Enterprise Data Management:Consumer Driven Strategy

April, 2015

Prepared for CDO SUMMIT

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About Sutter Health

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Facts at a Glance 100 Communities

5,000 Affiliated Physicians 48,000 Employees

24 Acute Care Hospitals $9.6 billion in Revenues (2013)

31 Surgery Centers 10 NICUs

9 Cancer Centers 8 Cardiac Centers

5 Acute Rehab Centers 4 Trauma Centers

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Mission, Vision & Values

Vision:Sutter Health leads the transformation of health

care to achieve the highest levels of quality, access and

affordability.

ValuesMissionWe enhance the well-being

of the people in the communities we serve through a not-for-profit

commitment to compassion and excellence in health

care services.

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Vijay Venkatesan - Enterprise Data Management

Expert in healthcare data, analytics and business intelligence

Expertise and experience managing large enterprise data functions

 VP, Analytics and Business Intelligence, SPS

VP, Management Information and Analysis, KP

Divisional VP for Enterprise Client Reporting and Informatics, HCSC, Chicago

BS, Computer and Information Science, Cleveland State University

MBA, University of Michigan

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EDM Definition

EDM includes management, integration and visualization of information from:–Enterprise Transactional (structured and unstructured), –Operational, –Clinical, –Social, –Genomics–Device, and–Machine Data

To support internal and external needs of data in support of strategy, operations, financial, performance management, medical networks, clinical and patient experience functions.

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Objective and role for Enterprise Data Management

Objectives for Enterprise Data Management

Serve as a central, system-level hub for enterprise reporting and analytics • Includes retrospective, prospective, real-time and predictive data• Provide data visibility to all business and clinical functions• Govern the use and methods of reports and analytical tools via the Data Governance Council• Eliminate the creation of duplicate reports through EDM processes • Empower rapid decision-making through convergence of disparate analytics activities• Drive variation reduction in analytics approaches and methodologies

Curation, preparation, and visualization of enterprise data

Interpretation of data and reports

End Users(Local functions)

Enterprise Data Management

(System function)

Data Sources(Clinical, financial,

transactional, social)

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Enterprise Governance

Proposed end-state governance structure

Business Intelligence & Performance Management

Enterprise Content Management

Content Delivery (Real Time and Post

Transactional)

Releasable Data Management

Metadata Management

Master and Reference Data

Management

Data Quality Management

Data Stewardship

Big Data, Enterprise Data Warehouse and Data Marts, Unstructured Content(Information Assets Management)

Architecture and Technology Enablement

Information Strategy

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External Paradigm Shifts

CHANGING ECOMONIC INCENTIVES Payment Reform Total Care Accountability (Shared

Risks and Shared Savings)

CHANGING TECHNOLOGIES Smart phone applications Devices, Sensors and monitors Social media and digital content

CHANGING THE GAME Transparency Coordination and prevention Increased access Personalization anywhere

everywhere Affordability

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Is Creating Data Explosion and Liquidity

Currently physical

world and software

worlds are detached

Internet of things

promises to bridge this – It is about

sensors and actuators

everywhere

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And generating new demands for Insight from this data……D

ata

Volu

me

Customer Data

Point of Sale

Mobile

Structured Data

Click Stream

Social Network

Location-based Data

Text Data

IMHO, it’s great!

Future20152011

Collect, process, and deliver insight to support real-time business

Access relevant information from structured and unstructured dataDocuments

Internet

Genomic Data

1111

Dealing with Volume and Variety of Data……..

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Requires a Paradigm Shift…………..

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Current State of Data and Analytics….

Situation

Widely-dispersed, non-integrated disparate data

sources

Departmental analytics

Problem

Data inconsistency – No Single Source of Truth

Time and costs associated with data

gathering/information

Speed of diligence incorporating new data

sources

Desired State

Sub-optimal business impact enterprise wide

Optimized business impact enterprise wide

Departmental Analytics

Vendor driven projects

Decentralized model (Silos)

Federated with strong governance

Centralized

Transforming from….

Fragmented pockets of analytics capabilities

Non-standard approaches of

conducting the same analytics

Greater redundancy of information and analytics

Lack of information sharing across the enterprise

To….Common approach to data integration and management, governance and stewardship

Integrated predictive models which support a wide array of decision making

Repeatable, sustainable and credible process that can promote enterprise adoption

Process and models adapt to the changing business model.

Faster access to Data to drive insights that create actions and decisions

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Current State of Data – Technical View

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Our Strategic Objectives

Clinical Excellence and Quality-Driven

Evidence-based best practices to enhance quality of care High impact, high value for patients, populations, and communities at-large Expand access to high quality, cost effective health care

Operational Excellence and Financial Strength

Improve data transparency and accountability across stakeholder groups Diversification of revenues and to strengthen brand and market position Adapt to changing regulatory environment

Employer Excellence

Maintain market position as the best-in-class organization Embrace structures that are sharing the risks and rewards of delivering the highest quality care Enable employees with the right tools, technology, and efficient processes

Commitment to Industry Innovation

Enhance and transform the approach to personal health, patient health, population health Innovate delivery models that improve outcomes for all stakeholders Contribute life-saving best practices to the larger healthcare industry

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Our Opportunities

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Target State – From Data to Action

