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First published August 4, 2003 as JAMIA PrePrint; doi:10.1197/jamia.M1369
Journal of the American Medical Informatics Association 2003;10(6):580-587
© 2003 American Medical Informatics Association

A more recent version of this article appeared on November 1, 2003
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Submitted on March 21, 2003
Accepted on June 30, 2003

A Pilot Study of Contextual UMLS® Indexing to Improve the Precision of Concept-Based Representation in XML-Structured Clinical Radiology Reports

Yang Huang MS1, Henry J. Lowe MD1*, and William R. Hersh MD2

Affiliation of the authors: 1 Stanford Medical Informatics and The Office of Information Resources and Technology, Stanford University School of Medicine, Stanford, CA; 2 Division of Medical Informatics & Outcomes Research, Oregon Health & Science University, Portland, OR

* To whom correspondence should be addressed.

Objective Despite the advantages of structured data entry, much of the patient record is still stored as unstructured or semi-structured narrative text. The issue of representing clinical document content remains problematic. Our prior work using an automated UMLS® document indexing system has been encouraging but has been impacted by the generally low indexing precision of such systems. In an effort to improve precision we have developed a context-sensitive document indexing model to calculate the optimal subset of UMLS® source vocabularies used to index each document section. This pilot study was performed to evaluate the utility of this indexing approach on a set of clinical radiology reports.

Design A set of clinical radiology reports that had been manually indexed using UMLS® concept descriptors was automatically indexed by the Saphire indexing engine. Using the data generated by this process we developed a system that simulated indexing, at the document section level, of this same document set using many permutations of a subset of the UMLS® constituent vocabularies.

Measurements We determined the precision and recall scores generated by simulated indexing for each permutation of two or three UMLS® constituent vocabularies.

Results While there was considerable variation in precision and recall values across the different subtypes of radiology reports, the overall effect of this indexing strategy using the best combination of two or three UMLS® constituent vocabularies was an improvement in precision without significant impact of recall.

Conclusion In this pilot study a contextual indexing strategy improved overall precision in a set of clinical radiology reports.




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