Christine Bessler, CIO at ProHealth Care,demonstrates how ProHealth Care became the first healthcare system to produce reports and data out of Epic's Cogito data warehouse in a production environment. In this slideshare, you'll learn: How they delivered clinically integrated insights to 460 physicians How access to analytics allows their physicians to easily see which patients need important health screenings or care interventions, setting the stage for enhanced preventive care and better management of chronic diseases ProHealth Care's strategy to integrate data from Epic with information from other EMRs and data sources to deliver clinically integrated business intelligence How the organization is positioning itself to deliver against an advanced self-service BI capability in the future

1. facebook.com/perficient twitter.com/Perficient_MSFTlinkedin.com/company/perficient
ProHealth Care - Innovating Population Health
Management with Clinically Integrated Insights
Christine Bessler, CIO, ProHealth Care
Juliet Silver, Director, Perficient

2. Perficient is a leading information technology consulting firm serving clients throughout
North America.
We help clients implement business-driven technology solutions that integrate business
processes, improve worker productivity, increase customer loyalty and create a more agile
enterprise to better respond to new business opportunities.
About Perficient

3. • Founded in 1997
• Public, NASDAQ: PRFT
• 2013 revenue ~$373 million
• Major market locations throughout North America
• Atlanta, Boston, Charlotte, Chicago, Cincinnati, Cleveland,
Columbus, Dallas, Denver, Detroit, Fairfax, Houston,
Indianapolis, Los Angeles, Minneapolis, New Orleans, New
York City, Northern California, Philadelphia, Southern
California, St. Louis, Toronto and Washington, D.C.
• Global delivery centers in China, Europe and India
• >2,100 colleagues
• Dedicated solution practices
• ~90% repeat business rate
• Alliance partnerships with major technology vendors
• Multiple vendor/industry technology and growth awards
Perficient Profile

4. BUSINESS SOLUTIONS
Business Intelligence
Business Process Management
Customer Experience and CRM
Enterprise Performance Management
Enterprise Resource Planning
Experience Design (XD)
Management Consulting
TECHNOLOGY SOLUTIONS
Business Integration/SOA
Cloud Services
Commerce
Content Management
Custom Application Development
Education
Information Management
Mobile Platforms
Platform Integration
Portal & Social
Our Solutions Expertise

5. Our Microsoft Practice

6. Strategic Business Consulting
Project Management
Information
Exchange
BI & Analytics
HIPAA 4010/5010 &
ICD-10 Compliance
System
Interoperability
Connected
Health
Technical Consulting
Knowledge Transfer & Delivery
Healthcare Solution Offerings

7. Select Healthcare Clients

8. Introduction
• Christine Bessler, PMP
CIO / VP of Information Technology
ProHealth Care
- Responsibility over information systems, telecommunication,
informatics (business and clinical) and project management office
- Involved in many professional and charitable organizations
- Serves on several boards involved in employee assistance and
promoting technology in healthcare
- Contributes as a mentor and educator in teaching opportunities to
students and other professional networks focused on topics on her
expertise in technology, governance, strategic planning, and project
management
- Has developed accredited courses on the topics of change
management, as well as portfolio and project management

9. Introduction
• Juliet Silver, MBA, FCMI, PMP
Director, Healthcare Strategic Advisory Services
Perficient, Inc.
- Healthcare Analytics Strategist and Management Consultant
- Supports ProHealth Care and other clients with guidance on BI
program leadership, establishing the Data Governance framework,
and creating the roadmap to operationalize the BICC
- Specializes in the development of strategic roadmaps and
implementation plans for providers, with specific focus on data
warehousing, clinical data models, healthcare business
intelligence and data analytics

10. Agenda
• Introduction
• An Innovative Approach
• The Result and Solution
• ProHealth’s Journey
• Risks and Lessons Learned
• BI Program
• Data Governance
• Business Intelligence Competency Center
• Q & A

