teradata next-generation healthcare analytics · 2019-12-06 · • big data analytics . 5 new...

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Teradata

Next-Generation Healthcare Analytics Nov 25th , 2016

Ozgur Kaynar

Senior Business Consultant [email protected]

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• Healthcare Trends & Challenges

• Teradata Approach to Healthcare

• Teradata Advanced Analytics

• Health Sector Analytical Use Cases

Agenda

© 2014 Teradata

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The Triple Aim of Healthcare for All Stakeholders

Better Care for Individuals • Safety and Effectiveness

• Patient-Centeredness

• Timeliness & Efficiency

• Equity

Better Health for Populations • Improve Outcomes

• Expand Access to Quality Care

• Influence Patient / Member Lifestyle Behavior

Reducing Per-Capita Costs • Administrative Efficiencies

• Value-Based Reimbursement

• Coordination of Care / Care Management

• Revenue Recovery

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Healthcare Industry Challenges

Adaption Challenges • Expanding Coverage (ACA)

• New Products

• Payer and Provider Collaboration

Chronic Conditions Frequency & Cost Are Rising • Type 2 Diabetes

• Asthma

• Heart Disease

• Obesity

Population Requirements • Care Improvement&Coordination

• Patient / Member Engagement

• Lifestyle Choices Drive Costs Up

New Technology • New Communication Channels

• Social Media, Facebook, Twitter

• mHealth, Telemedicine

• DIY Healthcare (i.e. FitBits)

• Big Data Analytics

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New Technologies, Adaption of Skillsets

Main Technology Challenges for Healthcare

© 2014 Teradata

Data & Application Silos

360 Patient Information

High Grow rate of Unstructured Data

Data Governance

Quality & Security

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• Teradata Approach to Healthcare



Agenda

© 2014 Teradata

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A New Approach is Required…

KNOW MORE. DO MORE.

• Leverage your existing ecosystem and capabilities

• Provide an integrated approach to harness all your data

• Data reuse to speed time to market and improve operational expenditures

Enable healthcare systems and insurer

High Quality, Low Cost Care Coordination

Consumer Engagement Driving Wellness / Growth

Integrated Finance Performance Management

Improved Population Health

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Healthcare Industry Framework

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Teradata Framework

Industry Solutions

•Deep Industry Knowledge

• Industry Models, Partners and Teradata Services

Professional Services & Partners SIs

•Best in class

• Expertise

• 99% retention rate

Applications

• Leading Integrated Marketing Management Solutions

•Marketing Analytics and Customer Data Management

•Alliance Program

Analytics Platform

• The world’s most scalable analytics platform for structured, multi-structured and Big Data analytics

• Leader in Gartner

•Open standards

UNIFIED DATA ARCHITECTURE DATA MODELS SERVICES APPLICATIONS

Discovery Platform

Business Consulting

Architect & Implement

Optimize & Manage

Analytical

Partner

Solution Modeling Building Blocks

Data Integration Roadmaps

Health Care Data Model

APPLICATIONS

DATA MODELS

UNIFIED DATA ARCHITECTURE

SERVICES

Integrated Marketing

Management

Data Platform

Integrated Data

Warehouse

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• Teradata Approach



Agenda

© 2014 Teradata

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Analyze all Data: Traditional + New Data Types

Business Transactions (claims, member billing,

enrollment, provider

payments)

Observations (clinical notes, UM and CM

notes, MRI’s, machine

sensors, medical charts)

Source: IDC, Gartner

Interactions (IVR, call center, hospital

admits, “likes”, authorizations,

tweets, weblogs, )

+ +

13 © 2014 Teradata

Healthcare Analytic Discovery Success

1. Invest in Discovery

Ask new (previously unanswerable) questions

Move from focus only on transactions to interactions

14 © 2014 Teradata


2. Analyze All Data

Start with your cleansed data that has been

integrated in your enterprise data warehouse

Access other valuable data in the ecosystem

Use new data which is never involved to analytics (

semi and unstructured data )

Use Analytics forAll Data – not subsets

15 © 2014 Teradata


3. Make it easy to use !

Analytics in Healthcare - Time sensitive - has to be quick

- With minimum effort & skillset – not a SW company ?

