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Confidential & Proprietary
Gregory J. Moore MD, PhD
Vice President Healthcare, Google Cloud
Google Inc.
@GJMooreMDPhD
Building a Healthier Future with ML and the Cloud
Confidential & Proprietary
Organize the world’s healthcare
and life sciences data, make it
accessible, secure and useful.
Confidential & Proprietary
Infrastructure for Healthcare
Machine Learning for All
Health Data Interoperability
Google Cloud Infrastructure , scale
security and compliance
Cloud AutoML, TensorFlow
Interoperability and Standardization
Three ingredients: Digital transformation for healthcare
Infrastructure for Healthcare
Confidential & Proprietary
Genomics data alone doubles every 7 months.
80% of medical data
is unstructured.
Unprecedented amounts of medical data
2X 80%
Stephens ZD, Lee SY, Faghri F, et al. Big Data: Astronomical or Genomical? PLoS Biology. 2015;13(7):e1002195. doi:10.1371/journal.pbio.1002195.; Datamark: Unstructured Data in Electronic Health Record Systems: Challenges and Solutions
Confidential & Proprietary
Healthcare data breaches to cost hospitals $300B over next 5 years
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$50
$100
$150
$200
$250
$300
$350
$400
$450
Health$380 Cost per data breach
higher in healthcare
than the average of
other industries
2x
Ponemon Institute’s 2017 Cost of Data Breach Study: Global Overview
Confidential & Proprietary
Layered Defense in Depth Security
Usage Operations Deployment Application
Network Storage OS+IPC Boot Hardware
Penetration testing
Confidential & Proprietary
Bug Bounty program
Confidential & Proprietary
Compliance for healthcare
Confidential & Proprietary
Genomics
Cloud Assets Serving Healthcare
Clinical Data Medical
Imaging
Collaboration
& Productivity
Enterprise
Devices
Machine
Learning
Confidential & Proprietary
Take a look….
Compute and storage needs were being
rapidly outpaced by amount of data being
generated. Migrated production genomics
processing services to Google Cloud.
Today, Broad processes over 250 genomes
per day, requiring:
Confidential & Proprietary
6,000,000
4,000,000
2,000,000
02009 2010 2011 2012 2013 2014 2015
Broad Genomics, by the numbers
Total Data Generated (Gigabases)
>100M compute core hours per
year
>35 PB of storage to date
2016 2017
8,000,000
10,000,000
12,000,000
14,000,000
16,000,000
Machine Learning for All
Train your own models
● Build on your own specialized
domain expertise
● Use Google tools for building
and training models
Machine Learning with Google Cloud
Use our models
● Leverage Google’s
domain expertise
● No tools or expertise
required
or
We’ve done the hard work for common scenarios
Cloud Natural Language
Cloud Jobs
Cloud Translate
Video Intelligence
Cloud Speech
Cloud Vision
Our model Pathologist*
Tumor localization score (FROC)
0.89 0.73
Sensitivity at 8 FP 0.92 0.73
Slide classification (AUC)
0.97 0.96
Gulshan & Peng et al. JAMA 2016 [preprint] Liu et al. “Detecting Cancer Metastases on Gigapixel Pathology Images” arXiv 2017
Cloud AutoML is a suite of Machine Learning
products that enable developers and businesses –
with limited machine learning expertise – to build
high-quality models leveraging Google’s state-of-the-
art transfer learning and Neural Architecture Search
technology.
What is Cloud AutoML?
Health DataInteroperability
Confidential & Proprietary
Fostering data interoperability and nurturing FHIR Community
“The HL7 FHIR Foundation is thrilled by this generous contribution of Google
Cloud Platform services to support the ongoing activities of the FHIR
community to help advance our goal of global health data interoperability,”
said Grahame Grieve, HL7 FHIR Foundation Board Member and HL7 FHIR
Product Director. “The future of health computing is clearly in the cloud, and
FHIR will serve to accelerate this transition.”
Grahame Grieve, FHIR Principal
Cloud and AI Enabled Digital Health Platform
Payer/Health Plans/Pharma
EMR, Legacy Systems
Genomics Data , Imaging PACS
On-prem Data warehouse Data/Analytics
Engine
Remote Monitoring Devices
Wellness and Fitness Devices
Patient Mobile and Tablet Apps
External Data
Healthcare Enterprise Landscape
Proprietary and confidentialProprietary and confidential
21
ChallengeBridging Chile’s healthcare
Chile’s 1,400 connected health facilities
and 1,000 remote medical facilities
lacked connectivity – while many of its
healthcare systems couldn’t easily, or
securely, interoperate.
Previous attempts to resolve failed due
to the overwhelming costs and
complexity of the solution.
