infectious diseases such
as HIV, as well as reproductive, maternal and child
health. Examples include the Wired Mothers program
in Tanzania, which provides text reminders, and
creates connections between expectant women and
healthcare providers, or the Text4Baby service in the
US, which targets low-income families and provides
health information for mothers and children [12].
Diagnosis
Diagnostic solutions allow healthcare professionals
to remotely respond to patient data and recommend
treatment. In addition to benefits of directly
connecting patients in remote areas, this has high
value in delivering support to remote, less experienced
healthcare professionals who require advice from
centrally located colleagues; a common issue in rural
areas of developing countries [12].
Treatment, management and monitoring
Mobile health solutions can help healthcare
professionals, carers and patients manage the
treatment of long-term and chronic illnesses,
improving outcomes and reducing exacerbations. This
can reduce relapse and the development of resistance
in infectious diseases such as tuberculosis and HIV/
AIDS. Examples include systems such as eMedOnline,
a mobile app available in the US that reminds patients
to take their medications [12, 16].
mHealth services: an overview

The challenges of data collection
and design of wearables
Wearables are often divided into two types – high-
tech medical-grade monitoring devices that track
physiological measures such as heart function, oxygen
levels or blood glucose levels and are worn long term,
and simpler and lower cost consumer devices that may
onlybewornforshortperiodsoftime,forexampleduring
a run or at the gym.These technologies typically monitor
the wellness of the user, and will track key variables such
as activity, sleep or heart rate, supplemented with user
supplied information, such as current diet, in order to
assess wellbeing.
“The burden or ‘cost’ of wearing or using a device must
not exceed the‘value’of the outcomes, for either patients
or caregivers. This brings in comfort and ease of use, and
balances it with the outputs of the device. Wearable
device design must focus on simplicity, appearance and
comfort in order to encourage habitual use. For devices
that require consistent data over a long duration in order
to be effective, such as devices that monitor chronic
disease in a clinical setting, this consideration seems
obviously important, however, medical-grade devices
have to date slipped behind consumer products in
delivering this experience. While consumer devices have
viewedthesequalitiesasintegraltocreatingamarketable
product, medical devices have traditionally been
designed through a scientific lens that hasn’t necessarily
recognized the value of the user experience. Caduff, CEO
of Biovotion, describes this very issue within current
heart rate monitoring technology, “To continuously
measure parameters such as heart rate, the device needs
to be attached tightly to the skin, otherwise the data
can be of poor quality. Depending on the body location
such attachment becomes uncomfortable, which is an
issue for offerings where the device needs to be worn for
longer periods.”This approach has failed to acknowledge
that users evaluate devices by balancing the burden or
‘cost’of its use against the value of wearing it.
Calculating this balance is not straightforward, with an
additional complexity that wearables and sensors must
produce results that are actionable for the ‘customer’,
whether this is a display for a patient, diagnosis for a
doctor or nurse, or outcomes or clinical trial data for a
contract research organization, healthcare provider or
pharmaceutical company or organizations. User interface
design is evolving to recognize that different categories
of users have different needs. Consumer users self-
monitoringwellnessindicators,suchasbloodcholesterol,
may only require a simple high/low display that shows
change over time. In a clinical setting however, greater
detail would be necessary. The challenge is to deliver
devices that meet the core needs of the user. Someone
who runs as daily exercise or to lose weight may simply
need a red or green indicator to keep their heart rate in
the right zone, whereas an elite athlete and his or her
trainer may want specific heart rate data.
However, this traditional divide whereby consumer
devices are small, slick but simple, and medical devices
are complex, capable but clunky, is going away. Two
categorieswilltakeonsomeofeachother’scharacteristics:
Medical-grade and consumer devices will move together
eventually, combining the appealing design, comfort
and ease of use of the consumer products, with the
sophistication, range of measurements and accuracy of
the medical devices.

The discussion so far has sought to highlight the
opportunities that further integration of RWD, wearables
and mHealth can deliver to patient services; however
this is not to say that there are not significant challenges
ahead, particularly in the case of data collection and
use. The discussed solutions depend on secure access
to standardized, quality data. Developing systems to
guarantee this, while respecting patient privacy and
remaining compliant is not an easy task. .
The security and regulation of data
A challenge for systems that work with personal
healthcaredataistoremainhighlysensitivetotheprivacy
and security concerns of the participants. Patients may
not want to disclose personal information to employers,
insurers, or even friends and family. In addition, if data is
not protected, it could be appropriated for identity theft.
As a result, the area is highly managed by regulators, and
those seeking to deliver services powered by personal
data must become agile in order to stay compliant. A
balance must of course be struck between regulation
and innovation, and following concerns that the
proposal could stifle research, the Healthcare Coalition
on Data Protection has urged lawmakers to protect and
reinstate research-friendly provisions, such as ensuring
that it remains possible to share anonymized health
data for research purposes within a properly-regulated
framework [22]. While the U.S. have been slow to adapt
medical device regulation - it was last amended in 1976
- guidance issued in September 2013 for mobile medical
Looking to the future
applications suggest that regulators might take a more
active interest. This is a needed progression say many, as
ill defined regulation can dampen innovation as much as
strict regulation; developers must know the boundaries
so that they can manage the risks.
Getting the data right
Once regulatory hurdles have been navigated,
securing quality data isn’t straightforward either. While
smartphone penetration is widespread, the adoption
of mHealth has been comparatively slow. Only 10% of
the US population have used mHealth support in some
form, and only around 10% of smartphone users have
actually downloaded a healthcare app [24]. The issue is
that individuals who are more inclined to take advantage
of mHealth services are those who are already engaged
in self-management, and comfortable with technology.
Since improvements in outcomes accrue to patients
who are most engaged in their care, this carries the risk
of creating skewed data sets not be representative of
the wider population. The challenge for the healthcare
industry will be to improve the attractiveness of digital
support, as well as to work with physicians who are able
to engage patients with these technologies at the point
of care, and encourage those who would not usually
"Trust will always be an issue –
people will want to know what you
are going to do with their data,
and it will be a case of building
a relationship and being open,
honest and transparent."
Nigel Hughes, Global Director, Marketing & Health
Information Technology, Janssen Diagnostics

