Keith F. Woeltje, MD, PhD, FAMIA

1. Data Governance and the Data and Information Lifecycle S11: Presentations - Leveraging Workflow and Data to Promote Efficiency Keith F. Woeltje, MD, PhD, FAMIA BJC HealthCare and Washington University School of Medicine St. Louis, MO

2. Disclosure • I and my spouse/partner have no relevant financial relationships with commercial interests to disclose.

3. Learning Objectives • Attendees will learn an approach for describing data as an asset, based on patient data flow and the data and information lifecycle. Participants will then learn how to apply specific tools and processes bringing vision into reality within a healthcare organization.

4. BJC by the Numbers As of year end 2017 31,811 EMPLOYEES $5.0 BILLIONNET REVENUE 168,828 HOME HEALTH VISITS 4,309 PHYSICIANS 15HOSPITALS 3,468 STAFFED BEDS 153,257 HOSPITAL ADMISSIONS 563,239 EMERGENCY DEPT. VISITS $12.9 MILLION COMMUNITY HEALTH PROGRAMS (providing more than 529,000 individual services) $370 MILLION CHARITY & UNREIMBURSED CARE

6. 1,465 full-time faculty physicians (76 sub-specialties) 3,426,181 total patient encounters in FY17 including: 1,121,579 outpatient visits 1,120,962 procedures 64,488 total hospital admissions on medical campus 65% of clinical activity on Washington University Medical Center Campus Affiliation agreement with BJC hospitals Washington University School of Medicine

7. BJC, like everyone else, is facing a data tsunami… Healthcare data volumes: An estimated 2,314 exabytes will be produced in 2020.* Visits documented in EHRs: 1 billion patients *

8. …and the industry is rapidly evolving. New Care Model = data New Technology = more data

9. Data as a Strategy • Organizations must manage “data as a strategic asset” and this starts with “implementing sound enterprise data management …. “ • F. Velasco, (Healthcare HIT News, Feb, 2019)

10. Data Governance Journey • Domain Work • 323 business glossary terms • 248 terms mapped to table/columns in 1 + systems • 69 terms mapped to a standard reference data • 25,617 system code values mapped to 9,315 standard code values • Match/merge rules, trust rules provided for MDM implementation • Standards developed/implemented in Epic directly or via MDM • Mappings actively used in MDM with regular upkeep • Data Strategy Program – Office & Community • Formed and launched steward community • DGC and DGTC founded • Mission/Vision • Initial role definitions • Collibra purchase and resources obtained Data Strategy Domain Work • 58 business glossary terms defined • 27 reference data sets standardized Processes • Standard registration • Capture/distribution custom drug knowledge • Name style standard • Change control • Data Strategy/ Management • Collibra re-messaging and launch of version 5.2 • DGO work focus - 2018 program plan • Update role definitions and complete job mapping • Data and information lifecycle management policy • Alignment with MDM and CCE – review data domains and organizational need Data Strategy Development • Accenture assessment • Operating model developed • Baseline maturity model 2013 2014 2015 2016 2017 2018

11. Data & Information Lifecycle Framework Secure Secure Secure Secure Dispose The appropriate archiving, removal from system origin, or destruction of data or information that is no longer required to meeting statutory requirements, and/or to support clinical, business or operational requirements Storage Access Display & Use Capture & Collect The retention of data or information, in an appropriate manner, to support, clinical, business, operational or legislative requirements The creation, acquisition or capture of the data or information needed to support clinical, business, operational or legislative requirements Ensures only authorized users have access to non-public information in order to achieve clinical, business, operational or legislative requirements The appropriate utilization and display of data or information to achieve clinical, business, operational or legislative requirements Secure The protection of data or information from the risk of accidental or malicious alteration or destruction, and from unauthorized access or disclosure. Ensures the appropriate levels of protection from breach, corruption and loss are provided for information that is private, confidential, secret, classified, essential to business continuity, or otherwise requires protection.

