HPE and Hortonworks join forces to Deliver Healthcare Transformation

1 © Hortonworks Inc. 2011 – 2016. All Rights Reserved

HPE and Hortonworks join Forces to Deliver Healthcare TransformationRichard ProctorGM Healthcare, HortonworksJohn SansonAlliance Manager, HPE


Agenda• Introductions• Healthcare - Current state• The Problem: Current data architecture• The Solution: Modern data Architecture with Hadoop• Healthcare Use Cases• HPE Hadoop Reference Architecture• Q&A


Data Driven Organizations-Shifting the Data Paradigm

o Regulatory-centrico Manual data review/collectiono Repressive data silo’so What data to store?o Expensive storage w/limited options

All data types Organization & Patient centric Store everything! Inexpensive storage with lots of options

Data as an independent business process(Silo’s of data)

Reactive reporting

Data as a byproduct of patient care Prospective analysis

Primary audience – Healthcare organization

Secondary audience

Secondary audience

Primary audience – regulatory agencies

Current data process with latent architecture

Modern Data Architecture with Hadoop


The problem: Current data architecture under pressureAP

PLIC

ATIO

NS

DATA

SYS

TEM

REPOSITORIES

SOU

RCES Existing Sources

ADT, Patient Accounting, GL, Payroll, Physician entry, Core measures, Patient Sat, AHRQ, External

benchmarks,, Clinical Systems (ED, Radiology, PACS), Other Sources (Clinics, home health, Ambulatory,

LTAC’s)

RDBMS EDW MPP

Business Analytics Custom Applications Packaged

ApplicationsOLTP, ERP, CRM Systems

Unstructured documents, emails

Clickstream

Server logs

Sentiment, Web Data

Sensor. Machine Data

Geolocation

Value in New data sources

• Limited Application interaction• Costly to Scale storage• Silos of Data• Inability to manage new data sources• Schema on Write vs. Read


New Data Paradigm- Winners will be Proactive not Reactive!

2.8 zettabytesin 2012

44 zettabytesin 2020

N E W

1 zettabyte (ZB) = 1 million petabytes (PB); Sources: IDC, IDG Enterprise, and AMR Research

Clickstream

PROD, LOE, SHE

Web & social

Geolocation

Internet of Things

Server logs

Files, emails

Transform every industry via full fidelity of data and analytics

Opportunity

T R A D I T I O N A L

LAGGARDS

LEADERS

Ability to Consume Data

Enterprise Blind Spot

90% of all information created by humans originated in the last 2 years



Thank you for the diagram, Robert Wood Johnson Foundation, 2014

7

Comprehensive Health Management

80% of healthcare determinants lie outsidethe US healthcare delivery system

Can healthcare systems expand into these other areas, and become true public health systems?


Imagine if your physician could say this to you…

“I can make a health optimization recommendation to you based on…

The latest clinical trials Your genomic make up and family history The local, regional, national & International data about patients just like you The real-world health outcomes over time of every patient like you the level of your interest and ability to engage in your own care

I can then tell you within a specified range of confidence, which treatment has the greatest chance of success for you.”

Thank you Dale Sanders at Health Catalyst for the quote


Learning from other industries!Step 1:

Retail Approach-• Build a Central Data Repository to store and process all longitudinal patient history “Data Lake”• Analyze information across multiple touch points and episodes of care within the Healthcare

system or across Providers, Clinics, pharmacies, Home Health, and specialty providers

Step 2:

Predictive Modeling/Analytics-• 360 degree Patient view used to build Predictive Models around high cost/high quality patients

e.g. long-term chronic disease management• Data gathered on patients after they leave the care setting enables more timely visibility into

patient behavioral/clinical changes.


Original 24 architects, developers, operators of Hadoop from Yahoo!

