Clinical vocabularies, terminologies or coding systems, are structured list of terms which together with their definitions are designed to describe unambiguously the care and treatment of patients. Terms cover diseases, diagnoses, findings, operations, treatments, drugs, administrative items etc., and can be used to support recording and reporting a patient's care at varying levels of detail, whether on paper or, increasingly, via an electronic medical record.

A nomenclature is a relatively simple system of names; a vocabulary is a system of names with explanations of their meanings; a classification is a systematic organisation of things into classes, and a thesaurus (such as MeSH) is designed to index medical literature and support search over bibliogaphic databases. But many of the terms used in this field can prove difficult to define accurately, and their use in practice can be inconsistent. We refer readers for more detailed introductory information and discussion on medical terminologies to the tutorial by Jeremy Rogers of Manchester University (see link below), and to Part 5 (chapters 16-18) of Enrico Coiera's Guide to Health Informatics entitled 'Language, coding and classification'.

Medical coding and classification systems form part of current moves towards implementing a standardised "language for health": a common (computerized) medical language for global use. The US Institute of Medicine 2003 report, Patient Safety: Achieving a New Standard for Care, highlights the importance of terminologies to healthcare and provides the following summary of their purpose and a likely outcome of current efforts in the field:

"If health professionals are to be able to send and receive data in an understandable and usable manner, both the sender and the receiver must have common clinical terminologies for describing, classifying, and coding medical terms and concepts. Use of standardized clinical terminologies facilitates electronic data collection at the point of care; retrieval of relevant data, information, and knowledge; and reuse of data for multiple purposes (e.g., disease surveillance, clinical decision support, patient safety reporting).

"No single terminology has the depth and breadth to represent the broad spectrum of medical knowledge; thus a core group of well-integrated, non-redundant clinical terminologies will be needed to serve as the backbone of clinical information and patient safety systems." [Patient Safety: Achieving a New Standard for Care P14-15 (OC)]

Some discussion points:

• A very large number of coding and classification systems have been developed for healthcare.
• Many standards have been proposed but widespread adoption has been slow.
• Current standards tend to compete.
• Existing medical vocabularies vary in their coverage and completeness.
• Many classifications overlap.
• Historically, vocabulary and classification systems have been designed to meet different and specific goals. Many codes have been designed mainly to support administation (e.g. billing) so have typically included, for example, only a limited number of diagnosis codes for each encounter. Widely-used but essentially administration-oriented system, such as ICD, have been mandated by government agencies and/or payor organizations but capture clinical data at an insufficient level of detail to support clinical needs that lie outside the limited range of activities they were designed to support.
• Systems designed to cover clinical information have tended to cover a relatively narrow subset of healthcare, such as nursing procedures or problem lists.
• Some systems that concentrate on coding fine-grained primary clinical data have been proprietary, custom-built, limited, difficult for clinicians to use and have resulted, in some cases, in low user acceptance.
• Coding systems can lose clinical information.
• It can be difficult to compare clinical coding systems.
• One stated ideal would be a system that allowed clinicians to record primary clinical data using natural language which could be automatically turned into standardized code.
• Interoperability is a significant problem. Content, structure, completeness, detail, cross-mapping, taxonomy, definitions, clarity vary between existing vocabularies.
• A single, comprehensive standard medical terminology which would improve the automated flow of clinical information does not exist - though remains a goal for many.
• Many of established medical coding systems lack a precise semantic underpinning. (The recent emergence of description logic encoded medical terminologies - particularly SNOMED CT - aims to address this problem.)
• Comprehensive clinical terminology systems are needed to help integrate patient data with health information technologies such as electronic medical records. SNOMED CT aims to help structure and computerize the medical record but needs to be used correctly and consistently to preserve data quality and maximise shareability.
• Integration of electronic patient records and medical terminologies with decision support systems is being researched, for example by the SAGE project in the USA and as part of the DeGeL digital guideline library infrastructure (Israel/USA).

• Medical terminologies are evolving from relatively "simple code-name-hierarchy structures, into rich, knowledge-based ontologies of medical concepts" [Cimino, 2001]
• Recent work has aimed to build shareable and reusable computerised vocabularies (such as GALEN)
• Semantic tools are under development to help end users manage vocabularies.
• The more recent emergence of Description Logic encoded medical terminologies has the potential to facilitate transition to the Semantic Web and pave the way for integration of medical computer systems into E-Grid networks.
Cimino [Cimino, 1998], continuing work published in [Cimino, 1989], has listed a set of desirable features for computerised medical vocabularies in the 21st Century offering the following propositions:
• Specify multiple hierarchies (rather than lists)
• Maintain formal definitions (replacing informal descriptions)
• Stress structurual and knowledge representation issues (not just on expanding content)
• Maintain systematics approaches to updating vocabularies
• Ensure domain completeness
• Eliminate "not elsewhere classified" terms (which may be introduced to deal with incompleteness in a vocabulary)
• Allow for graceful evolution in vocabulary design to support inclusion of new developments in healthcare and error correction.
• Be able to recognise redundancy where the same information is expressed in different ways.
• Ensure concept permanence: don't delete a concept or change its meaning
• Don't include meaningless concept identifiers
• Support multiple granularities to meet the differing needs of different users
• Maintain multiple consistent views: ensure consistency over different views of a hierarchy
• Represent context specific information to maintain the relationship between a concept and teh context in which it is used.

E. Coiera. The Guide to Health Informatics (2nd Edition). Arnold, London, October 2003. [Chapter 17 sample chapter - freely available: Healthcare Terminologies and Classification Systems] Other relevant chapters in this book include: Chapter 16: Terms, codes and classification Chapter 18: The trouble with coding

This sample chapter (17) from part of Part 5 of Coiera's book (Language, Coding and Classification) covers the history of medical classification systems and nonemclatures; discusses the characteristics, benefits and limitations of a number of specific systems (ICD, SNOMED ....), and looks at valid (and invalid) ways of comparing them.

J.H. van Bemmel, M.A. Musen (Editors). The Handbook of Medical Informatics. Springer-Verlag, New York, 1998. [V3.3 on MIEUR website]

Wyatt JC, Liu JL. Basic concepts in medical informatics. J Epidemiol Community Health. 2002 Nov;56(11):808-12. [PubMed]   [JECH Online]

" This glossary defines terms used in the comparatively young science of medical informatics. It is hoped that it will be of interest to both novices and professionals in the field. "

de Lusignan S. Codes, classifications, terminologies and nomenclatures: definition, development and application in practice. Inform Prim Care. 2005;13(1):65-70. [PubMed]   []

" The Primary Care Informatics Working Group of EFMI is working to help develop the core theory of primary care informatics (PCI). Codes, classifications, terminologies and nomenclatures form an important part of the science of PCI, as they allow clinical information to be readily stored and processed in information systems. This article provides definitions and a history of the International Classification for Primary Care (ICPC), and of the Read code and the Systematized Nomenclature for Medicine (SNOMED). The Working Group wishes to encourage shared definitions and an understanding of the practical application of structured data to improve quality in clinical practice. "