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First published October 18, 2007 as JAMIA PrePrint; doi:10.1197/jamia.M2506
Journal of the American Medical Informatics Association 2008;15(1):65-76
© 2008 American Medical Informatics Association

A more recent version of this article appeared on January 1, 2008
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Submitted on May 9, 2007
Accepted on August 8, 2007

A Model for Evaluating Interface Terminologies

S. Trent Rosenbloom MD, MPH1*, Randolph A. Miller MD2, Kevin B. Johnson MD3, Peter L. Elkin MD4, and Steven H. Brown MD5

Affiliation of the authors: 1 Department of Biomedical Informatics, Vanderbilt University, Nashville, TN; School of Nursing, Vanderbilt University, Nashville, TN; Department of Pediatrics, Vanderbilt University, Nashville, TN ; 2 Department of Biomedical Informatics, Vanderbilt University, Nashville, TN; School of Nursing, Vanderbilt University, Nashville, TN ; 3 Department of Biomedical Informatics, Vanderbilt University, Nashville, TN; Department of Pediatrics, Vanderbilt University, Nashville, TN ; 4 Mayo Foundation for Medical Education and Research, Rochester, MN; 5 Department of Biomedical Informatics, Vanderbilt University, Nashville, TN; U.S. Department of Veterans Affairs

* To whom correspondence should be addressed.

Evaluations of individual terminology systems should be driven in part by the intended usages of such systems. Clinical interface terminologies support interactions between healthcare providers and computer-based applications. They aid practitioners in converting clinical "free text" thoughts into the structured, formal data representations used internally by application programs. Interface terminologies also serve the important role of presenting existing stored, encoded data to end users in human-understandable and actionable formats. The authors present a model for evaluating functional utility of interface terminologies based on these intended uses. Specific parameters defined in the manuscript comprise the metrics for the evaluation model. These parameters include concept accuracy, term expressivity, degree of semantic consistency for term construction and selection, adequacy of assertional knowledge supporting concepts, degree of complexity of pre-coordinated concepts, and the "human readability" of the terminology. The fundamental metric is how well the interface terminology performs in supporting correct, complete and efficient data encoding or review by humans. Authors provide examples demonstrating performance of the proposed evaluation model in selected instances.




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