Crowdsourcing Data Governance
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AHIMA Presentation by Kam Jasti and Paul Boal - 2018
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Crowdsourcing Data Governance
- 1. 18#AHIMACON18 Power to the People: Internal Crowdsourcing for Data Governance That Actually Works Paul Boal, Amitech Solutions Kamalakar Jasti, SSM Health
- 2. 18#AHIMACON18 Objectives Understand the value and challenges of top-down and bottom-up approaches to data governance Appreciate the importance of access to information and process transparency Identify how a broad range of stakeholders at different levels can be engaged with data governance Design a strategy for establishing an impactful data governance program that fits your organization 2
- 3. 18#AHIMACON18 Agenda • What Drove Data Governance at SSM Health? • Why Do Data Governance Projects Fail… – Half-baked Vision and Execution – High-flying ideas that Crash and Burn – Programs that Suffer a Long, Slow Decline • And How to Prevent Failure! • How SSM Health is Succeeding! 3
- 4. 18#AHIMACON18 SSM Health 4 • $9+ billion in annual revenue • Over $500 Million in Community Benefit • 40,000+ Employees • 9,900+ Physicians/Providers • 300+ Physician Office/Outpatient Sites • 24 Hospitals • 10 Post-Acute Facilities • 83 Counties – SSM Health at Home • 5.4 Million Covered Lives – Navitus • 410,000 Covered Lives – Dean Health Plan • 40+ Managed Hospitals/ Affiliate Relationships
- 6. 18#AHIMACON18 Three Ways This Could Have Failed 6 Crash and Burn Long Slow DeclineHalf-Baked Effort
- 7. 18#AHIMACON18 1a: Half-Baked Tool-Centric Approach 7 If you build it, they will come 18#AHIMACON18
- 8. 18#AHIMACON18 1b: Half-Baked Process-Centric Approach 8 If you want to make God laugh, tell him about your plans. ~Woody Allen
- 9. 18#AHIMACON18 Technology, Process, People, Culture …the secret to high performance and satisfaction-at work, at school, and at home—is the deeply human need to direct our own lives, to learn and create new things, and to do better by ourselves and our world. 9
- 10. 18#AHIMACON18 2a: Burnout with No Motivation to Change Clichés about Change: • Change is a marathon • The only thing constant is change • Need quick wins to build buy-in • Kotter’s 8 step process for change 10
- 12. 18#AHIMACON18 2b: Crash Against Organizational Inertia • Top-down compliance breeds resentment. • Resentment leads to resistance. • Resistance leads to disengagement. • Disengagement leads to the Dark Side. 12
- 13. 18#AHIMACON18 Mythical Hierarchy 13 DG Steering Committee Manage Working Group / Business Steward Define / Monitor Technical Steward Confirm / Enforce Domain Trustee / Steward Define DG Executive Council Plan and Guide Data Executive Approve Information User Follows Procedures Strategic Tactical Operational Business Technical
- 14. 18#AHIMACON18 Top Down and Bottom Up 14 Strategic Tactical Operational Business Technical Operational Business Technical Tactical Strategic
- 15. 18#AHIMACON18 3a: Slow Decline by … • “Did you get data governance approval?” • “Did you see that there’s a new process for that?” 15
- 16. 18#AHIMACON18 3b: Slow Decline without Clear Results / ROI Benefits never materialize No data governance metrics 16
- 17. 18#AHIMACON18 Increasing Maturity Only Implies Value Measure Process Maturity Track Data Quality 17 Soarian Epic myBJC TOTAL ECHO Peoplesoft Epic bjc.org TOTAL Soarian Epic myBJC TOTAL Soarian Epic myBJC TOTAL Soarian Epic Scopeand charter is defined 1 1 1 0.8 0.8 1 0.8 0.8 0.8 0.8 0 0.8 0.2 0.8 1 Master data areidentified 1 1 0.8 0.8 0.6 0.4 0.8 0.6 0.4 1 0.6 0.2 0.2 0.2 0 Policiesand standards areenforced 0.8 0.8 0.8 0.8 1 0.6 1 0.4 0.6 0.4 0.2 0.8 0.2 0 0.6 Metrics and dashbaords areavailable 0.4 0 0 0 0.4 0 1 0.6 0.8 0.2 0.6 0.8 0 0.6 0.8 TOTAL Processes and tools aredefined 1 1 1 0.4 0.6 1 0.4 0.6 0.8 0.6 0.8 0.2 0.4 0.8 1 Controls and procedures arein place 1 1 0.8 0.4 0.2 0.2 0.4 1 0.6 1 0.2 0.4 0.4 0.6 0.2 Stewards areassigned 0.8 0.8 0.8 0.2 0.4 0.8 0.8 0 0.8 0.2 0.8 0.2 0.4 0.8 0 Stewards areachieving goals 0.4 0 0 0.4 0.8 0.6 0 0 0 0.2 0.2 0.6 1 0 0.2 TOTAL Data integration projects arereviewed by governance 1 1 1 0.8 0.8 0.6 0.8 0.6 0.4 0.6 0.8 0.6 0.8 0.4 0.6 Data stewards areengaged in integration projects 0.4 0.4 0.6 1 0.2 0.4 0.4 1 0.6 0.4 0.4 0.6 0.2 0.4 0.2 Agreement on ETL rules and data acceptancecriteria 0 0 0 0.8 0.8 0.6 0.2 0.8 0.8 0.6 1 0.6 0.2 0.8 0 Integration and quality rules arereusable 0 0 0 0.4 1 1 0 0.2 0.4 0.8 0.6 0.4 0.2 1 0 TOTAL Data quality processes arealigned with governance 0.2 1 1 1 0.4 0.8 0.8 0.4 0.8 1 0.6 1 0.6 0.4 0.4 Key data quality opportunities areidentified 0.2 1 0.8 0.8 0.6 0.8 0 0.8 0.2 0 0.6 0.2 0.2 0.2 0.4 Data quality policies areenforced 0.2 0.8 0.8 0 0.2 0.8 0.4 0.2 0.6 0.6 0 0.2 0.8 0.8 0.4 Data quality is actively monitored and maintained 0 0 0 0.6 0.8 0.2 0.8 0.4 0.2 0 0.2 1 0.2 0.2 0.8 TOTAL Metadata scopeand approach areidentified 1 1 1 0.8 0.8 0.2 1 0.8 0.4 1 0.4 0.2 0.4 0.6 1 Metadata priorities areestablished 1 1 0.8 0.4 0 1 0.8 0.2 0.2 0.8 0.8 0.8 0.8 0.4 0.8 Metadata policies and standards areenforced 0.8 0.8 0.8 0.6 0.6 0.8 0 0.2 0 0.4 0 0.6 0.2 0.4 0.4 Key data definitions areunder uniquestewardship control 0.4 0 0 0 0 0 0.2 0.2 0.4 0 0.4 0 0 0.6 0.8 TOTAL 0.38 0.38 0.56 0.43 0.47 0.47 0.37 0.61 0.60 0.53 0.48 Order Procedu 0.71 0.68 0.62 0.38 Location Data Stewardship Data Integration DataQualityMetadata Physician 0.71 0.48 0.50 Patient Data Governance 0.71 0.45
