Getting to the Bottom Line: Investing in Data Analytics to ... · Getting to the Bottom Line:...

Getting to the Bottom Line: Investing in Data Analytics to Reduce Operational CostsSoyal Momin09/22/2017

Learning Objectives

2

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

Presbyterian Healthcare Services At a Glance

3

Data Overload and Increased Focus on Health Outcomes

4

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

The “7-fold Path”: A Unique Data and Analytics Operating Model to Guide the Way

5

Value Realization

Analytics Organization

Data Warehousing

& Architecture

Information Management

Value Discovery

and Design

Governance & Sponsorship

Change Management

Management Process

Core Processes

Support Process

Value Realization2016

6

Seeing is Believing

7

IM Governance Value Realization

8

IM Governance is the foundation for a data driven culture

What Keeps Me Up at Night?People, Process, Technology

9

10

People: OpportunitiesPartnership & Operations Knowledge

11

Process: OpportunitiesChange Management

12

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

What is Next?Data-Driven Culture

13

14

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

15

Data-Driven Culture

Data Democratization

Data Literacy

Data Analysts

16

Essential Ingredients

Insights Search – User Experience

17

Essential Ingredients

18

Essential Ingredients

19

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

Soyal MominSMomin@Phs.org505-923-7532