ON

LY 100open source

Apache Hadoop data platform

%Founded in 2011

HADOOP1STprovider to go public

IPO Fall 2014 (NASDAQ: HDP)

subscriptioncustomers800 employees across

740+

countriestechnology partners1350+ 17

TM

Hortonworks Company Profile


Fastest growing Fortune 1000 customer baseCustomer Momentum• More committers to Hadoop than any other distribution• Non proprietary = FREE with no vendor lock in• Fastest software company in history to 100M revenue- 4 years (Barclays)

Largest Cluster in North America

32,000 NodesLargest Cluster in Europe

1,000 Nodes

Some notable migrations include many of the early adopters of Hadoop:

© Hortonworks Inc. 2011 – 2014. All Rights Reserved

Experience at Scale80,000 nodes under contract

Largest Known Cluster in APAC

400 Nodes

• 30+ customers migrated from other distributions


Use Cases - Providers


Historical and Legacy system data offloadHealthcare

Problem Legacy system licensing when moved to new EMR 22 years of data for 1.2 million patients ~ 9 million records Data on legacy system was not searchable nor retrievable Cost to move data to new system not feasible Difficulty in combining data from 2 systems

Solution Unified repository provides data to both researchers & clinicians “View only” legacy system retired, saving $500K 9 million historical records now searchable & retrievable Records stored with patient identification for clinical use, same data presented

anonymously to researchers for cohort selection

MPP

SAN

Engineered System

NAS

HADOOP

Cloud Storage

$0 $20,000 $40,000 $60,000 $80,000 $180,000

Fully-loaded Cost Per Raw TB of Data (Min–Max Cost)

Hadoop Enables Scalable Compute & Storage at a Compelling Cost Structure:

Storage Costs and licensing reduction of latent systems

$500,000/year

5 x the amount of usable storage, plus 5 x processing power, for about 30% of the cost of traditional technologies,”

14 © Hortonworks Inc. 2011 – 2016. All Rights ReservedPage 14 © Hortonworks Inc. 2011 – 2015. All Rights Reserved

A Healthcare Data PlatformFor a Single View of the Patient

Mercy

– 35 hospitals and 700+ clinics, 1 million patients annually, Multi State coverage– One of the earliest and largest EPIC deployments

Objective #1 Improved Documentation- Billing & Coding AccuracyObjective #2 Improved Clinical DocumentationObjective #3 Real-Time sensor data streaming- Virtual Care Center (VCC)


Mercy, St LouisObjective #1- Coding & Billing Accuracy

Problem

• Chart queries not being answered in a timely manner which produces problems with coding and payment accuracy. MDS (Medical Documentation Specialist) wastes time asking the same query without responses. Escalating problems occur too late in the billing cycle

• MDS staff use ”gut instincts” to determine which charts to review. There is 1 MDS for every 3,000 patients

Solution

• Identify the specific patient care paths to most likely include a secondary diagnoses and set up clinical rules to identify additional care delivery e.g. certain lab orders.

• Identify physicians with the lowest probability of answering follow up queries and create business rules to rank cases to determine which ones are highest value and most likely need 2nd review.

BenefitsVisibility into undocumented

secondary diagnoses and billing omissions

Improved staff utilization and chart review accuracy

More timely and accurate billing process resulting in 1M + additional annual revenue from documented secondary diagnoses and care

Ability to predict physicians documentation omission patterns

Healthcare


Mercy, St LouisImproved Clinical Documentation & Analytics

Problem

Moving Epic EMR data to Clarity EDW took 24 hours and was “never going to enable near real time analytics

Difficulty in combining non traditional (unstructured data) with structured data

SolutionNeeded to get ahead of the EMR-EDW lag time…

Mercy replicated all of its Epic data in the Hortonworks Hadoop data platform• Epic data is enriched with data from other internal systems and publicly available

data (Lawson, etc.,)• NLP and advanced OCR applications deployed to drive data exploration and

discovery

BenefitsOne query on 19,000 individuals

took two weeks on the current data architecture, but it ran in 0.5 days on HDP

Hyperlinks built to bring visibility to updates pushed back into EPIC

Current lag time of 3-5 minutes for new clinical entries

Mercy searches through terabytes of free-text lab notes, speeding clinical based insights from “never” to “seconds”