12. Patient and Data & Information Lifecycle

13. Need a Focus on Data Policies…… • D&ILM served as the framework and terminology for P&P Assessment and Gap analysis • Once D&ILM assessment and gap analysis was completed it identified BJC had a some P&P that support the D&ILM, but we also had gaps • Conclusions • Draft a governing policy and align current P&P, forms to each phase – to assess our current state and ID gaps and next steps

14. D&ILM Governing Policy

15. Core Policy Example • Capture and collect • Document standards that include the minimum clinical and business data elements as well as timeframes for collection. • Establish training and communication programs that informs employees and providers of their responsibilities related to minimum data collection standards. • Design systems to collect data in the most efficient, accurate, and consistent way.

16. Data Governance Sub-Committee • Purpose • Develop enterprise strong policies and procedures that describe the ways to manage data. • Define the rules of engagement for data. • Promote an enterprise way of thinking about data (i.e. Data & Information Lifecycle) and increase communications about data and data activities. • Identify the resources who manage data and hold them accountable to each other. • Assure alignment between BJC and WU related to Data Governance. • Assure that Data Governance sub-committee efforts support BJC clinical and business objectives/priorities.

17. Connecting People… DGO Steward Community Data Consumers Data Domain Goal Development, advisement, maintenance, and utilization of a business glossary and standardized metadata. • Data Strategy Support ...with Business Use Develop & Document “Business Glossary” Standard Code Values Business Terms Map Map Map Map Map ...of Technical Data Identify & Collect “Data Dictionary” (System and Database, Database Table, Table Column) Table Columns (Data Element) System Code Values

18. Practical Application of this Session • You too can set up a data governance program for your institution!

19. Questions • The purpose of good data governance is: • Options: • to meet regulatory requirements • to prevent any use of organizational data without permission • to ensure that organizational data can be used effectively for analysis and decision making • to assert control of organizational priorities

20. Answer • to meet regulatory requirements • to prevent any use of organizational data without permission • to ensure that organizational data can be used effectively for analysis and decision making • to assert control of organizational priorities • Explanation: The utility of good data governance is to ensure that data generated in an organization can be used to generate useful information and insights by allowing comparisons over time, and allowing data from disparate systems to be combined effectively. Regulatory requirements for data security can be met without necessarily having good governance. Good governance is not intended to inhibit users from making good use of the data (although there should be clear rules of the road and not uninhibited access to all systems). Organizational priorities should inform data governance, not the other way around.

21. Questions • The purpose of good data governance is: • Options: • Capture and Collect; Storage; Access; Display and Use; Dispose • Input; ETL; Analysis; Reporting • Garbage in, garbage out • Design; Transition; Operation

22. Answer • Capture and Collect; Storage; Access; Display and Use; Dispose • Input; ETL; Analysis; Reporting • Garbage in, garbage out • Design; Transition; Operation • Explanation: There are different formulation for a data and information life cycle, but a complete formulation should incorporate all steps from data generation to data disposal (which 'B' doesn't include); while 'C' is an absolute truism, it doesn't represent a life cycle. 'D' is part of the ITIL service life cycle, but only part of it.

23. References • Hripcsak G, Bloomrosen M, FlatelyBrennan P, Chute CG, Cimino J, Detmer DE, Edmunds M, Embi PJ, Goldstein MM, Hammond WE, Keenan GM, Labkoff S, Murphy S, Safran C, Speedie S, Strasberg H, Temple F, Wilcox AB. Health data use, stewardship, and governance: ongoing gaps and challenges: a report from AMIA's 2012 Health Policy Meeting. J Am Med Inform Assoc. 2014 Mar-Apr;21(2):204-11. doi: 10.1136/amiajnl-2013-002117. Epub 2013 Oct 29. PubMed PMID: 24169275; PubMed Central PMCID: PMC3932468. • Middleton J, Moses JS. HIMSS Practical Steps to Enterprise Data Governance. Available at: https://www.himss.org/practical-steps-enterprise-data-governance • Bresnick J. The Role of Healthcare Data Governance in Big Data Analytics. Available at: https://healthitanalytics.com/features/the-role-of-healthcare-data-governance-in-big-data-analytics

24. AMIA is the professional home for more than 5,400 informatics professionals, representing frontline clinicians, researchers, public health experts and educators who bring meaning to data, manage information and generate new knowledge across the research and healthcare enterprise. AMIA 2019 Clinical Informatics Conference | amia.org

25. Thank you! • keith.woeltje@bjc.org