Document Detail


Query log analysis of an electronic health record search engine.
MedLine Citation:
PMID:  22195150     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
We analyzed a longitudinal collection of query logs of a full-text search engine designed to facilitate information retrieval in electronic health records (EHR). The collection, 202,905 queries and 35,928 user sessions recorded over a course of 4 years, represents the information-seeking behavior of 533 medical professionals, including frontline practitioners, coding personnel, patient safety officers, and biomedical researchers for patient data stored in EHR systems. In this paper, we present descriptive statistics of the queries, a categorization of information needs manifested through the queries, as well as temporal patterns of the users' information-seeking behavior. The results suggest that information needs in medical domain are substantially more sophisticated than those that general-purpose web search engines need to accommodate. Therefore, we envision there exists a significant challenge, along with significant opportunities, to provide intelligent query recommendations to facilitate information retrieval in EHR.
Authors:
Lei Yang; Qiaozhu Mei; Kai Zheng; David A Hanauer
Publication Detail:
Type:  Journal Article     Date:  2011-10-22
Journal Detail:
Title:  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium     Volume:  2011     ISSN:  1942-597X     ISO Abbreviation:  AMIA Annu Symp Proc     Publication Date:  2011  
Date Detail:
Created Date:  2011-12-23     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101209213     Medline TA:  AMIA Annu Symp Proc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  915-24     Citation Subset:  IM    
Affiliation:
School of Information;
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