Access to biomedical information: the Unified Medical Language System

High on the list of interests in biomedicine is vocabulary control of patient records, to facilitate their exchange, to more easily retrieve information from them, and to link them to the medical literature. Research has shown that patient encounters of ten generate questions that could be addressed to machine-readable sources. UMLS could be used for interpreting terms present in patient records, converting these to the vocabularies of information sources, and selecting and connecting automatically to them. It might help to summarize or collocate data from patient records. It might serve as the mapping mechanism between user queries or vocabulary from other sources to patient record databases. Lindberg and Humphreys (1992) propose steps to achieve better structured and maintained automated patient records that would facilitate their use with UMLS. These proposals include adopting a standard format for recording patient data, using only full terms rather than abbreviations or shorthand expressions, and imposing some vocabulary control over the most standard elements of a record, with minimal use of locally developed vocabularies or extensions of existing ones. Though driven primarily by needs for cost control and outcomes research, the push for standardization of patient data may be helped by the promise of unified mechanisms for information use and retrieval as represented by the UMLS.

Several projects have been inspired by the UMLS paradigm of linking user queries directly to automated searches of databases. The program, Psychtopix, described by Powsner and Miller (1989), uses the machine-readable text of a psychiatry consult as the basis for an automated search of MEDLINE. Words in the consult are matched to a set of predetermined clinical "topics" which then invoke "canned" MEDLINE searches. This method, going from terms to topics rather than from terms to searches, is also used by Interactive Query Workstation (Cimino & Barnett, 1990) and Medline Button (Cimino et al., 1993). These programs depend on Meta for appropriate query interpretation and formulation. In the latter program, International Classification of Disease, 9th ed., Clinical Modification terms used to record patient information are mapped to MESH terms through Meta when MEDLINE searches related to patient care are desired.

In a similar way to the COACH browser, Nelson et al. (1990) used MetaCard to permit a searcher to identify concepts in Meta, post them to a clipboard, and then incorporate them in a search of MEDLINE.

Powsner and Miller (1992) also use Meta to look up words selected by a user from the text of clinical records. After automatically matching the user-selected terms, the user is presented with a set of MeSH terms relevant to his or her input. The user can then select terms from the set and choose Boolean connectors to combine them to form a MEDLINE search.

The structure of Meta inspired Fu et al. (1990) to create a similarly structured patient database where entries describe not medical concepts but medical events. This database of events can then be used to index and accumulate patient information from a variety of sources and may serve as a means of mapping between different clinical databases. Meta is used as the source of terms to fill the attribute slots in medical event entries.