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

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.

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?

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

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!

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?

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!

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?

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

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

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.

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

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

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?

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

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

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

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

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

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

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

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.

Data Governance Program Thank you Terri Mikol mikoltj@upmc.edu