1. DISCLAIMER: The views and opinions expressed in this presentation are those of the author and do not necessarily represent official policy or position of HIMSS.
The Convergence of mHealth:
A Consumer and Clinical
Perspective
April 12, 2015
Ahmed Albaiti CEO, Medullan

2. Conflict of Interest
Ahmed Albaiti, CEO, Medullan Inc.
Has no real or apparent conflicts of interest to report.
© HIMSS 2015

3. Learning Objectives
• Assess the current landscape of mHealth
• Illustrate the roles of consumers and patients
• Define the current issues

4. What is mHealth?
“I am
Baymax,
your personal
healthcare
companion”

5. The “formal” definition…
“Medical and Public Health practice supported by mobile devices,
such as mobile phones, patient monitoring devices, personal digital
assistants (PDAs), and other wireless devices.
mHealth involves the use of voice and short messaging service
(SMS) as well as more complex functionalities such as 3G systems,
global positioning systems (GPS), and Bluetooth technology”
Source: The Global Observatory for eHealth within the World Health Organization (WHO)

6. mHealth breaks down into…
Mobile
Health Apps
Wearables Connected
Devices

7. Mobile Health Apps - Functionality
46,389
Healthcare & Fitness or Medical
23,682
“Genuine” Healthcare & Medical
Multi-FunctionalityIndividual Functionality
Source: IMS Institute Patient Apps for Improved Healthcare October 2013

8. Mobile Health Apps – Therapy Areas
8.786
Prevention / Healthy Living
304
Symptomatic / Self-Diagnosis
931
Finding a Physician
562
Education Post-Diagnosis
200
Filling Prescription
225
Compliance
Source: IMS Institute Patient Apps for Improved Healthcare October 2013

9. Mobile Health Apps – Audiences
8.786
Prevention / Healthy Living
304
Symptomatic / Self-Diagnosis
931
Finding a Physician
562
Education Post-Diagnosis
200
Filling Prescription
225
Compliance
Source: IMS Institute Patient Apps for Improved Healthcare October 2013
37:06
35:40
33:57
25:26
21:21
Source: Nielsen, Statista Q42013

10. Mobile Health Apps - Hurdles
• Dizzying choice of apps without an easy way to navigate
• Demographic skew of smartphone users: patient populations most in need
aren’t serviced
• Lower potential ROI
• FDA approval process lengthens gestation period of app launch
> e.g. WellDoc and AgaMatrix
• Physicians wary of prescribing apps
• Lack of efficacy data to filter apps
• Lack of infrastructure to prescribe
• Patient Privacy concerns
• Legal and reimbursement incentives

11. Mobile Health Apps – managing the explosion
Managed app stores
e.g. VA App Store, NHS
App Library
Most tightly managed,
least “open” and
slowest to grow
Commercial app
“catalog” products
e.g. HealthTap, Happtique
Self-certification
process with self-
reported test results
Most growth
potential, least
trusted presently
Darkest horse,
most potential

12. Wearables – devices to ingestibles
Source: The Future of Biosensing Wearables, by RockHealth
The world's first wireless wearable heart
rate monitor, the Polar Sport Tester PE 2000,
was launched in 1982!

13. Wearables – engagement curve
Source: The Future of Biosensing Wearables, by RockHealth

14. Wearables - Hurdles
• Confusion of choices with no easy way to navigate
• Utility over time: here today, gone tomorrow
• Few wearables have the functionality and the reliability expected by the
healthcare business and clinical communities
• Even fewer have the convenience and smart feedback loops (software,
clinician engagement) to impact behavior change and outcomes

15. Connected devices – applications for all
settings
At the Hospital
e.g. Capsule Tech
In the Home
e.g. CliniColud
On the Go
e.g. AliveCor

16. Connected devices – more momentum?
• More clinical (vs. lifestyle) focus
• Biosensor cost structure dropping precipitously
• More clinically mature incumbents and start ups - lots of experience with
existing, non-connected devices is transferring
• Already targeting all contexts : in the hospital, in the home and on the go

17. We are going from
mHealth to Health IoT
“I have
some
concerns”

18. What can we expect from Health IoT?
From:
App computing Cloud computing
Biosensors Smart, connected devices
Predictive analytics Prescriptive analytics

19. IoT : explosive growth expected
Source: Harvard Business Review, Digital Ubiquity

20. Health IoT : Prescriptive analytics
“in context” prediction that
includes evidence, and
interpretation and
recommended actions for
each predicted outcome
linked to clinical priorities and
measurable events, such as
cost effectiveness, clinical
protocols, or patient outcomes