11. AN INNOVATIVE APPROACH TO
POPULATION HEALTH
MANAGEMENT
Christine Bessler, CIO, ProHealth Care

12. ProHealth Care Overview
• Community-focused healthcare system
• Regionally focused IDN in Waukesha, WI
• 15 primary care facilities, 3 hospitals, home health care, hospice
services, long term care and senior residence communities, health and
fitness center
• Not-for-profit organization
• 1000 physicians and 4800 employees
• Attested to Meaningful Use Stage 1 for hospitals and physicians
• Attained Stage6 designation on the HIMSS Analytics EMR Adoption
Model (EMRAM)

13. An Innovative Approach to Population Health
Management
Why Innovative?
• ProHealth Care is the first to use Epic’s Cogito data
warehouse in conjunction with the Microsoft BI stack to
manage population health
• ProHealth Care is the first health care system to use
Epic’s Cogito data warehouse in a production
environment

14. The Result
• Physicians can easily identify gaps in care
• Physicians have analytics tools to enhance preventive
care and the management of chronic diseases

15. The Solution
• Providers and/or their administrator(s) can assess the system only via supplied
credentials and secure login process which ensures the confidentiality of the
Protected Health Information (PHI) contained within the system
• Upon login, users must specify parameter values to run their report(s), including
provider specialty, provider name and measurement period month

16. The Solution
• After selecting the desired report parameter values, the physician performance profile is
displayed for the user. Measure are arranged by domain (e.g. Access, Administrative, Community
Benefit, Safety, Satisfaction, etc.) to assist in report organization and comprehension.
• Key report elements include:
• Metric-specific performance targets, total metric population, and specialty average
and rank

17. The Solution
• Some metrics allow users to drill-down on their performance to display patients with
gaps in care that require additional action or documentation during the selected
measurement period. These are displayed via underlined hyperlink.
• Users can click those hyperlinks to get their list of patients that are in that particular metric:

18. The ProHealth Care Journey

19. • Derive increased enterprise information value from existing
investments in EPIC EHR
• Enhance the level of clinical integration
• Address population health initiatives and proactive care management
of chronic conditions
• Provide data collection, measurement and analysis for ACO measures
Key Objectives

20. Business Challenges
• Initial challenges on the business side:
• Unable to monitor quality measures for ACO in a timely fashion
• Unable to monitor operational data in a timely fashion
• Inability to properly determine the cost of care (by business unit,
physician, etc.)
• Lack of personnel and funding
• Centralized model supporting report creation not sufficient
• Lack of decentralized reporting tool expertise within the various
business units
• Scope and competing priorities
• Need to align with key business initiatives/strategic plan
• Siloed culture
• Limited collaboration

21. Clinical Challenges
• Initial challenges on the clinical side:
• Data Use
• Information not actionable due to timeliness of data availability
• Workflow/Process
• Various Epic workflows not implemented
• Processes not always aligned with best practices
• Documentation
• Inconsistency in data and terminology causing confusion by providers

22. Technology Challenges
• Initial challenges on the technology side:
• Integration
• Clinical, operational and financial data not integrated
• Excessive manual touch points
• Data Integrity
• Mistrust of data
• Data definitions need to be defined, agreed and socialized
• Assessment of current tools
• Various best-of-breed still being utilized
• Multiple clinical systems (Epic, Centricity, McKesson, “homegrown”)
• Multiple reporting tools (Workbench, Crystal, Deski, Webi, Excel)
• Epic EHR not fully utilized
• Lack of standardized delivery platform
• Resources
• Skillsets not aligned with current needs and priorities

23. The Strategy
• Establish organizational commitment to develop an Business
Intelligence Strategic Roadmap and Implementation Plan
• Engage a national systems integrator to facilitate strategy development
and support implementation
• Implement the plan in a phased approach

24. The Focus:
 Analytic capabilities
 Data governance
 Business Intelligence Competency Center
 Organizational change management
 Reference architecture & technical foundation
 Data foundation
Plan and Roadmap for Enterprise BI, Data Warehousing and Data Governance:
 Improve enterprise accessibility to trusted data, ensuring data quality, and establishing
confidence in the data for improved business performance
 Translate complex BI Program and Data Governance vision and strategy into
manageable, phased deliverables
 Establish the enterprise BI technical foundation and reference architecture
 Realize transformational enterprise information management, cultural change
management and organizational readiness
GOVERNANCE
CHANGE
MANAGEMENT
BI COMPETENCY
CENTER
TECHNICAL
FOUNDATION
DATA
FOUNDATION
ANALYTIC
CAPABILITIES
BI Strategic Plan

