Data and Information Governance Glossary

Data Governance Glossary for the RHIA Exam

Understanding data governance terminology is essential for RHIA exam success. This glossary covers key terms related to health data management, data quality, information governance, and the standards that guide how healthcare organizations collect, store, protect, and use data assets.

Access Controls

Security mechanisms that regulate who can view or use resources in a computing environment. In healthcare, access controls ensure that only authorized individuals can retrieve or modify protected health information.

Audit Trail

A chronological record that documents the sequence of activities affecting a particular operation, procedure, or event. In EHR systems, audit trails track who accessed patient records, when, and what actions were taken.

Business Continuity Plan

A documented strategy that outlines how an organization will continue operating during and after a disruption. In HIM, this includes provisions for maintaining access to health records during system outages or disasters.

Clinical Data Repository (CDR)

A centralized database that consolidates patient data from multiple clinical information systems. The CDR provides a unified view of patient information for clinicians and supports clinical decision-making.

Data Accuracy

The degree to which data correctly reflects the real-world events or conditions it represents. Accurate health data is critical for patient safety, quality reporting, and reimbursement.

Data Architecture

The models, policies, rules, and standards that govern the collection, storage, arrangement, integration, and use of data within an organization. It provides a blueprint for managing data assets.

Data Classification

The process of organizing data into categories based on its sensitivity, value, and criticality. Healthcare organizations classify data to apply appropriate security controls and retention policies.

Data Cleansing

The process of detecting and correcting corrupt, inaccurate, or irrelevant records from a dataset. Also known as data scrubbing, it improves data quality for analytics and reporting.

Data Completeness

A data quality dimension that measures whether all required data elements are present in a record. Incomplete health records can lead to coding errors, claim denials, and patient safety issues.

Data Consistency

A data quality dimension that ensures data values are uniform and do not conflict across systems, databases, or records. Consistent data is essential for reliable reporting and interoperability.

Data Dictionary

A centralized repository of metadata that defines the structure, meaning, relationships, and allowable values of data elements within a database or information system.

Data Governance

The overall management of the availability, usability, integrity, and security of data within an organization. Data governance establishes policies, procedures, and responsibilities for managing data as an organizational asset.

Data Integrity

The assurance that data is accurate, complete, and reliable throughout its lifecycle. Data integrity controls prevent unauthorized modification or deletion of health information.

Data Lineage

The documentation of data's origins, movements, and transformations throughout its lifecycle. Data lineage helps organizations understand where data comes from and how it has been processed.

Data Mapping

The process of matching data fields from one system or standard to corresponding fields in another. Data mapping is essential for system migrations, integrations, and interoperability between healthcare systems.

Data Mining

The process of analyzing large datasets to discover patterns, correlations, and trends. In healthcare, data mining supports clinical research, population health management, and fraud detection.

Data Quality Management

The processes and practices that ensure organizational data meets defined standards for accuracy, completeness, timeliness, and consistency. It is a core function of health information management.

Data Steward

An individual responsible for managing and overseeing an organization's data assets to ensure data quality and compliance with governance policies. Data stewards serve as subject matter experts for specific data domains.

Data Timeliness

A data quality dimension that measures whether data is available when needed. In healthcare, timely data entry and availability support clinical decision-making and regulatory reporting.

Data Warehouse

A large, centralized repository that stores integrated data from multiple sources for reporting and analysis. Healthcare data warehouses support decision support, outcomes research, and population health analytics.

Database Management System (DBMS)

Software that manages the storage, retrieval, and updating of data in a database. Common DBMS types used in healthcare include relational, object-oriented, and NoSQL databases.

Enterprise Information Management (EIM)

An integrative discipline for managing and governing an organization's information assets across the enterprise. EIM encompasses data governance, content management, and business intelligence.

Health Information Exchange (HIE)

The electronic sharing of health-related information among organizations according to nationally recognized standards. HIE supports coordinated care and reduces duplication of services.

Information Governance (IG)

An organization-wide framework for managing information throughout its lifecycle. IG encompasses data governance, information technology governance, clinical governance, and corporate governance as they relate to health information.

Information Lifecycle Management

The policies and procedures that govern data from creation through its final disposition. In healthcare, this includes record creation, maintenance, use, retention, and destruction.

Interoperability

The ability of different information systems, devices, and applications to access, exchange, integrate, and cooperatively use data in a coordinated manner. Interoperability is essential for seamless health information exchange.

Master Data Management (MDM)

A method of managing an organization's critical data to provide a single, consistent, and authoritative source of truth. In healthcare, MDM often focuses on patient, provider, and facility data.

Master Patient Index (MPI)

A database that maintains a unique identifier for every patient registered in a healthcare organization. The MPI links patient records across different systems to ensure accurate identification and record matching.

Metadata

Data that describes other data, providing context about the content, quality, format, and structure of information. In health records, metadata includes information such as the author, date created, and document type.

Record Retention Schedule

A policy document that specifies how long different types of records must be maintained before they can be destroyed. Retention schedules must comply with federal and state regulations as well as accreditation standards.

Relational Database

A type of database that organizes data into tables with rows and columns, using relationships between tables to link related information. Most healthcare information systems use relational database architecture.

Semantic Interoperability

The ability of systems to exchange data and have the meaning of that data automatically interpreted by the receiving system. It requires shared vocabularies and coding standards such as SNOMED CT and LOINC.

Structured Data

Data organized in a predefined format that can be easily searched and analyzed, such as coded fields in an EHR. Examples include ICD-10 codes, CPT codes, and demographic data fields.

Unstructured Data

Data that does not have a predefined format or organization, such as free-text clinical notes, scanned documents, and audio recordings. Unstructured data requires special techniques like natural language processing to analyze.