The end-to-end process view across data-to-insight and insight-to-action can help design effective analytics solutions and enable targeted change management to embed them into business processes. In many respects, this is the real power of Enterprise Performance Management (EPM)

INTEGRATEGENERATE

COMMUNICATE

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Vision – Imagine iTunes for Sutter Health – WeConnectYouOperational and Ready for Enterprise Access

Current Initiatives • Advanced Illness

Management (In Production)

• ACO Shared Savings (4/3/2015)

• Clinical Documentation Initiative (WIP)

• West Bay Operating Unit (WIP)

Other pilots underway

• SHEMS Resiliency• EMIM Exceptions• ASC• Finance System

Dashboard• S3 CBO Dashboard

• Clinical Use Cases:• Predictive Model for

Readmissions• PCOC Models• …..

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Benefits

Information Islands Transparency

Information Independence

Information Interdependence

Accumulation of Data

Insight and Exceptions

Regional Ownership Enterprise Assets

Technical Reporting Teams

Real-time action & Decision

Support

Next generation tools enabling forward looking insight and modeling

New projects follow an established set of guiding principles

Business owners will be notified of unfavorable trends or conditions

Shared information supported by common data definitions, tools, and access methods

Data Manipulation Actionable Decisions

Business users receive timely information that is tailored to their needs

Execution will position us to exceed customer needs and become a industry leader

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Approach to Transformation

HINDSIGHT FORESIGHTRemediate and stabilize

current environment• Develop roadmap to address

completeness and timeliness of data

• Assess current architecture; rationalize redundancies

• Accelerate services to customers

Enable key business functions• Execute program roadmap

for quick hits, medium, and long-term business capabilities

• Align and rationalize in-flight projects

• Deliver critical initiatives

Advance governance and stewardship

• Implement governance model to align priorities

• Establish alignment objectives and execution plan

• Establish communication plan on roles and responsibilities

Enhance and build upon current information foundation

• Implement near-term information architecture

• Implement information prioritization council

• Develop metadata and taxonomy

Focused on delivering value now

KNOW WHERE TO START

DON’T BOIL THE OCEAN

CREATE DEMAND ITERATE

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FUNCTION

TOOLS

USE CASES

Clinical Quality & Care – Readmissions, AIM, ACO, Sepsis etc. Patient Experience – Personalized Continuum of Care, Sutter Health Plus

Information ServicesHuman Resources

FinancialSupply Chain

Operations – Care Provider Allocation

Epic - Info View & Reporting

Workbench

ETLFor Data Warehouse

and Data Marts

MDM Data Quality

Data Governance

Big Data Business IntelligenceReporting

VisualizationAdvanced Analytics

EDM Enterprise Solutions

Big Data – Success Criteria for Enterprise Adoption

People Analytical talent is respected and

leveraged across functions A central pool of experts enables cross-

learning Shifting from analysis to discovery

Technology Relevant technologies are leveraged

consistently across the organization— technologies related to (1) data and infrastructure, (2) Business Intelligence and reporting, (3) advanced and predictive analytics, (4) visualization, (5) Streaming and Machine Learning, etc.

Governance Standardization of processes and cross-

leverage. The ongoing program for insights includes

prioritization of areas to build predictive analytics, review of the impact delivered, and a test-and-learn environment for continuous improvement leveraging Lean

Strategic alignment and funding models

Data: Data assets across the organization are

understood, and there is a plan to integrate data across functional silos;

Integrity of information across the organization is maintained, such that there is a “single truth“.

Quality of the data is established Compliance, Privacy and Security principles

are adhered

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Sutter’s current progress in Enterprise Data Management

Level 4Enterprise Adoption

Level 3Business Adoption

Level 2Technical Adoption

Level 1Infancy

Level 5 Data & Analytics

as a Service

• Thinking about it• Initial Big Data environment in place• Proof-of-Concept / Pilot

• Using Big Data mostly for storage / transform• Usage primarily by IT• Some Big Data explanatory analytics

• Leveraging the discrete LOB use cases• Structured and unstructured analysis• Predictive analytics applied to Big Data

• Leveraging use cases for multiple LOBs• Integrated metadata, quality and governance across

Big Data• Predictive insights integrated into business operations

• Operating as a “data service provider”• Self-serve data• Collaboration and sharing analytics across the

enterprise

• Socialization of Big Data Strategy underway

• Completed pilots on Big Data Platform

• Established a Big Data Ecosystem for exploration

• Exploratory analytics on “Readmissions” completed

• Integration into EHR proof-of-concept underway

Sutter is here

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Critical Success Factors – “You cannot discover new oceans unless you have courage to lose sight of the shore”

Establish a narrative for Data – Shrink the changeEngage Legal, Strategic Sourcing, Stakeholders, Leadership,

Competition etc.Engage IS Technical and Infrastructure teamsIdentify uses cases that improve foundational and enable

business value creationStrategic vendor partnerships to create proof-of-conceptKeep the narrative relevant at the executive and grass roots

levelDon’t compete for table stakes – Forget Reports – Talk about

improvements in quality and access to timely and relevant dataShow capabilities that are business impactingChange the paradigm from reporting to self-serviceEnable business value within 90 days

Questions? Thank You