25. Plan Inputs and Drivers
• Rapid time to market to provide PHC and ProHealth Solutions (our
ACO) with the necessary data for the needed quality metrics
• Leveraging resources and integrating services between PHC and PHS
• Leveraging existing technology infrastructure and tools
• Ability to extract information from non-Epic source systems (e.g.,
claims data, Press Ganey, etc.)
• Ability to integrate operational, financial and clinical data into one data
warehouse and report from a single source
• A system that is flexible and scalable to promote the ability to adapt to
changing requirements over time
• A security framework which enables secure and appropriate access to
the reports and analytics

26. Key Requirements
Requirements:
• Initial priority was to address ACO analytical and reporting
requirements
• Implementation timeline completion within six months
• Minimize cost – look for most cost-effective approach
• Enable expansion of analytical and reporting capabilities for future
priorities

27. ACO Requirements
• 33 required quality measures that are part of the quality
performance standard, including:
• Consumer Assessment of Healthcare Providers and Systems
(CAHPS) patient experience survey measures
• Claims-based measures
• Electronic Health Record (EHR) Incentive Program measure
• Required Group Practice Reporting Option (GPRO) web interface
quality measures
• Required for purposes of ACO participants earning a Physician Quality
Reporting System (PQRS) incentive under the Medicare Shared Savings
Program
• Physician profiles to enable monitoring of screenings and care
interventions

28. Analytical Needs
Benchmarking
Outcome Analysis
ACO Analytics and Management
Population
Health
Management
Spend Analysis
Value Based Pricing
Claims AdjudicationValue Analysis
Quality
Labor Supply Optimization
Supply Chain Optimization
Waste and
Harm
Operations Management
Optimization
Efficiency & Effectiveness
Analysis
Disease Management
Practitioner Profiling & Quality
HEDIS 2010 (select measures)
Savings Opportunities
Harm Avoidance
Safety
Pharmacy Analysis
AHRQ
Harm Avoidance
Alerting
Actuarial Analysis
Claims Handling
Claims Adjudication
P4P
Patient Satisfaction
Performance Improvement

29. How We Made Our Platform Choice
Considerations:
• Could we leverage Epic’s Cogito DW model?
• What technology platform was needed (wanted to leverage existing
investments in technology)?
• If using Epic’s Cogito DW, how dependent would we be on Epic for
future development?
• Would we have real-time reporting?
• What was the time to value proposition?
• Would we have access to historical data?
• What were the implementation and annual costs?

30. How We Made Our Choice
Comparison of Options Considered:
Option 1 Option 2 Option 3 Option 4 Option 5 Option 6
Full Cogito +
custom
clinical
repository
Full Cogito +
packaged
solution
Partial Cogito
+ custom
clinical
repository
Partial Cogito
+ packaged
solution
Custom EDW
+ custom
clinical
repository
Packaged
solution for
clinical
repository
Leverage Epic's Cogito Yes Yes Yes Yes No No
Database Platform
MS SQL Server
2012 required
MS SQL Server
2012 required
MS SQL Server
2012 required
MS SQL Server
2012 required
Databased
platform
independence
MS SQL Server
2012 required
Epic dependency High High Medium Medium No No
Near Real-Time Reporting No No No No No Yes
Time to Value High Risk High Risk Medium Risk Quick Win High Risk Quick Win
Historical Data Yes Yes Yes Yes Yes No
Implementation Cost 5M 5M 6M 5M 11M 5M
Annual Costs <20K 550K <20K 550K <20K 750K
Narrowed options

31. How We Made Our Choice
Criteria
MS Stack
Solution
QlikTech
QlikView
SAP BI
Dashboards Tableau Tibco Spotfire
Cost of initial purchase and
maintenance Low Medium High Low Medium
Do we currently own it Partially No No No No
Can current IT Infrastructure
Support it Yes No Yes No No
Scalability Good RAM Limited Good Good Hardware Limit
Hiring related skill set (BA and
Report Writers) Moderate Difficult Moderate Difficult Moderate
Options Considered for Visualization Tools:
Narrowed options

