Hadoop Summit 2015

1. Moving Healthcare Analytics to Hadoop to build
better predictive models - Saving Cost and Lives
Dr. Joe Colorafi – Dignity Health CMIO
Dr. Graham Hughes – SAS CMIO
Bill Guise – Dignity Health Senior Director IT
Sunil Kakade – Dignity Health Director IT
June 11th, 2015

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 Dignity Health
 Emerging Healthcare Landscape
 What outcomes we will enable?
 Big Data Ecosystem
 Hadoop Architecture for
Healthcare Analytics
Agenda

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Healthcare Changing Landscape - Business Performance Challenges
Analytics is a mission critical Enterprise Capability to drive Transparency, Insights, Collaboration and
to driver operational improvements
Business
Performance
Increasing
Regulatory
Pressure
Decelerating
price growth
Continuing
Cost Pressure
Shifting Payer
Mix
Rapidly
evolving
technology
Deteriorating
Case Mix

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For example, every year, severe sepsis strikes more than a million Americans. It’s been
estimated that between 28 and 50 percent of these people die—far more than the
number of U.S. deaths from prostate cancer, breast cancer and AIDS combined***.
The potential for Analytics in Healthcare is huge
*** National Institute of General Medical Sciences

7.  What if Dignity Health’s 30 TB Clinical Data
 100 billion rows of data
 8000 unique provider users
 1.2 million meds doses/ year
 Could be turned into
 Right Information
 Right Time
 Right Form
 Right People & Processes
Bringing benefits of Big Data to Health systems

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Healthcare Analytics Challenges
Patient
Data is everywhere but
trapped in a myriad of silos
• High Complexity
• High Variety
• Fast Data
• Privacy

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Healthcare Analytics Challenges
• Legacy Systems
• Rigid data
formats
• Unstructured
• Dark Data

10. Copyr ight © 2015, SAS Institute Inc. All rights reser ved.Copyr ight © 2015, SAS Institute Inc. All rights reser ved.
Infinite Volume
and Variety of Data
Disruptive Technology
New Problem-solving Mindset
BUILDING NEW ANALYTICS CULTURE WITH BIG DATA
Unrivaled
Processing Power

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One Platform, Many Data Sources, Multiple Workloads, All Consumers
NoSQL Logs
Social
Media
Sensors
Legacy
Platforms
Cloudera’s Hadoop Distribution
EHR
CERNER
Lab
Patient
Sat.
ADT
MS4 Billing
Pop
Health
Predictive
Analytics
SAS Enterprise Business
Intelligence Platform
Unified
Security Model
SAS Data
Governance
SAS Visual
Analytics Platform
Text
Mining
Forecasting &
Optimization
Machine
Learning
Real-time
Analytics
Data Science
Unified Audit
and Logging
HIE CMS
Unified
Privacy and
Compliance
Unified
Person
Master Index
Unified API
Platform
Unified
Enterprise
Data Model
Public Data
Sources
RDBMS
Dignity Health Insights Big Data Ecosystem
Unified Data Integration – Source Data Once, Analyze Multiple Times
Analytic
Capability
SAS - Hadoop
Integration
Open Source
Hadoop
Platform with
Unified Dignity
Health
processes
Dignity Health
Data Sources
Open Access
Data
Exploration
SAS Intelligence
Security

12. Hadoop and SAS can enable analytics Spectrum
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Hadoop and SAS can enable full analytics Spectrum

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Roadmap of building Dignity Health Insights Big Data Hub
1. Distributed Storage/Computing -
Hadoop Ecosystem
2. Compliance - Audit & Logging
3. Security - SAS Intelligence
4. Data Governance - Dataflux
5. Analytics - SAS Enterprise Miner
6. SAS Visual Analytics

14. 14EHR Lab
Patient
Sat.
ADT Billing Pop
Health
SAS Analytics
Products
SAS Visual
Analytics
HIE CMS
Dignity Health Insights
Open Source Based in the cloud Big Data Ecosystem Architecture
Secure FTP – SQOOP – FLUME
Big Data Ecosystem
Cerner
SAS Intelligence Platform
Role Based, LDAP integrated and Metadata level security

15. Copyr ight © 2014, SAS Institute Inc. All rights reser ved.
Prepare data IN
Hadoop for
analytics
Move data FROM
Hadoop into a SAS
environment
Deploy and manage
model score code
IN Hadoop
Lift data IN to
memory for analytics
at scale
Model data at scale in-
memory WITH advanced
modeling tools
Use the
right
approach for
what needs
to be done!
Explore data at scale, in-
memory WITH data
visualization
SAS & HADOOP - THE PRAGMATIC APPROACH

