Medicaid Enterprise Data Governance Approach

MESConference August 21, 2012 Rashmi Menon, Deloitte Consulting LLP

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Session Objectives

Common Barriers and Key Benefits to Data Governance

A Framework Supporting Medicaid Data Governance

Alignment with MITA

The Elements of Data Governance

•  Alignment with MITA

•  Organization Structure

•  Roles and Responsibilities

Examples from the Field: The State of Texas, Health and Human Services

Critical Success Factors

Q & A

Agenda

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– Summarize the benefits of establishing governance capabilities

– Outline governance program principles for Medicaid systems

– Discuss strategies to govern Medicaid systems to support data integration across programs

– Share experiences in delivering full-lifecycle data governance

Session Objectives

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Common barriers mentioned by states: “This is my data and I can’t share it…” “We already have a data dictionary…” “If it is not on a claim, it is not Medicaid data…” “Our program is very different…” “We don’t have a tool to do that…” “This will just become an auditing function…”

Common benefits mentioned by states: “Data is more reliable as it adheres to set ranges of values and correlates to its business definition…” “Clearly defining the difference between an Encounter record and a Paid Claim record…” “Allows identification of members and providers across programs…” “Spend less time examining anomalies on reports and more time making decisions based on data…”

Survey results1 related to barriers and benefits

1 Source: TDWI Best Practices Report, 2008

There are barriers to data governance, but many benefits as well

Common Barriers and Key Benefits to Data Governance

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View information

as a strategic asset

Data Architecture

Technology

Processes & Practices

Governance Metrics

Policies, Principles & Standards

Organization

Data Governance Framework

View information

as a strategic asset

Driven by

business value

Enabled with a change

management program

Linked to strategic initiatives

–  Data Architecture: Align to integrate data in Medicaid Enterprise Systems

–  Organization: Provide appropriate resources to manage framework

–  Policies, Principles & Standards: Guide organization on data areas for enterprise compliance

–  Governance Metrics: Define how to measure compliance

–  Processes & Practices: Manage organization operation in enterprise

–  Technology: Build and monitor methods of governance

Deloitte’s Data Governance Framework

Deloitte’s data governance framework assesses the maturity of the Medicaid Enterprise across six dimensions

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Medicaid Business Areas Business

Relationship Management

Member Management

Care Management

Operations Management

Contract Management

Provider Management

Plan Management

Performance Management

Eligibility  and  Enrollment  Management  

Finance Management

Data Architecture Policies, Principles & Standards Governance Metrics Processes &

Practices

Medicaid Data Governance

Data Quality

State Medicaid Agency Functions

MITA  Framework  

Organization Technology

State  Self-­‐Assessment  

Business  Architecture  

Informa?on  Architecture  

Technical  Architecture  

Data Governance – Alignment with MITA

Supports aligning agencies with MITA Maturity and provides for interoperability of data across Medicaid Enterprise Systems

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Structure

Decentralized Federated Centralized

Key Elements §  Decisions made at local level §  No centralized governing body

§  Decisions made at local level §  Advice of centralized body

§  Decisions made by single organizational body for enterprise

Benefits

§  Local resources respond to issues

§  Autonomous operation §  Data closely tied to program

operation

§  Consistency for enterprise vision and strategy of data

§  Monitoring overall programs §  Decisions and enforcement

established at local level

§  Strong focus on policy setting §  Compliance established across

enterprise §  Enterprise view of data

Challenges §  Inconsistent between programs §  Difficulty summarizing at

enterprise level

§  Reliance on close coordination §  Enforcement is loosely tied to

vision and strategy

§  Enterprise resources required §  May be contrary to agency

culture

Data Governance – Organization Structure

There are several potential structures for Medicaid data governance – each with their own benefits and challenges

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Communicate policies and

seeks improvement

Work together toward the delivery of information

Advise in implementation of

policies

Share information about applications

and technology

Communicate information definition and seeks improvement ideas

Data  Owners  ▪  Define  requirements  for  informa?on  

▪  Monitor  quality  and  availability  of  informa?on  

▪  Authorize  access  to    informa?on  

▪  Reside  in  program  

Executive Sponsors

 Data  Stewards  

▪  Advise  in  implementa?on  of  policies  

▪  Plan  data  requirements  ▪  Validate  control  of  informa?on  

▪  Coordinate  delivery  efforts  ▪  Reside  in  program    

Data  Custodians  ▪  Capture,  store,  retain,    and  dispose  of  informa?on    per  owner  requirements  

▪  Design  technical  infrastructure    to  meet  requirements  

▪  Verify  security  of  data    ▪  Reside  in  IT  

Data  Users  ▪  Select  the  best  data  source  ▪  Understand  the  data  accessed  

▪  Comply  with  data  management  policies  

▪  Create  data  extract  to  meet  specific  needs  

▪  Reside  in  program  

Cooperatively determine data

requirements

Data Governance – Roles and Responsibilities

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Project Example: The State of Texas, Health and Human Services

A short- and long-term plan supporting Medicaid data governance

Data Standards

Governance Policy

Governance Procedures

Change Management

Processes

DATA GOVERNANCE STRUCTURE DEFINITION

AND ACTION PLAN DEVELOPMENT

Governance Structure Definition

DATA GOVERNANCE PRELIMINARY PLANNING

Solution Concept

AssessmentData Matching

Identification of Master Data

Areas

ENTERPRISE LEVEL POLICY & PROCESS

DEFINITION PROJECT, PROGRAM AREA,

OR SYSTEM ALIGNED

IMPLEMENTATION

Strategic Roadmap

Business Metadata

Repository Outline

Productivity Software

Assessment

User Training and Education

Strategy

PROGRESSIVE DATA

GOVERNANCE PLANNING APPROACH

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Key Success Factors for Data Governance Implementation

– Obtain executive-level sponsorship

– Involve stakeholders from key Medicaid programs in data governance discussions

– Execute a plan that incorporates short- and long-term goals with a vision across the enterprise

– Use a flexible and robust framework that grows with the life of Medicaid data

– Plan and deliver consistent communications to stakeholders about data governance capabilities

– Gain commitment from stakeholders and programs for recommended enterprise data governance standards, processes, frameworks, roles, responsibilities, and agreements

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Questions?

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