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

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


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

Topics: Original Investigation
Publisher: American Medical Informatics Association
Year: 2003
DOI identifier: 10.1197/jamia.M1133
OAI identifier:
Provided by: PubMed Central
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