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Getting to the Bottom Line: Investing in Data Analytics to Reduce Operational CostsSoyal Momin09/22/2017
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Learning Objectives
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Recognize the changing data and analytics requirements faced by healthcare providers with health plans
Analyze a new seven-step data and analytics operating model
Appraise the integration challenges a data and analytics transformation represents in a joint payer/provider organization
Assess the benefits an end-to-end data and analytics transformation can deliver
Evaluate experience-based recommendations for staging a successful data and analytics transformation in a complex digital environment
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Presbyterian Healthcare Services At a Glance
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Data Overload and Increased Focus on Health Outcomes
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Presbyterian Healthcare Services had made several strategic technology investments
• Facets - Health plan operations (e.g. claims processing)
• Cactus - Provider credentialing
• Epic – EMR
Proliferation of data and new applications
• Clinical encounters, physician profiles, membership data, claims, cost accounting, etc.
• Data rich, information poor: Lots of data without any actionable information
Strategic need to differentiate
• Budgeted care, outcome-driven clinical excellence, other industries more advanced in data
and analytics
• PHS needed to optimize the electronic data and information it was capturing
The solution? A data and analytics strategy that would achieve the Triple Aim and serve
a philosophy of One Presbyterian
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The “7-fold Path”: A Unique Data and Analytics Operating Model to Guide the Way
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Value Realization
Analytics Organization
Data Warehousing
& Architecture
Information Management
Value Discovery
and Design
Governance & Sponsorship
Change Management
Management Process
Core Processes
Support Process
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Value Realization2016
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Seeing is Believing
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IM Governance Value Realization
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IM Governance is the foundation for a data driven culture
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What Keeps Me Up at Night?People, Process, Technology
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People: OpportunitiesPartnership & Operations Knowledge
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Process: OpportunitiesChange Management
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Technology: OpportunitiesExecution - How Do We Accelerate?
Building blocks and the optimal path to get us there while simultaneously
delivering the value
Where we were
(2016)
What will it
look like
(2019 and On)
Building
Blocks
Building
Structures
2017-18 2018-19Timeline
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What is Next?Data-Driven Culture
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Progression of Change/Data-Driven Culture Adoption
All parts of the organization proactively seek out data to identify options for solving
business problems and to make critical decisions
SUP
PO
RT
FOR
CH
AN
GE
Awareness
Understanding
Adoption
Commitment
TIME
Negative Perception
Confusion
Support Withdrawn
Navigation Leadership Enablement Ownership
Change Sponsors
Change Agents
Change Targets
Capability Terminated
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Data-Driven Culture
Data Democratization
Data Literacy
Data Analysts
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Essential Ingredients
Insights Search – User Experience
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Essential Ingredients
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Essential Ingredients
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Data-Driven Culture: Lessons Learned
1. Follow Product Management Approach with Data and
Analytics Tools
2. Information Management Governance is Key
3. Start Small and Show Value
4. Leverage Business Champion(s)
5. Consider Implementing Center of Excellence/Knowledge
Center to Increase Operational Knowledge of Data and
Analytics Staff