Editor’s Note: Download the complimentary MapR Guide to Big Data in Healthcare for more information: https://mapr.com/mapr-guide-big-data-healthcare/ There is no better example of the important role that data plays in our lives than in matters of our health and our healthcare. There’s a growing wealth of health-related data out there, and it’s playing an increasing role in improving patient care, population health, and healthcare economics. Join this webinar to hear how Baptist Health is using big data and advanced analytics to address a myriad of healthcare challenges—from patient to payer—through their consumer- centric approach. MapR Technologies will cover broader big data healthcare trends and production use cases that demonstrate how to converge data and compute power to deliver data-driven healthcare applications.

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© 2016 MapR Technologies

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Today’s Presenters
George Demarest
Director of Industry Solutions
@g_demarest
Email: gdemarest@mapr.com
Alicia d’Empaire
AVP, BI and Decision Support
Email: aliciad@baptisthealth.net

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Agenda
• Big Data Trends in Healthcare
• Introduction of Baptist Health South Florida
• Healthcare Changes and Challenges
• Role of Technology and Analytics
• BHSF Big Data Analytics Strategy
• Big Data Analytics Challenges
• Questions

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A Once-in-30-Year Re-Platforming of the Enterprise
Critical infrastructure for next-gen applications
Data platform enabler for required Speed, Scale, Flexibility
NewApplications ExistingApplications
Open Source Analytic Innovations Legacy
Disruptive Data Platform
On Premise Private Cloud Public Cloud
Heterogeneous Hardware
Next Gen Data Platform

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(100,000)
(80,000)
(60,000)
(40,000)
(20,000)
-
20,000
40,000
60,000
80,000
100,000
120,000
2013 2014 2015 2016 2017 2018 2019 2020
N.G. Architecture Growth vs. Legacy Shrinkage ($M)
Total $ Growth of IT Mkt N.G. $ Growth Legacy Mkt Growth/Shrink in $
IT Spending at an Inflection Point: Next-Gen is Now
Data source: IDC, Gartner; Analysis & Estimates: MapR

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5 Examples of Big Data in Healthcare That Can Save People’s Lives
http://www.datapine.com/blog/big-data-examples-in-healthcare/
Electronic Health Records (EHRs)
Real-time Alerting
PredictiveAnalytics in Healthcare
Using Health Data For Informed Strategic
Planning
Telemedicine

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Big Data Trends in Healthcare and Life Sciences
Healthcare Analytics
• Clinical decision support
• Predictive modeling across conditions
• Disease management
• Population health management
Data Management
• Electronic Medical Records (EMR)
• Medical imaging
• Genomics
• Insurance claims data
IoT and Networked Medical Devices
• Consumer devices
• Wearables
• Internally embedded devices
• Stationary devices (drug dispensers, et al)
Fraud, Waste and Abuse
• False claims, identity theft
• Kickbacks and beneficiary fraud
• Waste from Duplication and unbundling
• Insurance Claims Data

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Building a Healthcare Data Lake on MapR
Data
Lake
Claims
Clinical
Pharmacy
EMR
Logs and
Notes
3rd Party
Additional
Data
CB Header data, Social, ...
Historical procedures, co-morbidities (prof & inst.)
Lab results, vital signs, ...
Dr. Notes, Customer call logs, emails
Licensing, death master, …
Electronic Medical Records, images & text
Prescriptions, adherence

9. Solving Healthcare
Problems with Big Data
Alicia d’Empaire

10. Agenda
Ø Introduction of Baptist Health South Florida
Ø Healthcare Changes and Challenges
Ø Role of Technology and Analytics
Ø BHSF Big Data Analytics Strategy
Ø Big Data Analytics Challenges
Ø Questions

11. Baptist Health South Florida
Baptist Hospital of
Miami
Doctors Hospital Homestead Hospital Mariners Hospital South Miami Hospital West Kendall Baptist
Hospital
Baptist Cardiac and
Vascular Institute
eICU Medical Arts and
Surgery Center at
Baptist Hospital
Medical Arts and
Surgery Center at South
Miami Hospital
Urgent Care Centers Imaging / Diagnostic
Centers
Miami Cancer Institute Sleep Centers
Endoscopy Centers Home Care International Center Employed Physicians
BHMG - 163 physicians
(41 practices)
Baptist Health Quality
Network (BHQN) - 850
community physicians
Employee Health &
Wellness

12. Baptist Health Statistics
Ø Admissions ………………………………………………..… 71,681
Ø Patient Days …………………………………………..… 342,942
Ø Births ……………………………………………………….… 10,977
Ø ED Visits ……………………………………………….…. 313,116
Ø Urgent Care Visits …………………………….……… 242,177
Ø Total Surgical Cases ……………………………….…… 64,662
Ø International Patients …………………………………… 7,710
Ø Licensed Beds ……………………………………………… 1,742
Ø BHMG visits ……………………………………………….. 203,059

13. Baptist Health Statistics
Ø Medical Staff …………………………………………...…...… 2,211
Ø Employees ……………………………………….……...……... 16,300
Ø Charity Care and uncompensated services
(at cost) ………………………………..………………..… $292,190,000

14. Healthcare Challenges
• Affordable Care Act
o Access to & Affordability of Care and Quality & Cost of Care
üMedicare
1. Reduce Avoidable Utilization
2. Improve Coordination of Care
3. Quality, Service, & Cost Transparency
üMedicare population +
1. Percentage increase of ages 65+ from 2014 – 2022: 27% increase (Counties: Miami Dade increase
of 27%, Broward increase of 23%, Palm Beach increase of 32%)
2. Medicare is to become majority patient volume by 2022
üMedicaid Expansion

15. What is Consumer-Centric Healthcare
Source: IBM

16. Consumers
Key drivers and factors for Consumers in selecting healthcare services
1. Out of Pocket
Expenses
2. Access
3. Convenience
4. Transparency

17. HCAHPS
HCAHPS: a survey instrument and data collection methodology for
measuring patients' perceptions of their hospital experience.

