Development and validation of search filters to find articles on palliative care in bibliographic databases

Abstract

Background: Healthcare professionals and researchers in the field of palliative care often have difficulties finding relevant articles in online databases. Standardized search filters may help improve the efficiency and quality of such searches, but prior developed filters showed only moderate performance. Aim: To develop and validate a specific search filter and a sensitive search filter for the field of palliative care. Design: We used a novel, objective method for search filter development. First, we created a gold standard set. This set was split into three groups: term identification, filter development, and filter validation set. After creating the filters in PubMed, we translated the filters into search filters for Ovid MEDLINE, Embase, CINAHL, PsychINFO, and Cochrane Library. We calculated specificity, sensitivity and precision of both filters. Results: The specific filter had a specificity of 97.4%, a sensitivity of 93.7%, and a precision of 45%. The sensitive filter had a sensitivity of 99.6%, a specificity of 92.5%, and a precision of 5%. Conclusion: Our search filters can support literature searches in the field of palliative care. Our specific filter retrieves 93.7% of relevant articles, while 45% of the retrieved articles are relevant. This filter can be used to find answers to questions when time is limited. Our sensitive filter finds 99.6% of all relevant articles and may, for instance, help conducting systematic reviews. Both filters perform better than prior developed search filters in the field of palliative care.