Yearb Med Inform 2008; 17(01): 80-82
DOI: 10.1055/s-0038-1638586
Original Article
Georg Thieme Verlag KG Stuttgart

Decision Support, Knowledge Representation and Management: Structuring Knowledge for Better Access

Findings from the Yearbook 2008 Section on Decision Support, Knowledge Representation and Management
A.-M. Rassinoux
1   University Hospitals of Geneva, Geneva, Switzerland
,
Managing Editor for the IMIA Yearbook Section on Decision Support, Knowledge Representation and Management › Author Affiliations
Further Information

Correspondence to

Anne-Marie Rassinoux, Ph. D.
University Hospitals of Geneva Service of Medical Informatics Unit of Clinical Informatics 24, rue Michelidu-Crest
CH-1211 Geneva 14, Switzerland
Phone: +41 22 372 6293   
Fax: +41 22 372 8680   

Publication History

Publication Date:
07 March 2018 (online)

 

Summary

Objectives To summarize current outstanding research in the field of decision support, knowledge representation and management.

Method Synopsis of the articles selected for the IMIA Yearbook 2008.

Results Five papers from international peer reviewed journals have been selected for the section on decision support, knowledge representation and management. They address a wide range of topics such as the recognition and extraction of negation or time from clinical narratives, the use of ontological elements to reduce the complexity of natural language processing applications or to strengthen the precision of document retrieval as well as the benefits of integrating clinical decision support within computer provider orderentry.

Conclusions The best paper selection brings to light that whatever the methodological approach used in decision support, knowledge representation and management, all applications benefit from manipulating information that is expressed in both a meaningful and structured way. In order to combine the flexibility and expressive power of natural language with the computational tractability of structured data, the electronic health record based on structured narrative offers new perspectives.


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  • References

  • 1 Kumar A, Smith B. Biomedical informatics and granularity. Comp Funct Genomics 2004; 05: 501-8.
  • 2 Tange HJ, Schouten HC, Kester ADM, Hasman A. The granularity of medical narratives and its effect on the speed and completeness of information retrieval. J Am Med Inform Assoc 1998; 05: 571-82.
  • 3 Lovis C, Baud RH, Planche P. Power of expression in the electronic patient record: structured data or narrative text?. Int J Med Inform 2000; 58-59: 101-10.
  • 4 Bernstein K, Bruun-Rasmussen M, Vingtoft S. A method for specification of structured clinical content in electronic health records. Stud Health Technol Inform 2006; 124: 515-21.
  • 5 Los RK, van Ginneken AM, de Wilde M, van der Lei J. OpenSDE: Row modeling applied to generic structured data entry. JAm Med InformAssoc 2004; 11 (02) 162-5.
  • 6 Friedman C, Hripcsak G. Natural language processing and its future in medicine. Acad Med 1999; 74 (08) 890-5.
  • 7 Chen L, Friedman C. Extracting phenotypic information from the literature via natural language processing. Medinfo 2004; 11 Pt2 758-62.
  • 8 Stenzhorn H, Beisswanger E, Schulz S. Towards a top-domain ontology for linking biomedical ontologies. Medinfo 2007; 12 Pt2 1225-9.
  • 9 Hung PW, Johnson SB, Kaufman DR, Mendonça EA. A multi-level model of information seeking in the clinical domain. J Biomed Inform 2008; 41: 357-70.
  • 10 Augusto JC. Temporal reasoning for decision support in medicine. Artif Intell Med 2005; 33 (01) 1-24.
  • 11 Zhou L, Hripcsak G. Temporal reasoning with medical data - a review with emphasis on medical natural language processing. J Biomed Inform 2007; 40 (02) 183-202.
  • 12 Huang Y, Lowe HJ. A novel hybrid approach to automated negation detection in clinical radiology reports. JAm Med InformAssoc 2007; 14 (03) 304-11.
  • 13 Fan JW, Friedman C. Semantic classification of biomedical concepts using distributional similarity. J Am Med Inform Assoc 2007; 14 (04) 467-77.
  • 14 Moskovitch R, Martins SB, Behiri E, Weiss A, Shahar Y. A comparative evaluation of full-text, concept-based, and context-sensitive search. J Am Med Inform Assoc 2007; 14 (02) 164-74.
  • 15 Kuperman GJ, Bobb A, Payne TH, Avery AJ, Gandhi TK, Burns G. et al. Medication-related clinical decision support in computerized provider order entry systems: a review. J Am Med Inform Assoc 2007; 14 (01) 29-40.
  • 16 Brigl B. Decision Support, Knowledge Representation and Management: A broad methodological spectrum. In Haux R, Kulikowski C. editors. IMIA Yearbook of Medical informatics 2006. Methods Inf Med. 2006. 45 Suppl 1: 81-3.
  • 17 Meystre S. Electronic patient records: Some answers to the data representation and reuse challenges. In Geissbuhler A, Haux R, Kulikowski C. editors IMIAYearbook of Medical Informatics. 2007: 47-8.
  • 18 Fujii H, Yamagishi H, Ando Y, Tsukamoto N, Kawaguchi O, Kasamatsu T. et al. Structuring of free-text diagnostic report. Medinfo 2007; 12 Pt1 669-73.
  • 19 Chen ES, Hripcsak G, Friedman C. Disseminating natural language processed clinical narratives. AMIA Annu Symp Proc 2006; 126-30.
  • 20 Johnson SB, Bakken S, Dine D, Hyun S, Mendonça E, Morrison F. et al. An electronic health record based on structured narrative. J Am Med Inform Assoc 2008; 15 (01) 54-64.

