An Enterprise Data Strategy for Powering Healthcare Modernization & Innovation MarkLogic Corporation & Intel Corporation

Size: px

Start display at page:

Download "An Enterprise Data Strategy for Powering Healthcare Modernization & Innovation MarkLogic Corporation & Intel Corporation"

Sybil Fox
6 years ago
Views:

1 An Enterprise Data Strategy for Powering Healthcare Modernization & Innovation MarkLogic Corporation & Intel Corporation BILL GAYNOR U.S. Healthcare Executive, MarkLogic MARCEE CHMAIT Strategic Development & Innovation, SCAN Health Plan DAVID E. DANHAUER, MD, FAAP System VP / CMIO, Owensboro Health DAVID DILORETO, MD, FACS, MBA HCEG Board Member SVP, GE Healthcare Camden Group

2 It ain t what you don t know that gets you into trouble. It s what you know for sure that just ain t so. The Big Short (2015) SLIDE: 2

3 HEALTHCARE IN 2017 Healthcare Organization Data Challenges $ 4 MILLION PER BREACH % 50 LOWER SATISFACTION % 20 REDUCED PAYMENTS $355 per record, $158 average in other industries Ponemon Study Compared to other service and insurance industries leveraging unstructured data Satmetrix High Price, High Volume FFS Procedures Most Impacted, Shift to Value-Based Models CMS SLIDE: 3

4 DATA CHALLENGES The Massive Cost of Legacy Technology 80 % OF TIME WASTED By data scientists just wrangling data NYT 60 % OF THE COST Of data warehouse projects is on ETL TDWI for Informatica $ 3.5 BILLION IN SPENDING In 2016 on data integration software Gartner SLIDE: 4

Healthcare s Experts at Integrating Data From Silos MATURITY CREDIBILITY EXPERTISE 1,000+ global customers

gov Aetna Consulting Services Data integration experts for payers, providers and HIT vendors 250+ partners

(lead funding from Sequoia Capital and Wellington) AMA, American Medical Association M Modal AHA, American

5 Healthcare s Experts at Integrating Data From Silos MATURITY CREDIBILITY EXPERTISE 1,000+ global customers Decade of customer success HEALTHCARE: Healthcare.gov Aetna Consulting Services Data integration experts for payers, providers and HIT vendors 250+ partners 525+ employees worldwide Wellcare ICA 24x7 Expert Support From true engineers Capitalized for success (lead funding from Sequoia Capital and Wellington) AMA, American Medical Association M Modal AHA, American Hospital association, Health Forum Online Community Free dev software, collaborate with tens of thousands of people Free Training Web-based and instructor-led SLIDE: 5

DATA CHALLENGES Solving Enterprise Data Integration Challenges 3 Top 10

Metadata, Structured & Unstructured Data, Real-time Delivery at Scale

Real-Time Enrollment The largest personal data integration government

- STEPHEN PARENTE, PHD, MPH, MS Global Trade Store Integrated Data,

6 DATA CHALLENGES Solving Enterprise Data Integration Challenges 3 Top 10 Payers Enterprise Data Hubs Consumer360, Medicaid, Operational Data, Metadata, Structured & Unstructured Data, Real-time Delivery at Scale and Centers of Excellence Data Services Hub & App Dev Platform for Real-Time Enrollment The largest personal data integration government project in the history of the Republic. - STEPHEN PARENTE, PHD, MPH, MS Global Trade Store Integrated Data, Integrated Post-Trade Processing Dynamic Content Delivery at Scale Integrated Data, Multi-Device Delivery SLIDE: 6

DATA CHALLENGES Popular Healthcare Next Gen Data Projects Enterprise Data Hub IT Initiatives Business Initiatives Master Data Management Data Governance & Compliance / Security Cybersecurity Metadata

7 DATA CHALLENGES Popular Healthcare Next Gen Data Projects Enterprise Data Hub IT Initiatives Business Initiatives Master Data Management Data Governance & Compliance / Security Cybersecurity Metadata / Search Hadoop Complement Hadoop Alternative Data Enrichment / Semantics IoT Health Device Data Building Apps FLEXIBLE DATA MODEL UNSTRUCTURED & STRUCTURED DATA FAST INGEST, INDEX, SEARCH & ALERTING ENTERPRISE RELIABILITY Mergers & Acquisitions Engagement & Service 360⁰ View & Search of Anything Communications & Social Media Payment Reform ACO, MACRA, FWA Quality & Outcomes STARS, HEDIS Real-time Alerts Product / Plan Management Clinically Integrated Networks (CIN) SLIDE: 7

8 Not Just a NoSQL Database An Enterprise Platform Native advanced features add greater value and deliver a simplified enterprise architecture SLIDE: 8