Choose big data analytics technologies that - Support iterative analysis with very short cycles

- Connect to familiar BI & stats tools

- Shorten time-to-answer (and run-time) How do we do that? We connect your favorite BI &

Stats tools to ALL the data using

the latest analytics power tools

16 © 2014 Teradata


4. Embrace multi-structured data

Nothing to be afraid of – text, sensor, web-log, social

media data doesn’t bite

You may have to learn new data management or

analytics techniques

There is a lot of it – estimates range from 70%-90% of

enterprise data is multi-structured

17 © 2014 Teradata


5. Ramp up with an experienced team

You have a very capable IT staff and brilliant

healthcare analytics leaders – still, ask for use cases

Specific technology, tool and data scientist

experience will jump-start your project

Shadow the experienced team, learn and take

over if you like

How do we do that? We have the largest professional

workforce dedicated to big data

analytics, +250 by 2016

18 © 2014 Teradata


6. Plan to democratize analytics

Don’t limit analysis to a few highly paid data

scientists

Don’t have to send every business analyst to

training for Hbase, MapReduce, Impala, Hive & Pig

This early decision will affect the tools and partners

you choose How do we do that? your favorite BI & Stats tools

connect to all the data using the

latest analytics tools

19 © 2014 Teradata


7. Measure the VALUE

Estimate business Value & priority and try to reach

that in a limited time/resources/simplicity

Talk with Value and Benefit for Sustaning analytics in

the company

Try before you buy !

How do we do that? We want you to be convinced

with the value by answering your

questions on your data

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• Teradata Approach



Agenda

© 2014 Teradata

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Population Management

Out of Area/Network Utilization

Atypical Antipsychotic Utilization Trends

Predictive Path to Surgery

Patient

Admission to

Discharge

Analysis

Drug & Medical Condition Affinity Analysis

Missing

Diagnosis

(Risk)

Prediction

Operations

Claims Overpayment Review

Text Analysis -HL7

Call Center

IVR

Optimization

Marketing Sales

Web Based Insurance Path to Purchase

Attribution of

marketing

campaigns

Patient

Satisfaction

Reduce Complaints to Medicare:

Member & Provider Interactions

Healthcare Discovery Use Cases

22 © 2014 Teradata

HL7 DATA PARSER PATIENT AFFINITY & LENGTH OF STAY PATIENT COMPARE ADMISSION DIAGNOSIS PROCEDURE PATHS PATHS TO SURGERY DIABETES PATIENT READMISSION DRUG PRESCRIPTION AFFINITY ANALYSIS HEALTHCARE IMPACT ANALYSIS SUSPICIOUS DOCTORS

SHAREABLE, REPEATABLE APPS WITH TERADATA ASTER APPCENTER

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HL7 DATA PARSER

PARSE SEMI-STRUCTURED DATA FOR CARE INSIGHTS

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RAW HL7 DATA IS TOUGH TO ANALYZE

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HL7 PARSER APP MAKES THE DATA READABLE FOR ANALYSIS

WHICH IS USEFUL FOR ; DETECTING DISCREPANCY between HL7 and TREATMENT or DETECTING ANOMALIES caused by FRAUD

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Out of Area/Network Utilization

Atypical Antipsychotic Utilization Trends

Predictive Path to Surgery

Patient

Admission to

Discharge

Analysis

Drug & Medical Condition Affinity Analysis

Missing

Diagnosis

(Risk)

Prediction

Operations

Claims Overpayment Review

Text Analysis -HL7

Call Center

IVR

Optimization

Marketing Sales

Web Based Insurance Path to Purchase

Attribution of

marketing

campaigns

Patient

Satisfaction

Reduce Complaints to Medicare:

Member & Provider Interactions

Healthcare Discovery Use Cases

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HEALTHCARE PATIENT READMISSION

