1. Data Governance Program September, 2015
“Better data is everyone’s job!”

2. Data Governance Program
UPMC At a Glance
Largest employer in Pennsylvania, with more than 60,000 employees.
More than 3,500 employed physicians .
More than 20 academic, community, and specialty hospitals and 500 outpatient sites.
Serving 2.5 million Health Plan members.
Ongoing strategic affiliation with the University of Pittsburgh.
Ranked among the top 10 recipients of NIH funding.

3. Data Governance Program
UPMC has been working successfully in the Data Warehousing and Business Intelligence spaces for over 20 years.
Why is UPMC deploying a Data Governance Program now?

4. Data Governance Program
UPMC Fosters ‘Personalized Medicine’ with $100 Million Investment in Sophisticated Data Warehouse and Analytics , October 1, 2012.
Every piece of data could impact a future patient outcome!
Data Explosion
More than 1,000 internal applications
Genetic and Population Data
Medical Devices
Self Reported and Social Data

5. Data Governance Program
The solution is REVOLUTION not evolution!
Answering questions about length of stay, case mix, and payer mix trends will no longer make you a hero.
Today we are asked questions that require data from dozens of data sources.
Determine the cost of managing the diabetic population and how to manage this population more efficiently.
Are we maximizing the value of the spend on blood products?
How can we provide the exact care a patient needs, at the right time, at the right place, and in a way that is most convenient for the patient?
Small teams of specialized analysts using disparate data sources can NOT SCALE!
It’s time to deploy a model that will scale!

6. Data Governance Program
Guiding Principles
Lying at the heart of the “data driven healthcare organization” is a commitment to treating data as a valuable asset that must be broadly available, managed over time, and constantly improved.
To promote data analytics as a core competency, working with data must extend well beyond IT and Informatics Teams.
Better data is everyone’s job. What is your data role?

7. Data Governance Program
UPMC’s Data Governance Program Focus
Answering these common questions:
Where can I find the information I need?
Is the data any good?
Does the data mean what we presume it means?
Did the data come from a trusted source?
What am I allowed to do with this information?
This is not “NEW” work. What is new is an enterprise approach supported by enterprise technology and processes!

8. Data Governance Program
Do you believe…
Answers to our most challenging healthcare questions are in our data?
With more data than ever imagined, why can’t we answer our questions?

9. Data Governance Program
How many employees within the healthcare industry have the ability, access, and tools to query/analyze data?
Not enough.

10. Data Governance Program
Of those employees…
What do the majority spend their time doing?
Unproductive.
Locating data
Parsing bad data
Understanding data
Manually mapping terms
Navigating multiple sources
Analyzing data OR
Discovering actionable insights

11. Data Governance Program
The Role of Data Governance in Analytics
Do we really need more piles of data, or do we need a pile of data that everyone can use?
Enable access to data that is:
Legal
Broad
Easy to use
Well-defined
High quality
Harmonized
Make self-service analytics a reality. Reduce the dependency on “phone a friend”.
Elevate the “analytics” ability of our organization by engaging more people in data work. Remove the “secret sauce”.
Transition data related decisions to the business.

12. Data Governance Program
A Tiered Program of Accountability
Enterprise Analytics Leadership
Data Governance Council
Data Governance Office
Information Owners
Data
Stewards
Application
Stewards
Analytics
Stewards

13. Data Governance Program
Executing a Plan
Data Governance practices become standard in the project life cycle
Metadata and master data are used broadly
Progress is demonstrated through improved trending of data quality metrics
There is compliance with Data Governance Policies and Guidelines
Adoption
Phase Four
Council drives priorities
Begin policy/guideline approval
Information owners begin to govern
Publish data quality metrics
Deploy master data
Deploy metadata
Begin measuring steward performance
Engagement
Phase Three
Communicate
Begin naming the Stewardship Community
Educate (make it personal)
Define initial master data and metadata priorities
Establish Business Glossary guidelines
Create data profiling standards
Awareness
Phase Two
Foundation
Establish council and office
Define roles aligned with policy
Educate council and staff
Define scope
Acquire and implement tools
Engage Human Resources
Phase One

14. Data Governance Program
Provide tools for employees and Information Owners to discover UPMC’s data landscape
For each Data Domain…
Which applications or external sources collect the data?
Where all is the data moved?
What are the data definitions and vocabularies?
What are the data quality issues?
What are the use/security rules?
What are the business rules for “fit for use”?
What is leaving the organization, how and why?

