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

Data Governance ProgramSeptember, 2015

“Better data is everyone’s job!”

Data Governance Program

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UPMC At a GlanceLargest 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.


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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?


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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!

More than 1,000 internal applications

Medical Devices

Genetic and Population Data

Self Reported and Social Data

Data Explosion


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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!

Wu, Jie

You meant "Are we.." right?


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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?


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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!


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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?


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How many employees within the healthcare industry have the ability, access, and tools to query/analyze data?

Not enough.


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Of those employees…

What do the majority spend their time doing?

Locating data

Parsing bad data

Understanding data

Manually mapping terms

Navigating multiple sources

Analyzing data

OR Discovering actionable insights

Unproductive.


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The Role of Data Governance in Analytics

Enable access to data that is:

LegalBroadEasy to useWell-definedHigh qualityHarmonized

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.

Do we really need more piles of data, or do we need a pile of data that everyone can use?


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A Tiered Program of Accountability

Enterprise Analytics Leadership

Data Governance Council

Data Governance Office

Information Owners

DataStewards

ApplicationStewards

AnalyticsStewards


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Executing a Plan

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

• 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

• 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

• 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


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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?


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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


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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


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Data Governance Roles in the System Development Life Cycle (SDLC)Requirements

o Select best data sourceso Profile data o Identify reference data/vocabularieso Identify master datao Define business termso Define data use ruleso Define metadata needs

Designo Define business rules for data transformation and

data integrityo Define data dictionarieso Define master data trust ruleso Map/group reference data and vocabularieso Map source to targeto Design security and auditingo Define source to target balancing


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Data Governance Roles in theSystem Development Life Cycle (SDLC)Develop

o Build custom metadata modelso Populate business and data glossarieso Generate data lineageo Create master data modelso Create reference data and vocabulary modelso Create data integrity score cards

Testo Verify data readinesso Validate master data trust ruleso Determine metadata value

Deploy/Maintaino Source to target balancingo Master data enhancementso Business rule enhancementso Reference data/vocabulary maintenanceo Business and Data Glossary maintenanceo Data integrity Improvementso Metadata adoption


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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


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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


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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 metadataPromote use of approved definitionsReduce duplication of solutionsIntroduce more interactive toolsCreate self-service policies and processesCreate 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


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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.


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Thank you

Terri [email protected]

Documents

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