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Driving Information Governance: Data Governance Within the IG Framework

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Driving Information Governance: Data Governance Within the IG Framework Driving Information Governance: Data Governance within the IG Framework Lydia Washington, MS, RHIA, CPHIMS Senior Director, HIM Practice Excellence AHIMA [email protected] #IGNOW © 2015 AGENDA • Why Data Governance (DG) now • How DG is different from and relates to information governance (IG) • The primary DG functions • The key DG roles • The Information Trustworthiness Competency © 20152015 Big Data Volume Variety Velocity Veracity Value © 20152015 Healthcare data explosion • Drivers/unique data types – Imaging – EHRs – Genomics/Personalized medicine – Clinical research – Mobile/environmental/sensors – Health care as a data-driven business • Improvements in patient care • Reduced costs • Better experience and engagement © 20152015 Managing the explosion • Storage/repositories/ warehouses/cloud • Data management processes and practices • Also a people issue Training, policies, oversight, etc. © 20152015 ©AHIMA 2015 © 20152015 7 © 2015 DG and IG—difference in focus Data Governance Information Governance • Focus on inputs • Broader, encompasses DG – Data models • Focus on outputs – Metadata – Sharing and disclosure Management • HIE, e-discovery, legal holds – Privacy protections – Master data – Uses management • Business efficiency • Single source of truth – e.g. Patient care – Content management documentation – Data security • Regulatory compliance • Intellectual property – Data quality management Enterprise Health Information Management and Data Governance, 2015. Merida L Johns, PhD, RHIA. © 20152015 ©AHIMA 2015 © 20152015 Hallmarks of Governance • Strategic • Supports decision-making relative to data/information • Enterprise/organization level • Provides controls/accountabilities © 20152015 Knowledge Check 1: Which of the following is not a challenge associated with big data? A. Its variety B. The fact that it is virtual C. All of it does not have the same value D. Veracity can be questioned Correct Answer: B—Variety, variability in value and veracity are issues frequently associated with big data © 20152015 Knowledge check 2: True or False? Information governance is focused on inputs while data governance places more emphasis on outputs Correct Answer: False—Information is comprised of data which are the building blocks of information; data precedes information and therefore its governance is focused on inputs. © 20152015 How does Data Governance fit with Information Governance in Your Organization? • DG is part of the larger IG program and uses the IG structure • Addressed in IG strategy – Business intelligence – Population Health – Analytics • Beginning of the IG Journey for many © 20152015 Five Dimensions of Data Governance • Data Models • Master data management (MDM) • Metadata management • Data classification • Data Quality Mgt © 20152015 Data Models (representations of data that document user and developer requirements) DG for Data Models will address: • How data models are created and maintained • Functions, roles, and responsibilities associated with data models • Data dictionaries which describe entities, attributes and relationships • Quality control and metrics for managing data architectures © 20152015 Master Data Management (ensuring that mission critical data has a consistent meaning/single source of truth) MDM Functions DG for MDM addresses Data collection processes • Identifying data owners • and stewards • Identifying master and • Bus. Requirements reference data • Development and • Data scrubbing maintenance • Data Matching • Security • Quality metrics • Data validation • Change management • Audit/remediation © 20152015 Metadata Management Data Governance addresses: Metadata: A special type of structured • Standards and functional data that enables searching, requirements retrieval ,and use • Capture and maintenance of other data and information • Security requirements resources • Quality controls © 20152015 Data Classification • Categorizes data based on its sensitivity and value. DG assures classification helps manage security risk and facilitates data preservation and disposition. © 20152015 Data Quality Management AHIMA DQM model © 20152015 Data Quality Management and DG • Define data quality metrics and requirements • Assure data quality management is built into business processes and systems • Develop policies and procedures for DQ • Identify the roles and functions associated with achieving and sustaining DQ • Provide remediation/corrective action for DQ problems © 20152015 Information Trustworthiness: The Goal of Data Governance Data quality Mgt Master Data Mgt Trusted Data and Data Models Information Data Classificati on Metadata Mgt © 20152015 Knowledge Check 3 Which of the five functions of data governance specifically addresses data matching? A. Data Modeling B. Metadata management C. Data classification D. Master data management (MDM) Correct Answer: D (see slide 14) © 20152015 Knowledge check 4 True or False? Ensuring that mission critical data has a consistent meaning and is the single source of truth is the definition of metadata management. Correct answer: False—this is the definition of master data management © 20152015 Governance Roles Data Owner Accountability Transparency Compliance Data Steward © 20152015 Governance Roles • Decisions about data and information generated by/for the business unit(s) Data • Shift from data as the Owner responsibility of IT to data as the responsibility of the business owner © 20152015 Information Governance vs IT Governance Leading the Adoption of IG in Healthcare ©AHIMA 2015 AHIMA.ORG/INFOGOV © 2015 Data Governance Roles • Drives accountability in the way data and information is managed • Business unit to IT interface Data • Bus. Unit to Bus. Unit Steward interface • Implements, carries out policies and procedures for five DG functions • SME for business unit data © 20152015 AHIMA IG Adoption Model © 2015 Trustworthiness as an IG Competency • There is an increasing need to ensure that data and information is trustworthy and actionable © 20152015 As you start on DG, consider: • In what order of priority or sequence will you address the five dimension? • Overlap and dependencies? • Who needs to be involved? – Decision makers – Core team • Necessary skills and training? • Initial goals and success measures © 20152015 Data Governance Competency • Unique to the organization • No one size fits all • Influencing factors – culture – communication – engagement – resources • Start with SMART goals © 20152015 Thank You © 2015 IG PulseRate – a quick check into your organization’s IG status. •Free instant assessment of the adoption level of IG in your organization available at www.IGIQ.org •Review and rate the key success measures that impact organizational IG adoption •Evaluate your organization’s strengths and help identify weaknesses that may be impeding your organization’s path to enterprise information governance © 2015 Driving IG for HealthCare: Recommended Reading • AHIMA. “Information Governance • Enterprise Health Information Management Principles for Healthcare™” 2014. and Data Governance, 2015. Merida L Chicago, IL. AHIMA, 2014. Available at: Johns, PhD, RHIA. www.ahima.org/infogov • ARMA International. “Generally • The Information Governance Initiative. “The Accepted Recordkeeping Principles”. Information Governance Initiative Annual ARMA International, 2013. Available at Report”. 2014 and 2015 . New York, NY. www.arma.org www.IGinitiative.com • Cohasset Associates and AHIMA. “A Call to Adopt Information Governance • The Joint Commission. “Information Practices.” 2014 Information Governance Management (IM) Chapter”, in Healthcare. Minneapolis, MN. Comprehensive Accreditation Manual for Hospitals, 2014, Oakbrook Terrace, IL: The • Cohasset Associates, 2015. Cohasset Joint Commission, 2014, pp.IM-1—IM-10. Associates and AHIMA. “Professional Readiness and Opportunity” 2015 Information Governance in Healthcare. • The Sedona Conference. “Commentary on Minneapolis, MN. Cohasset Associates, Information Governance” The Sedona 2015. Conference® Working Group Series. A project of The Sedona Conference® • Implementing Health Information Working Group on Electronic Document Governance, 2015. Linda Kloss, MA, RHIA, FAHIMA Retention and Production (WGI) © 20152015 © 2015 .
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