15. Data Governance Program
Tasks at a glance…
Data Quality
Data Profiling as a service
Journaling exercises
Data Quality Portal (by Data Domain)
Define business rules / quality thresholds for Enterprise Analytics
Publish data quality scorecards for transparency and planning purposes
Master Data Management
Vocabulary with named Data Stewards
Patients/Members
Providers/Organizations
Facilities/Locations
Patient/Provider/Facilities Relationships
Provider attribution for encounters and quality

16. Data Governance Program
Tasks at a glance…
Metadata Management
Application Inventory
Core Reports/Dashboards Inventory
Analytics resources roadmap
Business Glossary and Data Dictionaries with named Data Stewards
External Reporting Inventory
Data Movement/Flow
Policy / Guidelines
Information Ownership
Business Glossary Change Management
Use of test persons in production systems
Self-service use of data
Data movement authorization
Report documentation standards

17. Data Governance Program
Data Governance Roles in the
System Development Life Cycle (SDLC)
Requirements
Select best data sources
Profile data
Identify reference data/vocabularies
Identify master data
Define business terms
Define data use rules
Define metadata needs
Design
Define business rules for data transformation and data integrity
Define data dictionaries
Define master data trust rules
Map/group reference data and vocabularies
Map source to target
Design security and auditing
Define source to target balancing

18. Data Governance Program
Data Governance Roles in the
System Development Life Cycle (SDLC)
Develop
Build custom metadata models
Populate business and data glossaries
Generate data lineage
Create master data models
Create reference data and vocabulary models
Create data integrity score cards
Test
Verify data readiness
Validate master data trust rules
Determine metadata value
Deploy/Maintain
Source to target balancing
Master data enhancements
Business rule enhancements
Reference data/vocabulary maintenance
Business and Data Glossary maintenance
Data integrity Improvements
Metadata adoption

19. Data Governance Program
Engagement is key to maturing a Data Governance Program
People will learn by doing!
DG Council members are aligned to specific initiatives to gain
hands-on experience.
Data Domains
Categorize data for ownership and organization
Nominate Information Owners
Assist Information Owners with Data Steward selection
Guide Application Stewards as they map applications and interfaces to data domains
Guide Analytics Stewards as they map reports to data domains
Policy/Compliance
Promote the DG roles in the System Development Life Cycle
Measure compliance to policies and guidelines
Establish performance metrics for the stewardship community
Conduct program maturity assessments annually
Use online forums to gather policy and guideline needs
Communicate privacy definitions

20. Data Governance Program
DG Council members are aligned to specific initiatives to gain
hands-on experience.
Master Data Management
Define what data should be “mastered
Fill workgroups with active Stewards and Information Owners.
Approve master data trust rules
Assess the value and accuracy of “gold records”
Prioritize the deployment of master data in UPMC systems and operational areas
Work with Information Owners to gain adoption/use of master data across the organization
Metadata Management
Use online forums and existing collaboration meetings to identify needed metadata
Prioritize metadata initiatives
Drive process changes to promote the population, timely maintenance, and adoption of the deployed metadata
Assess the value and adoption of metadata deployments
Data Integrity
Work with Information Owners to select key data sets for profiling
Work to incorporate data profiling into our standard system development life cycle
Approve the designs of error reports and scorecards
Engage Information Owners in prioritization of integrity issues and setting goals for remediation
Promote the transparency of Data Integrity issues

21. Data Governance Program
DG Council members are aligned to specific initiatives to gain
hands-on experience.
Analytics Stewards
Identify needs for policies and guidelines to govern reports and analytics solutions
Name Analytics Stewards
Guide Information Owners as they select gold standard reports and analytics solutions
Create a roadmap specifying which analytics team will perform what types of analytics
Prioritize initiatives for the Analytics Stewards
Improve report metadata
Promote use of approved definitions
Reduce duplication of solutions
Introduce more interactive tools
Create self-service policies and processes
Create testing guidelines
Communications
Educate the masses on the program goals, content, and progress
Introduce mandatory and optional training
Introduce the DG Council and the Stewardship Community
Introduce the Data Governance Office and processes
Communicate job performance metrics
Offer Stewards certifications and performance recognition
Engage external organizations for collaboration
Identify speaking and publication opportunities

22. Data Governance Program
Lessons Learned
Don’t quit.
Passion works.
Continuously communicate and educate.
Use real data examples to educate.
You are never done. Embrace the new work style.
Name only those you plan to engage soon.
The council must be actively engaged.
Network.

23. Data Governance Program
Thank you
Terri Mikol