Integrating the framing of clinical questions via PICO into the retrieval of medical literature for systematic reviews

Harrisen Scells, Guido Zuccon, Bevan Koopman, Anthony Deacon, Leif Azzopardi, Shlomo Geva

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

39 Citations (Scopus)
382 Downloads (Pure)

Abstract

The PICO process is a technique used in evidence based practice to frame and answer clinical questions. It involves structuring the question around four types of clinical information: Population, Intervention, Control or comparison and Outcome. The PICO framework is used extensively in the compilation of systematic reviews as the means of framing research questions. However, when a search strategy (comprising of a large Boolean query) is formulated to retrieve studies for inclusion in the review, PICO is offen ignored. This paper evaluates how PICO annotations can be applied and integrated into retrieval to improve the screening of studies for inclusion in systematic reviews. The task is to increase precision while maintaining the high level of recall essential to ensure systematic reviews are representative and unbiased. Our results show that restricting the search strategies to match studies using PICO annotations improves precision, however recall is slightly reduced, when compared to the non-PICO baseline. This can lead to both time and cost savings when compiling systematic reviews.

Original languageEnglish
Title of host publicationCIKM 2017 - Proceedings of the 2017 ACM Conference on Information and Knowledge Management
Place of PublicationNew York
Pages2291-2294
Number of pages4
DOIs
Publication statusPublished - 6 Nov 2017
Event26th ACM International Conference on Information and Knowledge Management, CIKM 2017 - Singapore, Singapore
Duration: 6 Nov 201710 Nov 2017

Conference

Conference26th ACM International Conference on Information and Knowledge Management, CIKM 2017
Country/TerritorySingapore
CitySingapore
Period6/11/1710/11/17

Keywords

  • PICO process
  • information retrieval
  • clinical information
  • integration

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