The development of PubMed search strategies for patient preferences for treatment outcomes. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: van Hoorn, Ralph; Kievit, Wietske; Booth, Andrew; Mozygemba, Kati; Lysdahl, Kristin; Refolo, Pietro; Sacchini, Dario; Gerhardus, Ansgar; van der Wilt, Gert; Tummers, Marcia
• Is Part Of: BMC medical research methodology. Volume 16:Issue 1(2016)
• Page Start: 1
• Page End: 7
• Publication Date: 2016-12
• Subjects: Patient preferences -- Treatment outcome -- Evidence-based medicine* -- Information storage and retrieval/methods* -- MEDLINE; Medicine -- Research -- Methodology -- Periodicals; 610.72
• DOI: 10.1186/s12874-016-0192-5
• Languages: English
• ISSNs: 1471-2288

Abstract

Abstract Background The importance of respecting patients' preferences when making treatment decisions is increasingly recognized. Efficiently retrieving papers from the scientific literature reporting on the presence and nature of such preferences can help to achieve this goal. The objective of this study was to create a search filter for PubMed to help retrieve evidence on patient preferences for treatment outcomes. Methods A total of 27 journals were hand-searched for articles on patient preferences for treatment outcomes published in 2011. Selected articles served as a reference set. To develop optimal search strategies to retrieve this set, all articles in the reference set were randomly split into a development and a validation set. MeSH-terms and keywords retrieved using PubReMiner were tested individually and as combinations in PubMed and evaluated for retrieval performance (e.g. sensitivity (Se) and specificity (Sp)). Results Of 8238 articles, 22 were considered to report empirical evidence on patient preferences for specific treatment outcomes. The best search filters reached Se of 100 % [95 % CI 100-100] with Sp of 95 % [94–95 %] and Sp of 97 % [97–98 %] with 75 % Se [74–76 %]. In the validation set these queries reached values of Se of 90 % [89–91 %] with Sp 94 % [93–95 %] and Se of 80 % [79–81 %] with Sp of 97 % [96–96 %], respectively. Conclusions Narrow and broad search queries were developed which can help in retrieving literature on patient preferences for treatment outcomes. Identifying such evidence may in turn enhance the incorporation of patient preferences in clinical decision making and health technology assessment.