Literature DB >> 8803668

Knowledge retrieval as one type of knowledge-based decision support in medicine: results of an evaluation study.

R Haux1, W Grothe, M Runkel, H K Schackert, H J Windeler, A Winter, R Wirtz, C Herfarth, S Kunze.   

Abstract

We report on a prospective, prolective observational study, supplying information on how physicians and other health care professionals retrieve medical knowledge on-line within the Heidelberg University Hospital information system. Within this hospital information system, on-line access to medical knowledge has been realised by installing a medical knowledge server in the range of about 24 GB and by providing access to it by health care professional workstations in wards, physicians' rooms, etc. During the study, we observed about 96 accesses per working day. The main group of health care professionals retrieving medical knowledge were physicians and medical students. Primary reasons for its utilisation were identified as support for the users' scientific work (50%), own clinical cases (19%), general medical problems (14%) and current clinical problems (13%). Health care professionals had accesses to medical knowledge bases such as MEDLINE (79%), drug bases ('Rote Liste', 6%), and to electronic text books and knowledge base systems as well. Sixty-five percent of accesses to medical knowledge were judged to be successful. In our opinion, medical knowledge retrieval can serve as a first step towards knowledge processing in medicine. We point out the consequences for the management of hospital information systems in order to provide the prerequisites for such a type of knowledge retrieval.

Mesh:

Year:  1996        PMID: 8803668     DOI: 10.1016/0020-7101(96)01160-9

Source DB:  PubMed          Journal:  Int J Biomed Comput        ISSN: 0020-7101


  3 in total

1.  Evaluation of Term Ranking Algorithms for Pseudo-Relevance Feedback in MEDLINE Retrieval.

Authors:  Sooyoung Yoo; Jinwook Choi
Journal:  Healthc Inform Res       Date:  2011-06-30

2.  Analysis of PubMed User Sessions Using a Full-Day PubMed Query Log: A Comparison of Experienced and Nonexperienced PubMed Users.

Authors:  Illhoi Yoo; Abu Saleh Mohammad Mosa
Journal:  JMIR Med Inform       Date:  2015-07-02

3.  A study on PubMed search tag usage pattern: association rule mining of a full-day PubMed query log.

Authors:  Abu Saleh Mohammad Mosa; Illhoi Yoo
Journal:  BMC Med Inform Decis Mak       Date:  2013-01-09       Impact factor: 2.796

  3 in total

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