„„ 'Smart' textiles that monitor blood glucose,
pulse, breathing and heart rate, which can
help with disease management or improve
training
„„ Contact lenses that track retinal changes
or blood glucose levels, improving the
management of type I and type II diabetes,
and enabling earlier intervention
„„ 'Smart' toilets and 'smart' fridges that analyze
nutrition, vitamin intake and hydration,
providing feedback on diet and nutrition
„„ Wearable sensors or sensors in smartphones
that continuously check stress and anxiety
levels, allowing the individual to learn to
recognize the signs and take steps to relieve
or avoid the stress, or alerting the healthcare
professional to provide treatment and
support
„„ Handheld breath analyzers ('digital noses')
that replicate the ability seen in some dogs,
to be able to detect disease biomarkers in
cancer, infections and other disorders
„„ Functional fibers used to create dressings that
not only protect wounds but also detect and
identify pathogens, allowing more targeted
antibiotic treatment
„„ Pressure sensitive bed coverings based on
resistive technology that could detect and
warn when a patient might be developing
pressure sores
„„ Devices that can detect a variety of different
measures, such as stress, sleep, blood pressure
and blood glucose, and provide immediate
feedback
Summary of pipeline
wearable and mHealth
innovation:11, 31, 33
adopt the technology to consider support.
There is a question as to where the limits of this approach
lie; it is likely a social reality that some of us will always
be more engaged than others in managing our health.
With this in mind the question becomes, how does the
industry deliver the benefits of this form of support to
those they cannot engage? “We are working to lower
the barriers for collecting data, using sensors to gather
data without patient input where possible," explains
Andy Jones of AstraZeneca. "This would create more
representative data with less bias. We have a Bluetooth-
enabled inhaler that sends a message to a mobile phone
when it is used, and blister packs that signal when an
individual blister is broken.”
Conclusions
There is no denying that the growth of mHealth and RWD
is driving a huge amount of innovation, however, it is still
difficulttosaywhichdirectionthiswillgo.Assmartphones
becomeevermoresophisticatedanditsroleinhealthcare
increases, many are of the opinion that they will take
over from many existing purpose-built wearables and
monitors. Built-in cameras in smartphones could double
as handheld otoscopes and colposcopes, or as tools for
eye and oral cavity examinations [25]. We think that the
most interesting developments will come through the
progression and integration of different technologies.
With increased connectivity, smartphones could be used
to analyze and direct other smart wearables; for example,
fitness trackers are being developed that can record your
run speed, give you prompts on posture and also adjust
the temperature of your shoes [26, 27].
The key lesson from the Telcare Diabetes case study was
that greater interconnectivity is the route to improving
outcomes through keeping patients more engaged. For
those in pharma therefore, creating networked systems
will be of particular interest; the value of adherence
solutions is well understood, both as a value-ad and as a
complement to marketed products, however initiatives
so far have failed to live up to promise. If better results
can be achieved through using networked systems that
involve a combination of mHealth powered devices,
remote physician support or better informed carers, then
this is where we may see the most activity.
As well as powering solutions, RWD will also be effective
in helping pharma better understand the adherence

needs. Analysis of real world data could help to provide
greater insights into the 'patient journey, for example
helping to understand primary non-adherence, where
patients don't fill their prescriptions, and the reasons why
and associated impact of clinical outcomes, activities of
daily living and costs.
This space could see interesting developments
beyond adherence too. Personalized medicine will
need application of monitoring technology, including
wearables and sensors, along with other technologies
such as genetic fingerprinting.” In spite of this there is a
myriad of opportunities, creating systems that can stay
relevant to the needs of many different users will be a
challenge. Keeping key design principles in mind will
be important, such as ensuring actionable insights and
prioritizing intuitive use.
With the benefits of progression in mHealth devices,
from improved efficacy through personalized care,
better adherence, or cost-effective delivery of remote
care, many different stakeholders stand to gain from
advances here. However, following our discussion,
success in improving the delivery of patient services with
technology will ultimately depend on better integration
between different points of interaction with the patient,
Stakeholders will have to each take on a role so that
they can all realise the benefits. Stakeholders, including
payers, pharma, patients, physicians and carers all stand
to gain, but communicating the value proposition to
each and building partnerships will not be easy. In
order for the advances in the technology to be realized,
much groundwork will have to be done at a personal,
engagement level, through more collaborative and open
partnerships.
1 Comfort: Long-term monitoring devices must use designs that fit with the everyday
activities of the user or can be embedded in objects that are already habitually used.
2 Value to the user: Create actionable results for the ‘customer’ is critical, whether a display
for a patient, a diagnosis for healthcare professionals or outcomes for clinical researchers.
3 Easeofuse: Interfaces should be intuitive for patients, healthcare professionals AND caregivers.
Key takeaways for Device Design

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