- 18. 18#AHIMACON18 Define the ROI Upfront • Undeliverable addresses • Inaccurate billing • Delayed account setup • Product standardization 18
- 19. 18#AHIMACON18 Context and Connections in Moments that Matter Knowledge workers should share their knowledge 19
- 21. 18#AHIMACON18 21 The Work of Health System Leadership What patients think I do What nurses think I do What doctors think I do What I want to do someday What I have to do today
- 22. 18#AHIMACON18 Time to Reset Expectations 22 System Execs WI STL OK Care Mgmt Clinic Hospital Operations Physicians Nursing The System Executives will determine which are the right metrics and goals. Subject Matter Experts from across the system will work together to standardize exactly how the measures will be calculated
- 23. 18#AHIMACON18 Performance-Driven Management 23 System Execs WI STL OK Care Mgmt Clinic Hospital Operations Physicians Nursing Regional Executives Performance Management Department Heads Manage and Execute Executive Leadership Strategic Prioritization
- 24. 18#AHIMACON18 Tightly Align with Strategic Direction 24 • Executives will be reviewing performance during regular joint meetings. • They’ll also need access to the detailed information on how metrics are calculated now. i
- 25. 18#AHIMACON18 Provide Valuable Information 25 Usable information and business context, provided by real people involved in the decision-making process. InformationPortfolio
- 27. 18#AHIMACON18 Bottom-Up Involvement in Data Governance • Information Portfolio Content provided by hands-on subject mater experts • Content owners are business leaders, not data or IT specialists 27 System Execs WI STL SLU Care Mgmt Clinic Hospital Operations Physicians Nursing
- 28. 18#AHIMACON18 Example: All Cause Readmissions 1. Different regions used different definitions and business rules: – Which authority is defining readmissions? – How is the information being used? – Do we include or exclude observation stays? – Skilled nursing facility confusion – What is the right goal? 2. What are the challenges in bringing SMEs to agreement – We are saying the same words but not meaning the same thing. – It takes time to drill down into the details. – Some time has to be spent as a group, some time one-on-one. 3. How the wiki helped facilitate that: – Writing things down and reviewing them always helps. – Putting those written works in a “public” place makes you think harder about how someone else might interpret it. 28
- 29. 18#AHIMACON18 Next Steps • Next use cases: – Population Health – Clinical Quality – centralizing / standardizing – MACRA/MIPS • Increase adoption: – Standard process for adding new areas and new information – Integrate existing information from other systems and build additional forms and templates – Mobile capabilities 29
- 30. 18#AHIMACON18 Thank You And Good Luck! 30
Notes de l'éditeur
- Setting the stage: A year ago, SSM Health hired a new CEO from outside the organization. There are lots of challenges that come with a new CEO – for the new CEO, for existing leadership, for everyone up and down the organization.
- Worked well for Kevin Costner but doesn't usually work out well for IT projects. EXAMPLE: Fresenius DW Next Tools built by information management professionals for information professionals, rather than business users. EXAMPLE: Data Dictionary with cheeseburger definitions Knowledge repositories that typically contain technical knowledge but lack business context. “Adoption is a management issue.”
- Process that are built around compliance as opposed to value. Don’t focus closely enough on what the ultimate objective is – cleaner data, better decisions, faster analysis, etc. Ignoring the fact that people have to be involved in doing the process. Talk about the Item Add process at BJC
- There are a lot of clichés about change and even more books about how to lead and manage change. Some of the best lessons I learned about change management came at a time where I was trying to introduce my executive team to data governance, lead subject matter experts into a new way of sharing all of their knowledge with the broader organization, and literally training to run a marathon at the same time. Quick wins...
- The counter-example of centralization Talk about the conversations with Scott about his email inbox
- Setting the stage: A year ago, SSM Health hired a new CEO from outside the organization. There are lots of challenges that come with a new CEO – for the new CEO, for existing leadership, for everyone up and down the organization. Came in from a highly mature organization / structured Hospital KPIs all available What she saw was lots of astrixes… each hospital does things slightly differently
- Expectation Standardized way of comparing Reality Each person has their own binder Meetings / accountability is show-and-tell
- Leads to… Vision Top down: system determines measures and goals Bottom up: determining standard definitions, informed by real understanding of operations, workgroups, SMEs, agreement on standard way to defining
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