21. Health IoT : still a lot of hype…
Source: Gartner

22. What about the patients?
“Does Karate
make me a
better
healthcare
companion?”

23. What are patients’ needs and wants?
Sources: McKinsey Digital Patient Survey,
Manhattan Research, ComScore, MaKovsky Health
86%of the general
population is
online for health
information
75%of patients would
like to use digital
healthcare
services
20%of all patients
state that mobile
is essential for
managing their
care
39%
of MS patients
state that mobile
is essential for
managing their
care
32%
of diabetes patients
state that mobile is
essential for
managing their
care

24. What’s most important to patients?
Core features patients expect from their health system are
surprisingly mundane: efficiency, better access to information,
integration with other channels, and the availability of a real
person if the digital service doesn’t give them what they need”
Sources: McKinsey Digital Patient Survey, Manhattan
Research, ComScore, MaKovsky Health

25. Mobile versus the demographics
Sources: McKinsey Digital Patient Survey, Manhattan
Research, ComScore, MaKovsky Health
70%
of patients (50
years or older)
want to use
digital healthcare
services
2xmore millenials (vs.
those 66 years or
older) are likely to
use a mobile app
to manage their
health
51%
of baby boomers
have never
downloaded an
app

26. Mobile vs wearables adoption
Wearable awareness is
high, adoption is low
If Pebble smartwatch,
a relatively unknown
brand funded on
Kickstarter, already
holds the #2 ownership
spot after FitBit …
Sources: Manhattan Research, ComScore,
MaKovsky Health
72%
of consumers own
a smartphone
79%
are willing to
use a wearable
…imagin
e what
the
Apple
Watch
will do?

27. Smartphones are no threat to wearables
Smartphones won’t cannibalize wearables. It’s
simple – they are too big. Average screen size
has gone from 2.59” to 4.86” in the last 7 years
Sources: Manhattan Research,
ComScore, MaKovsky Health
23%
don’t see the
benefit
48%
not interested
54%
too expensive
The real barriers to wearable adoption are utility,
price, and convenience

28. What about the clinicians?
“I will add
fist bump
to my
caregiving
matrix”

29. What will get traction with clinicians?
Sources: Chilmark Research, Manhattan
Research, HIMSS Analytics
• Communication
capabilities
• Voice, video, text, and
e-mail
• Informational resources
• Guidelines, Literature,
References
• Hospital information
systems
• EHRs, EMRs, CDSSs,
and PACSs, LIMs
• Clinical software
applications
• Disease Diagnosis
Aids, Medical
Calculators

30. Anecdotal evidence reveals gaps
Source: Medullan Research
63%
don’t use apps as
part of their work
35%
use their own personal
mobile device
60%
don’t have or not aware
of mobile EH/MR

31. Consumers vs. vendors are driving adoption
Sources: Medullan Research, Chilmark Research
HCOs are still doing the bare minimum
when it comes to digital interactions
with patients.
Most [vendor] deployed patient portals
today have limited or no mobile-
friendly patient tools (beyond mobile-
optimized browsers) or advanced care
planning applications.
75%
find the data that
wearables
provide to be
useful
9%
have patients that
bring wearables
with them to
consults

32. What are the Health IoT
headwinds?
“I am not fast”

33. Health IoT : headwinds for adoption
• Ownership, privacy and portability of patient data
• Serious ramifications described by the New Deal on data
• Lack of certification and measurement of outcomes for
heath mobile apps in any consistent manner
• Clinician cost and incentives/reimbursement for use of
apps, connected devices, or wearables
• Supplier middling on delivering clinical software that
drives patient engagement

34. Fast forward : can Health
IoT change the future of
Health Care?
“Flying makes
me a better
healthcare
companion!”

35. Other industry disruptors have emerged
By focusing
relentlessly on
customer satisfaction,
not margins, Amazon
is turning retail into a
subscription-like
relationship…
By connecting riders with
transport (and other
riders), Uber redefines
what personal transport
should cost – everyday,
every hour, everywhere
(soon)...
By connecting
consumers, home
devices, and energy
companies – Nest is
driving a focus on
energy usage
outcomes…
We don’t just need the Internet of Things.
We need the Internet of the Right Things!”
- John Driscoll, CEO, CareCentrix
‘‘

36. Where will Health IoT disruption emerge?
Knowing who
patients really
are…
Knowing when +
where your
patients are…
Knowing what
really matters…
Prescriptive Analytics:
Interventions,
Decision Support,
Mobility: Phones,
Tablets, Watches,
TVs, etc etc.
Data: Connected
Devices, ODLs,
Genomics
Empowered
patient self-
management
Informed
shared-
decision
moments

37. Questions?
Let’s continue the conversation!
ahmed@medullan.com