Healthcare


Near Real Time Analytics with Epic

EPIC W P

OracleClarity

W P

Batch

Gov

erna

nce

& In

tegr

atio

n

Secu

rity

Ope

ratio

ns

Data Access

Data Management

Near Real-time

APPL

ICAT

ION

S

Business Analytics Custom Applications Packaged

Applications

Sqoop

The Process:Initial bulk load via sqoop from Oracle/Clarity EDW to HDP. They then capture deltas every 3-5 minutes from cache into HDP.


Monitor Patient Vitals in Real-Time with Sensor data

Problem

Managing The Volumes of System Sensor Data In a typical hospital setting, nurses do rounds and manually monitor patient vital signs. They may

visit each bed every few hours to measure and record vital signs but the patient’s condition may decline between the time of scheduled visits.

This means that caregivers often respond to problems reactively, in situations where arriving earlier may have made a huge difference in the patient’s wellbeing.

Solution

Hadoop Empowers Healthcare by Converting High Volumes of Sensor Data into a Manageable Set of Data New wireless sensors can capture and transmit patient vitals at much higher frequencies, and these

measurements can stream into a Hadoop cluster.

Caregivers can use these signals for real-time alerts to respond more promptly to unexpected changes.

Over time, this data can go into algorithms that proactively predict the likelihood of an emergency even before that could be detected with a bedside visit.

BenefitsProactively Predict Events rather

than reactivelyReal-time AlertsCapture & Transmit Patient

Vitals at Much Higher Frequencies

Improve Patient SatisfactionImproved response timesReduce adverse drug response

times

Healthcare


Real Time Predictive care

Mercy’s Journey- The Virtual Care Center (VCC)

ClinicalDocs

Vital SignMonitoring

SinglePatient Record

Lab NotesArchive

PrivacyDatabase

Medical Decision Support

DeviceData

Ingest

PreventiveCare

The path to Real Time Care

• First of its kind in the World!• 24/7/365 monitoring• $54M Investment with 330 specialized

medical professionals• 36 Medical Centers/33 ED’s• 478 Critical Care beds/28 Critical Care

units• 2,431 Acute Care beds• 15% reduction in LOS


Yield, Quality & Process Optimization at Merck

ProblemMerck was seeing higher-than-usual discard rates on certain vaccines. The team was looking into the causes of the low vaccine yield rates, but the usual investigative approach involved time-consuming spreadsheet-based analyses of data collected throughout the manufacturing process.

Key Challenges • Data Silos• High Cost of Data Retention• High Cost of Testing Hypothesis in the Real World

The Solution Hadoop enables the pharmaceutical company to crunch huge amounts of data resulting in the ability to develop

and bring to vaccines to market faster and at lower cost. Through 15 billion calculations and more than 5.5 million batch-to-batch comparisons, Merck discovered that

certain characteristics in the fermentation phase of vaccine production were closely tied to yield in a final purification step.

Plans for the Future• Analyze Streaming Machine Sensor Data in Real time• Proactively minimize Yield Variability• Predictive Equipment Maintenance


Other common use cases with Hadoop

• Low cost & searchable centralized storage of genomic data, PDF’s, Images, etc. • Storage of ICU device data • Storage of large data not persisted in another location or repository • RTLS – Real Time Location System Patient, doctor, and hospital staff real time location tracking within

the hospitals• EPIC/Cerner Integration • Medication Safety- Error reduction through use of data• Clinical Trial Cohort Identification• Breach/Threat Security Assessment• Store medical research forever• Theft & Abuse- “Drug Diversion”• 360 View of drug safety• Clinical Text note search (Google type search)• Population Health initiatives (re-admissions)• Wearable's Monitoring Analytics• Payment Integrity/Fraud Streaming


Join the Hortonworks Healthcare User Group!

