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First published September 23, 2002 as JAMIA PrePrint; doi:10.1197/jamia.M1133
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Journal of the American Medical Informatics Association 10:21-38 (2003)
© 2003 American Medical Informatics Association

Model Formulation

Integrating Query of Relational and Textual Data in Clinical Databases: A Case Study

John M. Fisk, MD, Pradeep Mutalik, MD, Forrest W. Levin, MS, Joseph Erdos, MD, PhD, Caroline Taylor, MD and Prakash Nadkarni, MD

Affiliations of the authors: Center for Medical Informatics, Yale University School of Medicine, New Haven, Connecticut (JMF, PM, PN); Information Technology Office, Veterans Administra-tion Medical Center, West Haven, Connecticut (FWL, JE); Department of Radiology, Veterans Administration Medical Center, West Haven, Connecticut (CT).

Correspondence and reprints: Prakash M. Nadkarni, Center for Medical Informatics, Yale University School of Medicine, PO Box 208009, New Haven, CT 06520-8009; e-mail: <Prakash.Nadkarni{at}yale.edu>.

Objectives: The authors designed and implemented a clinical data mart composed of an integrated information retrieval (IR) and relational database management system (RDBMS).

Design: Using commodity software, which supports interactive, attribute-centric text and relational searches, the mart houses 2.8 million documents that span a five-year period and supports basic IR features such as Boolean searches, stemming, and proximity and fuzzy searching.

Measurements: Results are relevance-ranked using either "total documents per patient" or "report type weighting."

Results: Non-curated medical text has a significant degree of malformation with respect to spelling and punctuation, which creates difficulties for text indexing and searching. Presently, the IR facilities of RDBMS packages lack the features necessary to handle such malformed text adequately.

Conclusion: A robust IR+RDBMS system can be developed, but it requires integrating RDBMSs with third-party IR software. RDBMS vendors need to make their IR offerings more accessible to non-programmers.




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