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Driving Information Governance: Data Governance within the IG Framework

Lydia Washington, MS, RHIA, CPHIMS Senior Director, HIM Practice Excellence AHIMA Lydia.Washington@ahima.org #IGNOW

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• 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

AGENDA

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Volume Variety Velocity Veracity Value

Big Data

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• 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

Healthcare data explosion

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• Storage/repositories/ warehouses/cloud

• Data management processes and practices

• Also a people issue Training, policies, oversight, etc.

Managing the explosion

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DG and IG—difference in focus

Information Governance • Broader, encompasses DG • Focus on outputs

– Sharing and disclosure • HIE, e-discovery, legal holds

– Privacy protections – Uses

• Business efficiency – e.g. Patient care

documentation • Regulatory compliance • Intellectual property

management

Data Governance • Focus on inputs

– Data models – Metadata

Management – Master data

management • Single source of truth

– Content management – Data security – Data quality

Enterprise Health Information Management and Data Governance, 2015. Merida L Johns, PhD, RHIA.

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• Strategic • Supports decision-making relative to

data/information • Enterprise/organization level • Provides controls/accountabilities

Hallmarks of Governance

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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

Knowledge Check 1:

Correct Answer: B—Variety, variability in value and veracity are issues frequently associated with big data

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True or False? Information governance is focused on inputs

while data governance places more emphasis on outputs

Knowledge check 2:

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.

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• 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

How does Data Governance fit with Information Governance in Your Organization?

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• Data Models • Master data management (MDM) • Metadata management • Data classification • Data Quality Mgt

Five Dimensions of Data Governance

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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

Data Models (representations of data that document user and developer requirements)

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Master Data Management (ensuring that mission critical data has a consistent meaning/single source of truth)

DG for MDM addresses • Identifying data owners

and stewards • Bus. Requirements • Development and

maintenance • Security • Quality metrics • Change management

MDM Functions • Data collection processes • Identifying master and

reference data • Data scrubbing • Data Matching • Data validation • Audit/remediation

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Metadata Management

Metadata: A special type of structured data that enables searching, retrieval ,and use of other data and information resources

Data Governance addresses: • Standards and functional

requirements • Capture and maintenance • Security requirements • Quality controls

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• Categorizes data based on its sensitivity and value. DG assures classification helps manage security risk and facilitates data preservation and disposition.

Data Classification

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Data Quality Management

AHIMA DQM model

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• 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

Data Quality Management and DG

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Data quality Mgt

Master Data Mgt

Data Models

Data Classificati

on Metadata

Mgt

Information Trustworthiness: The Goal of Data Governance

Trusted Data and Information

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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)

Knowledge Check 3

Correct Answer: D (see slide 14)

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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.

Knowledge check 4

Correct answer: False—this is the definition of master data management

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Governance Roles

Data Owner

Data Steward

Accountability Transparency Compliance

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Governance Roles

• Decisions about data and information generated by/for the business unit(s)

• Shift from data as the responsibility of IT to data as the responsibility of the business owner

Data Owner

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Leading the Adoption of IG in Healthcare

AHIMA.ORG/INFOGOV

Information Governance vs IT Governance

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Data Governance Roles

• Drives accountability in the way data and information is managed

• Business unit to IT interface • Bus. Unit to Bus. Unit

interface • Implements, carries out

policies and procedures for five DG functions

• SME for business unit data

Data Steward

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AHIMA IG Adoption Model

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Trustworthiness as an IG Competency

• There is an increasing need to ensure that data and information is trustworthy and actionable

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• 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

As you start on DG, consider:

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• Unique to the organization • No one size fits all • Influencing factors

– culture – communication – engagement – resources

• Start with SMART goals

Data Governance Competency

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Thank You

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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

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Driving IG for HealthCare: Recommended Reading

• Enterprise Health Information Management and Data Governance, 2015. Merida L Johns, PhD, RHIA.

• The Information Governance Initiative. “The Information Governance Initiative Annual Report”. 2014 and 2015 . New York, NY. www.IGinitiative.com

• The Joint Commission. “Information Management (IM) Chapter”, Comprehensive Accreditation Manual for Hospitals, 2014, Oakbrook Terrace, IL: The Joint Commission, 2014, pp.IM-1—IM-10.

• The Sedona Conference. “Commentary on Information Governance” The Sedona Conference® Working Group Series. A project of The Sedona Conference® Working Group on Electronic Document Retention and Production (WGI)

• AHIMA. “Information Governance Principles for Healthcare™” 2014. Chicago, IL. AHIMA, 2014. Available at: www.ahima.org/infogov

• ARMA International. “Generally Accepted Recordkeeping Principles”. ARMA International, 2013. Available at www.arma.org

• Cohasset Associates and AHIMA. “A Call to Adopt Information Governance Practices.” 2014 Information Governance in Healthcare. Minneapolis, MN.

• Cohasset Associates, 2015. Cohasset Associates and AHIMA. “Professional Readiness and Opportunity” 2015 Information Governance in Healthcare. Minneapolis, MN. Cohasset Associates, 2015.

• Implementing Health Information Governance, 2015. Linda Kloss, MA, RHIA, FAHIMA

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