Controlled Medical Vocabularies (CMV)

Description:
CMV’s are tools that are used to arrange information in standard forms for reasons of gaining, encasing, changing, scouting, and analyzing data. CMV’s are databases of medical words or common phrases that are accessed to create an ease of use to scout the database for gaining the vocabulary in a medical dictionary through a simple search. Controlled medical vocabularies are essential to the medical field in today’s medicine because of their ease of use and quick access by medical staff. With the ability to simply search for a term by medical professionals there is a quickness associated to the treatment of patients. It is also a useful tool for doctors to read up on their past studies or to learn new terms. Terms that have just recently been coined by the scientific community. It is a great asset to todays medical staff in the assortment of information that has been amassed by humanity. Having this vast abundance of knowledge only increases the treatment, dedication, and overall professionalism of today’s doctors, nurses, and medical technicians.

The purpose of CMVs is to address the many needs and limitations of healthcare's information infrastructure, including:
  • reduce ambiguity that is inherent in normal human languages (for example, how heart attack, myocardial infarction, and MI may mean the same to us, but have no relation to a computer)
  • exchange information consistently between different providers, care settings, researchers, etc.
  • overcome differences in medical information recording from one place to another (unified medical terminology system needed)
  • summarize medical information
  • allow symbolic manipulation of data (searches for specific analysis)
  • automated reasoning (i.e. clinical decision support)

Applications:
The application of CMVs can be seen through various examples created for health care and used in varying facets and processes. Some CMVs include Systematized Nomenclature of Medicine Clinical Terms (SNOMED), Logical Observation Identifiers Names and Codes (LOINC), OpenGALEN, and the Unified Medical Language System (UMLS).
There are vocabularies that address the need to store information from paper records to electronic formats, as well as addressing the issue of differing electronic formats used - more specifically some vocabularies serve as translations to standardize electronic information received from various sources or locations.

Brief Overview of Examples of CMVs:

LOINC
  • database and universal standard for identifying laboratory observations
  • created in response to the demand for an electronic database for clinical care and management - publicly available at no cost
  • endorsed by the American Clinical Laboratory Association and the College of American Pathologist
  • applies universal code names and identifiers to medical terminology related to the Electronic Health Record (EHR)
  • purpose is to assist in electronic exchange and gathering of clinical results (such as laboratory tests, clinical observations, outcomes management and research)

OpenGALEN
  • not for profit organization, where you can download an open source medical terminology
  • terminology written in a formal language called GRAIL (GALEN Concept Representation Language)
  • GALEN Common Reference Model is designed to be a re-usable application-independent and language-independent model of medical concepts

UMLS-
  • a compendium of many controlled vocabularies in biomedical sciences
  • used to translate between various terminology systems
  • provides facilities for natural language processing
  • designed and maintained by US National Library of Medicine

SNOMED
  • systematically organized computer processable collection of medical terminology
  • allows consistent way to index, store, retrieve, and aggregate clinical data
  • helps organizing the content of medical records
  • compositional concept system - concepts can be specialized by combinations with other concepts
  • based on Description Logic and designed so content can be maintained as dynamic resource
  • Sample Computer Applications Using SNOMED CT:
    • Electronic Medical Records
    • Computerized Provider Order Entry Such As E-Prescribing Or Laboratory Order Entry
    • Remote Intensive Care Unit Monitoring
    • Laboratory Reporting
    • Emergency Room Charting
    • Cancer Reporting
    • Genetic Databases


Graphic:
external image post-coordination-v3-1.jpg

Related Terminology:
HL7
Mapping
Metadata
Information Infrastructure
Controlled Vocabulary

Citations/References:

http://www.pubmed.gov

http://www.ihtsdo.org/

College of American Pathologists (original creators of SNOMED CT)

National Library of Medicine