TRIPLE STORES DATA MINING KNOWLEDGE GRAPHS ENTITY EXTRACTION PREDICTIVE ANALYTICS MACHINE LEARNING A.I. COGNITIVE

9 Data Platform vs. Standalone Tools KEY- VALUE COLUMN NoSQL DB Includes Native Search & App Server DOCUMENT GRAPH PROPERTY GRAPHS TRIPLE STORES DATA MINING KNOWLEDGE GRAPHS ENTITY EXTRACTION PREDICTIVE ANALYTICS MACHINE LEARNING A.I. COGNITIVE COMPUTING MarkLogic Native Capabilities NATURAL LANGUAGE PROCESSING SLIDE: 9 CONFIDENTIAL Proprietary Information Do not disclose or distribute to third parties COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.

10 DR. DAVID DANHAUER OWENSBORO HEALTH

11 Owensboro Health Owensboro Health is a nonprofit serving communities in Kentucky and Indiana with two hospitals, a medical group comprising over 180 providers in 25 locations, a certified medical fitness facility and a cancer center. Owensboro Health has been recognized for outstanding care, safety and clinical excellence by The Joint Commission, U.S. News & World Report and Becker s Hospital Review. As the largest employer west of Louisville, Owensboro Health has 4,088 employees, and in FY 2015 saw 18,380 inpatient admissions and 823,072 outpatient encounters. SLIDE: 11

12 Physician Documentation Issues Challenges in EMR versus paper Patient story lost Time-consuming and cumbersome Limited Integration with transcription/voice recognition technology Note bloat Copy/paste Templating Lost communication with Care Team Coding issues SLIDE: 12

13 The Quest for Innovation Replace outdated legacy technology Innovative technology - Functional - Easy to use - Maintain workflows - Integrated - Improved quality of notes - Transform unstructured data to discrete data Metrics Driven - ROI SLIDE: 13

14 The Process for Catalyzing Innovation Search committee of key stakeholders Delineation of problem and needs Vendor search Head-to-head business and technical evaluation Formal ranking against needs Selection of vendor Project Development - Scope, timeline, budget, etc. - Metrics SLIDE: 14

15 Outcomes: Focusing on Physician Satisfaction Physician Satisfaction Ease of use - 5 ways to document to help meet differing providers workflows - Survey 70% favorable, 41% above average or exceeds expectations - No lost voice files due to cloud-based solution - Mobile Quality of notes Provider reviewing provider notes - Survey 83% favorable, 37% above average or exceeds expectations Turn-Arounds All turn-around times well beyond HIM requirements SLIDE: 15

16 Outcomes: Leveraging Unstructured Data Transform Unstructured Data to Discrete Data CAPD - 53% response to suggested documentation improvements - Most alerts related to ICD-10 documentation CDI - Coding is current without backlog Patient Safety/Quality - Abdominal aortic aneurysms - Lung nodules SLIDE: 16

17 MARCEE CHMAIT SCAN HEALTH PLAN

Part of the SCAN family, SCAN Health Plan is committed to keeping seniors healthy and independent.

18 SCAN HEALTH PLAN Keeping Seniors Healthy and Independent SCAN Health Plan is one of the nation s largest not-for-profit Medicare Advantage plans with nearly 180,000 members in California. Part of the SCAN family, SCAN Health Plan is committed to keeping seniors healthy and independent. In addition to Medicare Advantage, SCAN Health Plan also offers Special Needs Plans, including coverage for those who are dually eligible for Medicare and Medi-Cal. Our story 40 years of seniors serving seniors SLIDE: 18

19 Service Center/Portal Clearinghouse/Portals CARE CHALLENGES Consumer Access to Healthcare Seems Impossible EOB, Claims, Bills Health Plan Enterprise Systems Medical Records SLIDE: 19

20 CARE INNOVATION Innovation Requires a Leap Frog Approach Business Model Senior Experience Company Service & Data Model MA Plan SLIDE: 20

21 DOMAIN-CENTRIC CONSUMER-CENTRIC GRAPH TECHNOLOGY Connecting the Consumer to Their Ecosystem Facebook: Social Graph Walmart: Loyalty Graph LinkedIn: Economic Graph CrunchBase: Business Graph BBC: Storyline Graph Google s Knowledge Graph SLIDE: 21

EXPERIENCES CONTENT TRIGGER STAGE PERSONALIZED CARE Our Independent Living Knowledge Personal Pathways in a Graph PREPARE to live Independently ENGAGE in your local community RISE TO INDEPENDENT

