baptist health: solving healthcare problems with big data

®© 2016 MapR Technologies 1

®

© 2016 MapR Technologies


Today’s Presenters

George DemarestDirector of Industry Solutions

@g_demarestEmail: [email protected]

Alicia d’EmpaireAVP, BI and Decision SupportEmail: [email protected]


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


A Once-in-30-Year Re-Platforming of the Enterprise

Critical infrastructure for next-gen applicationsData platform enabler for required Speed, Scale, Flexibility

New Applications Existing Applications

Open Source Analytic Innovations Legacy

Disruptive Data Platform

On Premise Private Cloud Public Cloud

Heterogeneous Hardware

Next Gen Data Platform


(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


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

Predictive Analytics in Healthcare

Using Health Data For Informed Strategic Planning

Telemedicine


Big Data Trends in Healthcare and Life SciencesHealthcare 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


Building a Healthcare Data Lake on MapR

DataLake

Claims

Clinical

Pharmacy

EMRLogs 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

SolvingHealthcareProblemswithBigData

Aliciad’Empaire

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

BaptistHealthSouthFlorida

BaptistHospitalofMiami

DoctorsHospital HomesteadHospital MarinersHospital SouthMiamiHospital WestKendallBaptistHospital

BaptistCardiacandVascularInstitute

eICU MedicalArtsandSurgeryCenteratBaptistHospital

MedicalArtsandSurgeryCenteratSouth

MiamiHospital

UrgentCareCenters Imaging/DiagnosticCenters

MiamiCancer Institute SleepCenters

EndoscopyCenters HomeCare InternationalCenter EmployedPhysiciansBHMG- 163physicians

(41practices)

BaptistHealthQualityNetwork (BHQN)- 850communityphysicians

EmployeeHealth&Wellness

BaptistHealthStatistics

Ø Admissions………………………………………………..…71,681Ø PatientDays…………………………………………..… 342,942Ø Births……………………………………………………….… 10,977Ø EDVisits……………………………………………….…. 313,116Ø UrgentCareVisits…………………………….………242,177Ø TotalSurgicalCases……………………………….……64,662Ø InternationalPatients…………………………………… 7,710Ø LicensedBeds………………………………………………1,742Ø BHMGvisits……………………………………………….. 203,059

BaptistHealthStatistics

Ø MedicalStaff…………………………………………...…...… 2,211Ø Employees……………………………………….……...……... 16,300Ø CharityCareanduncompensatedservices

(atcost)………………………………..………………..… $292,190,000

HealthcareChallenges

• AffordableCareActo Accessto&AffordabilityofCare andQuality&CostofCare

üMedicare1. ReduceAvoidableUtilization2. ImproveCoordinationofCare3. Quality,Service,&CostTransparency

üMedicarepopulation+1. Percentageincreaseofages65+from2014– 2022:27%increase(Counties:MiamiDadeincrease

of27%,Browardincreaseof23%,PalmBeachincreaseof32%)2. Medicareistobecomemajoritypatientvolumeby2022

üMedicaidExpansion

WhatisConsumer-CentricHealthcare

Source: IBM

Consumers

KeydriversandfactorsforConsumersinselectinghealthcareservices

1. OutofPocketExpenses

2. Access3. Convenience4. Transparency

HCAHPS

HCAHPS:asurveyinstrumentanddatacollectionmethodologyformeasuringpatients'perceptionsoftheirhospitalexperience.

RoleofTechnologyandAnalytics

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

RoleofTechnologyandAnalytics

•Medical•NonMedical•Wearables•SocialMedia•Structured•Unstructured

ConsumerData

•HL7•ETL(Extraction, TransformationandLoading)•Analytics tools – BigDataHadoop, Predictive Analytics,MachineLearning,NLP, Tableauetc.

IntegratedRealTimeData •Mobile devices

•Email•TextMessaging•MarketingCampaign viamail•SocialMedia

MultiChannelstoConsumer

HealthcareBigDataUseCases

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

DataAnalyticsMaturityModel

Reporting

EnterpriseDataWarehouse

BusinessPerformanceManagement•Dashboards•Scorecards

BigData•Hadoop

AdvancedAnalytics•PredictiveAnalytics•MachineLearning•NaturalLanguageProcessing(NLP)

DAT

A SY

STEM

SAN

ALYT

ICS

APPL

ICAT

IONS

DAT

A SO

UR

CES

BHSFDataAnalyticsFutureState

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 WarehouseIndependent Data Marts Big Data:

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

BHSFBigDataStrategyNextSteps

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.

BHSFBigDataStrategyNextSteps

Ø Continue to expand our tools for Advanced Analytics:

§ Predictive Analytics§ Machine Learning§ Natural Language Processing

BHSFAdvancedAnalyticsNextSteps

SuccessfulStrategy:4KeyPillars

Data• InformationManagementFoundation•DataGovernance

•DataStandardization

Technology• AppropriateTechnologyPlatform

People• Organization•Organizationalstructure&Roledefinitions

•CentersofExcellence

Process• InformationasanEnterpriseAsset• Standardizationofworkflows

•Adoption

Big Data Analytics Challenges

ØNew Stack of Technology and Data

ØLack of resources

ØInteroperability challenges

ØHIPAA restrictions

ØLack of Data Governance

KeyTake-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


MapR Converged Data Platform

Typically 1/3 less hardware needed

Multi-tenant

Self-service data exploration with Drill

Industry’s only mirroring, point-in-time consistent snapshots

Trillions of files vs. 100M limit

POSIX, NFS

Typically2x-7x faster

Built-in real time NoSQL DBMS and Streaming

Most complete Spark stack Multiple

versions of community software supported

Big data foundation for files, enterprise apps


MapR Healthcare Architecture


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


MapR Healthcare Blog

© 2016 MapR Technologies

Q & A1. Coming Soon:

MapR Guide to Big Data in Healthcare

2. eBook:Implementing a Digital Transformationhttps://www.mapr.com/architect-guide-to-digital-transformation

baptist health: solving healthcare problems with big data

Data & Analytics