CMDP key terms

The system of decision rights and accountability that determines who can take which actions with which data, and under what rules. It sets policy and oversight rather than performing daily data tasks.

The hands-on role of caring for a defined set of data on behalf of others: resolving quality issues, approving definitions, and enforcing governance policy. Stewards translate policy into operational practice within a domain.

The accountable executive or role with authority to approve access, define permitted uses, and accept risk for a data domain. Ownership is about accountability and decision rights, not day-to-day maintenance.

A person assigned to maintain the quality, definitions, and appropriate use of data within a subject area. Stewards coordinate issue resolution and serve as the point of contact for questions about that domain.

A catalog of data elements with their names, definitions, formats, allowed values, and ownership. It gives everyone a shared, unambiguous meaning for each field used in systems and reports.

Data that describes other data, such as source, format, ownership, refresh date, or sensitivity classification. Metadata makes data findable, interpretable, and governable without opening the underlying records.

The documented path showing where data originated, how it was transformed, and where it flows downstream. Lineage supports impact analysis, audit, and trust in reported results.

The record of the origin and history of a data value, including its source system, collection context, and any changes made. It answers whether a value can be trusted and traced.

The discipline of creating and maintaining a single trusted reference for core entities such as patients, providers, and facilities across systems. It reduces duplication and conflicting versions of the same entity.

The measurable characteristics used to judge fitness of data, commonly accuracy, completeness, consistency, timeliness, validity, and uniqueness. Each dimension needs an explicit definition and a way to measure it.

A structured review that measures data against defined quality dimensions and thresholds, then documents gaps and remediation. It produces evidence that data are fit for their intended use.

The process of examining a dataset statistically to reveal patterns, anomalies, missing values, and value distributions. Profiling informs which quality rules and validations are needed.

A defined, testable condition that data must meet, such as a required field, an allowed range, or a cross-field consistency check. Rules convert quality expectations into repeatable automated tests.

The process of confirming that data meet predefined rules for format, range, consistency, and completeness before use. Validation may occur at entry, during transfer, or before analysis.

Independent confirmation that data match their source or intended value, often performed by a second person or system. Verification differs from validation in that it checks against an external reference.

The degree to which all required data elements are present and populated for each record. Completeness is measured against a defined requirement, not simply against whatever fields exist.

The assurance that data remain accurate, unaltered, and consistent throughout their lifecycle, including protection from unauthorized or undetected change. It is supported by controls such as audit trails and access restrictions.

A secure, time-stamped record of who created, changed, or accessed a data value, including the reason when required. It allows reconstruction of the data's history without altering the original entries.

A set of expectations for trustworthy records: attributable, legible, contemporaneous, original, accurate, plus complete, consistent, enduring, and available. They are widely applied to clinical trial and regulated health data.

The original record where a clinical observation is first captured, such as a hospital chart, lab report, or device output. Source documents are the reference against which entered trial data are checked.

Comparison of data entered into a study database against the original source documents to confirm agreement. It detects transcription errors and supports the credibility of trial results.

The structured instrument, paper or electronic, used to collect protocol-specified data for each study participant. Its design and completion rules determine what data reach the study database.

An automated or manual rule applied during data entry that flags values failing format, range, or logic conditions. Edit checks catch errors early and generate queries for resolution.

The process of raising, tracking, and resolving questions about discrepant or missing data between reviewers and data originators. Complete documentation of resolutions preserves an auditable record.

Assignment of standardized codes to diagnoses, procedures, drugs, or devices based on clinical documentation. Coding enables billing, statistics, and interoperability but depends on documentation quality.

An international classification system for diseases, injuries, and causes of death, maintained by WHO with national clinical modifications. It supports morbidity and mortality statistics and, in the US, diagnosis coding for reimbursement.

A comprehensive, concept-based clinical terminology with formal relationships between concepts, used to represent findings, procedures, and other clinical ideas. Its hierarchy and synonyms support detailed, computable clinical documentation.

A standard vocabulary of codes and names for laboratory tests and clinical observations. It lets results from different laboratories be recognized as measuring the same thing.

A defined collection of codes drawn from one or more terminologies to represent a clinical concept for a specific purpose. Value sets make rules and quality measures computable and consistent.

The documented process of linking concepts in one vocabulary or local code system to equivalent concepts in another. Maps require review because equivalence is often partial rather than exact.

A system that assigns a single identifier to each person across multiple source systems by matching demographic and other attributes. It reduces duplicate records and enables a consolidated view of care.

The electronic movement of health information among organizations according to agreed standards and governance. It aims to make relevant data available at the point of care across organizational boundaries.

The ability of systems to exchange data and to use the exchanged data correctly without special effort. It requires agreement on transport, structure, and meaning, not just a network connection.

The level of interoperability at which exchanged data carry shared, unambiguous meaning so receiving systems can interpret and act on them. It depends on standard terminologies and shared information models.

A standard that defines modular resources and modern web interfaces for exchanging health data. Its granular, API-based design supports mobile apps, queries, and targeted data exchange.

A specification that lets third-party applications launch within a clinical system and access FHIR data under controlled authorization. It pairs an app platform with standard security and data-access patterns.

Individually identifiable health information held or transmitted by a covered entity or its business associate. Its use and disclosure are restricted by the HIPAA Privacy and Security Rules.

The principle that uses and disclosures of protected health information should be limited to the least amount reasonably needed for the purpose. It guides access design and routine release decisions.

The process of removing or transforming identifiers so health information no longer identifies an individual, using either safe-harbor removal of specified identifiers or expert statistical determination. Correctly de-identified data fall outside many privacy restrictions.

The likelihood that a person could be identified from supposedly anonymous data by combining it with other information. Small populations and rich quasi-identifiers raise this risk even after direct identifiers are removed.

An access model in which permissions are assigned to job roles and users receive access by holding a role. It simplifies administration and supports least-privilege and minimum-necessary requirements.

A contract required when a vendor handles protected health information on behalf of a covered entity, setting out permitted uses, safeguards, and breach obligations. It extends privacy and security duties to the vendor.

The legal duty to inform affected individuals, regulators, and sometimes the public when protected health information is impermissibly accessed or disclosed. Timelines and thresholds are set by applicable law.

A contract that limits how a recipient may use and disclose a defined dataset, often for research or secondary purposes. It specifies permitted purposes, prohibitions, and safeguards for the data.

The processes and systems that capture, record, and enforce a patient's choices about how their data may be used or shared. It ensures exchanges respect patient preferences and applicable legal requirements.

The stages data pass through from creation or capture to use, sharing, archiving, and eventual disposal. Governance, quality, and security controls are applied at each stage.

The rules and schedule defining how long each category of data must be kept to meet legal, clinical, or business needs. Retention periods must balance requirements against privacy risk from keeping data too long.

The controlled destruction or irreversible removal of data once retention requirements end. Disposal must be documented and performed securely so records cannot be reconstructed.

The technique of replacing or obfuscating sensitive values with realistic substitutes so that non-production users can work without seeing real identifiers. Masking preserves format while removing sensitivity.

The program that ensures clinical records accurately and completely reflect the patient's condition, care, and outcomes. It improves communication and the reliability of coded and reported data.

The graphical presentation of data, such as charts, maps, or dashboards, designed to make patterns and comparisons understandable. Effective design matches the visual form to the question and audience.

A quantifiable measure chosen to track progress toward a specific objective. Good indicators are defined precisely, tied to a decision, and monitored consistently over time.

The practice of combining data, narrative, and visuals to communicate a finding and its implications clearly. It focuses attention on the message and the action it supports, not on every available number.