22 EXPERIENCES CONTENT TRIGGER STAGE PERSONALIZED CARE Our Independent Living Knowledge Personal Pathways in a Graph PREPARE to live Independently ENGAGE in your local community RISE TO INDEPENDENT LIVING SIMPLIFY your daily living at home ADAPT as your capabilities change BALANCE their caregiving with life living PLANNING RETIRING SLOWING DECLINING TRANSITIONING WHAT TO EXPECT SOCIAL NEEDS LIVING NEEDS ADAPTING NEEDS PERSONAL NEEDS Senior-Specific Planning: For independent living: Financial plan Legal plan Social support Senior-Friendly Places: Working Volunteering Interest Groups Local Events Learning Venues Senior-Tailored Services: Getting to doctor appts. Transportation Eating well Housekeeping Yard work Senior-Designed Products/Services: Seeing Hearing Walking Talking Remembering Senior-Supporting Services: Personal care Family connection Friendly visitors Geriatric case management In-Home Tech Pet Care SLIDE: 22

PERSONALIZED CARE The Independent Living

23 PERSONALIZED CARE The Independent Living Situation Using Graphs Proactive Education Family & Friend Circle plans for independence Experience Content inspires a better way Progressive Profiles Personalized Content Streams Consumer Intent Brand Innovations Personal Assistant elevates results Senior-Tailored Services improves adoption Proactive Conversations Prescriptive Algorithms SLIDE: 23 Connected Life

Client Team Planning & Partnership Community

Assessed goals Guiding content Progressive

COMMUNITY EDUCATION Prepare Planning Needs

Capability Needs Balance Care Needs Community

Business Metrics CONNECTED ECOSYSTEM Employee

24 PERSONALIZED CARE The Independent Living Platform DIGITAL ENGAGEMENT GUIDED EXPERIENCE Client Team Planning & Partnership Community Education & Onboarding PERSONAL PATHS Assessed goals Guiding content Progressive solutions Assisted daily routine Rise Path COMMUNITY EDUCATION Prepare Planning Needs Engage Social Needs Simplify Home Needs Adapt Capability Needs Balance Care Needs Community Insight Consumer Surveys and Assessments Business Metrics CONNECTED ECOSYSTEM Employee App Senior Circle Rise Advisors Local Service Networks SLIDE: 24

25 DR. DAVID DILORETO HCEG BOARD MEMBER GE HEALTHCARE CAMDEN GROUP

26 The Healthcare Executive Group The HealthCare Executive Group (HCEG) is a national network of executives representing the supply side of healthcare: health plans, health systems, provider organizations and other health industry participants coming together to continually learn, grow, share and reshape the industry. HCEG s members are executive leaders from some of the most dynamic health plans, health systems, and provider organizations in the United States. The HealthCare Executive Group is supported by a select network of sponsor partners, industry advisers and alumni. A single membership fee covers all HCEG events and content including HCEG s Annual Forum, Executive Leadership Forums, a wide range of live and recorded education content and programming delivered via multiple channels, and other benefits. SLIDE: 26

27 SLIDE: 27

28 QUESTIONS Next Gen Data Tech in Healthcare Video: Harness the Power of Modern, Innovative Healthcare With MarkLogic and Intel (3:24) -

30 The MarkLogic Alternative An Operational and Transactional Enterprise NoSQL Database EASY TO GET DATA IN Flexible Data Model Data ingested as is (no ETL) Structured and unstructured data Data and metadata together Adapts to changing data and changing data structures EASY TO GET DATA OUT Ask Anything Universal Index Index once and query endlessly Real-time and lightning fast Query across JSON, XML, text, geospatial, and semantic triples in one database TRUSTED TO RUN YOUR BUSINESS Enterprise Ready Flexible cloud deployment Enterprise-grade data security Reliable data and transactions (100% ACID compliant) Out-of-the-box failover, replication, and backup SLIDE: 30

31 CLOUD Flexible Deployment Run It Wherever You Want Linux or Windows On-premises (virtual or physical) VIRTUAL Private cloud, hybrid cloud, public cloud AWS or Azure Any storage architecture, including Hadoop PHYSICAL SLIDE: 31 CONFIDENTIAL Proprietary Information Do not disclose or distribute to third parties COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.

32 How MarkLogic Data Hub Works... Improved Agility & Time to Market SLIDE: 32 CONFIDENTIAL Proprietary Information Do not disclose or distribute to third parties COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.

REDACTION, CERTIFICATION MANAGEABILITY OPS DIRECTORY, ROLLING UPGRADES,

33 PRODUCT ROADMAP & INVESTMENT THEMES MarkLogic 9 (early release phase) DATA INTEGRATION - SEMANTICS, QUERY, MOVEMENT SECURITY ADVANCED ENCRYPTION, REDACTION, CERTIFICATION MANAGEABILITY OPS DIRECTORY, ROLLING UPGRADES, TELEMETRY SLIDE: 33 CONFIDENTIAL Proprietary Information Do not disclose or distribute to third parties

34 How Does it Work? Schema-agnostic design Real-time indexing for search and query Reverse queries for event processing and alerting Bitemporal Scale-out shared-nothing cluster topology Analytics and Visualization Transactions SLIDE: 34 CONFIDENTIAL Proprietary Information Do not disclose or distribute to third parties COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.