PREDICT READMISSION BASED ON PATIENT METADATA AND USING PREDICTIVE ANALYTICS

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SELECT DIFFERENT METADATA FIELDS TO PERFORM THE ANALYSIS AGAINST

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PLOT PREDICTIVE OUTCOMES BASED ON DIFFERENT FACTORS

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NAÏVE BAYES DASHBOARD SHOWS READMISSION PREDICTIONS

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GLM DASHBOARD SHOWS READMISSION PROPENSITY

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Aster Analytics Evolving Use & Value Examples Affinity & Influencer Analysis: (Product, Service, Social, Warranty)

Predictive Analysis (Behaviors, Components, Social,…)

Behavioral (paths & pattern sequences)

Text Analytics

(sentiment, documents, voice of customer )

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Start building solutions with BUSINESS MIND

Consider always BUSINESS PAINPOINTS, STRATEGY, IMPROVEMENT AREAS

Prioritization and Measure with VALUE

Use Frameworks, Templates and have a ROADMAP

Fail Fast, Succeed Fast – Become AGILE

Implement, Evaluate, Improve with BUSINESS CONSULTING

Plan and Pilot a BIG DATA Program

Ask TERADATA to become YOUR STRATEGIC PARTNER

Closing Thoughts

© 2014 Teradata

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For more information, please visit:

www.teradata.com

www.teradata.com/blogs

www.teradatamagazine.com

www.forbes.com/sites/teradata

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• Could you use a predictive model to assess the likelihood of readmission?...there’s an App for that

© 2014 Teradata

Patient Readmissions

A Closer Look

65% Medicare Readmissions

deemed Avoidable

$26B Medicare Costs (2015) from

Readmissions within 30 days

Predictive Model

Quality of Care

Patient Satisfaction

Operational Efficiency

Cost Control


Profitability

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• Predicting patient readmission using several analytic methods – Naïve Bayes

– GLM

– Random Forest

• Using various features of the patient – Time in hospital

– Number of procedures in last year

– Medications and past diagnosis history

– Etc.

• Visualize output in AppCenter and Tableau server

Diabetes Patient Readmission

© 2014 Teradata

Predictive Model

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• Want to identify doctors with suspicious behavior?...there’s an App for that

© 2014 Teradata

Anomalous Profiles: Medicare/Medicaid Fraud

A Closer Look

$60B+ Conservative estimate of

Medicare Fraud each year Behavioral Analytics

Cost Control


Fraud Prevention

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• Uncover doctors that are out of step with their expected behavior

• Analytics performed on public CMS Part B provider dataset

• Utilize SQL-GR function pSALSA to explore the distinct features of similarity between doctors

• Visualize using Tableau server and AppCenter Sigma

Healthcare Fraud Anomalous Doctors

© 2014 Teradata

Behavioral Analytics

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• Do you need to illuminate all clinical pathways traversed to optimize a patients journey?...there’s an App for that

Barriers impeding Quality of Care and Patient Satisfaction:

• Poor continuity and coordination across disciplines

• Specialists acting in silos yield suboptimal care

• Lack of an aggregate view across all patients

© 2014 Teradata

Path Analysis: Admission Diagnosis Procedure

A Closer Look

Path

and

Pattern

Quality of Care

Patient Satisfaction Operational Efficiency

Cost Control Population

Management

Processing Efficiency

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• Discovery analysis to better understand patient path/touch points

• What are patients doing after they are admitted with x disease? – What is my golden path(common expected behavior)?

– Are there any outlier sequences of events?

– Could patterns of behavior be utilized for a predictive model?

• Utilize patented n-Path SQL-MR function for path and pattern analytics

• Visualized with Sankey, Tree, and Sunburst visuals

Admission Diagnosis Procedure Pathways

© 2014 Teradata

Path and Pattern

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AppCenter Healthcare Prebuilt Analytics Templates Repeatable Applications, Shareable Results

Analytic Templates

Available Now:

• Admission Diagnosis Procedure Paths

• HL7 Parser

• Impact Analysis • Paths to Surgery

• Patient Affinity and LOS

• Patient Compare

• Diabetes Patient Readmission

• Drug Affinity Analysis • Suspicious Doctors

• Suspicious Doctors Similarity graph

teradata next-generation healthcare analytics · 2019-12-06 · • big data analytics . 5 new...

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