From data to knowledge through concept-oriented terminologies: experience with the Medical Entities Dictionary

Abstract

Knowledge representation involves enumeration of conceptual symbols and arrangement of these symbols into some meaningful structure. Medical knowledge representation has traditionally focused more on the structure than the symbols. Several significant efforts are under way, at local, national, and international levels, to address the representation of the symbols though the creation of high-quality terminologies that are themselves knowledge based. This paper reviews these efforts, including the Medical Entities Dictionary (MED) in use at Columbia University and the New York Presbyterian Hospital. A decade's experience with the MED is summarized to serve as a proof-of-concept that knowledge-based terminologies can support the use of coded patient data for a variety of knowledge-based activities, including the improved understanding of patient data, the access of information sources relevant to specific patient care problems, the application of expert systems directly to the care of patients, and the discovery of new medical knowledge. The terminological knowledge in the MED has also been used successfully to support clinical application development and maintenance, including that of the MED itself. On the basis of this experience, current efforts to create standard knowledge-based terminologies appear to be justified.

Figure 1

Two representations of the medical concept “Serum Glucose Test,” using frame-based (top) and conceptual graph (bottom) formalisms. In each case, the other terms (“Laboratory Test,” “Serum Specimen,” and “Glucose”) are also controlled terms represented with their own knowledge.

Figure 2

Example from the Medical Entities Dictionary. The term in the box (Plasma Glucose Test) is shown in relation to its parents in the isa hierarchy (solid lines) and by nonhierarchic semantic links (broken lines) to other terms in the network.

Figure 3

Screens from two applications that use the Medical Entities Dictionary (MED) knowledge about spreadsheets. Top, A display from the Decision-supported Outpatient Practice application, an X-Window application, showing the Chem-20 spreadsheet. Each row corresponds to a class of laboratory test terms in the MED.

Figure 3

Screens from two applications that use the Medical Entities Dictionary (MED) knowledge about spreadsheets. Bottom, Use of the same information by WebCIS to create a Chem-20 display for the Web.

Figure 4

A concept-oriented view of a patient's medical record, generated from Medical Entities Dictionary knowledge. In this example, the problem of interest is pulmonary heart disease, and the data displayed are a subset of medication orders.

Figure 5

Integrations of DXplain with a clinical information system. Top, The numeric results from a chemistry panel have been converted to specific clinical findings to be passed to DXplain.

Figure 5

Integrations of DXplain with a clinical information system. Bottom, The differential diagnosis obtained from DXplain.