35 Operational Data Hub Solution Next Gen Enterprise Integration Pattern Platform for building apps, analytics and running your business Convergent: Operational & Analytical. Provides 2- way interaction between users and data Contextual: Data harmonized with semantic metadata Data-centric: Integrates at the data level, not just functionally OPERATIONAL APPLICATIONS XML BIDIRECTIONAL ANALYSIS OF ALL DATA Data-Centric Architectural Pattern MULTI-CHANNEL DISTRIBUTION Cost-effective: Minimizes ETL, data copying, business silos, technical silos and people-centric integration JSON SSD, DAS, SAN, NAS, S3, Hadoop/HDFS Secure: Provides a platform for rich data governance SLIDE: 35 Complementary: Leverages existing assets and patterns CONFIDENTIAL Proprietary Information Do not disclose or distribute to third parties

INGEST HARMONIZE SERVE MarkLogic Data Hub

Applications RDBMS Source 1 Documents Enveloped

Documents Indexes, Query, Scripts Enveloped

Analysis/BI Operational Apps Content Feed

36 INGEST HARMONIZE SERVE MarkLogic Data Hub Source Systems Staging Final Consuming Applications RDBMS Source 1 Documents Enveloped Documents (Entity 1) Message Bus Source 2 Documents Indexes, Query, Scripts Enveloped Documents (Entity 2) Indexes, Query, Scripts Analysis/BI Operational Apps Content Feed Source N Documents Enveloped Documents (Entity N) Data Feeds Data Flow SLIDE: 36

37 Better Data Ingest, Index, Search, Harmonization & Enrichment 1 Ingest Data As-Is 2 Access the Data Operationalize MARKLOGIC APPROACH TO DATA INTEGRATION Harmonize & Enrich the Data SLIDE: 37 CONFIDENTIAL Proprietary Information Do not disclose or distribute to third parties COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.

38 JSON XML SEMANTIC DATA GEOSPATIAL DATA BINARY MLCP HOW MARKLOGIC DELIVERS Load Data As-Is Load structured and unstructured data Keep data and metadata together Harmonize data in the database Ability to skip: OTHER METHODS REST APIs, Java Client API, Node.js Client API, Java /.NET XCC Upfront modeling ETL tools SLIDE: 38

39 JAVASCRIPT XQUERY REST API JAVA API SPARQL SQL VIEWS TRANSACTIONAL APPS SEARCH APPS ANALYTICAL APPS HOW MARKLOGIC DELIVERS Developer and User Access Variety of Interfaces Modern programming languages familiar to developers Application Services Simplifies architecture and speeds up development Developer Productivity Tools and frameworks to speed delivery SLIDE: 39

Real-Time Analytics Range indexes can be used for Faceted search Aggregation and visualization Analytics including custom user-defined functions Co-occurrence SQL, ODBC, and BI

40 Real-Time Analytics Range indexes can be used for Faceted search Aggregation and visualization Analytics including custom user-defined functions Co-occurrence SQL, ODBC, and BI integration ODBC SQL Range Indexes SLIDE: 40 CONFIDENTIAL Proprietary Information Do not disclose or distribute to third parties COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.

If You Have an EDW Enterprise Data Warehouse Batch-oriented Analysis only Structured data ETL and model dependent Reactive, query-based MarkLogic Data Hub

41 If You Have an EDW Enterprise Data Warehouse Batch-oriented Analysis only Structured data ETL and model dependent Reactive, query-based MarkLogic Data Hub Real-time interactive Two-way analysis & operations All of your data Load data as-is, model alongside discovery Proactive, alert-capable at massive scale SLIDE: 41

If You Have a Data Lake Data Lake Issues with data governance and provenance Batch-oriented Analysis only Save everything and process with brute

governance and provenance features Real-time Two-way analysis & operations Save and index everything for sub-second processing Mature and

42 If You Have a Data Lake Data Lake Issues with data governance and provenance Batch-oriented Analysis only Save everything and process with brute force Simplified security model Limited or no context Multi-layered ecosystem encourages technical silos MarkLogic Data Hub Advanced data governance and provenance features Real-time Two-way analysis & operations Save and index everything for sub-second processing Mature and fine-grained security model with redaction features Advanced Semantics capability for rich context Multi-model capability eliminates technical silos SLIDE: 42

Building a Data Strategy for a Digital World

Building a Data Strategy for a Digital World Jason Hunter, CTO, APAC Data Challenge: Pushing the Limits of What's Possible The Art of the Possible Multiple Government Agencies Data Hub 100 s of Service