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 ROCK HEALTH is powering the future of the digital health ecosystem, bringing together the brightest minds across disciplines to build better solutions. Rock Health funds and supports startups building the next generation of technologies transforming healthcare. ROCK HEALTH partners include Alexandria Real Estate Equities, Boehringer Ingelheim, Fenwick & West, GE, Genentech, Harvard Medical School, Kaiser Permanente, Kleiner Perkins Caufield & Byers, Mayo Clinic, Mohr Davidow Ventures, Montreux Equity Partners, NEA, Ogilvy Public Relations, Qualcomm Life and UCSF. LEARN MORE AT rockhealth.com

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 Presentation copyright © 2012 Rock Health GET IN TOUCH: Rock_Health research@rockhealth.org