32. How We Made Our Choice
Options Considered for BI Suite:
Narrowed options
Criteria MS SQL 2012
Business
Objects
(SAP) Oracle OBIEE IBM Cognos
Cost of initial purchase and
maintenance Medium Medium High High
Do we currently own it Yes Yes No No
Can current IT Infrastructure
Support it Yes Yes No No
Scalability Good Better Best Better
Hiring related skill set (BA and
Report Writers)
Relatively
Difficult Available Available Available
Supports Self-Service Reporting Average Best Better Better
NOTE: Considered other standard BI Suits like Microstrategy, SAS, etc.
and ruled them out.

33. How We Made Our Choice
Options Considered for Database Technology:
Selected option
Criteria MS SQL 2012
MS SQL
2008r3 Oracle 11g IBM DB2
Cost of initial purchase and
maintenance Medium Medium High Very High
Do we currently own it Yes Yes 10g No
Can current IT Infrastructure
Support it Yes Yes Yes No
Scalability Good No Best Better
Adequate data storage
capability Good Worse Better Best
Hiring related skill set (DBA
and SA) Moderate Available Moderate Difficult
Available HL7v3 RIM data
model Feb. 2013 Yes Yes (costly) Yes
Visualization and data
discovery Yes No Yes Yes
In-memory database
technology Yes No Expensive Expensive
Proven technology No Yes Yes Yes
NOTE: Considered cloud solutions (Azure, Google etc) and appliances
and ruled them out.

34. Solution Defined  Option 3
• Use Cogito DW first release as initial framework, but don’t wait on
future upgrades. Incorporate rest of Epic data elements, as needed
• Have ability to expand on DW model with Financial, Operational and
other data
• Consolidate PHS (ACO) transactional data into Cogito DW.
• Leverage existing technology
• Take moderate approach to cost, addressing speed-to-market

35. Business Value
• Use Cogito as the initial framework (lower cost of initial setup), but
allow expansion of data model for loading other sources
• No dependency on Epic upgrades to bring rest of data from Clarity
• Leveraged existing infrastructure technologies (database, visualization,
etc.)
• Able to deliver initial program within six months
• Quickest realization of ACO Quality Measures with lowest risk
• Minimal cost

36. Phase 1: Solution Architecture

37. Tools
Category Vendor Product
Data Warehouse
Model
Epic Systems Cogito
BI Reporting Microsoft SSRS
Data Integration (ETL) Microsoft SSIS
Presentation Microsoft SharePoint
Database Microsoft SQL Server

38. Risks
Leading Edge Technology (for ProHealth)
• Cogito Data Warehouse (CDW) not in production for
Epic at any location:
• Starting early
• Epic Systems assisting
• Phased approach
• SharePoint 2013 (initial introduction with 2013 BI Team
Deliverables):
• Augmenting team with SharePoint expertise
• Minimal risk

39. Risks
Leading Edge Technology (for ProHealth)
• New Skills Required (SSRS, SSAS, PowerPivot) will
require education of end users and IT – planning in
process:
• Consultants augmenting team with appropriate skills
• New additions to team (e.g., PowerPivot trainer, etc.)
• Dearth of data definitions and comprehensive data
integration (e.g., profile measures by specialty, etc.):
• Data elements in support of ACO metrics refined to smaller
subset

40. Lessons Learned
• Epic’s Cogito was in early stages of development:
• Gap analysis of initial Cogito data model unveiled critical missing
elements that needed to be built
• This took an extra few weeks of development that was unplanned
• Security needed on physician profiles was complex:
• Enabling practice managers to have access to providers profiles
required establishing new procedures for tracking provider to
manager relationships  did not exist
• Building business glossary was daunting task:
• Organization not prepared for complexity in establishing common
definitions for initial data elements

41. Lessons Learned
• Enabling data dictionary was unplanned:
• Did not prepare for how to track metadata in support of DW  tool
needed to be selected
• Budgeting for appropriate resources:
• Due to timing of implementation of BI program, organization did not
have time to appropriately plan for new roles needed (Data Quality
Manager, BICC Manager, etc.)
• Organization not prepared for time needed from data owners and
data stewards

42. OPERATIONALIZING THE BI PROGRAM,
DATA GOVERNANCE & BICC AT
PROHEALTH CARE
Juliet Silver, Director, Strategic Advisory Services, Perficient
Inc.

