The Unified Medical Language System (UMLS) and Computer-based Patient Records

  • Donald A. B. Lindberg
  • Betsy L. Humphreys
Part of the Computers in Health Care book series (HI)

Abstract

The purpose of the Unified Medical Language System (UMLS) (Lindberg and Humphreys 1989; Humphreys and Lindberg 1989) is to make machine-readable information relevant to particular practice and research questions readily available to health care practitioners and investigators. Important biomedical information is distributed among many different machine-information sources. These include databases of scientific literature, patient record, factual databanks, knowledgebased expert systems, and directories of individuals and institutions. Unfortunately, a number of significant barriers separate potential users from the information in such sources. The barriers include the variety of ways the same concepts are expressed in the different information sources and by the users themselves, the difficulty of identifying all the available sources and selecting those most appropriate to particular questions, and the range of access paths and conditions that must be negotiated to retrieve information from multiple sources. Such problems prevent individual users from gaining access to relevant machine readable information and also impede the development of more powerful search interfaces to help these users. The UMLS project is working to overcome these barriers and to facilitate the development of much more powerful and user friendly interfaces to machinereadable biomedical information. The UMLS is not an attempt to impose a single standard vocabulary on the biomedical community. It is an effort to deal effectively with continued diversity in biomedical terminology and information sources.

Keywords

Patient Record Control Vocabulary Current Procedural Terminology Unify Medical Language System External Information Source 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1992

Authors and Affiliations

  • Donald A. B. Lindberg
  • Betsy L. Humphreys

There are no affiliations available

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