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ENABLING THE DATA TO DECISION LIFECYCLE WITH SAS
AND HADOOP ECOSYSTEM
Access & Manage Data
Advanced data management
capabilities (ELT, ETL, DQ,
virtualization) enabled for Hadoop
Interactively Explore & Visualize
Quickly Visualize Data in Hadoop, Discover New
Patterns, Publish Reports Via Web Reports, Mobile
Devices, MS Office Apps
Analyze & Model
Uncover Patterns and trends in Hadoop data.
Interactive and visual environment for analytics.
Apply Domain specific high-performance analytics
Deploy & Integrate
Automatically deploy and score analytic
models in the parallel environment.
Manage & analyze real time data

17. Copyr ight © 2014, SAS Institute Inc. All rights reser ved.Copyr ight © 2014, SAS Institute Inc. All rights reser ved.
Data Store
SAS
Data
In-Database
Data Store
SAS
Traditional SAS
HADOOP + SAS - DESIGN PATTERNS
These approaches are complementary & can be combined for maximum effect
Data Store
SAS
Data
In-Memory
Memory
Data

18. Copyr ight © 2014, SAS Institute Inc. All rights reser ved.Copyr ight © 2014, SAS Institute Inc. All rights reser ved.
Results
Modeling Code
HiveQL
Data
Enterprise Miner with Hadoop (Model Dev)
Enterprise Miner
Access to Hadoop
Hadoop Cluster
Enterprise Miner
High Performance Analytics
Hadoop Cluster
Small
Data
Volumes
Everything
Else
Data is pulled to the EM
server and computation
happens on the EM
server
Code is pushed to the
Hadoop cluster and
computation is executed
on the cluster
Results
Results

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SMP Architecture
LASR Analytic Server
Hadoop Cluster
MPP Architecture
LASR Analytic Server
Hadoop Cluster
Small
Data
Volumes
Everything
Else
Data is pulled into
memory on the single
machine
Data is pulled in parallel
from the Hadoop cluster
data nodes directly to the
LASR worker nodes
VISUAL ANALYTICS WITH SAS + HADOOP

20. Analyze Sepsis Alerts
By Mortality Rate
By Provider Response
By Length of Stay
By Facilties
BioSurvillence SepsisAnalytics with Hadoop and SAS VisualAnalytics
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21. 21EHR Lab
Patient
Sat.
ADT Billing Pop
Health
SAS Analytics
Products
SAS Visual
Analytics
HIE CMS
Dignity Health Insights
Cloud based Security Compliant Big Data Architecture
Secure FTP – SQOOP – FLUME
HADOOP Ecosystem
Cerner
SAS Intelligence Platform
Role Based, LDAP integrated and Metadata level security

22. Social Community
UI, Authenticate, Submit & Request Data, Navigate & Access
Applications, Collaborate & Share Insights
Packaged Analytic Applications & Actionable Insights
Predictive Models, Benchmarks, Actions/Alerting – Clinical,
Administrative, Operations, Financial , Quality, Gaming Theory
 Analytic Tools Foundation
Data Connectivity, Data Quality, Visualization, Segmentation,
Data Mining, Forecasting, Audit Trails, NLP, Machine Intelligence
 Storage & Data
Bladed Environment - EDW, ODS, Marts, Hadoop + Customer
Data, In-Memory Databases, Virtual Data Marts
Secure Cloud
EHR Lab
Patient
Sat.
Reg/Adt
 Patients
 EHR
 Call Center
 Visualization
 MS Office
 Regulatory
reporting
 Partners
Data
Insights
Billing Other
Patients
Clinicians
Managers
Analysts
IT Staff
Users
Any Customer
Any Channel
Any Device
Any Input Source
Internal/External
Any Service
Any vertical or
horizontal
Slice of stack
Any Output Destination
Internal/External
3rd Party App
The Technology: Dignity Health Insights
Manage
Financial
Risks &
Incentives
Proactively
Manage Care
Quality &
Outcomes
Improve
Efficiency of
Care Delivery
Population
Health and
Engage
Patients
Capabilities used in
Sepsis Biosurvillence
 Open Source Big
Data Platform
 User Authentication
with Dignity Security
System
 Audit and Logging
 Integration with
Registration and
Clinical systems
 SAS Enterprise
Business Intelligence
 SAS Visual Analytics
 SAS Data Quality
tools
 Mobile Delivery Pilot
Desired
Export
Dignity Health Insights
One Platform, Many Data Sources, Multiple Workloads, All Consumers

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Dignity Health Insights use cases are endless..
• Patient readmission reduction Predictive Model
• Broad System Exploration with Speed – COMPASS
• Legacy Reporting System modernization
• Pharmacy Analytics
• UMPI – Universal Master Patient Index

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