43. BI Roadmap Work Streams
Business Intelligence Roadmap
Data
Governance
BI Program
BICC
Technology
Foundation
Stakeholder Engagement
Release Master Plan Project and Program Management
Information Life-Cycle
Success Metrics
Communication Plan
Change Management
 Governance Policies
 Governance Charters
 Data Quality Management
Plan & Quality Assurance
 Audit, Logging and
Reporting
 Master Data Management
 Data Management
 Classification and Metadata
 Data Stewardship
 Data Standards Data Architecture
 Data Security
 Governance Organization
Framework and Processes
Program Objectives
 Organizational
Structure
 Resources, Roles,
Responsibilities
 Operational
Framework
 Processes
 Service Catalogue
 Functions
 Architectural Review
Board
 Transactional Data
Foundation
 Data
Integration/Distribution
Framework
 Data Storage
Framework
 Data Access Services
 Information Delivery
Framework
 Data Structure
 Systems and Tools Recommendations
and Selection
 Reference Architecture
Implementation
Release 1: Charter Domain Release 2
Refine Roadmap
Move to
Implementation
Phase(s)

44. October 31st Q1 2014 Q2 2014 Q2 2014 Q3 2014 Q4 2014 Q1 2015Q1 2014Q4 2013
PROHEALTH BUSINESS INTELLIGENCE ROADMAP (DRAFT)
Program
Governance
BICC
Stakeholder
Engagement
Release Strategy
Project Plan
Information Life-cycle
Analyze Phase
2 Report
Requirements
Huron Report
Release
Master Plan
Program Visual
and Narrative
BI SharePoint Site
Publish
Release
Master Plan
Draft Project
Plan
Update
Project Plan
Model Flow –
Part 1: ACO/
P4P
Model Flow –
Ad-Hoc
Requests
Deliver Phase 1 ACO/P4P Measures Deliver Phase 2 ACO/P4P Measures
Report Requirements | Development | Test | Release Report Requirements | Development | Test | Release Report Requirements | Development | Test | Release
Data Arch. | ETL | Quality | Classification | Bus. Glossary
Phase 2 Phase 3 Phase 4
Data Arch. | ETL | Quality | Classification | Bus. Glossary Data Arch. | ETL | Quality | Classification | Bus. Glossary
Communication
Plan
Comm. Plan
Framework
Publish
Comm. Plan
Socialize Phase
2 Release
Demo
Dashboards,
Report etc.
User
Feedback &
Champions
Project
Reporting
Project Plan
Phase
Updates
Project
Retrospectives
Project
Reporting
Project Plan
Updates
Project
Retrospectives
Project Plan
Updates
Project Reporting
Project
Retrospectives
Model Flow
Part 2: ACO/
P4P
Refine Model
Flow Phase 2
Refine Model Flow
Ad-Hoc
Align Comm.
Plan to Program
User
Training
Program
Status &
Phase 2
Emails,
presentations
Announcements
BI SharePoint Site
Socialize
Phase 3
Release
Demo
Dashboards,
Report etc.
User
Feedback &
Champions
User
Training
CohortCohortCohort
Socialize
Phase 4
Release
Demo
Dashboards,
Report etc.
User
Feedback &
Champions
User
Training
Program
Status &
Phase 3
Emails,
presentations
Announcements
BI SharePoint
Site
Program
Status &
Phase 3
Emails,
presentations
Announcements
BI SharePoint Site
Metrics
Develop Draft
Metrics/
Scorecard
Verify
Measures
Build System of
Measurement
Publish Program
Measurement
Model Flow
Phase 3
Refine Model
Flow Phase 3
Refine Model Flow
Ad-Hoc
Model Flow
Phase 4
Refine Model
Flow Phase 4
Refine Model Flow
Ad-Hoc
Policies
Classification and
Metadata
Data Stewardship
