Teradata Next-Generation Healthcare Analytics

Transcription

1 Teradata Next-Generation Healthcare Analytics Nov 25 th, 2016 Ozgur Kaynar Senior Business Consultant 1

2 Agenda Healthcare Trends & Challenges Teradata Approach to Healthcare Teradata Advanced Analytics Health Sector Analytical Use Cases Teradata

3 The Triple Aim of Healthcare for All Stakeholders 3 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

4 Healthcare Industry Challenges Adaption Challenges Expanding Coverage (ACA) New Products Payer and Provider Collaboration Population Requirements Care Improvement&Coordination Patient / Member Engagement Lifestyle Choices Drive Costs Up Chronic Conditions Frequency & Cost Are Rising Type 2 Diabetes Asthma Heart Disease Obesity New Technology New Communication Channels Social Media, Facebook, Twitter mhealth, Telemedicine DIY Healthcare (i.e. FitBits) Big Data Analytics 4

5 Main Technology Challenges for Healthcare Data & Application Silos 360 Patient Information Data Governance Quality & Security High Grow rate of Unstructured Data New Technologies, Adaption of Skillsets 5

6 Agenda Healthcare Trends & Challenges Teradata Approach to Healthcare Teradata Advanced Analytics Health Sector Analytical Use Cases Teradata

7 A New Approach is Required 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 KNOW MORE. DO MORE. Enable healthcare systems and insurer High Quality, Low Cost Care Coordination Consumer Engagement Driving Wellness / Growth Integrated Finance Performance Management Improved Population Health 7

8 8 Healthcare Industry Framework

9 Teradata Framework SERVICES APPLICATIONS DATA MODELS UNIFIED DATA ARCHITECTURE SERVICES Business Consulting Architect & Implement Optimize & Manage APPLICATIONS Integrated Marketing Management Analytical Partner DATA MODELS Solution Modeling Building Blocks Data Integration Roadmaps Health Care Data Model UNIFIED DATA ARCHITECTURE Data Platform Integrated Data Warehouse Discovery Platform 9 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 Industry Solutions Deep Industry Knowledge Industry Models, Partners and Teradata Services Analytics Platform The world s most scalable analytics platform for structured, multistructured and Big Data analytics Leader in Gartner Open standards

10 Agenda Healthcare Trends & Challenges Teradata Approach Teradata Advanced Analytics Health Sector Analytical Use Cases Teradata

11 Analyze all Data: Traditional + New Data Types Business Transactions (claims, member billing, enrollment, provider payments) + + Interactions (IVR, call center, hospital admits, likes, authorizations, tweets, weblogs, ) Observations (clinical notes, UM and CM notes, MRI s, machine sensors, medical charts) 11 Source: IDC, Gartner

12 Healthcare Analytic Discovery Success 1. Invest in Discovery Ask new (previously unanswerable) questions Move from focus only on transactions to interactions Teradata

13 Healthcare Analytic Discovery Success 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 Teradata

14 Healthcare Analytic Discovery Success 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 Teradata the latest analytics power tools

15 Healthcare Analytic Discovery Success 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 Teradata

16 Healthcare Analytic Discovery Success 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 Teradata analytics, +250 by 2016

17 Healthcare Analytic Discovery Success 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 Teradata latest analytics tools

18 Healthcare Analytic Discovery Success 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! Teradata How do we do that? We want you to be convinced with the value by answering your questions on your data

19 Agenda Healthcare Trends & Challenges Teradata Approach Teradata Advanced Analytics Health Sector Analytical Use Cases Teradata

20 Healthcare Discovery Use Cases 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 21

21 SHAREABLE, REPEATABLE APPS WITH TERADATA ASTER APPCENTER ADMISSION DRUG PATIENT DIABETES HEALTHCARE PRESCRIPTION SUSPICIOUS AFFINITY PATHS DIAGNOSIS PATIENT HL7 PATIENT DATA TO IMPACT COMPARE & SURGERY DOCTORS LENGTH PARSER AFFINITY READMISSION PROCEDURE ANALYSIS OF ANALYSIS STAY PATHS Teradata

22 HL7 DATA PARSER PARSE SEMI-STRUCTURED DATA FOR CARE INSIGHTS 23

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24 25 RAW HL7 DATA IS TOUGH TO ANALYZE

25 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 26

26 Healthcare Discovery Use Cases 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 27

27 HEALTHCARE PATIENT READMISSION PREDICT READMISSION BASED ON PATIENT METADATA AND USING PREDICTIVE ANALYTICS 28

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29 30 SELECT DIFFERENT METADATA FIELDS TO PERFORM THE ANALYSIS AGAINST

30 31 PLOT PREDICTIVE OUTCOMES BASED ON DIFFERENT FACTORS

31 32 NAÏVE BAYES DASHBOARD SHOWS READMISSION PREDICTIONS

32 33 GLM DASHBOARD SHOWS READMISSION PROPENSITY

33 Aster Analytics Evolving Use & Value Examples Behavioral (paths & pattern sequences) Affinity & Influencer Analysis: (Product, Service, Social, Warranty) Text Analytics (sentiment, documents, voice of customer ) Predictive Analysis (Behaviors, Components, Social, ) 34

34 Closing Thoughts 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 Teradata

35 37 For more information, please visit:

36 Appendix Real Use Cases Teradata

37 A Closer Look Patient Readmissions $26B Medicare Costs (2015) from Readmissions within 30 days Could you use a predictive model to assess the likelihood of readmission?...there s an App for that Quality of Care Profitability 65% Operational Efficiency Predictive Model Cost Control Medicare Readmissions deemed Avoidable Patient Satisfaction Population Management Teradata

38 Diabetes Patient Readmission Predictive Model 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 Teradata

39 A Closer Look Anomalous Profiles: Medicare/Medicaid Fraud Want to identify doctors with suspicious behavior?...there s an App for that $60B+ Conservative estimate of Medicare Fraud each year Population Management Behavioral Analytics Fraud Prevention Cost Control Teradata

40 Healthcare Fraud Anomalous Doctors Behavioral Analytics 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 Teradata

41 A Closer Look Path Analysis: Admission Diagnosis Procedure 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 Do you need to illuminate all clinical pathways traversed to optimize a patients journey?...there s an App for that Cost Control Population Management Quality of Care Path and Pattern Processing Efficiency Operational Efficiency Patient Satisfaction Teradata

42 Admission Diagnosis Procedure Pathways Path and Pattern 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 Teradata

43 AppCenter Healthcare Prebuilt Analytics Templates Repeatable Applications, Shareable Results 45 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