Automatic identification of comparative effectiveness research from medline citations to support clinicians' treatment information needs

Mingyuan Zhang, Guilherme Del Fiol, Randall W. Grout, Siddhartha Jonnalagadda, Richard Medlin, Rashmi Mishra, Charlene Weir, Hongfang Liu, Javed Mostafa, Marcelo Fiszman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Online knowledge resources such as Medline can address most clinicians' patient care information needs. Yet, significant barriers, notably lack of time, limit the use of these sources at the point of care. The most common information needs raised by clinicians are treatment-related. Comparative effectiveness studies allow clinicians to consider multiple treatment alternatives for a particular problem. Still, solutions are needed to enable efficient and effective consumption of comparative effectiveness research at the point of care. Objective: Design and assess an algorithm for automatically identifying comparative effectiveness studies and extracting the interventions investigated in these studies. Methods: The algorithm combines semantic natural language processing, Medline citation metadata, and machine learning techniques. We assessed the algorithm in a case study of treatment alternatives for depression. Results: Both precision and recall for identifying comparative studies was 0.83. A total of 86% of the interventions extracted perfectly or partially matched the gold standard. Conclusion: Overall, the algorithm achieved reasonable performance. The method provides building blocks for the automatic summarization of comparative effectiveness research to inform point of care decision-making.

Original languageEnglish (US)
Title of host publicationMEDINFO 2013 - Proceedings of the 14th World Congress on Medical and Health Informatics
PublisherIOS Press
Pages846-850
Number of pages5
Edition1-2
ISBN (Print)9781614992882
DOIs
StatePublished - Jan 1 2013
Event14th World Congress on Medical and Health Informatics, MEDINFO 2013 - Copenhagen, Denmark
Duration: Aug 20 2013Aug 23 2013

Publication series

NameStudies in Health Technology and Informatics
Number1-2
Volume192
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Other

Other14th World Congress on Medical and Health Informatics, MEDINFO 2013
CountryDenmark
CityCopenhagen
Period8/20/138/23/13

Keywords

  • Comparative effectiveness research
  • computer assisted decision making
  • information needs
  • machine learning

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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  • Cite this

    Zhang, M., Del Fiol, G., Grout, R. W., Jonnalagadda, S., Medlin, R., Mishra, R., Weir, C., Liu, H., Mostafa, J., & Fiszman, M. (2013). Automatic identification of comparative effectiveness research from medline citations to support clinicians' treatment information needs. In MEDINFO 2013 - Proceedings of the 14th World Congress on Medical and Health Informatics (1-2 ed., pp. 846-850). (Studies in Health Technology and Informatics; Vol. 192, No. 1-2). IOS Press. https://doi.org/10.3233/978-1-61499-289-9-846