A R O C K R E P O R T B Y
BIG DATA
IN DIGITAL HEALTH

About
this
REPORT
We wanted to know more about the status and potential of big data and health.
This report sources data and feedback from interviews conducted with
entrepreneurs and investors working in the space as well as industry research.
Thanks to100 Plus, Appistry, Asthmapolis, Athena, Dell, DNAnexus, Explorys,
Factual, Genome Health Solutions, Ginger.io, GNS Healthcare, Health Fidelity,
Humedica, Humetrix, IBM, IHME, Microsoft, NextBio, One Health, Practice Fusion,
Predixion, Qualcomm Life, Sickweather, Sproxil, The Broad, WellDoc, X-Prize, Zeo,
who all contributed their minds and thoughts to this report.
Produced by
Dr. Bonnie FeldmanLeslie Ziegler
@lesliejz @drbonnie360
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2005 2008 2010 2012 2015 2020
40 TIMESas fast as the world population
The amount of data is growing
130EB 422EB 1227EB
2720EB
7910EB
35000EB
EB = exabytes

So, what is big data?
Stephen Gold,
VP of World Wide Marketing
at IBM Watson
Big Data is the fuel–it is like
oil, if you have it in the
ground it doesn’t have
much value. As soon as you
extract the oil from the
ground and start to refine
it, it amplifies not only its
usefulness but its value.
“
”
Tom Lawry,
Director, World Wide
Marketing at Microsoft
When we talk about areas of
large and growing volume
(petabytes), variety (structured vs
unstructured) and high-velocity
data; when those things are
present in some combination, we
consider that big data.
“
”

2012 2015 2017
The big data market will hit
$50B in five years
Source: Wikibon
$5.1B
$32.1B
$53.4B

Big data could save healthcare
$300B+ per year
$25-50B
Poorly coordinated
care
$175-250B
Administrative & clinical
inefficiency
$125-175B
Fraud & abuse
Source: IBM IT-enabled personalized healthcare

OF BIG DATA
The four Vs
Volume
(amount)
Variety
(type &
sources)
Velocity
(speed)
Veracity
(quality &
trust)

New streams are producing even more data.
By 2015, there will be
1Bsmartphones
400Mtablets
1Bpersonal computers
Volume

Variety
“
”
Dan Riskin,
CEO at Health Fidelity
We spend time thinking of
structured data, data that
goes into databases and can
be nicely put into rows and
columns, but all of a sudden
we find ourselves with the
majority of information being
unstructured, not just in text
but in other forms.
“
”
Stephen Gold,
VP of Worldwide Marketing
at IBM Watson
Structured vs. Unstructured
The fact is that healthcare is
like any other industry where
80% of the content is
unstructured and the
remaining is structured to
use by machine processes.

Health care,
from
a technology
perspective, is
at least a
decade behind
the rest of the
world.
“
”
Jeremy Delinsky,
CTO at Athena Health
Healthcare is primed for big data
Better analytic tools
New data streams
More rapid IT development
Healthcare cost/quality problems
Need for big data

EXISTING DATA NEW DATA
Claims
Clinical trials
Genomics
EMR
Sensors
Mobile phones
Web
EHR
And these new data streams are
creating new opportunities
Correct diagnosis the first time
Match treatment to patient
Decrease costs over time
Identify problems
Reduce readmissions
Forestall hospital acquired infections
Personalized medicine Preventative medicine

ProvidersPayers
Medical Device Companies Governments
Pharmaceutical Companies Software
Patients
So, who cares?
Seamless flow of tech into medical care
Error-free, compassionate care
Real time access to data
Tech as tool, not encumbrance
Enable real-time data monitoring
Integrate personal data with medical
Reduce costs
Maximize social value of data
Stratify population risk
Guide them to new business models
Reduce product failures
Access data points
Exploit growing markets

6 ways big data could
change healthcare
1. Support research: genomics and beyond
2. Transform data to information
3. Support self care
4. Support providers
5. Increase awareness
6. Pool data to build an ecosystem

Genomics & beyond
Offers a cloud-based, community-inspired collaborative
and scalable data technology platform that provides next
generation sequencing (NGS) data management, analysis
and visualization.
Adapts learning from FedEx and the Department of
Defense to streamline the storage, management,
analysis and interpretation of big data in genomics.
Combines large public datasets with private datasets
to enable new and unique discoveries not possible
otherwise.
Builds mathematical cause-and-effect models to
determine drivers of outcomes.

Transform data to information
A cloud based EMR and analytics company that focuses
on standardizing health record systems across providers.
Uses cloud-based predictive analytics software to
explain patterns in hospital datasets to reduce
readmissions,
and prevent hospital-acquired conditions.
Uses natural language processing to turn
unstructured
data into structured data to address needs in revenue
cycle management, compliance and analytics.
A free cloud based EMR platform for medical
practices that also aggregates population data
across multiple sites to improve clinical research
and public health analysis.

