Data Dictionary

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A data dictionary is a document, or collection, of data elements and their associated metadata.[1] The purpose of the data dictionary is to ultimately create an understanding of the data within a system.[2] It is often used a part of an organization's overall Data Governance strategy.

Rationale for a Data Dictionary

Within most modern healthcare organizations exists a large collection of systems collecting and presenting data. These systems often do so using similar terminology. Within each system, however, each term may have a different definition. This can create repositories of data that are disparate until the context of each element is fully understood. A data dictionary aims to create a central location to store and track all of these elements from each system within an organization. This allows for more meaningful understanding of relationships and a uniform set of definitions governing all systems within the organization.[3]


A common example is shown by describing an organization utilizing different EHRs between clinical departments. In this example, an organization’s Emergency Department uses an EHR that utilized the World Health Organization’s definition of an adolescent as any person between the ages of 10 and 19.[4] If this same adolescent is subsequently admitted to the hospital under the care of the Pediatrics Department they may use a separate EHR that arbitrarily defines an adolescent as any person between nine and 17. In this scenario the term adolescent is not always representative of the same population. This may have implications in the organization’s data operations including government reporting, monitoring, and research.

Types of Data Dictionaries

Most data dictionaries fall within two broad categories. The first, a database management system (DBMS), is a tool used to document the actual database layer within a target system. This is often utilized by the information technology department in managing their database infrastructure. The second type of data dictionary is the organization-wide data dictionary.[5] This dictionary aims to describe the common terms that might be utilized within several different systems throughout an organization. Its main focus is to bring data integrity to an organization’s entire data set through documentation of standard definitions, formats, and use cases.

It is likely that most organizations would require creation of both available types to form a complete picture of their data and to further the organization’s data governance strategy.

Example Metadata

The metadata included within a data dictionary will depend on which type of data dictionary is being created and the use case for the dictionary. A brief healthcare-focused example might be to describe a single set of metadata used to capture a medication’s name.

Database Management System

System PharmacyApp
Database dbPharmacyData
Table dbo.MedicationNames
Element Name medication_name
Full Path dbPharmacyData.dboMedicationsNames.medication_name
Type String
Size 32-bits
Format [a-z]
Allow Null? False
Primary Key NamesID
Child Tables
  • dbo.MedicationsDoses
  • dbo.MedicationRoutes
  • dbo.MedicationSchedules
  • Check dbo.MedicationNames.nameType to identify which type of name.
    • if nameType = G, the name is a generic type.
    • if nameType = B, the name is a brand type.
    • if nameType = C, the name is a chemical type.
Comment Stores each medication’s name as a lowercase string.

Organization-wide Data Dictionary

Element Name Generic Medication Name
Type String
Minimum Size 3 characters
Maximum Size 50 characters
Format lowercase letters (a-z)
Example omeprazole
Usage Utilized to uniquely identify each medication’s official name as assigned by the United States Adopted Names Council (USAN).
Associated Elements Medication Brand Name, Medication Doses, Medication Routes, Medication Schedules
Utilizing Systems PharmacyApp, Adverse Event Reporting System
Validation Source United States Adopted Name Council


  1. S&I Framework Clinical Element Data Dictionary.
  2. Northwest Environmental Data-Network. Best Practices for Data Dictionary Definitions and Usage. v 1.1 2006-11-14.
  3. Managing a Data Dictionary. AHIMA HIM Body of Knowledge.
  4. Adolescent development.
  5. LaTour, Kathleen, Eichenwald Maki, Shirley. Health Information Management: Concepts, Principles, and Practice. p 185-187. 4th Edition. Chicago, IL: AHIMA, 2013.

Submitted by Nicholas Perkins