DISCOVERING CLINICAL EVIDENCE FOR EVIDENCE-BASED MEDICINE

Yunan Chen and Chaomai Chen
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Yunan Chen: College of Information Science & Technology, Drexel University, 3141 Chestnut Street, Philadelphia, PA, 19104, USA
Chaomai Chen: College of Information Science & Technology, Drexel University, 3141 Chestnut Street, Philadelphia, PA, 19104, USA

Chapter 21 in Knowledge Management:Nurturing Culture, Innovation, and Technology, 2005, pp 247-259 from World Scientific Publishing Co. Pte. Ltd.

Abstract: AbstractThe rapid growth of the medical literature has increased the challenge of finding information relevant to specific clinical questions. There is an urgent need for tools to assist the discovery of best evidence. In this paper we described a knowledge domain visualization based approach to the searching of best clinical evidence in medical literature. We applied the citation-based approach to two case studies of standard evidence-based medicine. We compared the gold standard papers used in the original case studies and articles identified by the citation-based approach. The results showed that gold standard papers and highly cited papers with high co-citation centrality are closed related. The strengths and limitations of our approach are discussed. We concluded that it is more effective and reliable to use our visualization tool to extract evidence to support clinicians' decision making than the traditional EBM approach.

Keywords: Knowledge Management; Knowledge Sharing; Knowledge Discovery; KM Tools and Technologies; Communication and Organization Culture (search for similar items in EconPapers)
Date: 2005
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