Support self care
Uses public and private data to motivate consumers to take
small healthy steps to change daily habits via a mobile
application.
Combines social and clinical data streams with
flexible
APIs to create the first real-time behavioral health
records.
Using automated real-time coaching that integrates
behavioral and clinical data to help patients manage
chronic diseases such as diabetes.
Analyzing over a million nights of data to help
consumers improve their sleep.

Support providers
Built a cloud-based computing platform that
aggregates large amounts of data from many
disparate sources–financial, operational, and clinical
data from multiple partners.
Watson is the first of a new class of analytical platforms and
decision support systems that use deep content analysis,
evidence-based reasoning and natural language processing
to support faster and more precise diagnostics and clinical
decision making.
A clinical informatics company that provides SaaS
business intelligence using clinical and patient
information across varied settings and time periods
to generate longitudinal and comprehensive views
of patient care.

Increase awareness
Collects data from patients and provides them with
feedback which helps them better manage their
asthma.
Scans social media to track outbreaks of disease,
offering forecasts to users, similar to weather
forecasting.
Uses big data to identify counterfeit drugs, to protect patient health
and enable pharmaceutical companies to track drug distribution and
prevent theft.
Gathering a variety of big global data sets for data
mining that can guide policy decisions to improve
population health.

Pool data to create an ecosystem
Enabling a global wireless health connectivity platform (2net) and
open ecosystem that brings healthcare data–new and existing
biometric data sources–together in ways that have never been done
before.
Wants to democratize access to healthcare data.
Interdisciplinary science community tackling big
medical questions to benefit humanity.

54%
50%
44%
43% 43%
25%
21%
Cultural
adoption
Aligning
clinical &
tech terms
Info
overload
Data kept
in silos
Inadequate
funding
Lack of
governance Not willing
to share
data
Challenges:
Technology integration
Source: PWC Health Research Institute Clinical Informatics Survey, 2011

Trends

Using natural language
processing to turn
unstructured data into
structured data
What:
Doctors, providers,
billing groups,
analytics companies
Who:
Working with limited
data sets
Trend
Dan Riskin,
CEO at Health Fidelity
My two year goal is to
convince the world that
unstructured data and natural
processes should be the
underlying technology in
healthcare.
“
”

Trend
Uses predictive analytics to
explain patterns in the data
and minimize hospital
readmissions.
What:
Providers & patientsWho:
Mixing limited data sets
Trend
Jamie MacLennan,
Cofounder & CEO
Predictive analytics allow
you to aggregate the data
to see what patterns are
realistically making a
difference in the decisions
you make.
“
”

Trend
A big data platform to
aggregate, analyze, manage
and research data from
various sources for better
patient care at a lower price
What:
Providers (healthcare
facilities), researchers
(clinical and nonclinical)
Who:
Combining a greater
variety of data
Combining social and
clinical data streams with
flexible APIs to create the
world’s first real-time
behavioral health record
What:
Providers (healthcare facilities),
health plans, employers,
3rd party vendors
Who:
One Health

Trend
Pooling data for bigger &
better results
Trend
Enabling a global wireless health
and connectivity platform (2net)
and open ecosystem that brings
healthcare data–new and existing
biometric data sources–together
in ways never done before.
What:
Software, analysis and device
companies and healthcare providers
Who:
Democratizing access to
healthcare data
What:
Large companies who fund
the effort, doctors, smaller
startups, patients
Who:

The Future

Watson: a peek
into the future
Can read up to 200 million
papers in under 3 seconds
Monitors real time data and
articles as published
Patient EMRs, genomics, clinical
data, peer-reviewed publications
Volume:
Velocity:
Variety:
Machines as
personal assistants
to doctors, using
big data to aid
physicians in
decision making
What:

Andrew Litt,
Chief Medical Officer
at Dell
It is no longer about just
claims data, where we were
five years ago, or EMRs, where
we are today. The future is all
about home health monitoring
data, genomics data. It’s
about the patient.
“
”
Don Jones,
Global Strategy &
Market Development
for Qualcomm Life
What the experts think
Right now, most of the
companies are focused on
business-to-business
applications. In five years, I
expect to see a business-to-
consumer model where
software is made for the
individual.
“
”

Eva Ho,
Vice President of Marketing
& Operations at Factual
We believe open data is
the notion that data is
more acceptable and
accessible–less
encumbered and a lot
more affordable.
“
”
Jason Gilder,
Director of Data Curation
at Explorys
Open science movement
The open source community is
there to say everyone has a
shot to build something great
and everyone works together to
make those tools as good as
they can be.
“
”

Sources:
• McKinsey prepares us for the era of big
data by explaining how it is changing the
game
• O’Reilly explores all aspects of Big Data
• IBM’s overview of how to understand Big
Data
• McKinsey explores the Next Frontier for
Innovation, Competition and Productivity
• PEW Research Center Surveys the public
on their thoughts of big data and its
potential implementations
• Kauffman explores the world of data in
philanthropy
• World Economic Forum analyzes personal
data as a new asset class
• The Power of Big Data in Clinical
Informatics
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