• Monthly 1-hour calls covering thought leadership topics

• Past speakers: Mercy, UC Irvine, Mayo Clinic, Cardinal Health, Zirmed, Intermountain Health, CHOLA…

• 125+ members!"If I haven’t said it loud enough, this is an awesome forum!” Paul Vee, CHOLA

“This is one of the best uses of my time.” Lonny Northrup, Intermountain Healthcare


Lessons Learned…

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1. Like it or not: your business and success runs at the speed of software so IT leadership needs to lead on Hadoop

2. No Question: The Hadoop ecosystem is revolutionizing data management and analytics and evolving faster than any one company possibly can.

3. Adoption Curve: Start learning and adopting now; be ready for full adoption soon to stay competitive

4. There is only one Hadoop licensed by the Apache software foundation…choose your distribution carefully to avoid vendor lock from proprietary solutions as you scale out!

5. Our best customers are our most involved customers!


HPE Hadoop Architecture


HPE’s Hadoop Architecture is the difference!!!

Rapid design and deployment

Multiple Solution Options

Built and tested for Hortonworks

Reduce cost, risk, and errors

$


HPE offers three (3) Deployment Options

− Hortonworks tested− Traditional, symmetric− Standard Rack Co-location − Entry Big Data system− Small deployments (~20 nodes)

− Hortonworks tested − Purpose-built, symmetric− Mid-size to large deployments− Workload/Storage optimization− High density, lower power

− Hortonworks tested− Asymmetric architecture− Mid-size to large deployments− Multiple/Dynamic workloads− High density, lowest power

1 HPE ProLiant DL Server HPE Apollo Storage Server

2 3 Moonshot Server and Apollo Storage


Apollo 4530 System Hortonworks Reference Architecture Purpose-built for Hadoop and Big Data analytics

Analytics

At scale

Versatile performance

Unleash the full value of Big Data with Hadoop

42U rack comparison

Apollo 4530 - 1 management

node- 2 head nodes - 27 worker nodes - 1.8 PB raw storage

2U rack mount server- 1 management node- 2 head nodes - 18 worker nodes - 960 TB raw storage

Apollo 4530 advantage 33% more compute 2X storage capacity


New approach to address Big Data demands

Two Socket, 2U ServersYARN Apps, HDFS, ORC

Files, Parquet, Hbase,

Cassandra

Compute Optimized Servers

Storage Optimized Servers

YARN Apps

HDFS, ORC Files, Parquet,

Hbase, Cassandra

− Separate processing /storage tiers connected by Ethernet networking

− Standard Hadoop installed asymmetrically• storage components on storage servers• yarn apps on processing servers

− HPE Moonshot, HPE Apollo 4200; HPE Apollo 2000

HPE Big Data Reference Architecture

− Processing / storage always collocated− All identical servers− Data partitioned across servers on direct-

attached storage (DAS)

Traditional Big Data Approach


Unique ValueHPE Apollo & Moonshot Combined Solution

HPE Big Data Reference Architecture for HadoopInnovation delivering unique value to customers and the open source community

29

Data Consolidation− Shared storage pool for multiple Big Data

environments

Maximum Elasticity− Dynamic cluster provisioning from compute

pools without repartitioning data

Flexible Scalability− Scale compute and storage independently

Breakthrough Economics− Workload optimized components for better

density, cost and power

Ethernet (RoCE)

HPE Apollo 4000

HPE Moonshot or HPE Apollo 2000


Advantages* of HPE Big Data Reference ArchitectureA new standard for Big Data delivery at scale

30

HPE Big Data Reference Architecture

* Normalized on performance

Traditional Architecture

Traditional Architecture BDRA

Hadoop performance Equivalent

Density >2x more dense

Network bandwidth

40Gbit versus 10Gbit

HDFS Storage performance 2x greater

Power (watts) Half the power


Healthcare Customer Stories

Visit us at: http://hortonworks.com/industry/healthcare/


Thank You!

Technology

HPE and Hortonworks join forces to Deliver Healthcare Transformation