Correspondence to

Anne-Marie Rassinoux, Ph. D.
University Hospitals of Geneva Service of Medical Informatics Unit of Clinical Informatics 24, rue Michelidu-Crest
CH-1211 Geneva 14, Switzerland
Phone: +41 22 372 6293   
Fax: +41 22 372 8680   

  • References

  • 1 Kumar A, Smith B. Biomedical informatics and granularity. Comp Funct Genomics 2004; 05: 501-8.
  • 2 Tange HJ, Schouten HC, Kester ADM, Hasman A. The granularity of medical narratives and its effect on the speed and completeness of information retrieval. J Am Med Inform Assoc 1998; 05: 571-82.
  • 3 Lovis C, Baud RH, Planche P. Power of expression in the electronic patient record: structured data or narrative text?. Int J Med Inform 2000; 58-59: 101-10.
  • 4 Bernstein K, Bruun-Rasmussen M, Vingtoft S. A method for specification of structured clinical content in electronic health records. Stud Health Technol Inform 2006; 124: 515-21.
  • 5 Los RK, van Ginneken AM, de Wilde M, van der Lei J. OpenSDE: Row modeling applied to generic structured data entry. JAm Med InformAssoc 2004; 11 (02) 162-5.
  • 6 Friedman C, Hripcsak G. Natural language processing and its future in medicine. Acad Med 1999; 74 (08) 890-5.
  • 7 Chen L, Friedman C. Extracting phenotypic information from the literature via natural language processing. Medinfo 2004; 11 Pt2 758-62.
  • 8 Stenzhorn H, Beisswanger E, Schulz S. Towards a top-domain ontology for linking biomedical ontologies. Medinfo 2007; 12 Pt2 1225-9.
  • 9 Hung PW, Johnson SB, Kaufman DR, Mendonça EA. A multi-level model of information seeking in the clinical domain. J Biomed Inform 2008; 41: 357-70.
  • 10 Augusto JC. Temporal reasoning for decision support in medicine. Artif Intell Med 2005; 33 (01) 1-24.
  • 11 Zhou L, Hripcsak G. Temporal reasoning with medical data - a review with emphasis on medical natural language processing. J Biomed Inform 2007; 40 (02) 183-202.
  • 12 Huang Y, Lowe HJ. A novel hybrid approach to automated negation detection in clinical radiology reports. JAm Med InformAssoc 2007; 14 (03) 304-11.
  • 13 Fan JW, Friedman C. Semantic classification of biomedical concepts using distributional similarity. J Am Med Inform Assoc 2007; 14 (04) 467-77.
  • 14 Moskovitch R, Martins SB, Behiri E, Weiss A, Shahar Y. A comparative evaluation of full-text, concept-based, and context-sensitive search. J Am Med Inform Assoc 2007; 14 (02) 164-74.
  • 15 Kuperman GJ, Bobb A, Payne TH, Avery AJ, Gandhi TK, Burns G. et al. Medication-related clinical decision support in computerized provider order entry systems: a review. J Am Med Inform Assoc 2007; 14 (01) 29-40.
  • 16 Brigl B. Decision Support, Knowledge Representation and Management: A broad methodological spectrum. In Haux R, Kulikowski C. editors. IMIA Yearbook of Medical informatics 2006. Methods Inf Med. 2006. 45 Suppl 1: 81-3.
  • 17 Meystre S. Electronic patient records: Some answers to the data representation and reuse challenges. In Geissbuhler A, Haux R, Kulikowski C. editors IMIAYearbook of Medical Informatics. 2007: 47-8.
  • 18 Fujii H, Yamagishi H, Ando Y, Tsukamoto N, Kawaguchi O, Kasamatsu T. et al. Structuring of free-text diagnostic report. Medinfo 2007; 12 Pt1 669-73.
  • 19 Chen ES, Hripcsak G, Friedman C. Disseminating natural language processed clinical narratives. AMIA Annu Symp Proc 2006; 126-30.
  • 20 Johnson SB, Bakken S, Dine D, Hyun S, Mendonça E, Morrison F. et al. An electronic health record based on structured narrative. J Am Med Inform Assoc 2008; 15 (01) 54-64.