Nationwide API-based architecture
● Data and applications are easily, yet securely,
available
● Enables Public Alerts, Population Health
Management Programs, etc
● Connects HC Centers – large and small
● Reinforces and leverages digitizing
all clinical and administrative processes
New ApproachDigital Architecture
Furthering Our Efforts on Interoperability
Introducing Cloud Healthcare API
Cloud Healthcare API offers a robust, scalable
infrastructure that ingests and manages key
healthcare data types, and as a result, the
healthcare sector can leverage data assets to
improve patient outcomes, increase productivity
and reduce physician burnout.
Confidential & Proprietary
HL7v2, FHIR,
DICOM
Roadmap - Analytics
and ML integration
solutions
Promotes data
interoperability
Allows ingestion
of EHR data
Cloud Healthcare API
We’re not just thinkingabout now. We’re thinking about, what is next. And how we can build a healthier future...
Confidential & Proprietary
27
People, Process and Technology: The Strategic Alignment of AI/ML
H I M S S 2 0 1 8
W i l l i a m H . M o r r i s , M D M B A
28
“Drive innovation and efficiency through
ongoing ideation and development”
H o w D o W e D o T h i s
29
iOT * AI * Care Redesign= Transformation
Right dataRight time
Right format/deviceRight peopleRight cost
Better quality---------------Lower cost* * =
VISION
Proprietary + Confidential
Platform
Payer / Health Plans
EMR Legacy Systems
Ecosystem Partners
Data / Analytics Engine
Remote Monitoring Devices
Wellness & Fitness Devices
Patient Mobile & Tablet Apps
External Data
Health APIx
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Iterative to engage end users
every step of the way
A G I L E – L I K E D E V E L O P M E N T
Clinical and operational
API First
Evalgilize standards and adoption
I N T E G R A T I O N
Collaborating with innovators
Traditional HIT
Non-Traditional Verticals
P A R T N E R S H I P S
Align with Clinical and
Strategic Priorities
VALUE
A L I G N M E N T
WHAT WE DOT e c h n o l o g y I n n o v a t i o n
I N N O V A T I O N
32
PATIENT ENGAGEMENT
PRODUCT LINESE M E R G I N G C L I N I C A L S O L U T I O N S
CAREGIVERDELIVERY
POPULATIONCENTRIC
FOUNDATIONS –APP DEV
-New Partnerships
HIGH VELOCITY CLINICAL
DESIGN & ARCHITECTURE
Proprietary + Confidential
Health APIx: Developer Portal
34
Example SOLUTIONSE M E R G I N G C L I N I C A L S O L U T I O N S
35
eHOSPITALE M E R G I N G C L I N I C A L S O L U T I O N S
Remote “bunker” providing an additional clinical tier of monitoring for ICU patients
2-way audio and video capabilities between bunker and unit
More than 200 total beds monitored from 7pm to 7am
Bunker has access to Epic, can place orders, review labs and view
imaging studies
Bunker (think “clinical air traffic control”)
Risk Classified Patient List
Video/Audio Camera and Patient TV “Highjack”
Utilizes existing screen in the patient’s ICU room to display on demand:
Remote clinician video and audio
Images, etc as directed by remote clinician in support of local staff
Can power-on TV and remotely adjust audio levels from eHospital bunker
Bunker “Doorbell”
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VITAL SCOUT SCREENSAVERE M E R G I N G C L I N I C A L S O L U T I O N S
Provide high volume, floor based clinical data as a screensaver via a web based application. Display statuses of key vitals with
PHI removed for use throughout the hospital system.
‘Always On’* HIPAA de-identified information outside of Epic (location only) with the screen saver facilitates rapid recognition of
patient changes; full workflow remains within Epic
37
APPOINTMENT PASSE M E R G I N G C L I N I C A L S O L U T I O N S
AppointmentPass gives Cleveland Clinic patients a way to quickly, easily and privately check in for their
appointments using a self-service electronic kiosk.
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AI-Powered Intelligent
Experiences
Consumer
“I need
to see a
doctor”
Technology Vision
Cleveland Clinic
FHIR APIs
API-Management Layer
EMR
System
FHIR Resources
Health System Technology Enablement
Patient Resource
Appointment
ScheduleResource
Diagnosis
Wait Time
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Conclusion
iOT Be wary of solutions looking for Problems
AI Augment a Workflow
Care Redesign: Development were the work is performed.
Agile Discipline: Organize around the work, not the tools
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E M E R G I N G C L I N I C A L S O L U T I O N S
Confidential & Proprietary
Booths
Building a Healthier Future with Google Cloud @HIMSS
Developers Lab Events Talks
Thank you
Gregory J. Moore MD, PhD
Vice President Healthcare, Google Cloud
Google Inc.
@GJMooreMDPhD
