Methods Inf Med 2005; 44(05): 616-625
DOI: 10.1055/s-0038-1634017
Original Article
Schattauer GmbH

Methods for Evaluation of Medical Terminological Systems

A Literature Review and a Case Study
D. G. T. Arts
1   Academic Medical Center, Department of Medical Informatics, Amsterdam, The Netherlands
,
R. Cornet
1   Academic Medical Center, Department of Medical Informatics, Amsterdam, The Netherlands
,
E. de Jonge
2   Academic Medical Center, Department of Intensive Care, Amsterdam, The Netherlands
,
N. F. de Keizer
1   Academic Medical Center, Department of Medical Informatics, Amsterdam, The Netherlands
› Author Affiliations
Further Information

Publication History

Received: 15 April 2004

accepted: 15 March 2005

Publication Date:
07 February 2018 (online)

Summary

Objectives: The usability of terminological systems (TSs) strongly depends on the coverage and correctness of their content. The objective of this study was to create a literature overview of aspects related to the content of TSs and of methods for the evaluation of the content of TSs. The extent to which these methods overlap or complement each other is investigated.

Methods: We reviewed literature and composed definitions for aspects of the evaluation of the content of TSs. Of the methods described in literature three were selected: 1) Concept matching in which two samples of concepts representing a) documentation of reasons for admission in daily care practice and b) aggregation of patient groups for research, are looked up in the TS in order to assess its coverage; 2) Formal algorithmic evaluation in which reasoning on the formally represented content is used to detect inconsistencies; and 3) Expert review in which a random sample of concepts are checked for incorrect and incomplete terms and relations. These evaluation methods were applied in a case study on the locally developed TS DICE (Diagnoses for Intensive Care Evaluation).

Results: None of the applied methods covered all the aspects of the content of a TS. The results of concept matching differed for the two use cases (63% vs. 52% perfect matches). Expert review revealed many more errors and incompleteness than formal algorithmic evaluation.

Conclusions: To evaluate the content of a TS, using a combination of evaluation methods is preferable. Different representative samples, reflecting the uses of TSs, lead to different results for concept matching. Expert review appears to be very valuable, but time consuming. Formal algorithmic evaluation has the potential to decrease the workload of human reviewers but detects only logical inconsistencies. Further research is required to exploit the potentials of formal algorithmic evaluation.

 
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