Data Architecture &
Security
Data Quality
Governance Framework,
Audit, Logging and
Reporting
Validated data set for self-
service
Human Resources
BICC Framework
and Process
Functions and
Service Catalogue
Tools/Platform
(Technical
Foundation)
ARB
Staff Key
Positions, Role
Definitions
Training &
Education
Support Release
Mgmt.
ACO/P4P
Business
Glossary Draft
Draft Policies Review, update, approve Publish Policies
Review ACO/
P4P Business
Glossary
Approve and
Publish
Glossary
Assign
Stewards for
ACO/P4P
Data
Governance
Workshop
Cogito
Technical
Metadata
Data Modelling
for extended
Model
Establish New
Classification
Priorities
Assign
Stewards for
Priorities
Develop
Stewardship
Guidelines
DQ Management Plan Draft
Update with
ACO DQ
Standards
Review with
Data Stewards
Revise and
publish DQM
Plan (1st Ed.)
Approve
ACO/P4P
Data Security
Deliver Phase 1 Data
Snr. Executive
Sign-Off
Review Policies
Revise and
publish policies
Iterate through
classification
priorities
BICC Mgr, DQ
Lead, Architect,
Testers, Support
& Training
Release Mgr,
Infrastructure,
Security, ARB
Training/
Education
Demand
Management
Quality
Assurance
User Support and
Help Desk
QA for ACO/
P4P
Modify Help
Desk System
SharePoint KM
and BI Reporting
Environment
Business
Glossary
Repository
Report
Developers,
Analysts
Demand
Management
Demand
Management
app.
Report
Request
Delivery
BI
Developers
Dataflow
and DQM
Reports
Repository
ARB Process
Metadata
Admin.
Protoyping
/ App Dev.
BI Dev.
BI Dev
Studio,
PowerPivot
Approve and
Publish updated
Glossary
Data Quality
Management
Workshop
Establish New
Classification
Priorities
Iterate through
classification
priorities
Approve and Publish
updated Glossary &
Metadata
Assign
Stewards to
Priorities
Perform DQM
Tasks
Document Data
Quality Assurance
Establish New
Classification
Priorities
Iterate through
classification
priorities
Approve and Publish
updated Glossary &
Metadata
Assign
Stewards for
Priorities
Perform DQM
Tasks
Document Data
Quality Assurance
Risk Register,
Audit and
Reporting
Issues and
Decisions
Information
Risk
Management
Risk Register,
Audit and
Reporting
Issues and
Decisions
Information
Risk
Management
Revise and
publish DQM
Plan (2ndt Ed.)
Metadata
Integration &
Data Standards
Risk Register,
Exception
Reporting
Issues and
Decisions
Information
Risk
Management
Revise and
publish DQM
Plan 3rdt Ed.)
SLA’s
Data
Architecture
Phase 2
MDM
Security
Architecture
Phase 2
Elaborate Phase
2 Technical
Requirements
Technical
Requirements
TBD
Elaborate Phase
3 /Ad-hoc
Technical
Requirements
Technical
Requirements
TBD
Elaborate Phase
4/ Ad Hoc
Technical
Requirements
Technical
Requirements
TBD
MDM Admin.
Master Data
Management
Phase 3 Data Architecture, Security
and MDM Review and Approval Phase 4 Data Architecture, Security
and MDM Review and Approval
Review and update Human Resources and Organization Chart
Review and update Framework and Processes
Review and update service catalogue
Phase 1
Solution
Architecture
Phase 2
Solution
Architecture
Solution & Enterprise
Information
Architecture
Information
Life-cycle and
Data Lineage
Solution & Enterprise
Information
Architecture
ProHealth Care Roadmap Work Streams