19. Role of Technology and Analytics
Ø Use latest technology to track patient data throughout the continuum
of care – Home Health Devices, Wearables etc.
Ø Integrate data from multiple data sources real time
Ø Generate actionable insight using performance monitoring
analytics and providing automated alerts
Ø Optimize Outcome using Predictive Analytics
Ø Improve Patient Experience by personalizing care
Ø Reduce cost by analyzing data to identify cost saving opportunities

20. Role of Technology and Analytics
•Medical
•Non Medical
•Wearables
•Social Media
•Structured
•Unstructured
Consumer Data
•HL7
•ETL (Extraction, Transformation
and Loading)
•Analytics tools – Big Data
Hadoop, Predictive Analytics,
Machine Learning, NLP, Tableau
etc.
Integrated Real
Time Data •Mobile devices
•Email
•Text Messaging
•Marketing Campaign via mail
•Social Media
Multi Channels
to Consumer

21. Healthcare Big Data Use Cases
Ø Admission/Readmission prediction
Ø Telemedicine (Diabetes care & patient home monitoring)
Ø Sepsis early detection (real time vital signs streaming)
Ø Patient Engagement (Social Media)
Ø Genomics Study

22. Data Analytics Maturity Model
Reporting
Enterprise
Data
Warehouse
Business
Performance
Management
•Dashboards
•Scorecards
Big Data
•Hadoop
Advanced
Analytics
•Predictive Analytics
•Machine Learning
•Natural Language
Processing (NLP)

23. DATA
SYSTEMS
ANALYTICS
APPLICATIONS
DATA
SOURCES
BHSF Data Analytics Future State
Reporting and Analytics
• Dimensional Insight Diver
• SAP BOE
• IBM Cognos
• IBM Watson Content Analytics
• MS SQL Reporting Services
Data Visualization &
Dashboards
• Tableau
• Xcelsius
• SPSS
• Stata
• MCSS-
PASS
• SAS
• Treeage
• R
Research &
Statistical Analysis
Existing Sources
(EMR, Ancillary Systems, Devices)
Emerging Sources
(Sensor Streaming,Social Media,
Telemedicine, Unstructured)
Advanced Analytics
• Predictive Analytics
• Machine Learning
• NLP (Natural Language
Processing)
Traditional Data Warehouse
Independent Data Marts
Big Data:

24. Ø Implementing Hadoop (Big Data)
Ø Achieve cost savings via offloading storage
Ø As we migrate to Cerner, Big Data is a great
platform for us to store historical data from
our existing clinical and financial applications
BHSF Big Data Strategy Next Steps

25. Ø Pilot projects to begin:
1. Set up Hadoop environment and offload storage
2. Sepsis prediction by loading real time streaming
vital signs, labs, orders, census data, etc.
BHSF Big Data Strategy Next Steps

26. Ø Continue to expand our tools for Advanced
Analytics:
§ Predictive Analytics
§ Machine Learning
§ Natural Language Processing
BHSF Advanced Analytics Next Steps

27. Successful Strategy :
4 Key Pillars
Data
• Information
Management
Foundation
•Data
Governance
•Data
Standardization
Technology
• Appropriate
Technology
Platform
People
• Organization
•Organizational
structure & Role
definitions
•Centers of
Excellence
Process
• Information as
an Enterprise
Asset
•Standardization
of workflows
•Adoption

28. Big Data Analytics Challenges
ØNew Stack of Technology and Data
ØLack of resources
ØInteroperability challenges
ØHIPAA restrictions
ØLack of Data Governance

29. Key Take-Aways
Ø Use the BI Maturity Model to ensure the value of your current Analytics
investments while developing the capabilities for the Advanced
Analytics and Big Data phases.
Ø Although important, BI is not just about having the right tools.
Address your biggest challenges of the BI Maturity Model, such as
those related to data governance, cultural transformation, and BI-
related skills.
Ø Plan for the future by developing plans that consider patient-reported
data, events-driven architecture, social media, streaming data and
machine learning.
Ø Balance principles with pragmatism. Health care BI is an immature
and rapidly evolving area so progress may be made by taking “two
steps forward and then one step back.”
SOURCE: The Advisory Board Company

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MapR Converged Data Platform
Typically 1/3 less
hardware needed
Multi-tenant
Self-service data
exploration with Drill
Industry’s only mirroring, point-in-
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Trillions of files
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Most complete
Spark stackMultiple
versions of
community
software
supported
Big data
foundation for
files, enterprise
apps

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MapR Healthcare Architecture

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MapR Life Sciences and Healthcare Customers
Delivers clinical intelligence
to healthcare providers
Next generation data
platform for healthcare
and life sciences
Research grant analysis
80+ use cases; Fraud,
Waste and Abuse
Clinical integration, population
health, and value-based care
solutions and services
Diagnostics and solutions
for animal health
UnitedHealthcare A UHG Company
Drug discovery and
biomedical Research

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MapR Healthcare Blog

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Q&A
1. Coming Soon:
MapR Guide to Big Data in Healthcare
2. eBook:
Implementing a Digital Transformation
https://www.mapr.com/architect-guide-to-digital-transformation