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EPC methods. An exploration of the use of text-mining software in systematic reviews

Author: Robin Paynter; Scientific Resource Center (Portland, Or.),; United States. Agency for Healthcare Research and Quality,
Publisher: Rockville, MD Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services, April 2016.
Series: Research white paper.
Edition/Format:   eBook : Document : National government publication : English
Summary:
OBJECTIVE: This project's goal was to provide a preliminary sketch of the use of text-mining tools as an emerging methodology within a number of systematic review processes. We sought to provide information addressing pressing questions individuals and organizations face when considering utilizing text-mining tools. METHODS: We searched the literature to identify and summarize research on the use of text-mining  Read more...
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Genre/Form: Review
Material Type: Document, Government publication, National government publication, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Robin Paynter; Scientific Resource Center (Portland, Or.),; United States. Agency for Healthcare Research and Quality,
OCLC Number: 955092619
Description: 1 online resource (1 PDF file (various pagings))
Series Title: Research white paper.
Other Titles: Exploration of the use of text-mining software in systematic reviews
Responsibility: prepared for Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services ; prepared by Scientific Resource Center ; investigators, Robin Paynter, Lionel L. Bañez, Elise Berliner, Eileen Erinoff, Jennifer Lege-Matsuura, Shannon Potter, Stacey Uhl.

Abstract:

OBJECTIVE: This project's goal was to provide a preliminary sketch of the use of text-mining tools as an emerging methodology within a number of systematic review processes. We sought to provide information addressing pressing questions individuals and organizations face when considering utilizing text-mining tools. METHODS: We searched the literature to identify and summarize research on the use of text-mining tools within the systematic review context. We conducted telephone interviews with Key Informants (KIs; n=8) using a semi-structured instrument and subsequent qualitative analysis to explore issues surrounding the implementation and use of text-mining tools. Lastly, we compiled a list of text-mining tools to support systematic review methods and evaluated the tools using an informal descriptive appraisal tool. RESULTS: The literature review identified 122 articles that met inclusion criteria, including two recent systematic reviews on the use of text-mining tools in the screening and data abstraction steps of systematic reviews. In addition to these two steps, a preliminary exploration of the literature on searching and other less-studied steps are presented. Support for the use of text-mining was strong amongst the KIs overall, though most KIs noted some performance caveats and/or areas in which further research is necessary. We evaluated 111 text-mining tools identified from the literature review and KI interviews. CONCLUSIONS: Text-mining tools are currently being used within several systematic review organizations for a variety of review processes (e.g., searching, screening abstracts), and the published evidence-base is growing fairly rapidly in breadth and levels of evidence. Several outstanding questions remain for future empirical research to address regarding the reliability and validity of using these emerging technologies across a variety of review processes and whether these generalize across the scope of review topics. Guidance on reporting the use of these tools would be useful.

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