45. Data
Creation
Data
Storage
Data
Movement
Data
Usage
Data
Archiving
• Data Modeling
• Data Taxonomy
• Data Migration
• Data Storage
• Data Access
• Data Archiving
• Data Retirement
• Data Profiling
• Data Cleansing
• Data Monitoring
• Data
Compliance
• Data Traceability
DATA
STRUCTURE
DATA
ARCHITECTURE
DATA
QUALITY
• Data Privacy
• Data Retention
• DSP Data
Sharing
• Dealer Data
Sharing
• Data Ownership
• Data
Stewardship
• Data Policies
• Data Standards
• Data
Legalization
• Master Data
Management
• Reference Data
Management
• Metadata
Management
DATA
SECURITY
DATA
GOVERNANCE
MASTER DATA
& METADATA
Managing
Data
Data Governance & Managing Data

46. Data Governance Committee
• Chair and Executive Sponsor:
• Chief Innovation Officer
• Co-Chairs:
• Director, Performance Excellence
• Director, Business Intelligence
• Standing Members:
• CIO / VP of Information Technology
• Dir. Behavioral Hlth/Staffing, Hospital Division Directors
• Director, HIM
• Manager, Strategic Workforce Planning & HR Business
Intelligence
• Director, Business Development
• Director, Finance
• Medical Informaticist
• BICC Manager, Data Architect and Data Quality Lead will be in
attendance at Governance meeting, providing linkage back to
the BICC
• Ad Hoc Members:
• Additional data owners and data stewards attend governance
meetings, as needed, to discuss relevant issues

47. Data Governance Initiation
• Charter with scope, guiding principles, scheduled activities,
voting and decision rights
– Steering Committee and Data Governance Committee, informs
data strategy, prioritize work/project requests, address data
quality and information assurance concerns, approves business
metadata
• Policy Development
– Develops policies that encourage the desired organizational
behavior with respect to information security and data
classification, data quality and standards, life-cycle management
• Change Management, Stakeholder Engagement &
Communication
– Change Control, Visuals/Narrative, BI Demo Showcase

48. Data Governance Priorities
Examples of initial deliverables:
• Development of data governance policies
• Establish role of data stewards
• Ensuring that the data is properly defined and used
throughout the enterprise
• Development of business glossary and data dictionary
• Survey of power users and analysts to determine data
owners
• Training for appropriate end users (e.g., for executives,
data stewards, etc.)
• Development of Release Master Plan
• Development of Data Quality Management Plan

49. Data Governance / BICC
Data Governance
• Approve BICC estimates on Strategic requests
• Define Information requirements
• Control Change management process
• Define Data policies and standards
• Define Data Quality
BICC
• Manage Operational Resources
• Take decisions on day-to-day operational issues
based on Governance guidelines
• Approve Work group estimates
• Manage Work Group resource utilization
• Track and Complete demand request
• Make recommendations on technology/
processes/standards

50. BICC
• The (BICC) is responsible for promoting optimal use of business
intelligence across the organization.
• The BICC provides a central location for driving and supporting the
organization’s overall information delivery strategy.
• Staffed with representatives from the business and IT, the BICC
enables the organization to coordinate and complement existing
efforts, reducing redundancy and increasing effectiveness.

51. BICC Framework
Education & Support
Training, Development and
Implementation
Ad Hoc End User Support
Communication, Newsletters
and users groups
Advanced AnalyticsBI Program Management Data Stewardship
Intake & Prioritization
Requirements and Prototyping
Application Development
Business Metadata
Quality Assurance
Data Governance
Data Preparation
Data Mining
Statistical Modeling

52. BICC Priorities
Examples of initial deliverables:
• BICC role definitions
• Intake, Prioritization and Escalation process
• ‘Building and Maintaining Business Glossary’ training for data
stewards
• Ensuring that the data is properly defined and used throughout the
enterprise
• Selecting and implementing a tool to manage metadata
• Establishing the help desk and support function for BI related
issues
• Forming the DW and BI development team and executing on
operational requests and delivering Phase 1 requirements
• Developing prioritized requirements for a Release Master Plan
• Development of Data Quality Management Plan

54. Connect with Perficient

55. Thank You!
For more information contact:
Christine Bessler
CIO / VP of Information Technology, ProHealth Care
christine_bessler@phci.org
Juliet Silver
Director, Healthcare Strategic Advisory Services, Perficient
juliet.silver@perficient.com
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